The Pennsylvania State University

The Graduate School

College of Agricultural Sciences

SOURCES OF INOCULUM, EPIDEMIOLOGY, AND INTEGRATED MANAGEMENT

OF BACTERIAL ROTS OF ONION (ALLIUM CEPA) WITH A FOCUS ON CENTER ROT,

CAUSED BY PANTOEA ANANATIS AND PANTOEA AGGLOMERANS

A Dissertation in Plant Pathology

by

Emily E. Pfeufer

©2014 Emily E. Pfeufer

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

August 2014

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The dissertation of Emily E. Pfeufer was reviewed and approved* by the following:

Beth K. Gugino Associate Professor of Plant Pathology

Dissertation Advisor Chair of committee

Gary W. Moorman Professor of Plant Pathology

Maria del Mar Jimenez-Gasco Assistant Professor of Plant Pathology

Paul A. Backman Professor Emeritus of Plant Pathology

Shelby J. Fleischer Professor of Entomology

Frederick E. Gildow Professor of Plant Pathology

Head of the Department of Plant Pathology and Environmental Microbiology

*Signatures are on file in the Graduate School

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Dissertation abstract

Commercial acreage devoted to onion production has increased exponentially in Pennsylvania

(PA) over the past fifteen years for several reasons, including the development of the PA Simply Sweet®

marketing program, the establishment of grower cooperatives, and renewed consumer interest in fresh,

local produce. Even with increasing acreage of onions in PA, consumer demands for the crop are not met

by current production. Bacterial rots of onion are the most significant diseases reducing harvest and

storage yields of the crop, in some instances diminishing marketable yields by 60%. Growers manage

bacterial rots of onion through combinations of chemical and cultural practices, including copper

fungicides, plastic mulch, and drip irrigation; however, yields remain variable between seasons and farms.

These producers are interested in alternative practices, including plant defense-inducing treatments,

carefully planned applications of fertilizer during drip irrigation (fertigation), and targeted insect

management for more consistent control of bacterial diseases, however, data is lacking on the

effectiveness of these practices in PA. The ultimate goal of the following research is to contribute

additional integrated management tools to the existing grower knowledge base to increase the

profitability of growing onions in PA.

As a relatively new pathosystem in PA, basic and applied research was conducted in order to

better understand the impact of bacterial rots on marketable yield of onion in the state. The principal

bacterial pathogens were identified as Pectobacterium carotovorum subsp. carotovorum, Pantoea

agglomerans, and Pseudomonas marginalis pv. marginalis. Sources of bacterial inoculum, including soil,

transplants, and weeds, were elucidated in addition to investigation of ecological interactions between

these species, their hosts, and the cropping system. Aspects of the production system are suggested to

affect plant disease in both pathogen- and disease-specific ways, such as the association of black plastic

mulch with increased detection of P. agglomerans, and early-season soil nitrate resulting in decreased

detections of leaf pathogens. On-farm management factors as observed in PA and New York indicate that

higher incidences of bacterial rots of onion are associated with low foliar nitrogen and high soil

temperatures near the physiological onset of bulbing. Replicated field trials in which plant defense-

inducing and growth-promoting compounds were compared for their efficacy in managing center rot of

onion (Pantoea ananatis and P. agglomerans) indicated moderate disease incidence among all

treatments, including the copper-based grower standard treatment, which was only effective at low levels

of inoculum pressure. Comparisons of the source and timing of nitrogen fertilizer application were

completed in a replicated field study, and one year of data suggests an association between late-season

fertilizer application and higher incidence of center rot. In addition, data were generated in an effort to

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understand the role of thrips in the epidemiology of center rot disease. Taken together, these datasets

have increased the overall knowledge about the bacterial rot – onion pathosystem in Pennsylvania,

elucidated management practices that hold promise for future replicated study, and improved

management of bacterial rots of onion, particularly through dissemination of research results to growers

during extension presentations.

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Table of Contents

List of Figures .............................................................................................................................................. vi

List of Tables ................................................................................................................................................. x

Acknowledgements ..................................................................................................................................... xii

Chapter 1: A review of current onion production, focused on Pennsylvania .............................................. 1

References ........................................................................................................................................ 15

Chapter 2: Sources of bacterial inoculum in and around onion (Allium cepa) production fields in

Pennsylvania ............................................................................................................................................. 22

References ........................................................................................................................................ 44

Chapter 3: Epidemiology and ecology of Gram-negative bacteria potentially pathogenic to onion (Allium

cepa) in Pennsylvania ................................................................................................................................. 47

References ........................................................................................................................................ 68

Chapter 4: In-field management factors related to incidence of bacterial rot of onion (Allium cepa) in

Pennsylvania and New York ...................................................................................................................... 71

References ........................................................................................................................................ 84

Chapter 5: Efficacy of plant defense-inducing and growth-promoting products for the management of center rot of onion (Allium cepa), caused by Pantoea ananatis and P. agglomerans ............................. 87

References ...................................................................................................................................... 104

Chapter 6: Effects of nitrogen fertilizer on growth characteristics, center rot incidence and severity, and

other nutrient status in ‘Candy’ onion (Allium cepa)............................................................................... 107

References ...................................................................................................................................... 124

Chapter 7: Revised best practices for onion production in Pennsylvania and future work .................... 126

Appendix: Preliminary work with thrips identification by PCR primers and the impact of onion thrips (Thrips tabaci) on center rot of onion (Allium cepa) in Pennsylvania ..................................................... 129

References ...................................................................................................................................... 135

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List of Figures

Figs. 2.1a – b. Results of semi-anaerobic pathogenicity tests using nonpathogenic (a) and pathogenic (b) strains .. 27 Fig. 2.2. Severity of symptom development in pathogenicity tests (duplicate) under aerobic incubation after seven days. 1 = nonpathogenic; 2 = local discoloration or maceration; 3 = local symptom, plus discoloration or maceration on adjacent scale(s); 4 = up to half of bulb discolored or macerated; 5 = more than 50% of bulb discolored or macerated. The right half of each bulb is inoculated; bulbs were rated individually and average was reported if not identical ...................................................................................................................................................................... 28 Fig. 2.3. Number of bacterial species detected in symptomatic onion bulbs from harvest and storage combined, in 2011 and 2012 ........................................................................................................................................................... 39 Fig. 2.4. Pathogenicity of epiphytic and endophytic bacterial isolates originating from transplants, incubated under aerobic and semi-anaerobic conditions in pearl onion bulbs. Pathogenic isolates are indicated by blue-shaded portions of bars, nonpathogenic isolates are indicated by green portions of bars ................................................... 39 Fig. 2.5. Pathogenicity of epiphytic and endophytic bacterial isolates originating from common weeds collected at midseason, incubated under aerobic conditions in pearl onion bulbs. Pathogenic isolates are indicated by blue-shaded portions of bars, nonpathogenic isolates are indicated by green portions of bars. *Endophytic isolates are only from 2012, and were isolated on OEM, which is semi-selective for onion pathogens and onion-associated bacteria ....................................................................................................................................................................... 40 Figs. 2.6a - c. Disease severity induced on onion by P. agglomerans (A), P. carotovorum (B), and P. marginalis (C) isolates, from environmental and transplant sources from 2011 and 2012, in aerobic pathogenicity tests. Nonpathogenic proportions of isolates are indicated by green portions of bars (NP), pathogenic isolates are indicated by pink-red portions of bars. The shade of the bar indicates the severity of induced symptoms as described in Fig. 2.2; severity increases as the bars approach the x-axis. *Weed epiphytes and endophytes were isolated using semi-selective media in 2012; weed epiphytes include isolates from 2011 and 2012, while weed endophytes include isolates only from 2012. N = number of isolates tested from each source ................................................................ 41 Fig. 2.7. Representative gel of rep-PCR genomic fingerprints for tracking strains of Pantoea spp. from two fields’ transplant, weed, and symptomatic onion isolates. These fields were planted with transplants from the same lot, but were located approx. 32 km from each other, on different soil types. Isolates 562 and 563 originated from the same area of the same field, but 562 is an endophyte from purslane while 563 is an epiphyte from crabgrass. Isolate 551 is an endophyte from shepherd’s purse, while isolate 1617 is from an onion that developed symptoms after approx. 4 months in storage. All highlighted isolates are P. ananatis ....................................................................... 42 Figs. 3.1a – b. Symptomatic onions typified by the generic diseases surface rot (a) or inner scale rot (b). The green wire loop was surface-sterilized and indicates roughly where symptomatic tissue was harvested for DNA extraction and bacterial isolation ................................................................................................................................................ 51 Fig. 3.2. Detection of bacterial species in symptomatic bulbs pooled from at harvest (2011 and 2012) and from storage (2012 only) samples from which only one pathogen was detected and separated by the type of rot symptom observed (N=238). This represents approx. 36% of all symptomatic bulbs collected from 2011 and 2012. The ‘Other’ category includes positive detections for Burkholderia cepacia, Pseudomonas viridiflava, and either P. ananatis (surface rot bulbs [SR]) or B. gladioli pv. alliicola (inner scale rot bulbs [ISR]) ........................................................... 61 Figs. 3.3a - b. Pathogenicity of Pantoea agglomerans, Pectobacterium carotovorum subsp. carotovorum, and Pseudomonas marginalis pv. marginalis from onion transplants in aerobic and semi-anaerobic pathogenicity tests, divided by bacterial isolation source. *All 2012 isolates were generated from semi-selective OEM, while 2011 isolates were generated from KB (nonselective). Weed endophytes were only isolated in 2012 ......................................... 62

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Fig. 3.4. Bacterial epiphytes of the species Pantoea agglomerans, Pectobacterium carotovorum subsp. carotovorum, and Pseudomonas marginalis pv. marginalis from selected common weed sources collected in PA onion fields in 2011 and tested for pathogenicity under aerobic incubation. Purple-shaded portions of bars indicate pathogenic isolates of each species, while green shaded portions of bars indicate nonpathogenic isolates from each weed source, regardless of species. * Indicates proportionally more pathogenic isolates compared to each of the other weeds by Fisher’s exact test (α = 0.06) ....................................................................................................................................... 63 Fig. 4.1. Simple slopes analysis of projected relationships between average soil temperature three weeks preharvest and the incidence of total bacterial rot of onion, given different levels of foliar N, from PA-2011. Points of each line were calculated based on the covariance matrix of the multiple regression model in Table 1 (Aiken and West, 1991). Foliar N values (2.41% N [low], 2.75% N [avg], 3.09% N [high]; ±1 standard deviation from the sample mean) were chosen, then projected bacterial disease estimates were calculated based on chosen average soil temperatures three weeks preharvest (23.79, 24.29, 24.79°C; ± 0.5 °C from the sample mean). Simple slopes were compared to H0 = 0; for average and high foliar N lines, t was significant at P = 0.03. ............................................................................... 82 Fig. 4.2. Total bacterial disease incidence by foliar C/N ratio, combined data from PA-2011 and PA-2012. Ten leaves per plot were co-mingled, dried, homogenized, and analyzed for total C and N via dry combustion. Total bacterial disease incidence was the sum of the percentages of symptomatic bulbs at harvest and from storage as a total of the bulbs harvested per plot. Three plots were averaged for each field value; each point represents one field ..... 83 Fig. 4.3. Total bacterial rot incidence by cultivar grown, NY-2011 and NY-2012. Data were analyzed using a one-way ANOVA in Minitab 16.2, error bars represent the standard error of the mean, and letters above each bar indicate statistically significant differences by Fisher’s LSD (α = 0.05)..................................................................................... 84 Fig. 5.1. 2012 inoculation diagram with locations of high (red, center front), medium (orange, flanking red), and low (yellow, center rear) inoculum ................................................................................................................................... 99 Fig. 5.2. Foliar disease symptom rating scale. Foliar ratings are as follows: 0 – no lesion, asymptomatic (uninoculated plants only); 1 – local lesion (2.5 cm x 2.5 cm or less); 2 – expanded lesion, but less than ¼ of leaf; 3 – up to ½ of the inoculated leaf is chlorotic or bleached; 4 – more than ½ of the inoculated leaf is chlorotic or bleached, but uninoculated leaves do not show symptoms; 5 – entire inoculated leaf and a portion of an uninoculated leaf are symptomatic; 6 – multiple fully symptomatic leaves; 7 – ≥50% bleached and/or collapsed leaves ........................ 100 Fig. 5.3. Photograph of Landisville field showing topography of blocks ................................................................... 99 Fig. 5.4. Average center rot incidence and percentage of marketable large-size (>7.6 cm diameter) onions by treatment block, Landisville, 2011. Block was analyzed as a random factor in order to control for natural variation within the onion field; the arrow roughly indicates the topography of the field (low-lying, on left, to high-ground, on right). Data were analyzed using PROC GLM in SAS 9.2, with post-hoc comparisons completed using Fisher’s LSD (α = 0.05); statistically significant differences are indicated by different letters above each set of bars (disease incidence [red bars] = a-c; large bulbs [blue bars] = x-z). Bars represent the experiment-wide standard error ...................... 101 Fig. 5.5. Proportion of total marketable yield that was categorized as large (> 7.6 cm diameter) bulbs across all treatments grouped by pathogen pressure based on inoculation status (low, medium, and high) from Rock Springs and Landisville, 2012. Analysis was completed using PROC GLM in Minitab 16 with post-hoc comparisons using Fishers LSD (α = 0.05). Letters above each bar indicate statistical significance ...................................................... 101 Fig. 5.6. Center rot incidence by treatment under varying levels of inoculum pressure, Landisville, 2012. Center rot incidence at harvest was recorded for different areas of plots for each treatment. Inoculum pressure within plots includes low (uninoculated), medium (adjacent to inoculated), and high (inoculated) treatments. Error bars represent experiment-wide standard error. Different letters above each bar of the same inoculum pressure indicate statistically significant differences by Fisher’s LSD (α = 0.05)................................................................................... 102

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Fig. 5.7. Weekly foliar disease severity ratings post-inoculation, from Rock Springs in 2012. For each treatment, 20 inoculated plants per plot were rated for disease severity following the scale in Fig. 5.2. * indicates a statistically significant difference between GB03 and the grower standard Cu-EBDC treatment (Fisher’s LSD; α = 0.05). ........ 102 Fig. 5.8. Center rot incidence by treatment under varying levels of inoculum pressure, Rock Springs, 2012. Center rot incidence at harvest was recorded for different areas of plots for each treatment. Inoculum pressure within plots includes low (uninoculated), medium (adjacent to inoculated), and high (inoculated) treatments. Error bars represent experiment-wide standard error. Different letters above each bar of the same inoculum pressure indicate statistically significant differences by Fisher’s LSD (α = 0.05)................................................................................... 103 Fig. 5.9. Center rot incidence on research farms in 2012. Bars indicate the mean of each inoculation level on each farm, regardless of in-season treatment, and error bars indicate standard error of each mean. Statistically significant differences are indicated by different letters above the bars (Fisher’s LSD; α = 0.05) ............................................ 103 Fig. 6.1. Lesion development in differentially-fertilized onion seedlings after foliar inoculation with P. ananatis in a growth chamber assay. Inoculated plants are indicated by INC. Means at each date were compared between treatments using ANOVA with Fisher’s LSD; * indicates a statistically significant difference between the Nitrate and Ammonium-fertilized, inoculated plants, while ** indicates a statistically significant difference between inoculated control and nitrate fertilizer treatments compared to the ammonium-only fertilizer treatment. Error bars represent standard error of the mean ..................................................................................................................................... 119 Fig. 6.2. Center rot progression by fertilizer application timing in inoculated plants in the field. N treatments were combined within the timing variable since no differences were apparent between N types. Means within each type of timing were compared using a one-way ANOVA and Fisher’s LSD (α = 0.05). * indicates a statistically significant difference in disease severity between the full-season and half-season fertilized treatments ............................... 120 Figs. 6.3. Center rot at harvest by inoculation status, N fertilizer source and application timing. Bars indicate the average of four replicate plots, error bars represent standard error of the mean. Bars with different letters indicate statistical significance by Fisher’s LSD (α = 0.05) ..................................................................................................... 121 Fig. 6.4. Center rot incidence at harvest based on inoculation status and fertilizer application timing. Bars indicate the average of the plots within each category (N = 4 [unfertilized plots] or N = 8 [half- or full-season fertilized plots, regardless of N source]). Error bars represent standard error of the mean and different letters above each bar indicate statistical significance by Fisher’s LSD (α = 0.05) ........................................................................................ 121 Fig. 6.5. Sulfur content of asymptomatic bulbs at harvest by N fertilizer type and timing. Bars indicate averages by treatment group; different letters above bars indicate statistical significance by Fisher’s LSD (α = 0.05) .............. 122 Fig. 6.6. Analysis of covariance estimates with treatment (listed under each bar with the timing and form of inorganic N) as a main effect and calcium in foliage after three weekly fertilizer treatments as a covariate, with center rot incidence as the dependent variable. Inoculated treatments are solid color bars, uninoculated treatments are hatched. Dark blue indicates full-season application (N fertility applied weekly throughout the season), medium blue indicates half-season application (N fertility applied weekly prior to midseason), and light blue indicates no additional N fertility. Means shown are estimates with early-season foliar Ca included as a covariate in the model. Bars with different letters are significantly different by Tukey’s test (α = 0.05) ...................................................................... 122 Fig. 6.7. Analysis of covariance estimates with treatment (listed under each bar with the timing and form of inorganic N) as a main effect and nitrogen in foliage after six weekly fertilizer applications as a covariate, with center rot incidence as the dependent variable. Inoculated treatments are solid color bars, uninoculated bars are hatched. Dark blue bars indicate full-season fertilizer application, medium blue bars indicate half-season fertilizer application, and light blue bars indicate no fertilizer application. Means shown are estimates with N included in the model. Bars with different letters are significantly different by Tukey’s test (α = 0.05) ...................................................................... 123

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Fig. 6.8. Center rot incidence at harvest compared to amount of N fertilizer of either type applied by midseason. Statistically significant differences only exist between means in different inoculation categories. Error bars indicate standard error of the mean ..................................................................................................................................... 123 Fig. A.1. Frankliniella occidentalis (left) and Thrips tabaci (right) as viewed at 100x magnification ....................... 131 Fig. A.2. Representative electrophoresis gel of PCR reactions using published Thrips tabaci (expected amplicon size, 298 bp; Asokan et al., 2007), Frankliniella occidentalis (expected amplicon size, 249 bp; modified from Huang et al., 2010), and Thrips palmi (expected amplicon size, 390 bp; Asokan et al., 2007) primer sets .................................. 133

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List of Tables

Table 2.1. Detection of eight bacterial pathogens of onion from environmental and plant samples, collected in 2011 and 2012. The percentage of the total N of each sample type is given in the appropriate column; columns sum to more than 100% because many samples gave positive identifications for multiple targeted bacterial species ...... 38 Table 2.2. Summary of rep-PCR genomic fingerprinting analysis of environmental and pathogenic isolates from symptomatic onion tissue. Isolates of Pantoea spp. collected from a variety of sources in and around 26 onion production fields in 2012 were used as templates in rep-PCR genomic fingerprinting analysis to track bacterial strains through space and time ............................................................................................................................................. 43 Table 2.3. Logistic regression analysis of detections of P. marginalis and P. agglomerans in symptomatic onion bulbs at harvest and from storage predicted by environmental and transplant source species detections, using farm as a factor, from 2011 and 2012. Dependent variable is binary P. marginalis (A; C) or P. agglomerans presence (B; D; presence = 1) in symptomatic onion bulbs from harvest and storage; independents are positive transplant endophyte (A), detections in each of early-season soil (B), transplant epiphyte (C), and weed epiphyte samples (D) .............. 43 Table 3.1. Logistic regression of general types of bacterial rot (surface rot or inner scale rot) modeled by the detection of bacterial species in symptomatic bulbs collected at harvest and from storage in PA in 2011 and 2012. Dependent variable modeled is 1 = inner scale rot (n = 395), while independent variables are species detections (presence = 1) ............................................................................................................................................................ 61 Tables 3.2a – d. Logistic regressions of harvest and storage detections of Pantoea agglomerans (3.2a; N = 225 of 617), Pectobacterium carotovorum subsp. carotovorum (3.2b; n = 366 of 614), Pseudomonas marginalis pv. marginalis (3.2c; n = 171 of 614), and Pantoea ananatis (3.2d; N = 48 of 614) from symptomatic onion bulbs from PA, combined in 2011 and 2012; positive detections rated ‘1.’ Independent variables are detections of other bacterial species in symptomatic bulbs as well as environmental and production factors observed throughout the season .. 64 Tables 3.3a – b. Pantoea agglomerans detections in surface (3a; n = 68 of 174) and inner scale rot (3b; n = 128 of 348) bulbs with other bacterial species detections and environmental and management factors as independent variables ..................................................................................................................................................................... 66 Tables 3.4a – b. Pectobacterium carotovorum subsp. carotovorum detections in surface (3.4a; n = 163) and inner scale rot (3.4b; n = 225 of 360) bulbs with other bacterial species detections and environmental and management factors as independent variables ............................................................................................................................... 67 Table 4.1. Field-averaged results of multiple linear regression analysis of PA-2011 dataset. All variables were placed in a stepwise model selection procedure (α to add = 0.15, α to remove = 0.2), with total bacterial rot incidence as the dependent variable. For this model, R2 = 0.557; adj. R2 = 0.480; P = 0.001 ........................................................ 82 Table 4.2. Field-averaged results of multiple linear regression analysis of PA-2012 dataset. All variables were placed in a stepwise model selection procedure (α to add = 0.25, α to remove = 0.3), with a logistic transformation of total bacterial rot incidence as the dependent variable. For this model, R2 = 0.314; adj. R2 = 0.212; P = 0.052 ............... 83 Table 4.3. Field-averaged results of multiple linear regression analysis of combined NY-2011 and 2012 datasets. Independent variables were observed in 22 and 32 fields, respectively. All variables were placed in a stepwise model selection procedure (α to add = 0.15, α to remove = 0.2), with a square root transformation of total bacterial rot incidence for each field as the dependent variable. For this model, R2 = 0.161; adj. R2 = 0.126; P = 0.019 .............. 83 Table 4.4. Field-averaged results of multiple linear regression analysis of combined PA datasets. All independent variables observed in 54 fields were placed in a stepwise model selection procedure (α to add = 0.05, α to remove = 0.1), with a log transformation of total bacterial rot incidence as the dependent variable. For this model, R2 = 0.179; adj. R2 = 0.147; P < 0.001 ........................................................................................................................................... 84

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Table 5.1. Treatments, treatment schedule, and 2011 growth and disease incidence results from Rock Springs, 2011. Similar treatments and application schedules were conducted in the 2011 trial in Landisville as well the 2012 trials in Rock Springs and Landisville. Longest leaf means were separated using Fisher’s LSD (P ≤ 0.05); different letters following the mean indicate statistically significant differences ................................................................................ 98 Table 6.1. Relationships between foliar carbon (C), early-season soil ammonium (NH4), and silt content of soil to the foliar nitrogen (N) content from leaves collected at midseason, on 54 Pennsylvania onion fields over two years .................................................................................................................................................................................. 110 Table 6.2. Midseason growth estimates and thrips pressure by fertilizer treatment prior to inoculation in 2013 … 120 Table A.1. Sequences, expected amplicon sizes, and sources of primers used to identify thrips collected from PA to species ..................................................................................................................................................................... 133 Table A.2. Bacterial isolates from thrips tested for pathogenicity on onion through aerobic and semi-anaerobic pathogenicity tests. Ratios in each column pertain to the pathogenic isolates out of all isolates of that species tested; total columns indicate the total number of strains of each species in the collection ............................................. 134

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Acknowledgements

I would like to acknowledge the funding sources that supported parts of this dissertation: the

Northeast IPM Competitive Grants program, the Pennsylvania Vegetable Growers Association, the

Pennsylvania Vegetable Marketing and Research Program, and the Larry J. Jordan Endowment in Plant

Pathology and Environmental Microbiology at Penn State. I would also like to thank the onion growers of

Pennsylvania, who always welcomed me to their farms, even if my being there meant they had a

significant disease issue. Without their cooperation, much of this work would not have been possible, and

I have learned as much from them as they have learned from me. Thank you also to numerous extension

educators who facilitated our grower visits and offered advice along the way.

The Department of Plant Pathology and Environmental Microbiology has been a generous source

of financial, educational, and emotional support over the past six years, during both my Master of Science

and Ph.D. degrees. I would particularly like to thank Dr. Beth Gugino, my dissertation advisor, for her

untiring mentorship, excellent advice, positive attitude, and the multitude of opportunities she opened to

me. I am incredibly grateful for all of our teaching moments, whether in her office, our lab, at Rock Springs,

or on grower farms. Dr. Maria del Mar Jimenez Gasco, Dr. Gary Moorman, Dr. Fred Gildow, and Dr. John

Pecchia have also been wonderful sources of advice and friendship, and this process would not have been

the same without them. Thank you to the committee members I have not mentioned yet, Dr. Paul

Backman and Dr. Shelby Fleischer, who provided thoughtful critiques to help craft this dissertation into

what it has become. Tim Grove and members of the Rock Springs farm crew, and John Stepanchak, Jim

Bollinger, and members of the Landisville farm crew were instrumental in completing the research farm

trials. I am also grateful to all of the staff and current and former students from the department for their

friendship and assistance, including Dr. Michele Mansfield, Dr. Anissa Poleatewich, Ilse Huerta, Dr.

Vasileios Bitas, Sarah Bardsley, Freddy Magdama, Sara May, Roxanne Lease, Steve Conaway, and Anna

Testen.

Many thanks to all of my friends and family, without whose support this would not have been

possible. Thank you especially to my parents, Tony and Jan, as well as my siblings, who sparked my interest

in science at an early age, then fed the fire over the subsequent years! I was lucky to have many talented

teachers and professors early on, including Mrs. Laura Anderson, Mrs. Mary Buerk, Dr. Catharina Coenen,

and Dr. Ann Kleinschmidt. My friends, particularly Kat and groupchat (Liz S., Liz E., KP, Lindsay, and Eva),

saw me through successes and failures, and I am grateful to have their unrelenting encouragement.

Finally, thank you to my best friend and husband, Andy, who was a constant source of support as I became

a ‘plant-killer.’ He shares in this Ph.D., and I could not have done it without him.

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Chapter 1: A review of current onion production, focused on Pennsylvania

Social and economic significance of onion

Onions (Allium cepa L.) are an important component of countless cuisines around the world,

lending varied flavors from savory richness to striking sweetness to meals, both cooked and raw. An

ancestral vegetable, onion’s medicinal properties were described in a 2000-year-old Indian medical

treatise, it is mentioned in both the Old Testament of the Bible and the Koran, and bulbs have been

recovered from Egyptian tombs, indicating they were cultivated as early as 3200 B.C (Schwartz et al.,

2008). The per capita consumption in the U. S. is approximately 9.5 kg (21 lb) of onions per year. Onions

are rich in vitamin C, fiber, and folic acid (PA-DPN). Approximately 170,000 hectares were planted to onion

in the United States in 2012, and combined among green, summer, and storage onions, onion production

is greater than a two billion-dollar industry nationwide (NASS-USDA, 2013).

Bacterial bulb rots, the most significant diseases in fresh-market onion production in the Mid-

Atlantic region, may cause annual losses of up to 60% on some farms. In 2013, a year with particularly

high disease incidence, a number of sweet onion growers in PA suffered losses averaging $4000 per

hectare ($2500 per acre; J. Stoltzfus, adult educator, Eastern Lancaster County School District). Crop losses

may occur immediately at harvest or when the grower sells the onions after a short period of storage.

Efficient and effective management of bacterial diseases of onion remains a formidable challenge.

Onion production and marketing in the U. S.

Commercial onion production varies widely among regions and states. In perhaps the most well-

known onion producing state, Georgia, short-day sweet onions are produced from transplants of multiple

varieties approved for Vidalia® production, which are set in November or December in mulch-free, raised

beds with overhead irrigation. These onions are grown to maturity in one of twenty counties until March

or April, then harvested by undercutting the roots, field-cured for several days, then manually or

mechanically removed from the field and further cured in front of a fan for several more days. These

onions are marketed April through June as part of the Vidalia® marketing strategy; one estimate is that

1/3 of sweet onions sold are Vidalia®. Bacterial diseases are concerns in Georgia onion production are

primarily associated with late onion varieties or warmer than average temperatures. Fungal diseases

typically receive more attention in disease management programs (Boyhan and Kelley, 2007).

California leads the United States in terms of dry bulb onion production (USDA, 2013). Onions are

direct-seeded from September to May in low and high desert areas as well as in coastal regions. Onion

fields are irrigated in raised beds with overhead, furrow, or drip irrigation. Either short-day or

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intermediate day varieties are grown depending on the production location, and production soil types are

widely variable. As in all onion production systems, commercial production in California has high nutrition

requirements, particularly for nitrogen (Smith et al., 2011).

Washington, Oregon, and Idaho trail California in dry bulb production (USDA, 2013), but together

account for a large proportion of the bold cooking onions produced in the U. S., with some production of

sweet onions, particularly in Washington. All varieties are intermediate- to long-day onions. In these

states, plants are usually direct seeded into mineral soils in February or March, though some operations

start seeds in fall (particularly for Walla Walla production) or plant farm-grown transplants. Some onion

production on high organic matter, muck soils occurs in western Oregon. Plastic mulch is rarely used in

Pacific Northwestern systems, where growers may use overhead, furrow, or drip irrigation. Onions are

harvested in the region from August to October, depending on variety and crop maturity (Oregon State

Vegetable Production Guides, 2004).

Appreciable amounts of onion are commercially grown in Texas, Nevada, New York, Colorado,

New Mexico, and a number of other states. In New York, onions are primarily grown on high-fertility muck

soils with overhead irrigation. These fields are direct-seeded with some of the same onion varieties grown

in Pennsylvania, however, production is focused on bold cooking onions as opposed to sweet varieties. A

minority of producers in New York use plastic mulch and drip irrigation, much of which is used on mineral

soils.

Onion production and marketing in Pennsylvania

Most onions in PA are grown in small fields, sometimes as little as 0.1 hectare, by growers

producing a variety of other vegetable crops, in addition to other farm enterprises. In 2005, over 40

growers across the state were participating in the PA Simply Sweet® marketing program, on approximately

16 total hectares (38 acres; PVGA, 2010). In 2014, there are approximately 100 growers in Lancaster and

Chester counties commercially growing onions, with most participating in the Simply Sweet® program and

selling their crops through wholesalers, produce auctions, and directly through farm stands (J. Stoltzfus,

pers. comm.) In addition, at least 20 growers who may or may not be participating in the Simply Sweet®

program are also commercially producing onion in central, southwestern and eastern PA, primarily for

direct-market sales like farm markets and community-supported agriculture. Simply Sweet® onions,

Pennsylvania’s only trademarked crop, represent a burgeoning market for growers in the state, with crops

commanding premium prices in vegetable buyers’ markets. In 2012, despite an increasing number of

3

growers and over 100 acres in commercial production with the potential of producing over 5 million

onions, consumer demand continued to exceed supply.

To participate in the Simply Sweet® program, which is managed by the Pennsylvania Vegetable

Growers Association, accepted growers must pay a fee, estimate their expected yield, and plant one of

three approved low-pungency cultivars (‘Candy,’ ‘Expression,’ or ‘Enterprise’). All of these cultivars are

sweet, yellow, intermediate- or long-day summer onions, and intended for use as a fresh-slicing onion,

rather than a dry bulb storage onion. The Simply Sweet® program requires that the onions be larger than

a minimum size (7.62 cm in diameter; 3-in.) and analyzed to contain >6% soluble sugar in composite

samples of harvested bulbs. Growers are also required to grow onions using plastic mulch and drip

irrigation. Although not all PA onion growers are participating in the Simply Sweet® program, the majority

are growing ‘Candy.’

Onion plants are started from seed in fields by commercial producers in Arizona or Texas, or PA

growers produce their own plants in local greenhouses starting in December or January. In general,

transplanting of 10-12 week old plants occurs in late March or early April. Onions are a biennial crop, the

physiology of which is highly influenced by day length and temperature. Transplants only begin to produce

new leaves as the soil warms, typically in mid-April. Prior to transplanting, 20 – 30 cm (8 - 12-in.) tall raised

beds are plowed, two rows of drip irrigation tubes are put into position, and the raised bed is then covered

with plastic mulch. Standard plant spacing is 15 cm (6-in.) between plants within the row and 15 cm

between rows; in most fields, there are four rows of plants running longitudinally down the bed. By

changing plant spacing, bulb size can be manipulated, i.e., wider plant spacing generally results in larger

bulbs; some growers choose to alter plant spacing depending on several factors, such as target market or

field size.

Onion varieties have been developed for various regions based on anticipated air temperature

and daylength during the growing season. As a monocot, onions have unbranched, shallow roots that

extend from an extremely abbreviated ‘stem’ or basal plate, at the bottom of the bulb. Full-size bulbs,

composed of modified leaf tissue of approximately fifteen layers, or scales, evolved as a storage organ for

the biennial plant (Schwartz et al., 2008). Each scale in the bulb corresponds to a leaf blade that extends

from the narrowest point of the foliage, called the onion neck, and this leaf primarily produces

photosynthates to nourish its scale through the season (Mann, 1983). If leaves are removed,

carbohydrates are translocated through the basal plate to the orphaned scales, and the bulb overall will

be smaller than bulbs with all of their leaves (Bartolo et al., 1994; Mann, 1983). While onions may have

fifteen or more layers, plants typically only support ten or eleven leaves at a time, with the oldest leaves

4

progressively senescing, drying, and falling to the soil. After attaining eleven full size leaves in May and

early June, bulbing is induced in long-day varieties (recommended for PA) by fourteen to sixteen hours of

daylight, occurring in mid to late June. Bulbing is characterized by a lack of new leaf formation, rapid

transfer of carbohydrates from the leaves to the bulb, and a rapid build-up of bulb biomass, which is

desirable for harvest (Schwartz et al., 2008).

Onions are generally harvested in early to mid-July in PA, for a total field season length of

approximately three months. Most growers pull onions by hand from the ground, which are laid on the

plastic mulch for 1-2 days, with the leaves of one plant covering the bulbs of neighboring plants to prevent

sun injury before the tops are removed and the bulbs are loaded into bins. Alternatively, some growers

remove onion foliage immediately in-field and bulbs are loaded into bins, which are placed in shade or

cool storage. In either case, binned onions are placed near fan-forced air to expedite drying down of the

necks, which in addition to the outer few scales, dry to papery layers over at least a week. Neck drying

seals moisture inside and helps exclude pathogens; bulbs that are improperly dried typically do not store

well and are more susceptible to postharvest disease, such as Botrytis neck rot (Pfeufer, observation).

Growers who observe foliar bacterial disease symptoms in the field often choose to harvest earlier than

initially planned in order to ensure a larger proportion of asymptomatic bulbs; since bulbs produce a

significant amount of tissue (approx. 0.6 cm diameter / week; D. Zook, grower cooperative board member;

pers. comm.) in the last three weeks of the growing season, timing of harvest may significantly influence

yields. One estimate equated an additional 0.6 cm in diameter to a 20 – 25% increase in yield for the entire

crop (D. Zook, pers. comm.). Harvested onion bulbs are considered ‘colossal’ if they are greater than 10.16

cm (4-in.) in diameter and ‘jumbo’ if between 7.62 (3-in.) and 10.16 cm (4-in.) in diameter. Onions smaller

than 7.62 cm in diameter are sold by growers in one major cooperative for lower prices in netted bags, in

some cases to large grocery stores. These onions may also be kept by the grower for home use.

Primarily marketed as a fresh-slicing onion, the ‘Candy’ cultivar is sold in several different markets,

depending on grower location and management preferences. Most of the PA growers are located in

Lancaster and Chester counties, and participate in onion grower cooperatives. These cooperatives allow

the growers to take advantage of quantity discounts for transplant purchases, reduced capital investment

due to shared equipment, and allow smallholder growers to pool their harvests to sell as larger lots to

wholesalers, typically in 18 kg (40 lb) boxes. In an average year, a grower will plant approximately 125,000

transplants per hectare (50,000 plants per acre), and may expect yields of 1350 kg per hectare (1200 lb /

acre; D. Zook, pers. comm.). Growers in the cooperative may also reserve a portion of their harvest for

sale at produce auctions or at their own roadside stands. Growers not involved in cooperatives produce

5

onions for sale by the bulb at on-site markets, roadside stands, or community farmer’s markets, where

bulbs may sell for $1 each or more. Additionally, a few growers produce onions to include as part of their

own Community-Supported Agriculture (CSA) shares.

Growers’ demand for larger, more valuable bulbs may result in the use of intensive nutrient

management programs, including pre-plant manure applications (particularly by Amish, Anabaptist, and

other sect growers) as well as proprietary programs for applying fertilizer during drip irrigation

(fertigation), which are marketed and distributed by fertilizer industry representatives. While manure

application is often low-cost, fertilizer programs delivered during the season are heavily marketed by

company representatives and subsequently sold at a premium to growers; one figure for such fertility

programs was estimated at $1600 per hectare per season ($1000 per acre; J. Stoltzfus, pers. comm.). Since

the specific components of the fertilizer program are often proprietary, growers rely on company

consultants for weekly fertigation recommendations, which increases the number of farm visits by the

representative and associated costs. While this practice may help ensure more jumbo and colossal size

bulbs, it may also result in higher incidence of bacterial disease and over-fertilization of nitrogen (Diaz-

Perez et al., 2002), both of which reduce grower profits.

Onions are produced across PA, but commercial production is concentrated in the southern half

of the state where soils are more amenable to vegetable production. A majority of the growers included

in the first and second survey years are located in Lancaster and Chester counties, with areas near

Pittsburgh, Philadelphia, and Adams County also represented. The distribution of farm locations in

Chapters 2, 3, and 4 is representative of commercial onion production across the state. While other onion-

producing regions report problems with diseases as white rot (Sclerotium cepivorum), Botrytis leaf spot,

pink root (Fusarium spp.), iris yellow spot (caused by iris yellow spot virus), and purple blotch (Alternaria

porri), bacterial bulb rots are the most significant diseases that reduce marketable yields of onion in PA.

Causal agents of bacterial bulb rots, with a focus on Pantoea spp.

Bulb rots of onion may be caused by a number of different bacterial species, including Pantoea

ananatis Serrano, Pantoea agglomerans Beijerinck, Burkholderia cepacia Burkholder, Burkholderia

gladioli pv. alliicola Burkholder, Enterobacter cloacae Jordan, Pectobacterium carotovorum subsp.

carotovorum Jones, Pseudomonas viridiflava Burkholder, Xanthomonas axonopodis Kadota, and

Pseudomonas marginalis pv. marginalis Brown (Bull et al., 2010). Some diseases are typically associated

with particular pathogens: these include soft rots caused by P. marginalis pv. marginalis and P.

carotovorum subsp. carotovorum; center rot, caused by P. ananatis, P. agglomerans, and similar single-

6

scale rots caused by P. viridiflava and X. axonopodis; slippery skin, caused by B. gladioli pv. alliicola, and

sour skin, caused by B. cepacia. Enterobacter cloacae also causes bulb decay, particularly in storage

(Bishop and Davis, 1990; Schroeder et al., 2010), yet the pathogen occurs infrequently in PA and is more

common in NY and the Pacific Northwest. Overall, identification of the primary pathogens initiating

bacterial rots may be problematic, because multiple species of bacteria are regularly recovered from

symptomatic bulbs and diagnostic symptoms are difficult to discern; as such, bacterial rots of onion may

generally be referred to as disease complexes. P. ananatis and P. agglomerans may be considered

emerging pathogens of onion in the U. S., and certainly in PA, as a result of their recent increases in

incidence (Anderson et al., 2004).

The classic soft rot pathogen Pectobacterium carotovorum (formerly Erwinia carotovora) has an

extremely wide host range that includes vegetables, fruit, and ornamental plant hosts; one estimate is

over 35% of plant orders may be infected with this pathogen (Ma et al., 2007). P. carotovorum’s primary

mode of pathogenicity is the secretion of pectinolytic enzymes, which induce tissue maceration at plant

wound sites, particularly at low oxygen and cool conditions (Maher and Kelman, 1983). The majority of

strains have a type III secretion system that delivers effectors that suppress host defenses (Ma et al.,

2007). While Pectobacterium carotovorum as a species is considered monophyletic, members of the

carotovorum subspecies were found to be spread throughout several bacterial clades in a multigene

phylogenetic analysis, which resulted in Ma et al. suggesting the removal of the subspecies delineation

(2007); the subspecies delineation is retained here because the species-specific primers used in the

following work were based on strains reported with the subspecies carotovorum (Mansfield and Gugino,

2010). Ma et al. went on to note that multiple strains of P. carotovorum isolated from the same host plant

were located in different clades (2007), suggesting poorly defined intraspecific relationships. Conversely,

a different report noted that strains of P. carotovorum from monocots were more aggressive in monocot

disease severity tests than in dicot severity tests (Yishay et al., 2008). P. carotovorum has been isolated

from soils and as an epiphyte, and typically infects onion through the leaf or neck tissue, especially if the

tissue is wounded (Mohan, 2008).

Pseudomonas marginalis pv. marginalis induces similar symptoms on onion, initially causing

grayish, water-soaked lesions in leaves that progress to a leaf blight, then eventually maceration within

the onion bulb (Wright and Hale, 1992). This pathogen also causes rot in storage, and like P. carotovorum,

induces disease by way of pectin-degrading enzymes, even at low temperatures (Membre and Burlot,

1994). The Pseudomonas genus contains a large number of species such that it is further separated into

clusters, subclusters, and complexes based on relationships; P. marginalis and its three pathovars are

7

located in the P. fluorescens complex, and within that, in the P. fluorescens lineage (Bull et al., 2010;

Yamamoto et al., 2000). Past the P. fluorescens lineage, however, polyphyly becomes a possibility with

other closely related species, such that authors have called for additional reclassification; included in this

lineage are P. tolaasii, P. fluorescens biotypes A, B, and C, P. azotoformans, P. mucidolens, and P.

synxantha (Yamamoto et al., 2000). Again, the pv. marginalis designation is retained here as a result of

the use of reported pv. marginalis sequence to design the species-specific primer sets (Mansfield and

Gugino, 2010). Symptoms induced by both P. carotovorum subsp. carotovorum and P. marginalis pv.

marginalis appear very similar to center rot symptoms, with one or more discolored scales occurring

within a halved bulb (Mohan, 2008a); however, bulbs affected by soft rots comparatively have a greater

degree of maceration and are more odoriferous than bulbs affected by center rot, caused by P. ananatis

and P. agglomerans (Pfeufer, unpublished).

Center rot pathogens: Pantoea ananatis and P. agglomerans

P. ananatis (amended by Mergaert et al., 1993) and P. agglomerans (amended by Gavini et al.,

1989) are two closely related species that are increasingly recognized for the significant losses they cause

in onion production. P. ananatis strains have been shown to survive through epiphytic, endophytic, or

pathogenic associations with plants (Coutinho and Venter, 2009; Gitaitis et al., 2003), while P.

agglomerans is most well-known as a biocontrol organism via niche displacement (Bonaterra et al., 2003;

Costa et al., 2001) or antibiosis (Wright et al., 2001). However, P. agglomerans has also been shown to

function as an epiphyte, soil inhabitant, and pathogen of onion (Gitaitis et al., 2003; Edens et al., 2006).

P. ananatis and P. agglomerans may individually cause center rot of onion (Dutta et al., 2014), but

are sometimes found co-infecting symptomatic bulbs (Pfeufer, unpublished). Symptom progression after

infection with either pathogen generally follows a similar pattern: bacteria may infect a leaf through

stomata, or more often through a wound, and a lesion begins to form with little to no water-soaking. As

leaf lesions enlarge, the tissue appears bleached and loses its turgidity; the leaf blade remains upright

temporarily but eventually collapses. A confounding factor in the diagnosis of center rot, based on

symptoms, is the fact that as onion plants mature, their oldest leaves naturally senesce, lose turgidity, and

fall to the soil (or mulch); bleaching-type reactions may also occur in the tips of leaves if the plant receives

inadequate water (Pfeufer, unpublished). An onion plant with one mildly affected leaf that is older than

the most severely symptomatic leaf may indicate the onion is affected by center rot, rather than exhibiting

indication of senescence. As the infected leaf lodges, it is thought that bacteria have moved down the

leaf tissue into the onion neck, and subsequently into the bulb, which has been detailed for P. ananatis

8

by Carr et al., 2013. Disease development caused by P. ananatis has been associated with high air

temperatures and ample rainfall at bulbing in a direct-seeded production system (Schwartz et al., 2003).

Typical bulb symptoms associated with center rot include a single or few discolored scales with

little maceration inside the halved bulb, with the outer scales of the onion largely intact. Bulbs exhibiting

these symptoms generally do not differ from asymptomatic bulbs in terms of odor unless other pathogens

are co-occurring as a pathogen complex. Some infected bulbs may be culled at harvest by inspecting the

onion neck after it is topped: a soft, discolored ring is apparent in the neck of center rot-affected bulbs.

However, many growers do not inspect their bulbs for this subtle symptom, and combined with latently

infected bulbs, severe losses from storage may result from center rot.

Mechanisms of Pantoea spp. pathogenicity

A spectrum of virulence has been observed in isolates of both Pantoea species, ranging from

nonpathogenic strains, strains that display higher virulence as foliar pathogens, to strains noted for high

virulence on bulb tissue (M. Mansfield, research associate, pers. communication). Within P. ananatis,

pathogenic strains have been described for onion, pineapple, rice, maize, cotton, melons, eucalyptus, and

a few other crops, however, pathovar delineations have not yet been described (Coutinho and Venter,

2009). Draft genomes of epiphytic and endophytic biocontrol strains of P. ananatis have recently been

published (Kim et al., 2012; Smith et al., 2013), in addition to a pathogenic strain (De Maayer et al., 2010).

P. agglomerans is considered a ubiquitous soil inhabitant and now includes strains formerly called

Enterobacter agglomerans, Erwinia herbicola, Enterobacter milletiae, and Cornyebacterium beticola (Bull

et al., 2010). P. agglomerans may induce disease on gypsophila (baby’s breath), beet, rice, onion, maize,

and sorghum (Barash and Manulis-Sasson, 2009; Edens et al., 2006; Lee et al., 2010; Morales-Valenzuela

et al., 2007), with additional new hosts continuing to be described. Two pathovars have been defined

within P. agglomerans: pvs. gypsophilae and the related betae strain induce galls on baby’s breath and

beet, respectively, by way of a plasmid-borne pathogenicity island that likely was horizontally acquired

and includes a type III secretion system (Barash and Manulis-Sasson, 2009). P. agglomerans pv. milletiae

induces bleached lesions, especially at leaf margins, on pearl millet as reported in Zimbabwe and India

(Frederickson et al., 1997), however, relatively little additional work has been published on this pathovar.

More frequently, however, strains of P. agglomerans are recognized as niche-displacing and antibiotic-

producing biocontrol agents in pre- and postharvest agricultural production (Bonaterra et al., 2003; Costa

et al., 2001), and the species has also been shown to establish endophytic relationships with crop plants

(Araujo et al., 2002; Ferreira et al., 2008). Strains of both P. ananatis and P. agglomerans have been shown

9

to induce disease in immune-compromised people (De Baere et al., 2004; De Champs et al., 2000), and

genetic and virulence comparisons of clinical and plant pathogenic isolates of P. agglomerans

demonstrated ‘unlimited virulence potential’ among isolates in causing human disease, regardless of the

original isolation source (Volksch et al., 2009).

The type VI and type III secretion systems have been suggested to be mechanisms of pathogenicity

of P. ananatis and P. agglomerans, respectively (De Maayer et al., 2011; Barash and Manulis-Sasson,

2009). In gall-forming P. agglomerans as well as numerous other bacterial pathogens, the type III secretion

system is well-described as a sort of ‘nanosyringe’ for bacteria to inject host cells with effector proteins

(Barash and Manulis-Sasson, 2009; Records, 2011). The type VI secretion system is the most recently

discovered and the research area continues to be very active; orthologous gene sequences have been

identified in 25% of published bacterial genomes, with suggested roles in pathogenicity, host specificity,

and both cooperative and competitive interactions with other bacteria (Records, 2011). One suggested

function of the type VI secretion system, the delivery of lytic enzymes, may potentially be the mode of

pathogenicity employed by some onion-pathogenic P. ananatis and P. agglomerans (De Maayer et al.,

2011), though these pathogens still need to be thoroughly investigated for this to be confirmed. Type VI

secretion systems have additionally been implicated in the secretion of bacterially-synthesized

antimicrobials, which may be particularly relevant for P. ananatis and P. agglomerans, which have been

shown to produce a variety of antibacterial compounds (De Maayer et al., 2011; Pusey et al., 2008). In

addition to antibiotic production and potential type VI effectors, strains of both Pantoea species of

bacteria have been demonstrated to produce indole-3-acetic acid (IAA) or auxin, a plant hormone typically

involved in plant cell wall loosening and plant tissue elongation (Enya et al., 2007; Barash and Manulis-

Sasson, 2009). Both P. ananatis and P. agglomerans employ quorum-sensing to coordinate population

responses to their hosts (Barash and Manulis-Sasson, 2009; Morohoshi et al., 2007), which may also

contribute to the virulence of these organisms.

It is not unusual to isolate up to four different bacterial species from onion bulbs and leaves

(Gitaitis et al., 2003; Pfeufer, observation), and potential pathogens may even be isolated from seemingly

asymptomatic tissue. Secondary bacterial pathogens may proliferate after the primary infection has

occurred, which may especially be true during harvest, postharvest transport, and storage, which present

ample opportunity for tissue injury. Secondary pathogens add a layer of complexity to the management

of onion bulb rots, because different pathogens may require different interventions throughout the

season, depending on inoculum source and overall pathogen pressure.

10

Current integrated management of onion in PA

Disease management

Standard practices employed by growers to reduce the incidence of center rot and other onion

bulb rots involve cultural as well as chemical strategies. Cultural strategies include altering plant spacing

(Gugino and Hoepting, unpublished), using drip as opposed to overhead irrigation (Gitaitis et al., 2004),

crop rotation, managing soil fertility (Mohan, 2008a), using different types of plastic mulch (Gitaitis et al.,

2004; B.K. Gugino, unpublished), and performing weed control around the onion field. Chemical strategies

are mainly composed of frequent copper applications in combination with ethylene-bis-dithiocarbamate

(EBDC) fungicides (Gent and Schwartz, 2008a). Unfortunately, chemical methods are only marginally

successful, partially as a result of their protectant nature but also because these materials have no effect

on the pathgens once plant tissue is invaded. In addition, copper-tolerant strains of P. ananatis have been

isolated from onion plants in commercial fields in Georgia (Nischwitz et al., 2007), suggesting that resistant

strains may have developed in other areas where copper is relied heavily upon for in-season management.

Additional concerns about the accumulation of copper in soil and its potential effect on nonpathogenic

soil microbes (Giller et al., 1998) indicate a need for safer, more effective management strategies.

A spectrum of susceptibility to center rot exists within released onion cultivars (Gent and

Schwartz, 2008a), however, none of the lower-susceptibility cultivars are horticulturally desirable to the

majority of vegetable markets in PA as a result of grower involvement in the Simply Sweet® program.

Growers who anticipate widespread bacterial epidemics in their fields are likely to harvest early, forfeiting

the harvest of jumbo and colossal bulbs, which are more valuable at market. In addition, these growers

will sell their crops earlier from storage to avoid latent bulb decay from bacterial pathogens, shortening

the product’s storage life and reducing profits. Even though Simply Sweet® onions are not intended for

long-term storage, those held in storage longer have higher value than others when sold to wholesalers

and at market (Gugino, pers. communication).

As previously mentioned, both P. ananatis and P. agglomerans are bacterial species that are

common in the environment (Gent and Schwartz, 2008a; 2008b) and may survive epiphytically on onion

hosts in relatively high (105 CFU / g of tissue) concentrations. In PA, many onion growers plant transplants

grown and imported from Texas and Arizona, and the potential exists for pathogenic P. ananatis and P.

agglomerans strains to occur on such transplants. Growers who locally start their onions from seed remain

at risk for initiating center rot epidemics, even though local transplants do not undergo the same transport

stresses as imported transplants, since P. ananatis may be seed-transmitted (Goszczynska et al., 2006;

11

Walcott et al., 2002). In terms of winter survival, P. ananatis and P. agglomerans have been isolated as

epiphytes from perennial weeds surrounding agricultural fields (Gitaitis et al., 2002).

In addition to biotic factors, environmental variables impacting grower fields may serve to

exacerbate center rot epidemics. High rainfall and high humidity may be associated with disease

development, because bacteria proliferate more quickly in moist environments and rain splash may aid in

dispersal, in addition to promoting lush susceptible growth in the host plant (Schwartz et al., 2003). During

four seasons of growing onions and observing grower fields, it has been noted that low-lying areas within

onion fields regularly have higher incidences of bacterial disease (Pfeufer and Gugino, unpublished; C.

Hoepting, Extension Educator at Cornell University, pers. comm.), but whether this is due to standing

water, accumulation of fertilizer runoff, or some combination of factors is uncertain. Given that multiple

sources of inoculum may exist before and during the growing season, and several opportunities to lessen

the impact of environmental factors exist, it is imperative that growers implement integrated

management strategies to manage disease at all times prior to, during, and after the season.

As noted above, bulb infections are difficult to control as a result of their inaccessibility:

protectant, non-systemic chemicals may never access their target pathogens if the microbes are protected

by layers of host tissue. Both P. ananatis and P. agglomerans are facultative anaerobes (Gavini et al., 1989;

Mergaert et al., 1993), making sweet onion bulbs a particularly hospitable niche, providing protection

from the environment and competitors as well as an ample water and carbon source. Several

environmental conditions that are beneficial to onion growth, that is, warm temperatures, high humidity,

and transfer of plant nutrients from leaves into the bulb may also favor pathogen proliferation.

Plant defense: inducing compounds and microbial associations

With poor efficacy of the grower-standard copper-ethylene-bis-dithiocarbamate chemical sprays,

growers are interested in alternatives that may provide better management of bacterial rots of onion.

Plants are equipped with constitutive and inducible defense systems that are unlike the mammalian

immune system, but still may confer effective disease resistance. Constitutive defenses are oftentimes

structural; plant cell walls and plant-synthesized antimicrobial compounds found naturally in tissue are

two examples (Balmer et al., 2013). Inducible defense systems are triggered by stepwise plant perception

of microbes, through microbial- or pathogen-associated molecular pattern (MAMP or PAMP) recognition

by plant transmembrane receptors, termed PAMP triggered immunity, followed by pathogen effectors

binding to host proteins within the cell and encoded by R genes, which is termed effector triggered

12

immunity (Jones and Dangl, 2007). Effector triggered immunity then activates hypersensitive responses,

systemic acquired resistance (SAR), and/or induced systemic resistance (ISR).

Systemic acquired resistance, or SAR, is one type of inducible defense system in which salicylic

acid (SA), a plant-synthesized defense signaling molecule, activates plant defenses against new infections

(van Wees et al., 2006; Walters et al., 2005). SAR nonspecifically increases defenses in plant tissue distal

to the infection point, which is typically long-lasting and effective primarily against biotrophic pathogens

(Balmer et al., 2013; Spoel et al., 2007; van Wees et al., 2000). Synthetic analogs of SA, such as acibenzolar-

S-methyl (ASM), are commercially available as plant defense-inducing products marketed to growers. In

addition, proteins modeled after pathogen effectors that induce SAR have also been synthesized in order

to be used as defense inducers. For instance, harpin protein homologues are employed by several plant

pathogenic strains of bacteria, including Erwinia amylovora, the fire blight pathogen of apple (Wei et al.,

1992), causal agents of soft rots (Nasser et al., 2005) and Pantoea stewartii subsp. stewartii (Ahmad et al.,

2001). Harpin protein is now mass-produced and marketed commercially as a plant defense inducing

product, and has also been advertised as a means to increase marketable yields in several crops (Employ

label, 2011; http://www.kellysolutions.com/erenewals/documentsubmit/KellyData%5CVA%5Cpesticide

%5CProduct%20Label%5C71771%5C71771-3%5C71771-3_EMPLOY_12_2_2010_4_41_08_PM.pdf).

Though monocots and dicots have been shown to possess many of the same defense-related genes,

differences between plants’ SAR responses have been noted, such as instances of a lack of SA upregulation

in barley following infection and constitutively high SA levels in rice (Balmer et al., 2013). However, SA

treatment in onion was demonstrated to increase callose deposition in response to infection of Botrytis

spp. (Poliakovskiy and Dmitriev, 2011).

Induced systemic resistance (ISR) is similar to SAR in terms of the results it confers to plants,

however, the two defense responses have little else in common. ISR is typically triggered by

nonpathogens, such as rhizospheric associations with plant growth-promoting rhizobacteria (PGPR) or

arbuscular mycorrhizal fungi (AMF; Balmer et al., 2013; Liu et al., 2007). This results in an upregulation of

the signaling molecule jasmonic acid as well as the plant hormone ethylene, which activate defense

cascades against necrotrophic pathogens and insect pests (Spoel et al., 2007; Van Loon, 2007). ISR, like

SAR, may differ between monocots and dicots, however, in one case, Bacillus cereus – induced ISR was

effective at suppressing Botrytis elliptica for up to ten days post application in Lilium formanosum, which

was attributed to heat-labile eliciting factors produced by the bacteria, which remained effective even

after the bacteria were rendered nonviable by autoclaving (Liu et al., 2008).

13

Plant induced defenses regulated by the induction of SAR may come at the cost of reduced yields

as a result of a potential deficit in the plants’ metabolic resources in order to maintain high levels of

defense proteins (Gent and Schwartz, 2005; Louws et al., 2001; Romero et al., 2001; Walters and

Fountaine, 2009). The reduced-yield effect may be especially pronounced, as product labels warn, during

periods of plant stress. Some mitigation of the yield reduction effect has been reported by the use of PGPR

in amaranthus (Nair et al., 2006) and tomato (Obradovic et al., 2005), so combinations of SAR inducers

and plant-growth promoters may provide consistent disease control while still producing profitable yields.

In addition to direct ISR induction, both PGPR and AMF may alternatively serve to reduce plant nutrient

stress by way of their suggested roles of enhancing nutrient uptake. These additional nutrients could allow

plants to devote more resources to withstand bacterial ingress or mitigate yield reduction effects when

used in combination with plant defense inducers. While AMF colonization was shown to be delayed in SA-

overproducing tobacco in one study, the final level of AMF colonization between wild-type and mutant

plants did not differ (Herrera Medina et al., 2003). These studies suggest complicated interactions

between PGPR, AMF, and defense-signaling pathways, and relatively little research has investigated field

interactions between these organisms and commercial defense-inducing products.

Thrips

In addition to bacterial diseases, onions grown in PA are exposed to herbivory from several

different types of insects, including onion maggot, yellow striped army worm, and black cutworm;

however, the most significant insect pest of onions in the Mid-Atlantic is onion thrips. Thrips are small

(0.5 – 2 mm) insects that are polyphagous pests to many agricultural crops. The thrips lifecycle has two

feeding larval stages followed by the non-feeding pre-pupa and pupa stages, and a feeding adult phase.

Eggs are laid by adults within plant tissues, with larvae emerging a few days later (Alston and Drost, 2008;

Morse and Hoddle, 2006). It is assumed that larvae often feed on the same plant on which they were

hatched, as their wings are not yet developed. Pupal stages occur in the soil beneath the plant, from which

a winged thrips adult emerges. A single thrips individual may complete its entire lifecycle in as little as 14

days, if climatic conditions are warm and humid, but heavy rain does not occur. Thrips feed on plant leaves

and flowers using their ‘punch-and-suck’ mouthparts (Alston and Drost, 2008); the resulting feeding

symptoms are commonly referred to as ‘silvering’ of leaves or flowers, which appears as damage to

superficial layers of tissue. In addition to photosynthetic reduction and plant injury, over 20 species of

thrips are known to vector tospoviruses, including iris yellow spot virus, which are some of the most

economically damaging viruses worldwide (Morse and Hoddle, 2006).

14

Onion thrips, Thrips tabaci Lindeman, have been reported as the primary problematic insect

species for onion production in New York (Shelton et al., 2006), and varying levels of thrips damage were

found on all 32 PA farms surveyed in 2011 and 2012 (Pfeufer and Gugino, unpublished). Western flower

thrips and onion thrips have been demonstrated to vector P. ananatis and P. agglomerans in Georgia

(Wells et al., 2002; Gitaitis et al., 2003; Dutta et al., 2012, 2014), in addition to iris yellow spot virus (Gent

et al., 2006), which illustrates why thrips management for onions may have more significant impacts than

solely yield concerns. Thrips are difficult to identify to species as a result of their small size, plasticity in

morphology, and active lifestyle; in addition, a thorough study of the number and diversity of thrips

species in PA onion fields has never been conducted, and grower awareness of the presence and impact

of thrips on onion yields is lacking.

The goal of this dissertation is to refine integrated management of bacterial rots of onion, the

most locally significant diseases of this crop, to ultimately increase the profitability of producing sweet

onions in Pennsylvania.

Specific objectives are to:

1. Identify sources of bacterial inoculum in and around production fields through the middle of

the onion growing season in Pennsylvania.

2. Elucidate epidemiological relationships in situ among eight potentially pathogenic bacterial

species and environmental or production factors in onion production systems.

3. Identify environmental and management factors associated with high incidence of bacterial

disease in Pennsylvania and New York.

4. Determine the efficacy of plant defense-inducing and growth-promoting products as

alternatives to grower standard, copper-based treatments for the management of center rot

of onion.

5. Determine the influence of the type and timing of nitrogen fertilizer applications on center

rot incidence, severity, and micronutrient content of onions.

Through extension presentations, portions of these results have been disseminated to growers,

and continuing educational opportunities are planned in efforts to expand the grower knowledge base as

well as increase marketable yields of onion in Pennsylvania.

15

References Ahmad, M., Majerczak, D. R., Pike, S., Hoyos, M. E., Novacky, A., Coplin, D. L. 2001. Biological activity of harpin produced by Pantoea stewartii subsp. stewartii. Microbe-Plant Molecular Interactions 14: 1223-1234. Alston, D. G., Drost, D. 2008. Onion thrips (Thrips tabaci). Utah Pests Fact Sheet, Utah State University Extension. Ent-117-08PR. Anderson, P. K., Cunningham, A. A., Patel, N. G., Morales, F. J., Epstein, P. R., Daszak, P. 2004. Emerging infectious diseases of plants: pathogen pollution, climate change, and agrotechnology drivers. Trends in Ecology and Evolution 19: 535 – 544. Araujo, W. L., Marcon, J., Maccheroni, W., van Elsas, J. D., van Vuurde, J. W. L., Azevedo, J. L. 2002. Diversity of endophytic bacterial populations and their interaction with Xylella fastidiosa in citrus plants. Applied and Environmental Microbiology 68: 4906 – 4914. Balmer, D., Planchamp, C., Mauch-Mani, B. 2013. On the move: induced resistance in monocots. Journal of Experimental Botany 64: 1249 – 1261. Barash, I., Manulis-Sasson, S. 2009. Recent evolution of bacterial pathogens: the gall-forming Pantoea agglomerans case. Annual Reviews of Phytopathology 47: 133-152. Bartolo, M. E., Schwartz, H. F., Schweissing, F. C. 1994. Yield and growth response of onion to simulated storm damage. HortScience 29: 1465 – 1467. Bishop, A. L., Davis, R. M. 1990. Internal decay of onions caused by Enterobacter cloacae. Plant Disease 74: 692-694. Bonaterra, A., Marib, M., Casalinib, L., Montesinosa, E. 2003. Biological control of Monilinia laxa and Rhizopus stolonifer in postharvest of stone fruit by Pantoea agglomerans EPS125 and putative mechanisms of antagonism. International Journal of Food Microbiology 84: 93-104. Boyhan, G. E., Kelley, W. T. 2007. Onion Production Guide. UGA Extension. Accessed online June 25, 2014: http://extension.uga.edu/publications/detail.cfm?number=B1198-2 . Bull, C. T., De Boer, S. H., Denny, T. P., Firrao, G., Fischer-Le Saux, M., Saddler, G. S., Scortichini, M., Stead, D. E., Takikawa, Y. 2010. Comprehensive list of names of plant pathogenic bacteria, 1980 – 2007. Journal of Plant Pathology 92: 551 – 592. Butler, S. L., Doherty, C. J., Hughes, J. E., Nelson, J. W., Govan, J. R. W. 1995. Burkholderia cepacia and cystic fibrosis: do natural environments present a potential hazard? Journal of Clinical Microbiology 33: 1001-1004. Costa, E., Teixidó, N., Usall, J., Atarés, E., Viñas, I. 2001. Production of the biocontrol agent Pantoea agglomerans strain CPA-2 using commercial products and by-products. Applied Microbiological Technology 56: 367- 371.

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Coutinho, T. A., Venter, S. N. 2009. Pantoea ananatis: an unconventional plant pathogen. Molecular Plant Pathology 10: 325-335. De Baere, T., Verhelst, R., Labit, C., Verschraegen, G., Wauters, G., Claeys, G., Vaneechoutte, M. 2004. Bacteremic infection with Pantoea ananatis. Journal of Clinical Microbiology 42: 4393 – 4395. De Champs, C., Le Seaux, S., Dubost, J. J., Boisgard, S., Sauvezie, B., Sirot, J. 2000. Isolation of Pantoea agglomerans in two cases of septic monoarthritis after plant thorn and wood sliver injuries. Journal of Clinical Microbiology 38: 460-461. De Maayer, P., Chan, W. Y., Venter, S. N., Toth, I. K., Birch, P. R. J., Joubert, F., Coutinho, T. A. 2010. Genome sequence of Pantoea ananatis LMG20103, the causative agent of Eucalyptus blight and dieback. Journal of Bacteriology 192: 2936 – 2937. De Maayer, P., Venter, S. N., Kamber, T., Duffy, B., Coutinho, T. A., Smits, T. H. M. 2011. Comparative genomic of the type VI secretion systems of Pantoea and Erwinia species reveals the presence of putative effector islands that may be translocated by the VgrG and Hcp proteins. BMC Genomics 12:576. Diaz-Perez, J. C., Purvis, A. C., Paulk, J. T. 2002. Bolting, yield, and bulb decay of sweet onion as affected by nitrogen fertilization. Journal of the American Horticultural Society 128:144-149. Dutta, B., Gitaitis, R., Langston, Avci, U., Barman, A., Srinivasan, R. 2012. Acquisition and transmission of Pantoea ananatis and Pantoea agglomerans (causal agents of center rot of onion) by Thrips tabaci (Thysanoptera: Thripidae). Phytopathology S4:88. Dutta, B., Barman, A. K., Srinivasan, R., Avci, U., Ullman, D., Langston, D. B., Gitaitis, R. 2014. Transmission of Pantoea ananatis and Pantoea agglomerans, causal agents of center rot of onion (Allium cepa L.) by onion thrips (Thrips tabaci Lindeman). Phytopathology; doi: 10.1094/PHYTO-07-13-0199-R. Edens, D. G., Gitaitis, R. D., Sanders, F. H., Nischwitz, C. 2006. First report of Pantoea aggomerans causing a leaf blight and bulb rot of onions in Georgia. Plant Disease 90: 1551. Environmental Protection Agency (EPA). Harpin Protein (006477) Fact Sheet. Updated December 8, 2010. Accessed online, January 31, 2011. http://www.epa.gov/pesticides/biopesticides/ingredients/factsheets/factsheet_006477.htm . Enya, J., Shinohara, H., Yoshida, S., Tsukiboshi, T., Negishi, H., Suyama, K., Tsushima, S. 2007. Culturable leaf-associated bacteria on tomato plants and their potential as biological control agents. Microbial Ecology 53: 524 -536. Ferreira, A., Quecine, M. C., Lacava, P. T., Oda, S., Azevedo, J. L., Araujo, W. L. 2008. Diversity of endophytic bacteria from Eucalyptus species seeds and colonization of seedlings by Pantoea agglomerans. Federation of European Microbiological Societies: Microbiology Letters 287: 8 – 14. Frederickson, D. E., Monyo, E. S., King, S. B., Odvody, G. N. 1997. A disease of pearl millet in Zimbabwe caused by Pantoea agglomerans. Plant Disease 81:8.

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Gavini, F., Mergaert, J., Beji, A., Mielcarek, C., Izard, D., Kersters, K., De Ley, J. 1989. Transfer of Enterobacter agglomerans (Beijerinck 1888) Ewing and Fife 1972 to Pantoea gen. nov. as Pantoea agglomerans comb. nov. and description of Pantoea dispersa sp. nov. International Journal of Systematic Bacteriology 39: 337-345. Gent, D. H., Schwartz, H. F. 2005. Management of Xanthomonas leaf blight of onion with a plant activator, biological control agents, and copper bactericides. Plant Disease 89:631-639. Gent, D. H., du Toit, L. J., Fichtner, S. F., Mohan, S. K., Pappu, H. R., Schwartz, H. F. 2006. Iris yellow spot virus: an emerging threat to onion bulb and seed production. Plant Disease 90: 1468 – 1480. Gent, D. H., Schwartz, H. F. 2008a. ‘Bacterial Stalk and Leaf Necrosis’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 66 - 67. Gent, D. H., Schwartz, H. F. 2008b. ‘Center rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 64 - 66. Giller, K. E., Witter, E., McGrath, S. P. 1998. Toxicity of heavy metals to microorganisms and microbial processes in agricultural soils: a review. Soil Biology and Biochemistry 30: 1389 – 1414. Gitaitis, R., Walcott, R., Culpepper, S., Sanders, H., Zolobowska, L., Langston, D. 2003. Recovery of Pantoea ananatis, causal agent of center rot of onion, from weeds and crops in Georgia, USA. Crop Protection 21: 983-989. Gitaitis, R. D., Walcott, R. R., Sanders, H. F., Zolobowska, L., Diaz-Perez, J. C. 2004. Effects of Mulch and Irrigation System on Sweet Onion: II. The Epidemiology of Center Rot. Journal of the American Society of Horticultural Science 129: 225-230. Goszczynska, T., Moloto, V. M., Venter, S. N., Coutinho, T. A. 2006. Isolation and identification of Pantoea ananatis from onion seed in South Africa. Seed Science and Technology 34: 655-668. Herrera Medina, M. J., Gagnon, H., Piche, Y., Ocampo, J. A., Garcia Garrido, J. M., Vierheilig, H. 2003. Root colonization by arbuscular mycorrhizal fungi is affected by the salicylic acid content of the plant. Plant Science 164: 993-998. Hoepting, C. A. Cornell University extension educator and onion specialist. Personal conversations, April 2012 – present. Kim, H. J., Lee, J. H., Kang, B. R., Rong, X., McSpadden Gardener, B. B., Ji, H. J., Park, C-S., Kim, Y. C. 2012. Draft genome sequence of Pantoea ananatis B1-9, a nonpathogenic plant growth-promoting bacterium. Journal of Bacteriology 194: 729. Lang, J. M., Gent, D. H., and Schwartz, H. F. 2007. Management of Xanthomonas leaf blight of onion with bacteriophages and a plant activator. Plant Disease 91:871-878. Lee, H.B., Hong, J. P., Kim, S. B. 2010. First report of leaf blight caused by Pantoea agglomerans on rice in Korea. Plant Disease 94: 1372.

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Liu, J., Maldonado-Mendoza, I., Lopez-Meyer, M., Cheung, F., Town, C. D., Harrison, M. J. 2007. Arbuscular mycorrhizal symbiosis is accompanied by local and systemic alterations in gene expression and an increase in disease resistance in the shoots. The Plant Journal 50: 529-544. Liu, Y-H., Huang, C-J., Chen, C-Y. 2008. Evidence of induced systemic resistance against Botrytis elliptica in lily. Phytopathology 98: 830 – 836. Louws, F. J., Wilson, M., Campbell, H. L., Cuppels, D. A., Jones, J. B., Shoemaker, P. B., Sahin, F., Miller, S. A. 2001. Field control of bacterial spot and bacterial speck of tomato using a plant activator. Plant Disease 85:481-488. Ma, B., Hibbing, M. E., Kim, H.-S., Reedy, R. M., Yedidia, I., Breuer, J., Breuer, J., Glasner, J. D., Perna, N. T., Kelman, A., Charkowski, A. O. 2007. Host range and molecular phylogenies of the soft rot enterobacterial genera Pectobacterium and Dickeya. Phytopathology 97: 1150 - 1163. Maher, E. A., Kelman, A. 1983. Oxygen status of potato tuber tissue in relation to maceration by pectic enzymes of Erwinia carotovora. Phytopathology 73: 536 – 539. Mann, J. D. 1983. Translocation of photosynthate in bulbing onions. Australian Journal of Plant Physiology 10: 515-521. Membre, J. M., Burlot, P. M. 1994. Effects of temperature, pH, and NaCl on growth and pectinolytic activity of Pseudomonas marginalis. Applied Environmental Microbiology 60: 2017 – 2022. Mergaert, J., Verdonck, L., Kersters, K. 1993. Transfer of Erwinia ananas (synonym, Erwinia uredovora) and Erwinia sterwartii to the Genus Pantoea emend. as Pantoea ananas (Serrano 1928) comb. nov. and Pantoea stewartii (Smith 1898) comb. nov., respectively, and description of Pantoea stewartii subsp. indologenes subsp. nov. International Journal of Systematic Bacteriology 43: 162-173. Mohan, S. K. 2008a. ‘Other Bacterial Soft Rots’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 62. Morales-Valenzuela, G., Silva-Rojas, H. V., Ochoa-Martinez, D., Valadez-Moctezuma, E., Alarcon-Zuniga, B., Zelaya-Molina, L. X., Cordova-Tellez, L., Mendoza-Onofre, L., Vaquera-Huerta, H., Carballo-Carballo, A., Farfan-Gomez, A., Avila-Quezada, G. 2007. First report of Pantoea agglomerans causing leaf blight and vascular wilt in maize and sorghum in Mexico. Plant Disease 91: 1365. Morohoshi, T., Nakamura, Y., Yamazaki, G., Ishida, A., Kato, N., Ikeda, T. 2007. The plant pathogen Pantoea ananatis produces N-acylhomoserine lactone and causes center rot disease of onion by quorum sensing. Journal of Bacteriology 189: 8333-8338. Morse, J. G., Hoddle, M. S. 2006. Invasion biology of thrips. Annual Review of Entomology 51: 67-89. Nair, C. B., Anith, K. N., Sreekumar, J. 2007. Mitigation of growth retardation effect of plant defense activator, acibenzolar-S-methyl, in amaranthus plants by plant growth-promoting rhizobacteria. World Journal of Microbiological Technology 23: 1183-1187.

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Nasser, W., Reverchon, S., Vedel, R., Boccara, M. 2005. PecS and PecT coregulate the synthesis of HrpN and pectate lyases, two virulence determinants in Erwinia chrysanthemi 3937. Molecular Plant-Microbe Interactions 18:1205-1214. Nault, B. Cornell University research and extension entomologist. Personal conversation, February 2012. Nischwitz, C., Gitaitis, R., Sanders, H., Langston, D., Mullinix, B., Torrance, R., Boyhan, G., Zolobowska, L. 2007. Use of fatty acid methyl ester profiles to compare copper-tolerant and copper-sensitive strains of Pantoea ananatis. Phytopathology 97: 1298-1304. Obradovic, A., Jones, J. B., Momol, M. T., Olson, S. M., Jackson, L. E., Balogh, B., Guven, K., Iriarte, F. B. 2005. Integration of biological control agents and systemic acquired resistance inducers against bacterial spot on tomato. Plant Disease 89:712-716. Oregon State Vegetable Production Guides. 2004. ‘Dry Bulb Onions.’ Accessed online June 26, 2014: http://nwrec.hort.oregonstate.edu/onionb-w.html#top . Orloff, S., Natwick, E. T., Poole, G. J. 2013. Onion and Garlic Guidelines: Insects and Mites. UC-IPM Online: Statewide Integrated Pest Management Program. http://www.ipm.ucdavis.edu/PMG/pmgauthors.html . Pennsylvania Department of Public Welfare. ‘Onions.’ PA Nutrition Education Network: Volume I, Issue 16. Accessed online May 16, 2014: http://www.panen.org/sites/default/files/SNAC%20Materials/onion_newsletter2.pdf Pennsylvania Vegetable Growers Association (PVGA). Updated December 3, 2010, under ‘Services.’ Accessed online January 25, 2011: http://www.pvga.org/ . Poliakovskiy, S. O., Dmitriev, O. P. 2011. Study of priming for callose accumulation in Allium cepa during treatment with biotic inducers. Cytology and Genetics: 245 - 248. Pusey, P. L., Stockwell, V. O., Rudell, D. R. 2008. Antibiosis and acidification by Pantoea agglomerans strain E325 may contribute to suppression of Erwinia amylovora. Phytopathology 98: 1136 – 1143. Records, A. R. 2011. The type VI secretion system: a multipurpose delivery system with a phage-like machinery. Molecular Plant-Microbe Interactions 24: 751 – 757. Romero, A. M., Kousik, C. S., Ritchie, D. F. 2001. Resistance to bacterial spot in bell pepper induced by acibenzolar-S-methyl. Plant Disease 85:189-194. Schroeder, B. K., Waters, T. D., du Toit, L. J. 2010. Evaluation of onion cultivars for resistance to Enterobacter cloacae in storage. Plant Disease 94:236-243. Schwartz, H. F., Otto, K. L., Gent, D. H. 2003. Relation of temperature and rainfall to development of Xanthomonas and Pantoea leaf blights of onion in Colorado. Plant Disease 87:11-14. Schwartz, H. F., Mohan, S. K., Havey, M. J., Crowe, F. J. 2008. Introduction in: Compendium of Onion and Garlic Diseases. Pp. 1 – 7. APS Press: St. Paul, MN.

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Shelton, A. M., Zhao, J. Z., Nault, B. A., Plate, J., Musser, F. R., Larentzaki, E. 2006. Patterns of insecticide resistance in onion thrips (Thysanoptera: Thripidae) in onion fields in New York. Journal of Economic Entomology 99: 1798 - 1804. Smith, R., Biscaro, A., Cahn, M., Daugovish, O., Natwick, E., Nunez, J., Takele E., Turini, T. 2011. Fresh-market bulb onion production in California. UC Vegetable Research and Information Center. Publication 7242. Smith, D. D. N., Kirzinger, M. W. B., Stavrinides, J. 2013. Draft genome sequence of the antibiotic-producing epiphytic isolate Pantoea ananatis BRT175. American Society for Microbiology Genome Announcements 1: 1-2. Spoel, S. H., Johnson, J. S., Dong, X. 2007. Regulation of tradeoffs between plant defenses against pathogens with different lifestyles. Proceedings of the National Academy of Sciences 104: 18842 – 18847. Stoltzfus, J. Eastern Lancaster County School District Adult Educator. Personal communication April 2011 – present. United States Department of Agriculture (USDA) – National Agricultural Statistics Service. Statistics by Subject. Accessed online (Jan. 29, 2013): http://www.nass.usda.gov/Statistics_by_Subject/index.php?sector=CROPS . University of Minnesota. ‘Introduction to Thrips.’ Accessed online November 2011- January 2012: http://www.entomology.umn.edu/cues/inter/inmine/index.html . Van Loon, L. C. 2007. Plant responses to plant growth-promoting rhizobacteria. European Journal of Plant Pathology 119: 243-254. van Wees, S. C. M., de Swart, E. A. M., van Pelt, J. A., van Loon, L. C., Pieterse, C. M. J. 2000. Enhancement of induced disease resistance by simultaneous activation of salicylate- and jasmonate-dependent defense pathways in Arabidopsis thaliana. Proceedings of the National Academy of Sciences 97: 8711-8716. Volksch, B., Thon, S., Jacobsen, I.D., Gube, M. 2009. Polyphasic study of plant and clinic associated Pantoea agglomerans reveals indistinguishable virulence potential. Infection, Genetics, and Evolution 9:1381-1391. Walcott, R. R., Gitaitis, R. D., Castro, A. C., Sanders, F. H., Jr., and Diaz-Perez, J. C. 2002. Natural infestation of onion seed by Pantoea ananatis, causal agent of center rot. Plant Disease 86:106-111. Walters, D. R., Fountaine, J. M. 2009. Practical application of induced resistance to plant diseases: an appraisal of effectiveness under field conditions. Journal of Agricultural Science 147: 523 – 535. Walters, D., Walsh, D., Newton, A., Lyon, G. 2005. Induced resistance for plant disease control: maximizing the efficacy of resistance elicitors. Phytopathology 95:1368-1373. Wei, Z. M., Laby, R. J., Zumoff, C. H., Bauer, D. W., He, S. Y., Collmer, A., Beer, S. V. 1992. Harpin, elicitor of the hypersensitive response produced by the plant pathogen Erwinia amylovora. Science 257: 85-88.

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Wells, M. L., Gitaitis, R. D., Sanders, F. H. 2002. Association of tobacco thrips, Frankliniella fusca (Thysanoptera: Thripidae), with two species of bacteria of the genus Pantoea. Annals of the Entomological Society of America 95: 719-723. Wright, P. J., Hale, C. N. 1992. A field and storage rot of onion caused by Pseudomonas marginalis. New Zealand Journal of Crop and Horticultural Science 20: 435 – 438. Wright, S. A. I., Zumoff, C. H., Schneider, L., Beer, S. V. 2001. Pantoea agglomerans strain EH318 produces two antibiotics that inhibit Erwinia amylovora in vitro. Applied Environmental Microbiology 67: 284 – 292. Yamamoto, S., Kasai, H., Arnold, D. L., Jackson, R. W., Vivian, A., Harayama, S. 2000. Phylogeny of the genus Pseudomonas: intrageneric structure reconstructed from the nucleotide sequences of gyrB and rpoD genes. Microbiology 146: 2385 – 2394. Yishay, M., Burdman, S., Valverde, A., Luzzatto, T., Ophir, R., Yedidia, I. 2008. Differential pathogenicity and genetic diversity among Pectobacterium carotovorum ssp. carotovorum isolates from monocot and dicot hosts support early genomic divergence within this taxon. Environmental Microbiology 10: 2746 – 2759. Zook, D. PA onion grower and board member of Lancaster County onion cooperative. Personal communication April 2011 – present.

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Chapter 2: Sources of bacterial inoculum in and around transplanted onion (Allium cepa) fields in a plastic mulch production system

Abstract

Exclusion of pathogen inoculum from the production system is one of the foremost strategies for

managing bacterial diseases, particular in vegetable production. To determine the prevalent bacterial

pathogens of onion in PA, where growers may suffer yield losses of up to 60% due to several rot diseases,

and help define probable inoculum sources, extensive surveys were undertaken on 28 farms in 2011 and

26 farms in 2012, respectively. Environmental data and plant samples were gathered three times through

the growing season each year, with PCR-facilitated bacterial species detections in extracted samples as

well as isolations of viable bacteria from multiple sources. Two types of pathogenicity tests were

conducted with selected isolates from each potential source. Pathogenic isolates of Pectobacterium

carotovorum subsp. carotovorum, Pantoea agglomerans, and Pseudomonas marginalis pv. marginalis, the

most common pathogens in the PA onion cropping system, occurred in soil, transplant and weed tissues,

in addition to being present on the surfaces of both onion transplants and common weeds. More specific

associations were suggested between P. marginalis and transplants as well as P. carotovorum and P.

agglomerans and weeds. In addition, rep-PCR facilitated strain tracking of Pantoea ananatis indicated

matching strains isolated from surface-disinfested weed tissue collected at mid-season and a latently

infected onion that had been stored for four months. These results suggest research avenues for more

directed disease management strategies for reducing the impact of environmental inoculum sources on

bacterial rots of onion.

Introduction

Exclusion of pathogens from cropping systems is one of the primary methods for the management

of plant diseases. With low efficacy of chemical control methods, reducing primary inoculum is a

cornerstone of effective bacterial disease management in vegetables (Gitaitis et al., 1992; De Leon et al.,

2011). In order to successfully exclude pathogens, sources of bacterial inoculum must first be known.

Examples of exclusionary pathogen control strategies include the surface-sterilization of vegetative

propagation tools in managing TMV in petunia (Lewandoski et al., 2012) and tomato seed-cleaning

techniques in the case of Clavibacter michiganensis subsp. michiganensis (Ivey and Miller, 2004).

Bacterial rots of onion (Allium cepa L.) are the most significant diseases affecting commercial

production in the Mid-Atlantic and Northeast regions. Up to nine different species of bacteria have been

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shown to induce rot of onions in Pennsylvania, several of which are ubiquitous and inhabit multiple

environmental niches, in addition to causing crop disease. These include the center rot pathogens,

Pantoea ananatis Serrano and Pantoea agglomerans Beijerinck (Pagg), the soft rot pathogens,

Pectobacterium carotovorum subsp. carotovorum Jones (Pcar) and Pseudomonas marginalis pv.

marginalis Stevens (Pmar), and the slippery and sour skin pathogens, Burkholderia gladioli pv. alliicola

Burkholder and Burkholderia cepacia Burkholder, respectively. In addition, the leaf pathogens

Pseudomonas viridiflava Burkholder and Xanthomonas axonopodis pv. allii Hasse, and the storage decay

pathogen Enterobacter cloacae Jordan (Bull et al., 2010), also occur in the pathosystem, albeit

infrequently. It is not unusual to detect and isolate as many as four different pathogenic bacterial species

from a single symptomatic onion, and particular species typically do not induce diagnostic symptoms.

Based on previous work, different sources of bacterial inoculum have been suggested in onion

pathosystems, including B. cepacia from soil (Coenye and Vandamme, 2003), and P. ananatis and P.

viridiflava from the surfaces of perennial weeds (Gitaitis et al., 1998; 2002). In PA, the majority of onions

grown are transplanted into the field; transplants are produced in the southern U.S. or increasingly, locally

in greenhouses as plug plants. At least one of the previously mentioned pathogens, P. ananatis, has been

shown to be naturally seed-transmitted (Walcott et al., 2002), and since shipped transplants are injured

at least twice in the forms of root and leaf trimming, southern-U.S. transplants may potentially serve as

an inoculum source. Transplants have previously been shown to be sources of bacterial inoculum in other

plant pathosystems (Cuppels and Elmhirst, 1999; Gitaitis et al., 1992).

PCR-based detection strategies exist for several of the plant pathogens referenced above (Walcott

et al., 2002; De Paula Lana et al., 2012; Beer, pers. comm.), however, these current strategies only resolve

to the species level. Genomic fingerprinting methods have been employed as subspecies and strain-level

detection strategies in both environmental microbiology (Albert et al., 2003; Ishii and Sadowsky, 2009)

and plant pathology research (Louws et al., 1994; Lange et al., 2006). In particular, Lange et al. used rep-

PCR to track bacterial strains of Xanthomonas campestris pv. campestris, the black rot pathogen of

cabbage, from cruciferous weeds into diseased cabbage crops (2006). The efficacy of using genomic

fingerprinting for bacterial strain tracking, however, is reliant on several factors, including the number of

bands amplified, the analytical methods used, and the inherent genetic diversity in the target species

(Albert et al., 2003).

To identify potential sources of bacterial inoculum in and around sweet onion fields, extensive

surveys were undertaken on 28 and 26 farms in 2011 and 2012, respectively. Using a multiplex PCR

protocol, detections of eight species of bacteria were sought in soil, on or in transplants and weeds, and

24

in symptomatic onions obtained at harvest and during storage. Simultaneously, bacterial isolations from

the samples resulted in a database of over 2500 bacterial isolates from PA from two sample years; select

isolates were then assayed for their ability to induce disease in two different pathogenicity tests as well

as used in a rep-PCR based strain tracking protocol.

Materials and Methods

Sample collection: In 2011 and 2012, 28 and 26 farms, respectively, were visited three times each over

the course of the onion growing season. Farms were selected with the assistance of regional extension

educators; all PA growers grew ‘Candy’ onions (a sweet, yellow cultivar intended for fresh eating) on

raised beds with plastic mulch and two rows of drip irrigation. Fields ranged between 0.25 - 1 hectare in

size, and were actively crop rotated. Some PA growers had been growing onions for as many as ten years,

however, a first-year grower was included in each survey year. There were 24 repeat growers between

both years, but the fields where the onions were grown were not the same, with the exception of two

farms.

Sample visit 1: In April/May of each year, characteristics of each production field were recorded, including

type of plastic mulch used, spacing between plants, approximate field size, general fertilizer information,

and grower approaches to disease and weed management. Three 9.14 m plots were established by

flagging an area of the field visually estimated to be representative of the entire field with respect to field

length, width, and topography. Each plot was one bed wide, with typical bed width of approximately one

meter. Composite soil samples were collected from each plot (six samples equidistantly through the plot,

using a soil probe 2.54 cm in diameter to a depth of 7.6 cm for each sample). Composite samples of

approximately 30 onion plants, cultivar ‘Candy,’ were collected from growers prior to transplanting into

the field.

Sample visit 2: In approximately the middle of the growing season (second and third weeks of June in PA)

each year, five different, prevalent weeds were sampled from within or in close proximity to one of the

plots established in visit 1, placed in individual sealed plastic bags, and stored on ice, transported to the

lab, and then stored at 2⁰C until further processing. The time from collection until further processing was

generally within seven days.

25

Sample visit 3: Visits were timed as closely as possible to when growers began harvesting their full crop.

Soil was sampled according to the protocol described in visit 1, and the inner two rows of the inner 4.6 m

of each plot were harvested, graded by size, and evaluated for bacterial disease incidence (approx. 60

bulbs). Onions were graded into four size categories based on the bulb diameter: < 6.4 cm diameter are

graded small, 6.4-7.6 cm diameter are graded medium, 7.6-10.2 cm diameter are graded jumbo, and >10.2

cm diameter are graded colossal. In 2011 and 2012, 20% and 50% of the symptomatic bulbs at harvest,

respectively, were retained for further processing. Approximately 30 jumbo-size, asymptomatic bulbs

were retained for postharvest storage evaluation. If 30 jumbo-size, asymptomatic bulbs were not

available, 30 representatively-sized bulbs from the plot were sampled.

Postharvest bulb ratings

In both years, approximately 30 asymptomatic, jumbo-size onions per replicate plot were cured

under burlap in a greenhouse with forced air for at least 72 hours, then placed in 4⁰C storage for 75-120

days (depending on harvest date). In mid-late November of the harvest year, approximately four months

postharvest, the bulbs were sliced in half longitudinally, photographed, and evaluated for disease

incidence, denoted as a percentage of the 30 bulbs per replicate plot. In 2011 and 2012, 20% and 50% of

the symptomatic bulbs from storage, respectively, were retained for further processing.

Bacterial isolations from soil

Seven months (2011) or one week (2012) after soil sampling, one gram of soil was shaken for one

hour in phosphate buffered saline (Kphos buffer: 0.05M K2HPO4, 0.5M KH2PO4, 0.85% NaCl, pH 7.0), then

the supernatant was serially diluted onto King’s B medium (KB; King et al., 1954) to obtain single colonies.

After selecting the dilution, 100 µL was spread-plated on KB medium in 2011 or onion extract medium

(OEM; Zaid et al., 2012) in 2012. Plates were incubated for two days in a laboratory at ambient (21 – 23⁰C)

temperature, after which single colonies were streaked onto KB medium and allowed to grow 1 – 2 days.

Each isolate was numbered, photographed, and its source material and location were recorded. Isolates

were stored by individually transferring a single colony from these plates to sterile glass test tubes

containing 4 mL Luria-Bertani broth (LB; Difco Luria-Bertani broth, Miller, Becton, Dickinson and Co.,

Sparks, MD, USA) and incubating at 30⁰C with shaking (150 rpm) overnight. Sterile glycerol was added to

log-phase broth cultures to establish a 15% concentration of glycerol in cryovials (Denville Scientific,

Metuchen, NJ, USA), which were then maintained at -20⁰C. Each isolate was frozen in duplicate, and boxes

26

of frozen cultures were maintained in two separate locations. Leftover soil samples were retained in their

labeled bags at 4⁰C.

Bacterial isolations from transplants and weeds

Within eight days of sampling, roots were removed from a sample of transplants (approximately

25) and agitated in 200 mL sterile Kphos buffer (0.1% Tween-20) in 500 mL or 1 L flasks for 1 hr at 150

rpm. Aliquots of 50 mL were removed for DNA extraction, bacterial isolation, and archiving at -20⁰C. After

identification of the weed to genus (and species, if possible, using Uva et al., 1997), roots were removed

from each weed sample, then samples were individually combined with one mL sterile Kphos buffer / g

fresh weight plant tissue with 0.1% Tween-20, then agitated in sterile 500 mL or 1 L flasks for 1 hr at 150

rpm.

To obtain epiphytic bacteria from onion transplants and weeds, buffer fractions were serially

diluted, plated on KB to select the appropriate dilution to grow 20 - 200 colonies (typically 10-5 – 10-7),

then 100 µL was spread-plated on KB medium (transplants and 2011 weeds) or OEM (2012 weeds).

Bacterial isolations were conducted following the soil isolation protocol described above, to obtain

isolates archived in 15% glycerol and maintained at -20⁰C. Unused portions of epiphytic Kphos buffer

washes were archived at -20⁰C.

On the day of fractionation of the epiphytic sample, endophytic bacteria from transplant and

weed samples were obtained by washing the plants twice in 70% ethanol, then combining with sterile

Kphos buffer to the equivalent of 1 mL / g fresh tissue. Plant samples were then homogenized in a Waring

blender for 1 min. Aliquots of plant slurries were transferred to three sterile 50 mL centrifuge tubes for

DNA extraction, bacterial isolation, and archiving at -20⁰C. To obtain bacterial isolates, one mL of

transplant slurry was serially diluted, plated on KB to select the appropriate dilution, then 100 µL of the

appropriate dilution was spread on KB medium (transplants) or OEM (2012 weeds) using the protocol

described above and maintained at -20⁰C. The Waring blender was rinsed with water, then 70% ethanol

before homogenizing each plant sample.

Bacterial isolations from harvest and postharvest symptomatic onions

After each of the harvest and postharvest ratings, 20% or one bulb (whichever was greater, in

2011), or 50% or one bulb (whichever was greater, in 2012) of the symptomatic onions were

photographed and approximately 0.5 g of tissue was removed from the margin between symptomatic and

asymptomatic areas. Duplicate samples were removed from the same area and each was transferred to

27

sterile 1.8 mL Eppendorf tubes; one sample was used in the DNA extraction protocol and the other sample

was used for bacterial isolations. The isolation sample was ground with a sterile micropestle with an

additional 500 µL of sterile Kphos buffer, then serially diluted onto KB. Then 100 µL of the appropriate

dilution was spread-plated on KB to select single isolates to be maintained in duplicate (as described

above) at -20⁰C.

Semi-anaerobic pathogenicity tests

Isolates generated from samples from 2011 and 2012 were revived from -20⁰C storage by plating on KB

medium and incubating at 30⁰C for 1-3 days, until colonies were visible. A sterile toothpick was used to

transfer a single colony from the KB plate to a sterile tube containing 4 mL LB broth, then tubes were

placed in a 30⁰C incubator with agitation (150 rpm) overnight. The following day, log-phase broth culture

of each isolate was used to inoculate surface-sterilized (10% NaClO) and completely dry, symptomless,

yellow pearl onions purchased from local grocery stores. Sterile needles and syringes were used to

administer approx. 100 µL log-phase LB broth to two pearl onions by inserting the needle approx. halfway

through the bulb midway between basal plate and neck. These inoculated onions were placed in a

sterilized 200 mL screw-top

jar, one atop the other, and

the lid was screwed closed for

semi-anaerobic pathogenicity

test. These jars were incubated

on a lab benchtop at ambient

room temperature (21 – 23⁰C)

for fourteen days, then pearl

onions were halved on the

inoculation point and rated for

symptom development (0 or 1;

absence or presence; Figs. 2.1

a, b).

Aerobic pathogenicity tests

For aerobic pathogenicity tests, one-half of a surface disinfested, yellow pearl onion was

inoculated by administering approx. 100 µL log-phase LB broth culture through the side of the onion half,

a b

Figs. 2.1a-b. Results of semi-anaerobic pathogenicity tests using nonpathogenic (a) and pathogenic (b) strains.

28

parallel to the full slice. The other half of the onion was left uninoculated. Both halves of the onion were

placed in a sterile glass Petri dish with filter paper that had been moistened by sterile water. Two halved

bulbs per aerobic test were placed in each dish, but bulbs were duplicate pathogenicity tests of the same

isolate. Aerobic tests were incubated on a lab benchtop at ambient room temperature (21 – 23⁰C) for

seven days, then pearl onions were rated (1 – 5) for symptom development; an example of each rating is

shown in Fig. 2.2.

DNA extractions

DNA was extracted directly from soil, transplant epiphyte and endophyte samples, weed epiphyte

and endophyte samples, and symptomatic onion tissue. Soil extractions were completed using a 1 g

sample from the homogenized bag of soil within three weeks of sampling; this was dried for 48 hr in a

forced-air drying oven at 65⁰C. The “Experienced User Protocol” included in the MoBio Ultra Soil DNA kit

(MoBio Laboratories, Inc., Carlsbad, CA) was directly followed, using the vortex attachment option.

Transplant epiphytic and endophytic samples, weed epiphytic samples, and symptomatic harvest

and storage onion samples were processed within two weeks of sampling using the Wizard Genomic DNA

Fig. 2.2. Severity of symptom development in pathogenicity tests (duplicate) under aerobic incubation after seven days. 1 = nonpathogenic; 2 = local discoloration or maceration; 3 = local symptom, plus discoloration or maceration on adjacent scale(s); 4 = up to half of bulb discolored or macerated; 5 = more than 50% of bulb discolored or macerated. The right half of each bulb is inoculated; bulbs were rated individually and average was reported if not identical.

29

Purification kit (Promega, Madison, WI). For epiphytic samples, 50 mL surface wash was centrifuged at

5000 rpm, then the pellet was resuspended in 1 mL sterile Kphos buffer. Transplant endophytic samples

(800 µL) and 0.5 g symptomatic onion tissue were lyophilized for 4 hr at -40⁰C with vacuum (<150 mTorr),

ground, and extracted for DNA using the Promega DNA extraction kit outlined below. Briefly, 600 µL of

Promega Nuclei Lysis Solution was combined with the ground dried tissue, vortexed, and incubated for 30

min at 65⁰C. Next, 200 µL of 10M ammonium acetate (NH4CH3COO) was added, vortexed, and frozen at

-20⁰C for 10 min. Tubes were next centrifuged for 5 min at 13,000 x g, then supernatants were transferred

to sterile tubes with 600 µL isopropanol, which were inverted several times then centrifuged for 5 min at

13,000 x g. Supernatants were decanted, then the pellet was washed with 600 µL 70% ethanol and

centrifuged 1 min at 13,000 x g. The 70% ethanol was decanted and the pellet was dried for 1 hr, followed

by resuspension of the pellet in 100 µL TE buffer (10 mM Tris-HCl containing 1 mM EDTA-Na2, pH 8.0).

Weed endophytic samples were processed within two weeks of sampling using the Qiagen

DNEasy Plant Mini Kit (Qiagen Inc., Valencia, CA). Starting material was 800 µL weed slurry, which was

lyophilized for 4 hr at -40⁰C with vacuum (<150 mTorr), ground, then procedures in the Qiagen kit were

followed without modification.

Duplex PCR for species identification

Bacterial isolates were preliminarily identified to genus based on photographed phenotypic

characteristics. In general, Pseudomonas spp. fluoresce on KB medium, while Pantoea spp. and

Burkholderia spp. appear yellow, and P. carotovorum pv. carotovorum appears more cream-colored. Since

Pantoea spp. are typically more common in PA (Pfeufer, unpublished), phenotypically yellow colonies

were initially screened using the P. ananatis / P. agglomerans primer pairs. Based on these preliminary

identifications, sets of isolates were screened with species-specific primers using an established protocol

(Mansfield and Gugino, 2010). Primers were used in duplex reactions, with the following primer sets

combined and reactions on a thermocycling program with their respective annealing temperature (P.

ananatis and P. agglomerans, 60⁰C; B. gladioli pv. alliicola and B. cepacia, 60⁰C; P. carotovorum pv.

carotovorum and X. axonopodis pv. allii, 62⁰C; P. marginalis pv. marginalis and P. viridiflava, 62⁰C).

Template was approximately 1.5 µL removed directly from the 15% glycerol stock culture from -20⁰C

storage. Other reaction components were 12.5 µL TaqPRO Complete master mix (Denville Scientific,

Metuchen, NJ), 1 µL species 1 forward primer (10 mM), 1 µL species 2 forward primer (10 mM), 1 µL

species 1 reverse primer (10 mM), 1 µL species 2 reverse primer (10 mM), and 7.5 µL PCR water. PCR

conditions were as follows: (1) initial denaturation at 96°C for 10 min, followed by 34 cycles of (2) 99°C

30

for 30 s; (3) 60°C or 62°C for 1 min, (4) 72°C for 1 min; then a final elongation at (5) 72°C for 5 min and

storage at (6) 4°C continuous. Amplification was confirmed with a 1.5% agarose gel electrophoresis.

Specific fragment sizes were as follows: B. gladioli pv. alliicola, 752 bp; X. axonopodis pv. allii, 715 bp; P.

marginalis pv. marginalis, 651 bp; B. cepacia, 475 bp; P. carotovorum pv. carotovorum, 322 bp; P.

agglomerans, 248 bp; P. viridiflava, 181 bp; P. ananatis, 166 bp (Mansfield and Gugino, 2010).

rep-PCR for bacterial strain tracking

Pantoea spp. isolates were revived from -20⁰C storage by plating on KB medium and incubating

24 – 72 hr at 30⁰C. Two loopfuls of bacterial culture from the plate were suspended in 40 µL of sterile PCR

water in a 500 µL Eppendorf tube and vortexed. Tubes were placed in a boiling water bath for 5 min, then

centrifuged for 3 min at 5000 rpm. Repetitive extragenic palindromic-PCR (rep-PCR) protocols were

carried out as described by Versalovic et al. (1994) with the following modifications. Template (1.5 µL)

was pipetted from directly above the pellet from the boiled and centrifuged tubes. Autoclaved, membrane

filtered (0.22 μm) H2O was was reduced by 0.5 µL. Reaction products (12 µL) were mixed with 1.5 µL 6x

EZ-Vision Three dye (AMRESCO LLC, Solon, OH, USA), electrophoresced for 17 hr in a 2% SeaChem agarose

gel (Lonza Corporation, Visp, Switzerland) with two lanes containing 10-kb ladder (Denville Scientific,

Metuchen, NJ, USA).

Data analysis

Nonparametric comparisons

Comparisons of the frequencies of pathogenic and nonpathogenic isolates were conducted using

Fisher’s exact test (for 2x2 tables) and the Mantel-Haenszel-Cochran test (for experiment-wise tables in

which three species were tested). Comparisons of severity distributions were conducted using the Kruskal-

Wallis test (for comparisons between two species) and the Mann-Whitney test (for comparisons between

three species) in Minitab 16 (Minitab, Inc., State College, PA, USA).

Logistic regressions

Logistic regressions were conducted where selected species presence or absence (1, 0) in

symptomatic bulbs from harvest and storage was the dependent variable. Independent variables were

the presence or absence of the same species in soil, transplant epiphytic, transplant endophytic, weed

epiphytic, and weed endophytic samples, with farm of origin included as a factor. Weed epiphytic and

endophytic samples were rated as none (no detections of the selected species), some (1 or 2 detections

31

of the selected species out of 4 or 5 samples processed), or many (3, 4, or 5 detections of the selected

species out of 4 or 5 samples processed), with these species prevalence variables recoded as binary (0 if

false, 1 if true) independent variables in the analysis.

Odds ratios were calculated using SAS 9.2 (SAS, Cary, NC, USA); odds ratios approximate how likely

a binary outcome is to occur by relative risk. To interpret odds ratios, first the difference between the

point estimate and the modeled value, 1, is determined, then this difference indicates the relationship

between the independent variable and the dependent, binary variable. Point estimates below 1 indicate

a negative relationship between independent and dependent variables, while point estimates above 1

indicate positive relationships. The deviation from the modeled value indicates the relative change (for

each independent variable) in odds of detecting the chosen pathogen in each symptomatic onion sample

(Hosmer and Lemeshow, 1989). Variables were chosen using reverse selection in PROC LOGISTIC in SAS

9.2 (α to remove = 0.05). Only odds ratios for statistically significant (P ≤ 0.05) independent variables are

reported in the tables presented here.

rep-PCR fingerprinting

Preliminary analyses using three previously-used genomic fingerprinting primer sets, the

repetitive extragenic palindromic (rep) set, the enterobacterial repetitive intragenic consensus (ERIC) set,

and the BOXA1R (BOX) set (Versalovic et al., 1994) suggested the greatest number of bands were

generated for Pantoea spp. using the rep primer set, so that primer set was used in comparative analyses.

Analysis of rep-PCR gels was conducted using ImageJ software (NIH, Bethesda, MD, USA). Briefly, .jpg

photographs of rep-PCR gels were loaded into ImageJ, which after selection of lanes of interest, generated

peaks based on band brightness. Migration distances, based on pixels, were determined for dual 10 kb

ladders located on either side of the gel, which were used to construct a polynomial best-fit standard

curve. Migration distances of each unknown isolate were then determined and the size of each unknown

band was calculated from the curve. Band patterns were compared between isolates of Pantoea spp.

originating from the same farms, but from different types of samples. To be determined the same strain,

both genetic fingerprints needed to have at least 15 bands, with 95% of the bands concordant (band

present and within ± 2.5% of its putative pair size). These guidelines as or more conservative than other

published guidelines (Albert et al., 2003).

32

Results

Environmental and plant samples were processed for DNA extraction and the multiplex PCR

method was used to detect the presence or absence of eight bacterial species (Mansfield and Gugino,

2010). In 2011 and 2012, P. agglomerans (Pagg), P. carotovorum subsp. carotovorum (Pcar), and P.

marginalis pv. marginalis (Pmar) were the most commonly detected species in transplant epiphytic and

endophytic samples, weed epiphytic samples, and symptomatic bulbs from harvest as well as from storage

(Table 2.1). B. cepacia, P. ananatis, and P. viridiflava were detected in a few samples (1 – 14% of onion

samples) and X. axonopodis was very rarely detected (<1%; Table 2.1). In 2012, B. gladioli was detected

at relatively high frequency (64%) in transplant endophytes as well as in symptomatic bulbs from harvest

(24%; Table 2.1). Approximately 30% of soil samples collected early in the 2011 season, near the time of

transplanting, were positive for one or more of the eight bacterial species in the multiplex protocol (Table

2.1), however, over twice as many soil samples, 62%, collected early in the 2012 season were positive for

one or more of the species of interest (Table 2.1). The surfaces of weeds harbored target bacteria in 57%

and 89% of samples in 2011 and 2012, respectively (Table 2.1). The distributions of the number of bacterial

species detections in symptomatic bulbs was similar when 2011 and 2012 were compared; nearly 50% of

symptomatic bulbs in both years were infected with multiple bacterial pathogens of interest (Fig. 2.3).

Pcar was the pathogen that was most commonly detected singularly, accounting for 47% and 50% of

single-species detections in 2011 and 2012, respectively, followed by Pagg and Pmar, which accounted

for 22% and 16% of single-species detections, respectively (data not shown).

Epiphytic and endophytic bacterial isolates from transplants, of the species Pagg, Pmar, and Pcar,

were tested for pathogenicity using aerobic and semi-anaerobic pathogenicity tests. Approximately 73%

and 84% of epiphytic and endophytic isolates, respectively, induced symptoms on onion when incubated

aerobically, while 57% and 75% of epiphytic and endophytic isolates induced symptoms when incubated

semi-anaerobically. Overall, numerically more endophytic bacterial isolates were pathogenic than

epiphytic bacterial isolates, however, this result was not statistically significant in either an experiment-

wise Mantel-Haenszel-Cochran test (P = 0.22), or in 2x2 Fisher’s exact tests for each type of incubation

(Fig. 2.4). With few exceptions, isolates that were pathogenic in the semi-anaerobic test were typically

also pathogenic in the aerobic test (data not shown).

From six common weeds, epiphytic and endophytic bacterial isolates of the species Pagg, Pmar,

and Pcar, were tested for pathogenicity using aerobic and semi-anaerobic pathogenicity tests.

Approximately 65% and 89% of epiphytic and endophytic isolates, respectively, each induced symptoms

on onion when incubated aerobically, while 74% and 92% of epiphytic and endophytic isolates induced

33

symptoms when incubated semi-anaerobically (Fig. 2.5). There was no significant difference in the

frequencies of pathogenic epiphytes between each source in each type of incubation using Fisher’s exact

test, though numerically it appears that more weed epiphytes are pathogenic in semi-anaerobic tests

(74%; Fig. 2.5) than the frequency of transplant epiphytes that are pathogenic in semi-anaerobic tests

(57%; Fig. 2.4; P = 0.18).

Symptom severity ratings of Pagg (Fig. 2.6a), Pcar, (Fig. 2.6b), and Pmar (Fig. 2.6c) isolates from

various environmental and transplant sources indicated a spectrum of virulence among isolates tested

under aerobic pathogenicity test conditions. All isolate groups except transplant endophytic Pagg (Fig.

2.6a) and Pcar (Fig. 2.6b) included nonpathogenic isolates; in addition, all sources except soil included

isolates that induced severe symptoms (ratings of 4 or 5; Figs. 2.6a-c). No Pagg isolates tested were rated

at the highest severity level, 5 (Fig. 2.6a). Comparison of symptom severity distributions of epiphytic

bacterial isolates from weeds (of all three species, and using a Kruskal-Wallis test) was not significant (P =

0.28; Figs. 2.6a-c).

Using the repetitive extragenic palindromic (rep) primer set, genomic fingerprints of 35 isolates

(selected by farm of origin) of P. ananatis and P. agglomerans were generated and compared following

gel electrophoresis. A representative gel is shown in Fig. 2.7, where isolates from two farms with the same

local transplant supplier were used as templates for the rep-PCR protocol. Isolates 562 and 563 originated

from purslane tissue and epiphytically on crabgrass, respectively; these samples were collected from the

same field in very close proximity. Isolates 562 and 563 are assumed to be the same strain based on their

identical (≤ 40 bp; ± 2.5% of total band size) banding patterns (Fig. 2.7), which is stricter than the 10%

variation or less, which is one published criterion (Albert et al., 2003). Based on similar criteria, isolates

551 and 1617 are also suggested to be the same strain of P. ananatis (Fig. 2.7); 551 originated from within

the tissue of surface-sterilized shepherd’s purse (Capsella bursa-pastoris L. Medik.; a common weed),

collected in mid-June. Isolate 1617 originated from a symptomatic onion bulb harvested from the same

field in late July that was stored approx. four months at 4⁰C. Of 35 isolates tested, this is currently the only

matched pair identified (Table 2.2).

Species detections from symptomatic onion samples at harvest and from storage were compared

to farm-specific species detections in soil, transplant epiphyte and endophyte, and weed epiphyte

samples. In 2011 and 2012, the odds of detecting Pmar in a symptomatic onion bulb were 129 and 201%

higher, respectively, if Pmar was detected in the transplant endophytic and epiphytic samples that

corresponded to that farm, respectively (Tables 2.3a, 2.3c). In 2011, if Pagg was detected in an early-

season soil sample, the odds of detecting Pagg in a symptomatic bulb decreased 54% (Table 2.3b). In

34

2012, if Pagg was on at least three weeds out of the set of four or five weeds sampled at midseason, the

odds of detecting Pagg in a symptomatic bulb decreased 37% (Table 2.3d).

Discussion

Through two years of intensive survey of Pennsylvania onion production fields, different

environmental and plant sources were investigated to determine sources and pathogenicity of potential

bacterial inoculum. These efforts are intended to aid in updating management recommendations and to

elucidate targets for pathogen exclusion.

PCR detections from extracted samples in 2011 and 2012 indicated that the three most commonly

detected pathogens in symptomatic onion bulbs in 2011, P. agglomerans (Pagg), P. carotovorum subsp.

carotovorum (Pcar), and P. marginalis pv. marginalis (Pmar), were also the three most commonly

detected pathogens in onion in 2012 (Table 2.1). Since commercial production of onion is fairly novel to

PA agriculture and the production system overall is different from other onion systems in that the majority

of growers are already practicing recommended cultural controls (crop rotation, plastic mulch, drip

irrigation, etc.), identifying the major pathogens of concern in PA was an important first step. Detection

frequencies from 2011 and 2012 indicated multiple bacterial pathogens from symptomatic onions in

nearly 50% of the samples from harvest and storage (Fig. 2.2), and the most common pathogens identified

singly were Pcar and Pagg (data not shown), which may suggest primary roles for these two pathogens in

PA. As a result of the frequency of their detection, Pagg, Pcar, and Pmar were focused on more intensively

for the remainder of this work.

The data discussed above, in Table 2.1 as well as Fig. 2.2, are PCR-based species detections in

environmental and plant samples, which provide information about neither bacterial viability nor

pathogenicity. To assess the pathogenicity of bacterial isolates recovered from different sources prior to

harvest, two types of pathogenicity tests were undertaken. While both pathogenicity tests are dissimilar

to suggested infection processes, the tests may be completed rapidly with common equipment, and are

based on the marketable portion of the plant, the bulb. Two tests were used to approximate different

modes of pathogenicity: the aerobically-incubated pathogenicity test was intended to serve as a proxy for

bulb surface infections typical of soft rots (caused by Pmar and Pcar), while the semi-anaerobically-

incubated pathogenicity test was intended to serve as a proxy for leaf or neck-derived infections typical

of center rot (caused by Pagg and Pana; Carr et al., 2013). Bacterial isolate induction of symptoms was

typically well-correlated between the two tests (data not shown); as a result, more aerobic tests were

undertaken, since these require less time to completion.

35

Isolates of Pagg, Pcar, and Pmar generated from 2012 soil samples were tested for the ability to

induce symptoms in onion, and 76% of tested isolates (N = 21) were pathogenic (Figs. 2.6a-c). Though the

few 2012 Pagg isolates (N = 4) tested from soil were pathogenic to onion (Fig. 2.6a), through logistic

regression of the 2011 dataset, it was suggested that when Pagg was detected in early-season soils, the

frequency of detection of this bacterial species actually decreased in symptomatic bulbs from the same

farms (Table 2.4b). Since species detections in environmental samples do not indicate the lifestyle or

ecology of the microbe in question, one suggestion is that the presence of detectable Pagg in soil may

ultimately confer some disease suppressiveness overall, as has been demonstrated in antagonistic

interactions between Pagg and the soil- and seedborne Curtobacterium floccumfaciens pv. floccumfaciens

in bean (Hsieh et al., 2006) as well as antibiotic-producing Pagg and Erwinia amylovora in apple blossoms

(Pusey et al., 2011; Wright et al., 2001). Strains of Pagg have also been demonstrated to inhibit

Pseudomonas syringae pv. glycinea on soybean foliage (May et al., 1997); the same type of inhibition may

take place between nonpathogenic and pathogenic Pagg, however, this has not previously been

demonstrated, and would require competition growth assays and coinoculation experiments.

Several lines of evidence support the role of transplants as a source of bacterial epiphytes and

endophytes capable of inducing rot in onion. First, a relatively high frequency (22%) of detections of B.

gladioli pv. alliicola in symptomatic onions at harvest coincided with a high frequency (64%) of B. gladioli

pv. alliicola detected as endophytes from surface-sterilized transplants in 2012 (Table 2.1). Results from

pathogenicity tests on Pcar, Pagg, and Pmar isolates from transplants indicated that over 52% of isolates,

regardless of species, isolation location, or pathogenicity test, induced discoloration or maceration on

onion (Fig. 2.4). While lacking statistical significance, data numerically suggest a larger proportion of

pathogenic endophytic (75% - 84%) compared to epiphytic (57% - 73%) transplant isolates (Fig. 2.4).

Lending support to these data are logistic regressions of the detection of Pmar in symptomatic onion bulbs

from harvest and storage in 2011 and 2012, in which the odds of detecting Pmar in bulbs substantially

increased if Pmar was detected in either epiphytic (Table 2.3a; 2011) or endophytic (Table 2.3c; 2012)

samples from transplants.

In terms of management, these results suggest disease could be initiated by bacterial epiphytes

or endophytes from plants, and some species may be better suited to survival or transfer via transplants.

As in most agricultural production, growers should avoid planting transplants with noticeable symptoms

of disease. However, as has been suggested with seed-transmitted bacterial blight of onion (caused by X.

axonopodis pv. allii) inoculum may be spread via asymptomatic, latently-infected planting material

(Humeau et al., 2006). Since latent bacterial pathogens may induce symptoms later as a result of host

36

stress or changes in environmental conditions, previously described production practices that minimize

bacterial rots of onion, such as the use of plastic mulches that decrease soil temperatures (Chapter 4;

Gugino et al., 2011), might be encouraged among growers as management options to decrease bacterial

disease due to transplant-associated bacteria. Other options may be surface sterilizing or biological

control-based transplant dips, which may eliminate or compete with pathogenic bacterial populations on

onion foliage, as had been demonstrated on soybean by putative niche-displacing strains of gram-negative

bacteria (May et al., 1997). Finally, regulatory screening of transplants from southern states may be

suggested in order to eliminate the importation of infected plants, though accurate, rapid, and cost

effective sampling protocols need to be designed before regulations are imposed (Gitaitis et al., 1992).

As suggested by pathogenicity tests of Pagg, Pcar, and Pmar isolates from the surfaces and tissue

of weeds, a spectrum of virulence exists weed-derived members of these bacterial species, ranging from

nonpathogenic to highly aggressive (Figs. 2.6a-c). Weeds may play a role in onion diseases by supporting

a wide diversity of strains of these bacteria, and in dilution assays, at least six sampled weeds, including

lambsquarters, redroot pigweed, and purslane, can support endophytic populations of up to 108 CFU / g

fresh weight tissue (data not shown). Perennial weeds have already been demonstrated to harbor

potential bacterial pathogens of onion in Georgia (Gitaitis et al., 2002). PA weeds likely differ in terms of

prevalence, emergence, and biotype, all of which may affect the plants’ abilities to host these bacterial

pathogens, in addition to climatic differences between the two states, which may affect the survival and

colonization of bacteria associated with weeds. Though pathogenic epiphytic Pagg were frequently

isolated from the surfaces of common weeds, logistic regression of the 2012 dataset indicated that when

Pagg was prevalently detected on the surfaces of midseason weeds, the odds of detecting this bacterial

species decreased in symptomatic bulbs from the same farms (Table 2.3d; 62% of 2012 fields were

identified with Pagg as a prevalent weed epiphyte). Together with the logistic regression from 2011 soils

(Table 2.3b), these results reiterate that environmental, potentially nonpathogenic, Pagg strains may

negatively influence potentially onion-pathogenic Pagg strains. These results are based on PCR detection

only, however, and to more fully examine this hypothesis, competition assays between environmental

and onion-pathogenic Pagg strains are necessary, ideally in a field-based experiment. Some Pagg isolates

from multiple sources, including symptomatic onion, have been screened through rep-PCR genomic

fingerprinting, however, no matches have been indicated yet (data not shown).

However, using the same rep-PCR genomic fingerprinting, it was demonstrated that a P. ananatis

strain isolated from surface-disinfested, macerated shepherd’s purse tissue collected at mid-season, had

signficant similarity to a P. ananatis strain isolated from an onion from the same field that developed

37

symptoms in a four-month storage (Fig. 2.7). Matched strains are relatively rare in this type of genomic

assay, even though P. ananatis is fairly well-defined phylogenetically based on multi-locus sequence

analysis (Brady et al., 2008). In similar work with P. ananatis, De Paula Lana et al. (2012) reported high

species diversity among strains from maize, sorghum, and crabgrass, to a level at which rep-PCR using

three different primer sets completely differentiated all 15 strains tested. A prominent limitation of the

current study is that weeds were only sampled at mid-season, so it is difficult to suggest the ultimate

origin of the bacterial strain, whether seedborne (Walcott et al., 2002) on weed seeds; soilborne, then

splashed up to weed tissue; or originating on transplants and using weeds as ‘green bridges’ to move from

onion to onion. Repeated sampling procedures in small plots would help more clearly elucidate the

epidemiology of these pathogens. However these results, coupled with the pathogenicity tests from weed

epiphytes and endophytes, suggest a role for weeds in the in-field movement of bacterial rot pathogens

of onion in PA.

Select isolates originating from early-season soil, transplant surfaces and tissues, and weed

surfaces and tissues may induce discoloration, maceration, or both symptoms on onion in pathogenicity

tests (Figs. 2.4, 2.5, 2.6a-c), suggesting all of these as potential sources of bacterial inoculum. Some

evidence is present, however, for species specificity for some inoculum sources, such as Pmar associated

with transplant epiphytic and endophytic fractions (Tables 2.3a, c; Figs. 2.4, 2.6c), Pcar associated with

endophytic transplant and weed samples (Figs. 2.4, 2.5), and P. ananatis demonstrated to occur as both

an endophyte in a weed sampled at midseason as well as a pathogen in a symptomatic onion bulb from

storage (Fig. 2.7). While pathogenic Pagg isolates were found in or on all environmental and transplant

samples, the relationship between environmental and onion-pathogenic Pagg strains appears to be

complex, with logistic regression analyses suggesting the potential for antagonism between these strains

(Tables 2.3b, d); substantially more evidence than is presented here would be required to more solidly

prove this relationship.

Lastly, results presented here have helped identify several avenues of future research, specifically,

replicated field trials on transplant dips to reduce surface populations of bacteria, as well as potentially

bolstering the transplants’ natural defenses prior to the start of the growing season. In addition, dedicated

weed management should be undertaken both within and between mulched beds; some growers tend to

ignore the latter source of weeds because these plants do not directly compete with the onions growing

mulched beds. Successful implementation of these management strategies will contribute to growers’

integrated disease management programs, in PA and elsewhere, and will potentially increase the

profitability of onion production in the U. S.

38

Tables and Figures

Table 2.1. Detection of eight bacterial pathogens of onion from environmental and plant samples, collected in 2011 and 2012. The percentage of the total N of each sample type is given in the appropriate column; columns sum to more than 100% due to samples testing positive for multiple targeted bacterial species.

Bacterial species

At-planting soilu

Transplant epiphytev

Transplant endophytew

Weed epiphytex

Harvest bulbsy

Postharvest bulbsy

2011

P. agglomerans 8% 78% 61% 33% 41% 36%

P. carotovorum 13% 22% 30% 18% 58% 63%

P. marginalis 4% 70% 70% 21% 31% 32%

P. ananatis 1% 9% 0% 7% 2% 8%

B. gladioli 4% 0% 0% 4% 14% 10%

P. viridiflava 4% 30% 9% 10% 14% 3%

B. cepacia 4% 0% 0% 1% 5% 10%

X. axonopodis 0% 0% 0% 0% 0% 1%

None detectedz 70% 0% 13% 43% 7% 11%

Samples N = 84 N = 23 N = 23 N = 44 N = 171 N = 88

2012

P. agglomerans 26% 64% 100% 40% 40% 32%

P. carotovorum 16% 18% 55% 24% 59% 62%

P. marginalis 22% 36% 45% 27% 18% 33%

P. ananatis 2% 0% 18% 2% 7% 11%

B. gladioli 5% 0% 64% 1% 22% 2%

P. viridiflava 1% 0% 0% 6% 1% 6%

B. cepacia 2% 0% 9% 0% 1% 0%

X. axonopodis 0% 0% 0% 0% 0% 0%

None detectedz 38% 22% 0% 11% 10% 10%

Samples N = 87 N = 11 N = 11 N = 187 N = 188 N = 210 u Soil was collected from six equidistantly spaced points within plots, then homogenized, and 1 g was extracted using the MoBio Ultra Soil extraction kit. v Approximately 20 transplants from growers were shaken in 100 mL phosphate buffer (0.1% Tween-20) for 1 h, then was extracted using the Wizard DNA Extraction kit. w The 20 transplants from the epiphytic sample were shaken in 70% ethanol three times, then were macerated using a Waring blender until homogenous. Homogenate was extracted using the Wizard DNA extraction kit. x Five common weeds were sampled from each field in midseason, then shaken in 1 mL 0.1% Tween-20 phosphate buffer / g fresh wt tissue. Buffer fractions were pelleted and extracted as described in v. y Approximately 1 g of onion tissue was removed from a subset (20%, or one bulb, whichever is greater) of symptomatic bulbs from each farm, placed in a sterile 1.7 mL tube, and macerated with sterile phosphate buffer. Homogenate was extracted using the Wizard DNA extraction kit. z Extractions did not produce a band of the appropriate size following routine PCR.

39

Fig. 2.3. Number of bacterial species detected in symptomatic onion bulbs from harvest and storage combined, in 2011 and 2012.

0

10

20

30

40

50

60

70

80

90

100

Epiphytes(N = 26)

Endophytes(N = 19)

Epiphytes(N = 21)

Endophytes(N = 20)

Iso

late

s te

sted

(%

)

Aerobic Anaerobic

Nonpathogenic

P. marginalis

P. carotovorum

P. agglomerans

Fig. 2.4. Pathogenicity of epiphytic and endophytic bacterial isolates originating from transplants, incubated under aerobic and semi-anaerobic conditions in pearl onion bulbs. Pathogenic isolates are indicated by blue-shaded portions of bars, nonpathogenic isolates are indicated by green portions of bars.

Nonpathogenic

P. marginalis

P. carotovorum

P. agglomerans

40

0

10

20

30

40

50

60

70

80

90

100

Epiphytes(N = 91)

Endophytes*(N = 27)

Epiphytes(N = 57)

Endophytes*(N = 24)

Iso

late

s te

sted

(%

)Nonpathogenic

P. marginalis

P. carotovorum

P. agglomerans

Aerobic Anaerobic

Nonpathogenic

P. marginalis

P. carotovorum

P. agglomerans

Fig. 2.5. Pathogenicity of epiphytic and endophytic bacterial isolates originating from common weeds collected at midseason, incubated under aerobic conditions in pearl onion bulbs. Pathogenic isolates are indicated by blue-shaded portions of bars, nonpathogenic isolates are indicated by green portions of bars. *Endophytic isolates are only from 2012, and were isolated on OEM, which is semi-selective for onion pathogens and onion-associated bacteria.

41

Figs. 2.6 a-c. Disease severity induced on onion by P. agglomerans (A), P. carotovorum (B), and P. marginalis (C) isolates, from environmental and transplant sources from 2011 and 2012, in aerobic pathogenicity tests. Nonpathogenic proportions of isolates are indicated by green portions of bars (NP), pathogenic isolates are indicated by pink-red portions of bars. The shade of the bar indicates the severity of induced symptoms as described in Fig. 2.2; severity increases as the bars approach the x-axis. *Weed epiphytes and endophytes were isolated using semi-selective media in 2012; weed epiphytes include isolates from 2011 and 2012, while weed endophytes include isolates only from 2012. N = number of isolates tested from each source.

a: P. agglomerans

42

Fig. 2.7. Representative gel of rep-PCR genomic fingerprints for tracking strains of Pantoea spp. from two fields’ transplant, weed, and symptomatic onion isolates. These fields were planted with transplants from the same lot, but were located approx. 32 km from each other, on different soil types and under different management. Isolates 562 and 563 originated from the same area of the same field, but 562 is an endophyte from purslane while 563 is an epiphyte from crabgrass. Isolate 551 is an endophyte from shepherd’s purse, while isolate 1617 is from an onion that developed symptoms after approx. 4 months in storage. All highl ighted isolates are P. ananatis.

Transplants Midseason weeds Storage onions

NEG

43

Table 2.2. Summary of rep-PCR genomic fingerprinting analysis of environmental and pathogenic isolates from symptomatic onion tissue. Isolates of Pantoea spp. collected from a variety of sources in and around 26 onion production fields in 2012 were used as templates in rep-PCR genomic fingerprinting analysis to track bacterial strains through space and time.

Species Contributing fields

Transplant epiphytes

Transplant endophytes

Weed epiphytes

Weed endophytes

Thrips endophytes

Harvest isolates

Storage isolates

Total tested

Pairs of matched strains

P. ananatis 10 2 0 0 2 0 2 13 19 1

P. agglomerans 8 2 2 2 4 2 2 2 16 0

Table 2.3. Logistic regression analysis of detections of P. marginalis and P. agglomerans in symptomatic onion bulbs combined from harvest and storage, with species detections from environmental and transplant sources as independent variables and farm as a factor (2011 and 2012). Dependent variable is binary P. marginalis (A; C) or P. agglomerans (B; D; presence = 1) in symptomatic onion bulbs from harvest and storage; independents are detections of P. marginalis as a transplant endophyte (A) or epiphyte (C) and detections of P. agglomerans in early-season soil (B) or as a prevalent weed epiphyte (D).

Parameter df Estimate Standard error Wald chi-square P Odds ratioz 95% conf. interval (OR)y A: P. marginalis in 2011 (N = 187)

Intercept 1 -1.792 0.408 19.262 <0.001

Pmar transplant endophyte 1 1.131 0.446 6.430 0.011 3.099 1.293 – 7.427

B: P. agglomerans in 2011 (N = 187)

Intercept 1 -0.692 0.175 15.721 <0.001

Pagg in early-season soil 1 -0.768 0.354 4.713 0.030 0.464 0.232 – 0.928

C: P. marginalis in 2012 (N = 369)

Intercept 1 -1.693 0.272 38.751 <0.001

Pmar transplant epiphyte 1 0.832 0.303 7.518 0.006 2.297 1.268 – 4.163

D: P. agglomerans in 2012 (N = 369)

Intercept 1 -0.351 0.157 4.984 0.026

Pagg prevalent weed epiphyte 1 -1.464 0.219 4.481 0.034 0.629 0.409 – 0.966 z Briefly, odds ratio point estimates below 1 indicate a negative relationship between independent and dependent variables, while point estimates above 1 indicate positive relationships; the change in odds is determined by the absolute value of the magnitude of the difference between the odds ratio estimate and the modeled value, 1 (see Hosmer and Lemeshow, 1989). y 95% confidence interval of the point estimate of the odds ratio.

44

Acknowledgements Dr. Chris Smart, Holly Lange, and other members of the Smart Lab at Cornell University trained E. Pfeufer in rep-PCR protocols. Jeff Stoltzfus, Lee Stivers, Steve Bogash, and Scott Guiser, regional adult and extension educators in PA, identified grower-collaborator farms. The authors thank Ilse Huerta, Evan Stover, Jill Pollok, Marie Ebner, Khanh Nguyen, Anna Testen, Laura Ramos, Andy Kelly, and Laura del Sol Bautista for their field assistance. References Albert, J. M., Munakata-Marr, J., Tenorio, L., Siegrist, R. L. 2003. Statistical evaluation of bacterial source tracking data obtained by rep-PCR DNA fingerprinting of Escherichia coli. Environmental Science and Technology 37: 4554 – 4560. Brady, C., Cleenwerck, I., Venter, S., Vancanneyt, M., Swings, J., Coutinho, T. 2008. Phylogeny and identification of Pantoea species associated with plants, humans, and the natural environment based on multilocus sequence analysis (MLSA). Systematic and Applied Microbiology 31: 447 – 460. Bull, C. T., De Boer, S. H., Denny, T. P., Firrao, G., Fischer-Le Saux, M., Saddler, G. S., Scortichini, M., Stead, D. E., Takikawa, Y. 2010. Comprehensive list of names of plant pathogenic bacteria, 1980 – 2007. Journal of Plant Pathology 92: 551 – 592. Coenye, T., Vandamme, P. 2003. Diversity and significance of Burkholderia species occupying diverse ecological niches. Environmental Microbiology 5: 719-729. Cuppels, D. A., Elmhirst, J. 1999. Disease development and changes in the natural Pseudomonas syringae pv. tomato populations on field tomato plants. Plant Disease 83:759-764. Gent, D. H., Schwartz, H. F. 2008. ‘Bacterial Stalk and Leaf Necrosis’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 66-67. Gitaitis, R., McCarter, S., Jones, J. 1992. Disease control in tomato transplants produced in Georgia and Florida. Plant Disease 76: 651 – 656. Gitaitis, R., MacDonald, G., Torrance, R., Hartley, R., Sumner, D. R., Gay, J. D., and Johnson, W. C.1998. Bacterial streak and bulb rot of sweet onion: II. Epiphytic survival of Pseudomonas viridiflava in association with multiple weed hosts. Plant Disease 82: 935 - 938. Gitaitis, R., Walcott, R., Culpepper, S., Sanders, H., Zolobowska, L., Langston, D. 2002. Recovery of Pantoea ananatis, causal agent of center rot of onion, from weeds and crops in Georgia, USA. Crop Protection 21: 983-989. Gitaitis, R. D., Gent, D. H., Schwartz, H. S. 2008. ‘Leaf streak and bulb rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 59.

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Hsieh, T. F., Huang, H. C., Erickson, R. S. 2005. Biological control of bacterial wilt of bean using a bacterial endophyte, Pantoea agglomerans. Journal of Phytopathology 10: 608 – 614. Humeau, L., Roumagnac, P., Picard, Y., Robène-Soustrade, I., Chiroleu, F., Gagnevin, L., Pruvost, O. 2006. Quantitative and molecular epidemiology of bacterial blight of onion in seed production fields. Phytopathology 96:1345-1354. Ishii, S., Sadowsky, M. J. 2009. Applications of the rep-PCR DNA fingerprinting technique to study microbial diversity, ecology and evolution. Environmental Microbiology 11: 733–740. Ivey, M. L. L., Miller, S. A. 2004. Evaluation of hot water seed treatment for the control of bacterial leaf spot and bacterial canker on fresh market and processing tomatoes. Acta Horticulturae 695: 197 – 204. King, E. O., Ward, M. K., Raney, D. E. 1954. Two simple media for the demonstration of pyocyanin and fluorescin. Journal of Laboratory and Clinical Medicine 44, 301–307. Lange, H. W., Meeks, G. C., Glover, T. J., Smart, C. D. 2006. Weeds as reservoirs of Xanthomonas campestris pv. campestris in New York 96: S64. Lewandoski, D. J., Hayes, A. J., Adkins, S. 2010. Surprising results from a search for effective disinfectants for Tobacco mosaic virus-contaminated tools. Plant Disease 94: 542 – 550. Louws, F. J., Fulbright, D. W., Stephens C. T., de Bruijn, F. J. 1994. Specific genomic fingerprints of phytopathogenic Xanthomonas and Pseudomonas pathovars and strains generated with repetitive sequences and PCR. Applied and Environmental Microbiology 60: 2286: 2295. Mansfield, M., Gugino, B. 2010. Multiplex PCR for simultaneous detection of eight major onion bacterial pathogens. Phytopathology 100: S77. May, R., Volksch, B., Kampmann, G. 1997. Antagonistic activities of epiphytic bacteria from soybean leaves against Pseudomonas syringae pv. glycinea in vitro and in planta. Microbial Ecology 34: 118 – 124. Mohan, S. K. 2008a. ‘Other Bacterial Soft Rots’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 62. De Paula Lana, U. G., Gomes, E. A., Silva, D. D., Costa, R. V., Cota, L. V., Parreira, D. F., Souza, I. R. P., Guimaraes, C. T. 2012. Detection and molecular diversity of Pantoea ananatis associated with white spot disease in maize, sorghum, and crabgrass in Brazil. Journal of Phytopathology 160: 441 – 448. Pusey, P. L., Stockwell, V. O., Reardon, C. L., Smits, T. H. M., Duffy, B. 2011. Antibiosis activity of Pantoea agglomerans biocontrol strain E325 against Erwinia amylovora on apple flower stigmas. Phytopathology 101: 1234 – 1241. Uva, R. H., Neal, J. C., DiTomaso, J. M. 1997. Weeds of the Northeast. Cornell University Press: Ithaca, NY. 397 pp.

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Versalovic, J., Schneider, M., de Bruijn, F. J., Lupski, J. R. 1994. Genomic fingerprinting of bacteria using repetitive sequence-based polymerase chain reaction. Methods in Molecular and Cellular Biology 5: 25 – 40. Walcott, R. R., Gitaitis, R. D., Castro, A. C., Sanders, F. H., Diaz-Perez, J. C. 2002. Natural infestation of onion seed by Pantoea ananatis, causal agent of center rot. Plant Disease 86:106-111. Wright, S. A. I., Zumoff, C. H., Schneider, L., Beer, S. V. 2001. Pantoea agglomerans strain EH318 produces two antibiotics that inhibit Erwinia amylovora in vitro. Applied Environmental Microbiology 67: 284 – 292. Zaid, A. M., Bonasera, J. M., Beer, S. V. 2012. OEM – a new medium for rapid isolation of onion-pathogenic and onion-associated bacteria. Journal of Microbiological Methods 91: 520 – 526.

47

Chapter 3: Epidemiology and ecology of Gram-negative bacteria potentially pathogenic to onion, Allium cepa, in Pennsylvania Abstract As many as nine different species of bacteria have the ability to induce rots in onion, a potentially

lucrative crop which is rapidly expanding in Pennsylvania. Intensive surveys were undertaken on 28 and

26 farms in 2011 and 2012 in which bacteria were detected and isolated from symptomatic bulbs at

harvest and from storage, in addition to collection of environmental data from observational plots

throughout the growing season. Pectobacterium carotovorum subsp. carotovorum, Pantoea

agglomerans, and Pseudomonas marginalis pv. marginalis isolates from transplant and weed sources

were tested for pathogenicity under aerobic and semi-anaerobic incubations, and data suggested that

higher proportions of pathogenic strains were isolated as epiphytes from the common weeds

lambsquarters (Chenopodium album) and crabgrasses (Digitaria spp.) than from redroot pigweed

(Amaranthus retroflexus) and purslane (Portulaca oleracea). In addition, management factors influenced

pathogen detection in symptomatic onions in parasite- and disease-specific manners. Examples include

increased odds of detecting P. agglomerans in systems with standard black plastic mulch than in systems

using other plastic mulches, negative relationships between plant tissue carbon content and the detection

of P. carotovorum subsp. carotovorum, and the negative overall influence of early-season levels of soil

nitrate on bacterial disease that initiates in foliage. Elucidation of these factors will help refine integrated

strategies for managing ubiquitous, difficult-to-control bacterial pathogens in the onion cropping system.

Introduction

Onions (Allium cepa L.) are a rapidly-expanding and potentially lucrative crop for diversified

vegetable producers in Pennsylvania, but have only been commercially produced on a large scale for

fifteen years in the state. Bacterial rots, including soft rot (caused by Pectobacterium carotovorum subsp.

carotovorum Jones [Pcar] and Pseudomonas marginalis pv. marginalis Brown [Pmar]) and center rot

(caused by the emerging pathogens Pantoea agglomerans Beijerinck [Pagg] as well as Pantoea ananatis

Serrano; [Gent and Schwartz, 2008a; 2008b; Bull et al., 2010]), are the most significant diseases reducing

marketable yields in PA. In high disease incidence years, commercial growers experience yield reductions

of over 50%. In addition, it is common to detect many as four different species of bacteria from a single

symptomatic bulb (Chapter 2), suggesting primary and secondary plant infection by these bacteria.

48

The most frequently detected pathogens in rotting onion bulbs from PA are Pcar, Pmar, and Pagg,

species of bacteria that are ubiquitous in the environment and have high intraspecific variation ranging

from nonpathogenic to highly aggressive strains (Chapter 2). Pcar has been recognized for years as a

general pectinolytic pathogen of vegetables, fruits, and ornamentals (Ma et al., 2007), and was isolated

from soil, onion transplants, and weeds (Chapter 2; Ma et al., 2007). It is arguably the most prominent

postharvest pathogen as a result of its wide host range and ability to induce disease even at low

temperatures (Maher and Kelman, 1983); effective strategies targeted at managing Pcar have been

elusive as a result of its ubiquitous nature. Pmar is a genetically diverse bacterial species which also

includes pathogens with a wide host range and ubiquity in environments (Yamamoto et al., 2000); in

addition, as a fluorescent pseudomonad, Pmar may also function as a plant growth-promoting

rhizobacterium or niche-displacing biocontrol organism (Kloepper and Schroth, 1984), and may be

influential in diverse carbon cycles and environmental remediation as a result of the species’ adaptability

in substrate usage (Yamamoto et al., 2000). Similarly, Pagg has been found globally (Deletoile et al., 2009),

strains of which have been identified as pathogens on other plants (Barash and Manulis-Sasson, 2009), as

niche-displacing biocontrol agents in the management of plant disease (Bonaterra et al., 2003; Costa et

al., 2001), and even as an opportunistic human pathogen causing disease in immunocompromised

individuals (De Champs et al., 2000). In previous work, isolates of each of these bacterial species have

been found as epiphytes and endophytes from onion transplants and common weeds in and around onion

fields (Chapter 2).

Epiphytic bacteria inhabit the surfaces of aboveground plant parts, particularly the phyllosphere,

while endophytic bacteria asymptomatically reside within host plant tissue; both types of bacterial

lifestyle are characterized by their commensal interactions with their hosts (Hardoim et al., 2008). The

majority of research conducted on endophytic bacterial species has investigated their efficacy as

biocontrol organisms or root mutualists (Hardoim et al., 2008), however, other work has suggested that

soil and endophytic bacterial populations are distinct (Lemanceau et al., 1995). Many species of bacteria

have been isolated as endophytes, including some suggested to have quite stable relationships with their

plant hosts, including Pagg with citrus trees (Araujo et al., 2002) and Eucalyptus (Ferreira et al., 2008).

Frequent detections and isolations of Pcar, Pmar, and Pagg from the surfaces as well as within the tissue

of common weeds were demonstrated in Chapter 2, and pathogenicity tests of these organisms indicated

a range of aggressiveness, from nonpathogenic/asymptomatic isolates (of each species) to highly virulent

isolates capable of rotting a pearl onion bulb in days. While detections and isolations of some onion

pathogens from the surfaces of weeds have been conducted with P. ananatis and Pseudomonas viridiflava

49

Burkholder (Gitaitis et al., 1998; 2002), no investigations have been conducted where bacterial epiphytes

and endophytes have been isolated, tested for pathogenicity, and compared based on weedy host plants.

Phenotypic and genotypic characterizations are available for each of these three bacterial species,

in addition to descriptions of symptoms induced on infected plant hosts. However, some of these

descriptions are limited to type or well-characterized strains, as a result of characterization requiring

substantial time and effort (Holt et al., 1994). The classical plant disease triangle, in which a pathogen, its

susceptible plant host, and a conducive environment coordinate to result in plant disease becomes more

complicated when multiple pathogens are involved. Disease management strategies intended to reduce

the incidence of one pathogen may instead positively affect another pathogen, with the same ultimate

result: reduced crop yields; an example of this is in wheat, where NH4 fertilization and low soil pH have

been documented to reduce take-all (caused by Gaeumannomyces graminis), but in the same system,

NO3 nutrition and alkaline soils are preferable for the management of eyespot (caused by

Pseudocercosporella herpotrichoides; Huber and Thompson, 2007). In addition, while some integrated

management practices are designed to adversely affect pathogens, occasionally host plants are also

affected, perhaps increasing their susceptibility to infection by other pathogens.

With their wide host ranges, ubiquity in the environment, and potential for interspecific

interactions, integrated study of these bacteria was necessary to gain a more comprehensive view of their

lifestyles as epiphytes, endophytes, and pathogens. Observational studies were undertaken on 28 and 26

farms in 2011 and 2012, and approximately 2000 bacterial isolates were generated from soil, transplants,

weeds, thrips, and symptomatic onion at harvest and from storage. Selected bacterial strains were

assayed for their prevalence in symptomatic, single-species detection bulbs, their ability to rot onions

based on their isolation location (epiphyte or endophyte) and type of weed, and the impact of both

management factors and the incidence of other bacterial species in symptomatic onion bulbs.

Materials and Methods

Sample collection for bacterial isolations

In 2011 and 2012, 28 and 26 Pennsylvania farms, respectively, were visited three times each over

the course of the onion growing season. Early, mid-season, and harvest samples were taken from soil,

transplants, weeds, and symptomatic onion bulbs, following protocols outlined in Chapter 2.

50

Environmental and management factors

General production data, soil nitrogen analyses, and pre-plant transplant samples were collected

and processed after visit 1, which occurred in April or early May each year. Midseason ratings of weed

pressure, mulch integrity, foliar thrips damage, and bulb growth were recorded during visit 2, in addition

to the collection of weeds for bacterial isolations and onion foliar tissue samples for total nitrogen

measurements. At visit 3, plots were harvested, rated for disease, graded for size, and additional soil

samples were taken, in addition to retaining approx. 30 asymptomatic onion bulbs for a storage rating,

which took place in November. Three asymptomatic bulbs from each farm were each analyzed for total C

after the postharvest rating. Detailed descriptions of these protocols may be found in Chapter 2.

Bacterial isolations from transplants, weeds, harvest, and postharvest onions

Epiphytic and endophytic bacterial isolates were obtained from transplant and weed samples in

2011 and 2012, after the detailed protocols in Chapter 2. Onion extract medium (OEM; Zaid et al., 2012)

was used in 2012 for isolations from weed samples, while King’s B medium was used in 2011. Before

isolations, types of bacterial rots were grouped into general categories: surface rots, characterized by

discoloration and/or maceration initiating in the outer scales of the bulb and progressing inward (Fig.

3.1a), or inner scale rots, characterized by a single or a few discolored and/or macerated scales within the

bulb, which were thought to initiate in the onion foliage (Fig. 3.1b). Bulbs with both types of rots occurred

occasionally, these were not used for bacterial isolations unless no other symptomatic bulbs were

available from that plot, and the disease assignment deferred to inner scale rot. Symptomatic onions were

photo-documented for each isolation, and tissue (approx. 0.5 g and indicated by a surface-sterilized green

wire loop in Figs. 3.1a, b) was removed from the margin between symptomatic and asymptomatic areas.

In 2011 and 2012, respectively, samples were taken from 20% or 50% of symptomatic bulbs per replicate

plot or one bulb (whichever was greater) of each generic type of diseased onions (surface rot or inner

scale rot). Two samples (intended for DNA extraction and bacterial isolation, respectively) were removed

from the symptomatic area and transferred to sterile 1.8 mL Eppendorf tubes. The isolation sample was

ground with a sterile micropestle with an additional 500 µL of sterile Kphos buffer, then was serially

diluted onto KB, then 100 µL of the appropriate dilution was spread-plated on KB to select single isolates

to be maintained in duplicate (described in Chapter 2) at -20⁰C.

51

Figs. 3.1a – b. Symptomatic onions typified by the generic diseases surface rot (a) or inner scale rot (b). The green wire loop was surface-sterilized and indicates roughly where symptomatic tissue was harvested for DNA extraction and bacterial isolation.

Aerobic and semi-anaerobic pathogenicity tests

Aerobic and semi-anaerobic pathogenicity tests were completed using commercial, surface-

sterilized pearl onions that were inoculated with selected isolates of Pcar, Pagg, and Pmar (described in

detail in Chapter 2).

DNA extractions

DNA was extracted directly from soil, transplant, weed, and symptomatic onion tissue using the

MoBio Ultra Soil DNA kit (MoBio Laboratories, Inc., Carlsbad, CA) for soil samples, the Qiagen DNEasy

Plant Mini Kit (Qiagen Inc., Valencia, CA), and the Wizard Genomic DNA Purification kit (Promega,

Madison, WI) for onion samples, as outlined in Chapter 2.

Bacterial species identification

Bacterial isolates were preliminarily identified to genus based on photographed phenotypic

characteristics, then more definitively identified to species using the previously-described duplex PCR

protocol (Chapter 2; Mansfield and Gugino, 2010).

Data analysis

Nonparametric comparisons

Comparisons of the frequencies of pathogenic and nonpathogenic isolates of Pagg, Pcar, and

Pmar were conducted using Fisher’s exact test (for 2x2 tables) and the Mantel-Haenszel-Cochran test (for

52

experiment-wise tables in which three species were tested) using Minitab 16 (Minitab Inc., State College,

PA, USA).

Logistic regressions

Initial logistic regressions where surface (0) or inner scale rot (1) in symptomatic bulbs at harvest

and from storage were conducted with seven (all but X. axonopodis) species presence or absence (1, 0) as

independent variables, to associate generic types of disease with particular pathogens. Logistic

regressions where species presence (1) or absence (0) were dependent variables were conducted with

environmental and production factors as well as the presence or absence of other bacterial pathogen

species were independent variables. In all logistic regressions, the grower, field, and year were included

as class variables, then the stepwise selection procedure (α to add = 0.2; α to remove = 0.25) was used to

narrow the field of potential independent variables. Next, another logistic procedure was conducted

where the selected variables were placed in the model and removed one at a time based on P value

(largest removed), then the analysis was repeated. Removal of variables stopped when all variables had P

values below 0.05. Odds ratios were also calculated (SAS 9.2, SAS Institute, Cary, NC, USA); odds ratios

approximate how likely a binary outcome is to occur by relative risk. To interpret odds ratios, first the

difference between the point estimate and 1 is determined, then this difference indicates the relationship

between the independent variable and the dependent, binary variable. Point estimates below 1 indicate

a negative relationship between independent and dependent variables, while point estimates above 1

indicate positive relationships. In some cases, where a one-unit change in the independent variable

resulted in a very small change in odds, each value was multiplied by a constant in order to attain more

meaningful values (Hosmer and Lemeshow, 1989).

Results

In a logistic regression, where the generic type of bacterial rot symptom was classified either as

surface rot or inner scale rot (Figs. 3.1a, b) and was used as the dependent variable, only two species of

bacteria were consistently associated with each general type of disease. Burkholderia gladioli pv. alliicola

was associated with bulbs with surface rot; the odds of a bulb with inner scale rot testing positive for B.

gladioli were 59% lower than the odds of detecting that pathogen in surface rot bulbs, which was

statistically significant (P < 0.001; Table 3.1). Also statistically significant, the odds of a bulb with inner

scale rot testing positive for Pseudomonas viridiflava were nearly three times the odds of a surface rot

bulb testing positive for this bacterium (P < 0.001; Table 3.1). The incidence of a particular type of rot by

53

other bacterial species could not be statistically predicted (P > 0.05), however, based on the odds ratio

point estimates and their 95% confidence intervals, it may be suggested that Pmar and Pantoea ananatis

trend toward inner scale rots, and Burkholderia cepacia and Pantoea agglomerans (Pagg) trend toward

surface rots; P. carotovorum subsp. carotovorum (Pcar) seems to be equally detected in surface and inner

scale rot – affected bulbs (Table 3.1).

In symptomatic bulbs in which only one bacterial species was detected using the multiplex PCR

protocol, Pcar was the most commonly detected pathogen in surface and inner scale rots (38 – 55%; Figs.

3.1a, b and 3.2). Pantoea agglomerans (Pagg) was also frequently identified as a singular pathogen (22

– 24%), however, for its frequency in the environment, Pseudomonas marginalis (Pmar) was singularly

detected in fewer bulbs, only 12 – 14%. Burkholderia gladioli pv. alliicola and Pantoea ananatis were

detected in 12 and 6% of single-detection surface rot and inner scale rot bulbs, respectively (Fig. 3.2).

In aerobic and semi-anaerobic pathogenicity tests of epiphytic and endophytic Pagg, Pcar, and

Pmar from transplants, over 60% of isolates tested were pathogenic to onion (Fig. 3.3a). No statistically

significant differences between species or isolation source existed in the aerobic test, however,

numerically fewer Pmar isolates from transplants were pathogenic to onion as compared to the

frequencies of pathogenic isolates of Pagg and Pcar. In semi-anaerobic pathogenicity tests,

proportionally more Pmar endophytes were pathogenic than epiphytes, which was nearly statistically

significant (P = 0.059). No other statistically significant differences between epiphytes and endophytes

within each test (and disregarding species) were made apparent by a Mantel-Haenszel-Cochran test (P >

0.1; Fig. 3.3b).

When bacterial epiphytes from weeds collected in 2011 were considered nonspecifically in terms

of the type of weed they were isolated from (Fig. 3.4), proportionally more isolates from lambsquarters

(Chenopodium album L.) were pathogenic in aerobically incubated tests than the proportions of isolates

from each of crabgrasses (Digitaria spp. Haller; P = 0.058), redroot pigweed (Amaranthus retroflexus L.;

P = 0.017), and purslane (Portulaca oleracea L.; P = 0.007) using Fisher’s exact test. There were no

statistically significant differences between each of the other three weeds (Fig. 3.4).

The use of standard black plastic, the partial removal of mulch at midseason by the grower, the

silt content of soil, and the amount of total bulb tissue N at harvest all increased the odds of detecting

Pagg in the symptomatic bulb. Torn mulch increased the odds of detecting Pagg 62% over fields with

mulch left intact, in addition, the use of black plastic mulch doubled the odds of detecting Pagg in

symptomatic bulbs (Table 3.2a). For each 5% increase in silt content of soil, the odds of detecting Pagg

54

increased approx. 20%, and for every 0.25% increase in total N content in bulbs at harvest, the odds of

detecting Pagg increased approx. 32% (Table 3.2a).

Detections of Pcar were positively associated with the incidence of purple blotch in fields, while

foliar tissue C at midseason and early-season soil nitrate were negatively associated with the presence of

the bacterial species (Table 3.2b). Purple blotch is a fungal disease of Alliums caused by Alternaria porri

Ellis that commonly occurs on PA farms, particularly in wet weather (Pfeufer, observation). The odds of

detecting Pcar in symptomatic onions increase 59% if greater than 10% of plants have purple blotch at

midseason (Table 3.2b). However, an increase of 0.5% in total foliar C at midseason decreases the odds of

detecting Pcar 12%, as does an increase in early-season soil nitrate of approximately 10 mg nitrate / kg

dry soil (Table 3.2b).

Similarly, the odds of detecting Pmar in symptomatic bulbs decreased 11% for each increase of

early season soil nitrate of 10 mg / kg dry soil (Table 3.2c). Pmar detections were positively associated

with the detection of Pseudomonas viridiflava as well as bulbs that are larger than approx. 6 cm in

diameter at midseason, increasing the odds of detecting Pmar by 119% and 64%, respectively. An

increase in total foliar N of 0.5% increased the odds of detecting Pmar by 83% (Table 3.2c).

In addition to Pcar detections in symptomatic bulbs, the odds of detecting P. ananatis decreased

with both total foliar tissue C and the amount of early-season soil nitrate (Table 3.2d). However, the

opposite relationship with incidence of purple blotch was indicated, suggesting the odds of detecting P.

ananatis actually decreased 45% when more than 10% of plants were symptomatic for purple blotch in

midseason (Table 3.2d). Similar to Pmar, the odds of detecting P. ananatis in symptomatic bulbs more

than doubled if bulbs were at least 6 cm in diameter at midseason. In addition, for each additional ten

hours of soil temperatures at or above 30 ⁰C, the odds of detecting P. ananatis in symptomatic bulbs

increased 4% (Table 3.2d).

When separating diseased bulbs by the type of symptoms expressed as well as those with positive

detections of Pagg, the use of standard black plastic in either case doubled the odds of detecting Pagg in

symptomatic bulbs (Tables 3.3a, b). However, the odds of detecting Pagg in bulbs with surface rots

decreased nearly 65% if the bulb tested positive for Burkholderia gladioli pv. alliicola (Table 3.3a). In bulbs

with inner scale rots only, the odds of detecting Pagg increased with increased silt content of soils, higher

harvest levels of soil nitrate, larger bulb size at midseason, and particularly potentially mineralizable

nitrogen rate, which more than doubled the odds of detecting Pagg in symptomatic, inner scale rot bulbs

(Table 3.3b).

55

Detections of Pcar in surface rot bulbs were positively associated with two soil variables, the total

number of hours of soil temperature ≥ 30⁰C as well as the clay content of soils. An additional 22 hours of

soil temperatures at or above 30⁰C as well as an increase of 1% more clay in field soil increased the odds

of detecting Pcar by approx. 29% (Table 3.4a). A high degree of weed pressure between the raised beds

actually increased the odds of detecting Pcar by 84%, while for every additional 0.33% of total C in

harvested bulb tissue, the odds of detecting Pcar in surface rot bulbs decreased 25% (Table 3.4a).

Similar to surface rot bulbs, for every additional 0.33% of total C in foliar tissue at midseason, the

odds of detecting Pcar in inner scale rot bulbs decreased 8.5% (Table 3.4b). Early season soil nitrate as

well as very high weed pressure between raised beds also decreased the odds of detecting Pcar in inner

rot bulbs. Both the silt content of soil and the incidence of purple blotch symptoms at midseason increased

the odds of detecting Pcar; in particular, purple blotch symptoms on greater than 10% of plants increased

the odds nearly 46% (Table 3.4b).

Discussion

From intensive surveys and laboratory-based studies, the detection, isolation, pathogenicity

status, and influence of environmental variables on several bacterial species was assessed in order to

provide more information about the ecology of these organisms. Pectobacterium carotovorum subsp.

carotovorum (Pcar) occurred most frequently as the single bacterial pathogen identified from

symptomatic bulbs, with Pantoea agglomerans (Pagg) and Pseudomonas marginalis pv. marginalis also

accounting for proportions of single-detection symptomatic bulbs (Fig. 3.2). These results illustrate the

difficulty associated with attributing diagnostic symptoms to particular pathogens – expectations were

that Pcar would be prevalent in surface rot bulbs, but less so in inner scale rot bulbs, which were expected

to have more frequent detections of Pagg and Pmar, bacteria that both begin as leaf pathogens (Mohan,

2008; Gent and Schwartz, 2008). Results from logistic regression analysis with the general type of rot as

the dependent variable indicated two species of bacteria were consistently associated with a single type

of bacterial rot (Table 3.1). Burkholderia gladioli pv. alliicola was typically associated with surface rot

bulbs, and Pseudomonas viridiflava was associated with bulbs with inner scale rot (Table 3.1). These

regressions correspond well with previously published work in which the lifestyle and symptomatology

induced by each pathogen has been described: members of the Burkholderia genus are well-described as

bacterial soil inhabitants (Coenye and Vandamme, 2003), which would facilitate B. gladioli pv. alliicola

surface infections of bulbs, while P. viridiflava is considered the ‘leaf streak’ pathogen, which in advanced

cases, induces a rot of a single scale within symptomatic bulbs (Gitaitis et al., 2008).

56

Since Pcar, Pagg, and Pmar are the three most common pathogens in the onion – bacterial rot

pathosystem in PA (Chapter 2), selected isolates of each species originating from the surfaces and tissue

of transplants were tested for pathogenicity to onion. High frequencies (60% or more) of pathogenic

isolates originated from transplants, and though not statistically significant, Pmar generally tended to

have lower frequencies of pathogenic isolates in either type of pathogenicity test, compared to the other

two species of interest (Fig. 3.3a), which may be expected since Pseudomonas spp. are generally

considered aerobic (Holt et al., 1994). In addition, as might be expected, Pmar endophytes were more

frequently pathogenic to onion in semi-anaerobic tests than epiphytes (Fig. 3.3a), and support from

accompanying work suggested Pmar detections as transplant epiphytes or endophytes actually increase

the odds of detecting Pmar in symptomatic onion tissue (Chapter 2). Taken together, this suggests that

endophytic strains from transplants may actually represent latently infected plants, and may be a source

of bacterial inoculum in the production system. The use of a rep-PCR strain tracking assay will be used in

the future to more conclusively elucidate the hypothesis of pathogenic Pmar arriving with onion

transplants, ideally by generating matching genomic fingerprints between transplant isolates and isolates

inducing bulb symptoms (Chapter 2); this type of assay has been successfully completed with other

Pseudomonas species (Louws et al., 1994).

In a similar analysis, over 60% of Pcar, Pagg, and Pmar isolates from weeds were pathogenic to

onion in aerobic and semi-anaerobic pathogenicity tests (Fig. 3.3b). Though not statistically significant,

Pagg typically had higher proportions of pathogenic isolates than the other two species, with Pmar having

the lowest proportions of pathogenic isolates (Fig. 3.3b). These results may be reinforced by comparisons

between epiphytic isolates from weeds tested for pathogenicity and shown in Fig. 3.3b; for growers, this

may indicate that even if protectant copper bactericides are applied on both cropped onions and adjacent

weeds, bacterial pathogens have the ability to subsist within the weed tissue. Complete removal of weeds

from the field may be necessary in order to remove an inoculum source (weed endophytes) from grower

fields.

In aerobic pathogenicity tests of isolates from the four most common weeds found in PA onion

fields, a larger proportion of isolates originating from lambsquarters (91%) were pathogenic compared to

proportions of pathogenic isolates from crabgrasses (71%), redroot pigweed (55%), and purslane (62%; P

< 0.06), using Fisher’s exact test (Fig. 3.4). These results were unexpected; it was hypothesized that a

larger proportion of bacterial isolates would originate from crabgrasses, which as monocots, are more

closely related to onion than the other weeds and has been shown in other studies (Toussaint et al., 2012;

Yishay et al., 2008). In a study comparing Pcar strains, Yishay et al. found that isolates of Pcar that

57

originated from monocot hosts were more aggressive in monocot pathogenicity tests compared to dicot

pathogenicity tests, and vice-versa (2008). These authors further suggested, through genetic analyses

based on 16S rRNA sequence analysis, that monocot and dicot isolates were clearly differentiated at the

basal level, which may indicate co-evolutionary specialization (Yishay et al., 2008). Similarly, when

Xanthomonas campestris pv. vitians, a bacterial pathogen of lettuce, was inoculated onto foliage of

common weeds, Lactuca spp. supported higher pathogen populations than weeds that were more

distantly related to lettuce (Toussaint et al., 2012).

The present analyses, in which bacterial isolates are grouped nonspecifically into pathogenic and

nonpathogenic proportions, do not support the hypothesis of co-evolutionary specialization; rather,

another aspect influencing interactions between lambsquarters and its bacterial symbionts may impose a

selection pressure on these potential pathogens. For instance, as an early-emerging weed (Myers et al.,

2004), lambsquarters may support larger populations of bacteria, or some aspect of lambsquarters’

biochemical makeup may result in higher populations of bacteria pathogenic to onion. In syringe-

inoculations of wild transplanted lambsquarters, plants inoculated with 100 µL of 108 CFU / mL P.

agglomerans suspension appeared no different than uninoculated plants (Pfeufer, unpublished),

potentially allowing pathogenic bacteria to persist symptomlessly. In addition, in serial dilutions in the

isolation process of this observational study, some endophytic fractions of surface-sterilized weeds were

diluted to 10-8 before bacterial density was such that colonies were countable, indicating the potential for

lambsquarters to support large bacterial populations within their tissues. Hypotheses about relationships

between weed emergence, plant biochemistry, and pathogen populations, however, would need to be

tested further, in addition to conducting pathogenicity tests on isolates from a wider range of weed

sources.

While lab-based biochemical tests and growth assays are well-defined for many of these

pathogens (Holt et al., 1994), those phenotypic traits may not translate directly to pathogen abundance

in field situations, which illustrates why logistic regression analyses of detections of the prevalent species

of bacteria in symptomatic bulbs may contribute additional dimensions to our knowledge about each of

these bacterial pathosystems. Perhaps most strikingly, Pagg was demonstrated repeatedly to be

associated with standard black plastic mulch, which occurred regardless of what type of general bacterial

rot symptoms it was associated with (Tables 3.2a; 3.3a, b). Standard black plastic mulch has been shown

to result in overall higher incidence of bacterial disease (Gugino et al., 2011), perhaps by way of warmer

soil temperatures at and after midseason (Chapter 4). These results corroborate results that indicated the

use of black plastic increased the incidence and severity of center rot of onion, caused by P. ananatis

58

(Gitaitis et al., 2002) in addition to P. agglomerans. It may be hypothesized that warmer soils allow

pathogenic strains of Pagg to overtake nonpathogenic or inhibitory strains of Pagg. Temperature-

dependent virulence gene expression has been widely demonstrated in other plant pathogenic bacteria,

however, most well-studied examples describe downregulation of virulence at temperatures >28°C, with

the most notable exception being the tropical pathogen Ralstonia solanacearum (Smirnova et al., 2001).

Additional experimentation is necessary before concluding this point, but interestingly, if Pagg virulence

is upregulated at higher temperatures, this would more closely resemble a bacterial pathogen of humans

(Smirnova et al., 2001), which Pagg has already been demonstrated to be in immunocompromised people

(De Champs et al., 2001; Volksch et al., 2009).

Other variables influential in the detection of Pagg are the silt content of soil (Tables 3.2a, 3.3b)

and the potential antagonism between Pagg and B. gladioli pv. alliicola in bulbs with surface rots (Table

3.2a). It may be hypothesized that soils with ample silt may not support high populations of Pagg, since

soil texture is established as an important factor in determining rhizobacterial populations (Dey et al.,

2012), however, this would require further evidence. Both Pagg (Wright et al., 2001) and B. gladioli pv.

alliicola (Hu and Young, 1998) have been shown to produce antibiotic-like inhibitory compounds in media,

so further experimentation, such as concurrent culturing in media as well as in onion plants, would be

necessary to determine which bacterial species is the primary inhibitor.

Detection of Pcar in surface and inner scale rot bulbs allowed the further identification of variables

of interest for this difficult-to-manage bacterial pathogen. In particular, the negative relationships

between tissue C content and the incidence of Pcar in both surface rot (Table 3.4a) and inner scale rot

(Table 3.4b), may indicate future strategies to investigate for managing this pathogen: it may be that high

tissue C decreases onion susceptibility to this pathogen. These results correspond well to results

presented in Chapter 4, in which foliar tissue C as well as the C:N ratio of plant foliage appeared to

influence the incidence of bacterial rots at harvest and from storage (Chapter 4). While counterintuitive

when considering bacterial pathogens require plant hosts, in part, as a source of carbon, one suggestion

may be that plants with higher carbon in their tissues are less susceptible to infection as a result of better

overall plant health. Alternatively, higher carbon contained in the plant tissues may be involved in long

carbon chain precursors of defense-related antimicrobials, such as allicin (Kyung, 2012).

Pcar was also positively associated with the incidence of purple blotch in plants at midseason

(Tables 3.2b, 3.4b), while P. ananatis was negatively associated with purple blotch (Table 3.2d). Purple

blotch is a fungal disease of Alliums caused by Alternaria porri Ellis, and less often, Stemphylium vesicarium

Simmons, that commonly occurs on PA farms in wet weather (Pfeufer, observation). Symptoms initially

59

are small water soaked lesions that develop on leaves, turn chlorotic with a pale tan center before

coalescing and developing a purplish-brown color; A. porri-induced symptoms are characterized by

concentric rings (Miller and Lacy, 2008). Under severe purple blotch pressure, growers have informally

attributed rotting bulbs to A. porri (pers. comm., to Pfeufer), even though purple blotch symptoms

typically manifest as purple to brown outer papery scales and rots due to A. porri are thought to occur

infrequently (Miller and Lacy, 2008). Association between these pathogens and Pcar has only been

informally suggested (Paibomesai et al., 2012), and synergistic disease induction by these inter-kingdom

pathogens may be a subject for future research. For growers, this observation reinforces the

recommendation of tank-mixing copper products with ethylene-bis-dithiocarbamate fungicides when

managing onions for disease.

Another interesting point in these datasets is the differential effect of weed pressure between

raised beds in the field on the detection of Pcar in surface and inner scale rot bulbs. While weed pressure

between rows is positively associated with the detection of Pcar in surface rot bulbs, the same variable is

negatively associated with the detection of Pcar in inner scale rot bulbs (Tables 3.4a, b). Since weeds have

been shown to harbor pathogenic strains of Pcar on their surfaces and within their tissues (Chapter 2,

Figs. 3.3, 3.4), the relationship with inner scale rots was unexpected. One potential explanation is that

high weed pressure between the rows shades the raised beds enough to reduce soil temperatures, which

other results suggest may result in lower disease incidence (Gugino et al., 2011; Chapter 4). Replicated

field trials, however, are necessary to confirm this hypothesis.

Considering all the results presented here, it may be concluded that environmental variables

probably exert differential influences on various critical components of the plant disease triangle.

Examples of environmental variables primarily influencing the pathogen include the suggested benefit to

Pagg conferred by the use of standard black plastic mulch (Tables 3.2a; 3.3a, b) and the negative

association between Pcar and local tissue C (Tables 3.2b; 3.4a, b). On the other hand, environmental

variables may serve to increase the susceptibility of the host, or may influence the pathogen-host

interaction such that disease is overall enhanced. One example is the multiple positive relationships

between silt content of soils and the incidence of inner scale rot, which is assumed to initiate in the foliage

and develop as a result of infection by Pagg (Table 3.3b), Pcar (Table 3.4b), Pmar (Table 3.2c), and P.

ananatis (Table 3.2d). Another influential variable in the development of inner scale rot symptoms

appears to be early-season soil nitrate, which is negatively associated with detections of Pcar, Pmar, and

P. ananatis in inner scale rot bulbs, (Tables 3.2b-d, 3.4b), and is particularly interesting given other work

suggesting positive relationships between bacterial rots of onion and preharvest soil nitrate levels

60

(Chapter 4). However, it may be that in the later analysis (Chapter 4), early soil nitrate may positively

influence the surface rot-type diseases while simultaneously reducing the foliar inner scale rot diseases.

As a final word, although Pmar has been well-described in the literature as a primary pathogen of

onion (Wright and Hale, 1992), this species may function as a secondary pathogen in PA, or at least can

be considered less aggressive. This hypothesis is based on the relatively few Pmar single-species

detections in symptomatic bulbs (Fig. 3.2), even though Pmar is frequently detected throughout the

production system (data shown in Chapter 2). In addition, its frequent co-occurrence with P. viridiflava

(Table 3.2c) and other bacterial species, and its consistently lower proportions of isolates found to induce

symptoms in pathogenicity tests (Figs. 3.3a, b) may help reinforce this point. To more conclusively

demonstrate this, future work is necessary using Pmar single and co-inoculations with other bacterial

species isolated from symptomatic onions.

Acknowledgements

The authors thank Dr. Shelby Fleischer and Dr. Mark Otieno (Department of Entomology, Penn State) for several helpful conversations about statistical approaches.

61

Tables and Figures

Table 3.1. Logistic regression of general types of bacterial rot (surface rot or inner scale rot) modeled by the detection of bacterial species in symptomatic bulbs collected at harvest and from storage in PA in 2011 and 2012 (N = 614). Dependent variable modeled is 1 = inner scale rot (n = 395), while independent variables are species detections (presence = 1).

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 0.880 0.184 22.842 <0.001

B. gladioli 1 -0.892 0.259 11.845 <0.001 0.410 0.247 – 0.681

P. viridiflava 1 1.360 0.542 6.294 0.012 3.897 1.347 – 11.278

P. marginalis 1 0.268 0.218 1.517 0.218 1.307 0.853 – 2.002

P. ananatis 1 0.260 0.382 0.464 0.496 1.297 0.614 – 2.740

B. cepacia 1 -0.684 0.617 1.228 0.268 0.505 0.151 – 1.691

P. agglomerans 1 -0.229 0.191 1.436 0.231 0.795 0.546 – 1.157

P. carotovorum 1 0.335 0.190 0.031 0.860 1.034 0.713 – 1.501 z Briefly, odds ratio point estimates below 1 indicate a negative relationship between independent and dependent variables, while point estimates above 1 indicate positive relationships; the reduced (or increased) relative risk is determined by the magnitude of the difference (see Hosmer and Lemeshow, 1989). y 95% confidence interval of the point estimate of the odds ratio.

0

10

20

30

40

50

60

70

80

90

100

Surface rot (N = 78) Inner scale rot (N = 160)

Sin

gle

spec

ies

det

ecti

on

s (%

)

Other

P. ananatis (ISR)or B. gladioli (SR)P. marginalis

P. agglomerans

P. carotovorum

Other

B. gladioli (SR) or P. ananatis (ISR)

P. marginalis

P. agglomerans

P. carotovorum

Fig. 3.2. Detection of bacterial species in symptomatic bulbs pooled from at harvest (2011 and 2012) and from storage (2012 only) samples from which only one pathogen was detected and separated by the type of rot symptom observed (N=238). This represents approx. 36% of all symptomatic bulbs collected from 2011 and 2012. The ‘Other’ category includes positive detections for Burkholderia cepacia, Pseudomonas viridiflava, and either P. ananatis (surface rot bulbs [SR]) or B. gladioli pv. alliicola (inner scale rot bulbs [ISR]).

62

0

10

20

30

40

50

60

70

80

90

100

Pagg(N = 16)

Pcar(N = 12)

Pmar(N = 18)

Pagg(N = 18)

Pcar(N = 12)

Pmar(N = 18)

Iso

late

s te

ste

d (

%)

Aerobic pathogenicity test Semi-anaerobic pathogenicity test

Nonpathogenicendophytes

Nonpathogenicepiphytes

Pathogenicendophytes

Pathogenicepiphytes

0

10

20

30

40

50

60

70

80

90

100

Pagg(N = 43)

Pcar(N = 28)

Pmar(N = 47)

Pagg(N = 25)

Pcar(N = 25)

Pmar(N = 31)

Iso

late

s te

ste

d (

%)

Aerobic pathogenicity test Semi-anaerobic pathogenicity test

Nonpathogenicendophytes*

Nonpathogenicepiphytes

Pathogenicendophytes*

Pathogenicepiphytes

Figs. 3.3a - b. Pathogenicity of Pantoea agglomerans (Pagg), Pectobacterium carotovorum subsp. carotovorum (Pcar), and Pseudomonas marginalis pv. marginalis (Pmar) from onion transplants (a) and weeds (b) in aerobic and semi-anaerobic pathogenicity tests, divided by bacterial isolation source. *All 2012 isolates were generated from semi-selective OEM, while 2011 isolates were generated from KB (nonselective). Weed endophytes were only isolated in 2012.

a

b

63

Fig. 3.4. Bacterial epiphytes of the species Pantoea agglomerans, Pectobacterium carotovorum subsp. carotovorum, and Pseudomonas marginalis pv. marginalis from selected common weed sources collected in PA onion fields in 2011 and tested for pathogenicity under aerobic incubation. Purple-shaded portions of bars indicate pathogenic isolates of each species, while green shaded portions of bars indicate nonpathogenic isolates from each weed source, regardless of species. * Indicates proportionally more pathogenic isolates from lambsquarters compared to each of the other weeds by Fisher’s exact test (α = 0.06).

64

Tables 3.2a - d: Logistic regressions of harvest and storage detections of Pantoea agglomerans (3.2a; n = 225 of 614), Pectobacterium carotovorum subsp. carotovorum (3.2b; n = 366 of 614), Pseudomonas marginalis pv. marginalis (3.2c; n = 171 of 614), and Pantoea ananatis (3.2d; N = 48 of 614) from symptomatic onion bulbs from PA, combined in 2011 and 2012; positive detections rated ‘1.’ Independent variables are detections of other bacterial species in symptomatic bulbs as well as environmental and production factors observed throughout the season.

Table 3.2a. P. agglomerans

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 -4.964 0.852 33.943 <0.001

Torn mulch at midseason x 1 0.483 0.140 11.988 <0.001 1.622 1.233 – 2.132

Standard black mulch w 1 0.713 0.198 12.995 <0.001 2.041 1.385 – 3.007

Bulb tissue N at harvest v 1 0.822 1.280 8.594 0.003 2.274 1.313 – 3.939

Silt content of soil u 1 0.038 0.013 8.521 0.004 1.039 1.013 – 1.066

Table 3.2b. P. carotovorum subsp. carotovorum

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 11.148 2.888 14.905 <0.001

Foliar tissue C at midseason t 1 -0.285 0.075 14.594 <0.001 0.752 0.650 – 0.871

Early season soil nitrate s 1 -0.014 0.005 9.752 0.002 0.986 0.977 – 0.995

Purple blotch (>10%) r 1 0.467 0.123 14.437 <0.001 1.594 1.253 – 2.028

Table 3.2c. P. marginalis pv. marginalis

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 -4.896 0.988 24.544 <0.001

P. viridiflava detected in bulb q 1 0.786 0.346 5.161 0.023 2.194 1.114 – 4.320

Early season soil nitrate s 1 -0.013 0.005 5.964 0.015 0.988 0.978 – 0.998

Foliar leaf N, midseason p 1 0.979 0.278 12.427 <0.001 2.663 1.545 – 4.589

Bulb size, midseason o 1 0.497 0.143 12.134 <0.001 1.644 1.243 – 2.174

Table 3.2d. P. ananatis

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 16.107 5.796 7.721 0.006

Purple blotch (>10%) r 1 -0.592 0.230 6.619 0.010 0.553 0.352 – 0.868

Foliar tissue C at midseason t 1 -0.507 0.159 10.153 0.002 0.602 0.441 – 0.823

Early season soil nitrate s 1 -0.021 0.010 4.327 0.036 0.979 0.959 – 0.999

Bulb size at midseason o 1 0.782 0.303 6.660 0.010 2.186 1.207 – 3.960

Soil T >30⁰C (season-long) n 1 0.004 0.002 5.116 0.024 1.004 1.001 – 1.008

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z Briefly, odds ratio point estimates below 1 indicate a negative relationship between independent and dependent variables, while point estimates above 1 indicate positive relationships; the reduced (or increased) relative risk is determined by the magnitude of the difference (see Hosmer and Lemeshow, 1989). y 95% confidence interval of the point estimate of the odds ratio. x Torn plastic mulch at midseason visit coded ‘1;’ intact mulch coded ‘0.‘ w Standard black plastic mulch coded as ‘1’; other, non-standard mulches (silver-on-black, white, black biodegradable) coded ‘0.’ v Total bulb tissue N as measured from three asymptomatic bulbs per field; continuous variable. u Midpoint of the range of silt content for the field, reported by NRCS web soil survey (websoilsurvey.nrcs.usda.gov); continuous variable. t Total foliar tissue C as measured from thirty fully-expanded leaves, comingled in three samples by plot; value reported is the average of three plots for a field average; continuous variable. s Soil nitrate content early in season, in mg NO3 kg-1; field average derived from three plot averages consisting of six comingled samples each; continuous variable. r Purple blotch (caused by Alternaria porri) pressure on >10% of the plants in the observational plots coded as ‘1.’ q Pseudomonas viridiflava also identified from the same bulb tissue, coded as ‘1.’ p Total foliar tissue N as measured from thirty fully-expanded leaves, comingled in three samples by plot; value reported is the average of three plots for a field average; continuous variable. o Visually estimated bulb size as rated at midseason visit; larger than 6 cm diameter coded ‘2;’ from 4 – 6 cm diameter coded ‘1.’ n Season-long total hours of soil temperature ≥30⁰C by field; continuous variable.

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Tables 3.3a – b. Pantoea agglomerans detections in surface (3a; n = 68 of 174) and inner scale rot (3b; n = 128 of 348) bulbs with other bacterial species detections and environmental and management factors as independent variables.

Table 3.3a. P. agglomerans in surface rot bulbs

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 -0.765 0.305 6.299 0.012

Standard black mulch x 1 0.711 0.354 4.041 0.044 2.035 1.018 – 4.069

B. gladioli pv. alliicola w 1 -1.033 0.463 4.987 0.026 0.356 0.144 – 0.881

Table 3.3b. P. agglomerans in inner scale rot bulbs

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 -5.666 1.236 21.026 <0.001

At-harvest soil nitrate v 1 0.016 0.005 12.014 <0.001 1.016 1.007 – 1.025

Bulb size at midseason u 1 0.457 0.206 4.924 0.027 1.579 1.055 – 2.362

Standard black mulch x 1 0.979 0.279 12.312 <0.001 2.662 1.541 – 4.600

PMN, early season t 1 1.013 0.388 6.827 0.009 2.754 1.288 – 5.890

Silt content of soil s 1 0.050 0.023 4.683 0.031 1.051 1.005 – 1.100 z Briefly, odds ratio point estimates below 1 indicate a negative relationship between independent and dependent variables, while point estimates above 1 indicate positive relationships; the reduced (or increased) relative risk is determined by the magnitude of the difference (see Hosmer and Lemeshow, 1989). y 95% confidence interval of the point estimate of the odds ratio. x Standard black plastic mulch coded as ‘1’; other, non-standard mulches (silver-on-black, white, black biodegradable) coded ‘0.’ w Positive identification of Burkholderia gladioli pv. alliicola from the same symptomatic bulb coded ‘1.’ v Soil nitrate (in mg NO3 kg-1 dry soil) as measured from each plot at harvest; reported values are the field average of three plots, continuous variable. u Visually estimated bulb size as rated at midseason visit; larger than 6 cm diameter coded ‘2;’ from 4 – 6 cm diameter coded ‘1.’ t Potentially mineralizable nitrogen in early-season soils after a 31-40 day incubation, in mg kg-1 day-1; continuous variable. s Midpoint of the range of silt content for the field, reported by NRCS web soil survey; continuous variable.

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Tables 3.4a –b. Pectobacterium carotovorum subsp. carotovorum detections in surface (3.4a; n = 163) and inner scale rot (3.4b; n = 225 of 360) bulbs with other bacterial species detections and environmental and management factors as independent variables. Table 3.4a. P. carotovorum subsp. carotovorum in surface rot bulbs

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 46.814 15.527 9.090 0.003

Soil T > 30⁰C (season-long) x 1 0.013 0.004 9.677 0.002 1.013 1.005 – 1.022

Bulb tissue C at harvest w 1 -1.359 0.431 9.961 0.002 0.257 0.110 – 0.597

Clay content of soil v 1 0.258 0.094 7.559 0.006 1.294 1.077 – 1.555

Weed pressure between bedsh 1 0.624 0.267 5.451 0.020 1.866 1.105 – 3.152

Table 3.4b. P. carotovorum subsp. carotovorum in inner scale rot bulbs

Parameter df Estimate St. Error Wald Chi-square P Odds ratio z 95% C.I. (O.R.) y

Intercept 1 10.810 4.181 6.686 0.010

Silt content of soilu 1 0.035 0.013 7.186 0.007 1.036 1.010 – 1.063

Early season soil nitrates 1 -0.023 0.006 12.709 <0.001 0.977 0.965 – 0.990

Foliar tissue C at midseasont 1 -0.295 0.107 7.614 0.006 0.745 0.604 – 0.918

Purple blotch (<10%)r 1 0.376 0.181 4.312 0.038 1.456 1.021 – 2.075

Weed pressure between bedsq 1 -0.307 0.152 4.097 0.043 0.736 0.546 – 0.990 z Briefly, odds ratio point estimates below 1 indicate a negative relationship between independent and dependent variables, while point estimates above 1 indicate positive relationships; the reduced (or increased) relative risk is determined by the magnitude of the difference (see Hosmer and Lemeshow, 1989). y 95% confidence interval of the point estimate of the odds ratio. x Season-long total hours of soil temperature ≥30⁰C by field; continuous. w Total tissue C in bulbs at harvest as measured by three asymptomatic bulbs; value reported is the average of three bulbs for a field average; continuous. v Midpoint of the range of clay content for the field, reported by NRCS web soil survey; continuous variable. u Midpoint of the range of silt content for the field, reported by NRCS web soil survey; continuous variable. t Total foliar tissue C as measured from thirty fully-expanded leaves, comingled in three samples by plot; value reported is the average of three plots for a field average; continuous. s Soil nitrate content early in season, in mg NO3 kg-1; field average derived from three plot averages consisting of six comingled samples each; continuous. r Purple blotch (caused by Alternaria porri) pressure on >10% of the plants in the observational plots coded as ‘1’ q Visual rating of weed pressure between raised beds; very high weed pressure (shading beds or encroaching on plants) rated ‘1.’

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References Araujo, W. L., Marcon, J., Maccheroni, W., van Elsas, J. D., van Vuurde, J. W. L., Azevedo, J. L. 2002. Diversity of endophytic bacterial populations and their interaction with Xylella fastidiosa in citrus plants. Applied and Environmental Microbiology 68: 4906 – 4914. Barash, I., Manulis-Sasson, S. 2009. Recent evolution of bacterial pathogens: the gall-forming Pantoea agglomerans case. Annual Reviews of Phytopathology 47: 133-152. Bonaterra, A., Marib, M., Casalinib, L., Montesinosa, E. 2003. Biological control of Monilinia laxa and Rhizopus stolonifer in postharvest of stone fruit by Pantoea agglomerans EPS125 and putative mechanisms of antagonism. International Journal of Food Microbiology 84: 93-104. Coenye, T., Vandamme, P. 2003. Diversity and significance of Burkholderia species occupying diverse ecological niches. Environmental Microbiology 5: 719-729. Costa, E., Teixidó, N., Usall, J., Atarés, E., Viñas, I. 2001. Production of the biocontrol agent Pantoea agglomerans strain CPA-2 using commercial products and by-products. Applied Microbiological Technology 56: 367- 371. De Champs, C., Le Seaux, S., Dubost, J.J., Boisgard, S., Sauvezie, B., Sirot, J. 2000. Isolation of Pantoea agglomerans in two cases of septic monoarthritis after plant thorn and wood sliver injuries. Journal of Clinical Microbiology 38: 460-461. Deletoile, A., Decre, D., Courant, S., Passet, V., Audo, J., Grimont, P., Arlet, G., Brisse, S. 2009. Phylogeny and identification of Pantoea species and typing of Pantoea agglomerans strains by multilocus gene sequencing. Journal of Clinical Microbiology 47: 300-310. Dey, R., Pal, K. K., Tilak, K. V. B. R. 2012. Influence of soil and plant types on diversity of rhizobacteria. Proceedings of the National Academy of Sciences, India 82: 341 – 352. Ferreira, A., Quecine, M. C., Lacava, P. T., Oda, S., Azevedo, J. L., Araujo, W. L. 2008. Diversity of endophytic bacteria from Eucalyptus species seeds and colonization of seedlings by Pantoea agglomerans. Federation of European Microbiological Societies: Microbiology Letters 287: 8 – 14. Gent, D. H., Schwartz, H. F. 2008a. ‘Bacterial Stalk and Leaf Necrosis’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 66 - 67. Gent, D. H., Schwartz, H.F. 2008b. ‘Center rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 64 - 66. Gitaitis, R., Walcott, R., Culpepper, S., Sanders, H., Zolobowska, L., Langston, D. 2003. Recovery of Pantoea ananatis, causal agent of center rot of onion, from weeds and crops in Georgia, USA. Crop Protection 21: 983-989. Gitaitis, R. D., Walcott, R. R., Sanders, H. F., Zolobowska, L., Diaz-Perez, J. C. 2004. Effects of mulch and irrigation system on sweet onion: II. The epidemiology of center rot. Journal of the American Society of Horticultural Science 129: 225-230.

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Gitaitis, R. D., Gent, D. H., Schwartz, H. S. 2008. ‘Leaf streak and bulb rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 59. Hardoim, P. R., van Overbeek, L. S., van Elsas, J. D. 2008. Properties of bacterial endophytes and their proposed role in plant growth. Trends in Microbiology 16: 463 – 471. Holt, J. G., Krieg, N. R., Sneath, P. H. A., Staley, J. T., Williams, S. T. 1994. ‘Genus Pseudomonas;’ ‘Genus Pantoea.’ In: Bergey’s Pp. 93, 184. Hosmer, D. W., Lemeshow, S. 1989. Applied Logistic Regression. Wiley-Interscience Publications: New York, NY. 307 pp. Hu, F.-P., Young, J. M. 1998. Biocidal activity in plant pathogenic Acidovorax, Burkholderia, Herbaspirillum, Ralstonia, and Xanthomonas spp. Journal of Applied Microbiology 84: 263 – 271. Huber, D. M., Thompson, I. A. 2007. ‘Nitrogen and Plant Disease’ in: Mineral Nutrition and Plant Disease. APS Press: St. Paul, MN. Pp. 31 – 44. Louws, F. J., Fulbright, D. W., Stephens C. T., de Bruijn, F. J. 1994. Specific genomic fingerprints of phytopathogenic Xanthomonas and Pseudomonas pathovars and strains generated with repetitive sequences and PCR. Applied and Environmental Microbiology 60: 2286: 2295. Kloepper, J. W., Schroth, M. N. 1981. Relationship of in vitro antibiosis of plant growth-promoting rhizobacteria to plant growth and the displacement of root microflora. Phytopathology 71: 1020 – 1024. Kyung, K. H. 2012. Antimicrobial properties of Allium species. Current Opinion in Biotechnology 23: 142 – 147. Ma, B., Hibbing, M. E., Kim, H.-S., Reedy, R. M., Yedidia, I., Breuer, J., Breuer, J., Glasner, J. D., Perna, N. T., Kelman, A., Charkowski, A. O. 2007. Host range and molecular phylogenies of the soft rot enterobacterial genera Pectobacterium and Dickeya. Phytopathology 97: 1150 - 1163. Maher, E. A., Kelman, A. 1983. Oxygen status of potato tuber tissue in relation to maceration by pectic enzymes of Erwinia carotovora. Phytopathology 73: 536 – 539. Myers, M. W., Curran, W. S., VanGessel, M. J., Calvin, D. D., Mortensen, D. A., Majek, B. A., Karsten, H. D.,

Roth, G. W. 2004. Predicting weed emergence for eight annual species in the northeastern United States.

Weed Science 52: 913-919.

Paibomasai, M., Celetti, M., Tesfaendrias, M. 2012. Update on stemphylium leaf blight of onions in

Ontario. OMAFRA Hort Matters. Accessed online July 14, 2014:

http://www.omafra.gov.on.ca/english/crops/hort/news/hortmatt/2012/19hrt12a6.htm .

Toussaint, V., Benoit, D. L., Carisse, O. 2012. Potential of weed species to serve as a reservoir for Xanthomonas campestris pv. vitians, the causal agent of bacterial leaf spot of lettuce. Crop Protection 41: 64 – 70.

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Uva, R. H., Neal, J. C., DiTomaso, J. M. 1997. Weeds of the Northeast. Cornell University Press: Ithaca, NY. 397 pp. Volksch, B., Thon, S., Jacobsen, I.D., Gube, M. 2009. Polyphasic study of plant and clinic associated Pantoea agglomerans reveals indistinguishable virulence potential. Infection, Genetics, and Evolution 9:1381-1391. Wright, P. J., Hale, C. N. 1992. A field and storage rot of onion caused by Pseudomonas marginalis. New Zealand Journal of Crop and Horticultural Science 20: 435 – 438. Wright, S. A. I., Zumoff, C. H., Schneider, L., Beer, S. V. 2001. Pantoea agglomerans strain EH318 produces two antibiotics that inhibit Erwinia amylovora in vitro. Applied Environmental Microbiology 67: 284 – 292. Yamamoto, S., Kasai, H., Arnold, D. L., Jackson, R. W., Vivian, A., Harayama, S. 2000. Phylogeny of the genus Pseudomonas: intrageneric structure reconstructed from the nucleotide sequences of gyrB and rpoD genes. Microbiology 146: 2385 – 2394. Yishay, M., Burdman, S., Valverde, A., Luzzatto, T., Ophir, R., Yedidia, I. 2008. Differential pathogenicity and genetic diversity among Pectobacterium carotovorum ssp. carotovorum isolates from monocot and dicot hosts support early genomic divergence within this taxon. Environmental Microbiology 10: 2746 – 2759.

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Chapter 4: In-field management factors related to incidence of bacterial rot of onion (Allium cepa) in Pennsylvania and New York

Abstract

Bacterial diseases, including center and soft rots, are significant causes of onion crop loss in

Pennsylvania and New York, resulting in losses of up to 60%, even with conscientious management with

chemical and cultural methods. To identify environmental and production factors associated with high

incidence of bacterial rots of onion, replicated observational studies were undertaken in a total of 108

fields in PA and NY, in 2011 and 2012. Forty environmental and management variables were recorded

through three visits to each field in each season. Prior to data analysis, combined data from NY indicated

higher disease incidence in ‘Red Wing’ than the other eight varieties surveyed. Independent

environmental and management variables were placed in stepwise multiple linear regression models to

determine variables influential to total incidence of bacterial rot. Foliar nitrogen (N) and foliar carbon (C)

were negatively related to total incidence of bacterial rots of onion from the PA datasets, while pre-season

levels of soil nitrate (NO3) were positively related to total incidence of bacterial rots from PA and NY. Foliar

nutrient levels implicate early-season fertility in managing bacterial rots of onion, while associations

between soil NO3 and rot suggest ammonium (NH4) or organic N may be more effective N sources in

managing bacterial rots. In addition, soil temperatures near the physiological onset of onion bulbing were

positively related to total incidence of bacterial rot in PA in 2011 and in the combined NY dataset, which

agrees with previously published results. These results suggest greater complexity is necessary for N

fertility recommendations: not only should a field rate be suggested, but also the timing and type of N

applied may play roles in bacterial disease development. In addition, if possible, growers should also take

steps to lower soil temperatures, particularly near bulbing.

Introduction

Bacterial rots are significant diseases reducing marketable yields in commercial onion production

in Pennsylvania (PA) and New York (NY). Over several recent years, crop losses due to bacterial disease

have exceeded 60% for some PA farms, and up to 40% loss in NY, even with conscientious disease

management by these growers. In PA, leaf blight and bulb rot, caused by Pantoea agglomerans Beijerinck,

and soft rots, caused by Pectobacterium carotovorum pv. carotovorum Jones and Pseudomonas

marginalis pv. marginalis Stevens, are primary diseases, with the three species of bacteria frequently

occurring in complexes as well as being ubiquitous in environments. This contrasts to NY, where growers

typically experience higher losses due to slippery skin (Burkholderia gladioli pv. alliicola Burkholder), sour

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skin (Burkholderia cepacia Burkholder), and center rot (Pantoea ananatis Serrano); the Burkholderia

species are primarily associated with soil (Coenye and Vandamme, 2003), and P. ananatis is considered

an emerging pathogen (Coutinho and Venter, 2009).

In addition, the two production systems vary in size, predominant soil types, cultivars grown, and

grower inputs. In PA, highly diversified vegetable growers are typically producing ‘Candy’ (a large, sweet,

fresh-market cultivar) onions from transplants in silt loam fields between 0.25 – 1.5 hectares in size, over

a 100-day season. These highly managed systems are typified by raised plastic mulch beds with two rows

of drip irrigation, planned, sometimes proprietary fertigation programs, regular crop rotation, and

directed, integrated management via copper/ethylene-bis-dithiocarbamate (EBDC) spray treatments,

insecticides, hand-weeding, and pre- and post-emergent herbicides. In NY, growers typically direct-seed

bold cooking onions which are suitable for long-term storage, in high organic matter muck soil fields

ranging in size from two to 40 hectares or more. These larger systems usually do not have raised beds or

plastic mulch, most fertilizer is applied pre-plant, and integrated management is focused on copper-EBDC

treatments for disease and rotated insecticides for thrips management over a 130-day season, from

roughly late May to late August or early September.

Chemical strategies used by onion producers are primarily applications of copper hydroxide in

combination with EBDC fungicides (Gent and Schwartz, 2008; Sanchez et al., 2014). Unfortunately,

chemical approaches are only marginally successful, as a result of their lack of systemic activity and

inability to prevent bacterial degradation within the bulb once the plant is infected. Some of the

pathogens of concern in these systems initially infect onion leaves, then move into the bulb over

subsequent weeks (Carr et al., 2013; Pfeufer, unpublished). In addition, copper-tolerant strains of P.

ananatis have been isolated from commercial onion fields in Georgia (Nischwitz et al., 2007), which

suggests resistant strains may also have developed in other areas where copper is relied heavily upon for

in-season management. EBDC fungicides, such as mancozeb, have been suggested to increase the

availability of the copper ion, and therefore increase its efficacy, in bacterial disease management

(Conover and Gerhold, 1981).

Cultural strategies used by onion producers in the management of bacterial rots include practicing

crop rotation, managing soil fertility (Diaz-Perez et al., 2003; Mohan, 2008a), using different types of

mulch (Gitaitis et al., 2004; Gugino et al., 2011), and performing persistent weed management in and

around onion fields to reduce the impact of weeds as pathogen ‘green bridges’ (Gitaitis et al., 2003). In

addition to biotic factors, high rainfall and high humidity may be associated with disease development,

because bacteria proliferate more quickly in moist environments and rain splash may aid in dispersal

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(Schwartz et al., 2003), in addition to promoting lush susceptible growth of the host plant in non-irrigated

fields. After four seasons of growing onions and observing grower farms, it has been noted that low-lying

areas within onion fields regularly have higher incidences of bacterial disease (Hoepting, unpublished;

Pfeufer and Gugino, unpublished); whether this is implicated in excess soil water or fertilizer accumulation

is unknown. The onion pathogens discussed earlier have varying optimal temperatures for proliferation,

however, warmer air temperatures have been shown to be related to high levels of center rot (P. ananatis)

in Colorado (Schwartz et al., 2003). Since multiple sources of inoculum exist before and during the growing

season, and growers have several opportunities with which to lessen the impact of environmental factors,

it is imperative that they implement integrated disease management strategies at all times before and

during the season.

As noted above, bulb infections are difficult to manage as a result of their inaccessibility: non-

systemic, protectant chemicals will not reach their target pathogens if the bacteria are protected by layers

of host tissue. Several environmental conditions that are beneficial to onion growth, that is, warm

temperatures, high humidity, and transfer of plant nutrients from leaves into the bulb may also favor

pathogen proliferation. To refine disease management strategies for growers in the Northeast and Mid-

Atlantic regions, observational studies were undertaken in PA and NY in 2011 and 2012 to identify

management factors associated with bacterial rots of onion for further investigation in replicated field

trials. It was hypothesized that soil nitrogen and soil temperatures would be positively related to the

incidence of bacterial rots of onion in these systems.

Materials and Methods

Overview of sample sites

In 2011 and 2012, 28 and 26 Pennsylvania fields, and 22 and 32 New York fields, respectively,

were visited three times each over the course of the onion growing season. Farms were selected with the

assistance of regional extension educators; all PA growers grew ‘Candy’ onions on raised beds with plastic

mulch and drip irrigation, fields averaged between 0.5 – 1 hectare in size, and were actively rotated. The

majority of PA growers transplant onions with 15 cm between each plant within the row, four rows across

the bed, and 15 cm between each plant within the row. NY growers grew nine different cultivars (primarily

bold cooking onions, with one red cultivar included), which may or may not have been grown on plastic

mulch, ranged in size from five to 150 acres, with some fields monocropped with onions for more than

ten years. There were 24 repeat growers from PA between both years, however 52 of the 54 fields were

unique. There were five repeat growers from NY from both years, and in some cases the same field was

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sampled both years and/or multiple onion fields were sampled on the same farm. Soil texture estimates

in PA were determined by selecting the cropped field as a region of interest in the NRCS Web Soil Survey

(http://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx), choosing physical properties under

Soil Data Explorer, and surface layer as the depth under the percent clay (silt, sand) navigation tab.

Grower collaborator visits

Early season (visit 1)

In April/May of each year, in both states, characteristics of each production field were recorded,

including type of plastic mulch, plant spacing, approximate field size, general fertilizer information, and

grower approaches to disease and weed management. Three 9.14 m plots were established in an area of

the field visually determined to be representative of the entire field with respect to field length, width,

and topography. Each plot was one bed wide, with typical bed width of 1.44 m. Soil temperature sensors

(HOBO Pendant Temperature Data Logger; Onset, Pocasset, MA) were placed in two of the three plots at

a 3-in. soil depth beneath the plastic mulch. Composite soil samples were collected from each plot (six

samples equidistantly located in each plot, using a soil probe 2.54 cm (1-in.) in diameter to a depth of 7.5

cm (3-in.) for each sample) and bulk density was calculated. For each plot, soil was homogenized by hand

in plastic zip-bags and approximately 15 g was placed in a screw-top cup containing 100 mL 2M KCl and

shaken well. To measure potentially mineralizable nitrogen, another 15 g was placed in an empty screw-

top soil cup, and all six cups per field were placed on ice in an insulated cooler. On arrival at the lab, PA

samples in KCl were placed in a 4⁰C refrigerator for extraction, and dry cups were placed in a lab drawer,

with the lids loosened, for 31 - 40 days. KCl extracts were filtered through pre-moistened Whatman No. 1

filter paper, then extracts were analyzed for NO3-N and NH4-N using spectrophotometric analysis via the

VCl3 and salicylate-nitroprusside methods, respectively (Doane and Horwath, 2003; Mulvaney et al.,

1996). Soils were also analyzed for gravimetric water content (g H2O g soil-1) and bulk density. NY soil

samples were processed similarly (tests #2820 and 2511) through the Cornell Nutrient Analysis Lab (CNAL;

http://cnal.cals.cornell.edu/index.html).

Mid-season (visit 2)

In mid-season (second and third weeks of June in PA; third and fourth weeks of July in NY) each

year, plots were rated for weed pressure in and between raised beds on a 3-point scale (1 = few weeds, 2

= some weeds, 3 = very weedy), plastic mulch integrity on a three-point scale (1 = intact mulch, 2 = some

tears, 3 = very torn and/or mulch slashed), foliar thrips damage (ten plants per plot; 0-100% damage scale,

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modified from Nault and Shelton, 2010), and bulb growth (visual estimate; 1 = < 5.1 cm, 2 = 5.1 to 7.6 cm,

3 = > 7.6 cm). Five different, prevalent weeds were sampled from the field, placed in individual sealed

plastic bags, stored on ice, and then 4⁰C refrigeration until further processing. In PA , the fifth leaf of ten

equidistantly-spaced plants per plot was harvested, comingled in a paper bag, and dried in a 65⁰C drying

oven for ≥ 48 hr, and then was processed according to the tissue N protocol below. In NY, the inner four

leaves of ten plants were harvested, comingled by plot, dried, and processed according to standard CNAL

protocols for tissue analysis (test #6745).

Harvest (visit 3)

Growers were surveyed informally about the growing season in relation to production constraints

due to the weather, pests, etc. Soil was sampled according to the protocol described in visit 1, but only

the 2M KCl cup samples were prepared and processed. In PA, the inner two rows within 4.6 m of each

plot were harvested, graded by size, and evaluated for bacterial disease incidence (approx. 60 bulbs). In

NY, the entire plot was harvested, graded by size, and evaluated for bacterial disease incidence (approx.

130 bulbs). Onions were graded into four size categories based on the bulb diameter: < 6.4 cm diameter

are graded small, 6.4-7.6 cm diameter are graded medium, 7.6-10.2 cm diameter are graded jumbo, and

>10.2 cm diameter are graded colossal. In 2011 and 2012, 20 and 50% of the symptomatic bulbs,

respectively, were retained for further processing. Approximately 30 jumbo-size, asymptomatic bulbs

were retained for postharvest storage evaluation. If 30 jumbo-size, asymptomatic bulbs were not

available, 30 representatively-sized bulbs from the plot were sampled.

Postharvest bulb ratings

In both years, approximately 30 asymptomatic, jumbo-size onions per replicate plot were cured

under burlap in a greenhouse with forced air for at least 72 hr, then placed in 4⁰C storage for 75-120 days

(depending on harvest date). In mid-late November of the harvest year, approximately four months

postharvest, the bulbs were sliced in half longitudinally, photo-documented, and evaluated for disease

incidence, denoted as a percentage of the 30 bulbs per replicate plot.

Tissue N content

In 2011 and 2012, one representative asymptomatic, jumbo-sized bulb from the storage rating

from each grower plot was placed in a labeled paper bag and dried for ≥72 hr at 60⁰C. Thoroughly dried

leaf and bulb tissue samples were each ground to a fine, homogenous powder using a Cyclone Sample

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Mill grinder (UDY Corporation, Fort Collins, CO, USA) and maintained in tightly capped 50 mL (2011) or 25

mL (2012) centrifuge tubes until analysis. Analysis was performed in the Soils Research Cluster Lab in the

Department of Plant Sciences at Penn State, similar to (Russo, 2008; Westerveld et al., 2003). Briefly, a 4

g sample of each replicate sample was tared in a 502-186 foil cup (LECO Corporation, St. Joseph, MI) then

folded over to completely contain the powdered sample. Samples were analyzed via dry combustion in

EA1110 CHNSO Elemental Analyzer (Thermo Fisher Scientific, Milan, Italy), which produced a report

containing the C and N content of each sample. Elemental contents were calculated based on the weight

of the sample analyzed. NY samples were collected as described above and further processed by the CNAL

(test #6745).

Data analysis

Field values for each variable were represented by the average of three replicate plots and each

field was treated as a sample for each year and state. Total rot incidence was analyzed as the dependent

variable, which was the sum of the incidence of bacterial rot from harvest, plus the incidence of bacterial

rot at storage as a percentage of the remaining total of marketable bulbs. Data were analyzed using

multiple linear regression and the stepwise variable addition procedure (management variables), or the

one-way ANOVA procedure (NY cultivars) in Minitab 16.2 (Minitab Inc., State College, PA, USA). In some

datasets, transformations of total rot were necessary to ensure the datasets satisfied the assumption of

normality in the residuals (square root transformation, Table 3; logarithmic transformation, Tables 2, 4).

In some cases (PA-2011; combined NY), as many as three additional independent variables were not

included in models, since addition of the variables did not explain significantly more variation in the

models.

Interpretation of the interaction in the PA-2011 dataset was by simple slopes analysis (Aiken and

West, 1991), with foliar N values chosen as the sample mean ± 1 standard deviation and average soil

temperature three weeks preharvest chosen as the sample mean ± 0.5 °C (Fig. 1). The sample mean was

inputted as the foliar C value in all equations, since this variable did not interact with other independent

variables (cited in Preacher, 2003). Simple slopes were compared using a t test as described in Aiken and

West (1991), with α = 0.05.

Results

In PA in 2011, bacterial disease incidence at harvest from the set of 28 fields ranged from 0 to

50.2% and bacterial disease incidence from storage ranged from 2.1 to 41.6%. The summed total of

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bacterial rot incidence for the set of fields, therefore, ranged from 3.3 to 69.5%, which was the dependent

variable for the model in Table 4.1. Independent variables that were significant to the model were foliar

N and C from full-size, asymptomatic leaves collected at midseason, average soil temperature during the

3rd week preharvest (14-21 days prior; 3-wk soil temperature), and the interaction term between foliar N

and 3-wk soil temperature; other interactions in the model were not significant (Table 4.1). Prior to

addition of the interaction term, no multicollinearity was indicated among foliar N, foliar C, and 3-wk soil

temperature (variance inflation factors [VIFs] < 1.5; data not shown). All variables in the final model were

negatively related to total rot except the interaction term, which when investigated more closely by

simple slopes analysis (Fig. 4.1), indicated a positive relationship between average soil temperature and

total bacterial rot except at low levels of foliar N (one standard deviation below the mean), where 3-wk

preharvest soil temperature becomes less influential in the model and total bacterial rot incidence was

always projected to be high (Fig. 4.1).

In PA in 2012, bacterial disease incidence at harvest from the set of 26 fields ranged from 0 to

14.7% and bacterial disease incidence from storage ranged from 6.7 to 64.1%. Total bacterial rot for the

set, therefore, ranged from 7.6 to 68.6%, which was the dependent variable for the model. On initial

stepwise model fitting, no independent variables were selected for the model at α to add = 0.15 and α to

remove = 0.2. When model-fitting parameters were relaxed to α to add = 0.25 and α to remove = 0.3, nine

independent variables were added to the model; early soil NO3, foliar leaf N, and foliar leaf C at midseason

were the first three variables added to the model. When placed in multiple linear regression, these

variables gave an adjusted R2 = 0.212, no interactions were present, and there was no indication of

multicollinearity between the variables (VIFs < 1.7; Table 4.2). A positive relationship between total

bacterial rot and levels of soil NO3 early in the season was indicated (Table 4.2), as well as negative

relationships between each of the foliar tissue variables and the dependent total rot variable (Table 4.2);

the foliar tissue results were consistent with the PA-2011 dataset (Table 4.1). From graphical investigation

of single foliar nutrient variables, foliar N had a much stronger linear relationship with total bacterial

disease incidence than foliar C (data not shown); in some cases, inclusion of foliar N was necessary for

foliar C to be significant to linear regression models (Tables 4.1, 4.2, and 4.4). When foliar nutrients were

represented as the ratio of C to N and years were combined, a positive linear relationship was indicated

between foliar C/N ratio and total bacterial disease incidence (Fig. 4.2), however, inclusion of both foliar

elemental variables in regression analyses explained more total variation in bacterial disease incidence

than stating the variables as a single ratio (data not shown).

78

Total bacterial disease incidence at harvest was very low in NY in both 2011 and 2012, with

averages of 5.2% and 4.6%, respectively. Nine different cultivars were grown and the cv. ‘Red Wing’ had

significantly higher total bacterial disease incidence than seven other cultivars (Fig. 4.3). As a result, the

‘Red Wing’ fields were removed before the stepwise model fitting step for multiple linear regression

analysis. Since total disease incidence did not differ by year, the NY datasets were combined after

removing the five ‘Red Wing’ fields. In the remaining data (N = 49), total bacterial disease incidence at

harvest ranged from 0 to 18.6% and bacterial disease incidence from storage ranged from 0 to 9.9%.

Therefore, total bacterial rot for the dataset ranged from 0 to 22.7%, which was the dependent variable

for the model. On stepwise model fitting with α to add = 0.15 and α to remove = 0.2, midseason soil NO3

and average soil temperature five weeks preharvest were both positively related to total bacterial rot

incidence (Table 4.3). Bulb N, bulb C, and onion thrips damage ratings were also suggested for the model,

but inclusion of all of these variables only explained approximately 2.1% more total variation (data not

shown), thus, the variables were excluded.

In the combined PA dataset, total bacterial rot incidence ranged from 3.3 to 69.5% among 54

fields. In stepwise model fitting, the selection parameters were restricted to α to add = 0.05, α to remove

= 0.1, and both foliar N and C measured at midseason were significant factors in the model (Table 4.4).

These factors were both negatively related to total incidence of bacterial rots of onion and their

interaction term was not statistically significant (Table 4.4).

Discussion

Intensive surveys of farms growing onions in 2011 and 2012 indicated one novel trend among PA

datasets and another that bolsters results from other replicated trials. In ‘Candy’ onion, plant nutrition

and the total incidence of bacterial rots of onion are negatively related. Specifically, foliar nitrogen (N)

and carbon (C) were influential factors in both PA datasets (Tables 4.1 and 4.2), and very strong factors in

the combined PA dataset (Table 4.4); in addition, soil NO3 was influential in the PA-2012 and combined NY

datasets (Table 4.2 and 4.3). Foliar N in the PA-2011 dataset interacted with soil temperatures three weeks

prior to harvest (Fig. 4.1).

The foliar tissue test results are in direct contrast to a-priori hypotheses, wherein it was thought

that excessive N fertility would result in high levels of bacterial disease at harvest, which has been

demonstrated in other systems (Diaz-Perez et al., 2003; Mohan, 2008a; Gitaitis et al., 2008). Instead, the

negative relationship between midseason foliar N and bacterial disease incidence may indicate that

‘Candy’ onion plants that are N-stressed early in the season may be more susceptible to bacterial

79

infection, proliferation, and/or movement into the onion bulb. Other research identified that tissue N

levels differed by onion cultivar (Westerveld et al., 2003), so additional data would be necessary to

determine if the relationship between foliar nutrients and disease incidence is a unique attribute of

‘Candy’ onions or if this relationship may be applied more broadly to all onion cultivars.

In the combined PA datasets, levels of early-season soil NH4 and the silt content of soils were

positively related to levels of foliar N (data not shown), so site selection and the type of N fertilizer applied

may be of interest to growers. Nitrogen cycling is dependent on a number of soil characteristics, including

temperature, moisture, oxygen, pH, organic matter, and microbial diversity (Daroub and Snyder, 2007),

and texturally, more silt in soils may help ensure optimal levels of these characteristics. In the NY

combined dataset, no associations were indicated between foliar nutrient levels and bacterial disease

incidence, but a positive relationship between midseason soil NO3 and total disease incidence was

indicated (Table 4.3). At-harvest levels of soil NO3 and NH4 were not associated with bacterial disease

incidence or the proportion of large-size bulbs, and taken together, these begin to suggest the timing of

N availability may be more influential than a season-long, rate-based recommendation, which aligns well

with anecdotal evidence shared by experienced onion growers included in this study. One onion grower,

who has commercially produced onions for ten years and designs his own fertility program, remarked that

he does not fertigate after the first week of June (roughly two weeks prior to bulbing), and simply irrigates

until harvest the first week of July (pers. communication). In addition, similar timing of nutrient

availability, where N applications were reduced or eliminated after bulbing, indicated no adverse effects

on onion size or maturity (Brewster and Butler, 1989).

Coupled with the midseason foliar N measurements, the PA datasets indicate foliar C at

midseason is another critical predictor of bacterial disease incidence at harvest and from storage (Tables

4.1, 4.2, 4.4). While Pearson’s correlations suggested foliar N and foliar C were correlated (data not

shown), interactions between these variables in linear regression models were not significant in these

analyses. It is generally accepted that phytopathogenic bacteria parasitize plants in an effort to secure

carbon for their own metabolism, and centers of infection may act as photoassimilate sinks in plants

(Kosuge and Kimpel, 1982), however, results pertaining to midseason foliar C indicate a negative

relationship with total bacterial disease incidence. Work completed in Arabidopsis where induction of the

plant defense-related genes ATL31, ATL6, and their knockouts were compared under conditions of C and

N stress indicated increased symptom severity caused by Pseudomonas syringae pv. tomato DC3000

under nutrient-limiting conditions, and ATL31- mutant plants were less sensitive to low nutrient

conditions (Maekawa et al., 2012). ATL31 has been shown to function in both defense responses and

80

coordinate post-germinative growth in accordance with C/N ratio, however, this occurred under high C/N

conditions (Sato et al., 2009). This contrasts to the PA datasets presented here, where C/N ratio was

shown to be positively related to total incidence of bacterial rot of onion (Fig. 4.2). Specific assays would

need to be completed with onion in order to elucidate the effects of high tissue C/N ratios on bacterial

disease severity.

Other nutrient-related variables of interest associated with total bacterial disease incidence in

some of the models include positive relationships with the early-season (Table 4.2) or midseason NO3

levels in soil (Table 4.3). The results pertaining to NO3 levels are similar to results in other pathosystems,

where high levels of soil NO3 were correlated with high bacterial disease incidence (Rotenberg et al.,

2005), and taken together with the previously-mentioned positive relationship between early-season soil

NH4 and midseason leaf N, may indicate that onion, as a crop, prefers NH4 – N to NO3 - N. Associations

between disease incidence and the type of inorganic N fertilizer have been observed for other crops,

however, each pathosystem varies in how these relationships manifest (Elmer, 2000; Elmer and

LaMondia, 1999; Thompson and Huber, 2007). One suggestion from these works is that higher NH4

concentrations promote the acidity of soil and thus allow micronutrients, such as Mn and Zn, to be more

readily taken up by plants (Elmer, 2000; Elmer and LaMondia, 1999); higher levels of these micronutrients

have been implicated in bacterial disease reduction (Thompson and Huber, 2007). Combined with the lack

of reproducibility between years and sample sites, this theme indicates additional replicated trials may be

necessary before changes in fertility recommendations may be made to growers.

Positive relationships between soil temperatures three or five weeks preharvest and the total

incidence of bacterial rots were observed in the PA-2011 (Table 4.1) and the NY datasets (Table 4.3),

respectively. Positive relationships between air temperature as reported by weather stations and

bacterial rot are fairly well-established in the onion pathosystem (Gitaitis et al., 2008; Mohan, 2008a;

Schwartz et al., 2003), and soil temperatures have been suggested to be closely associated with center

rot of onion (Diaz-Perez et al., 2003; Gitaitis et al., 2003), however, explicit relationships between soil

temperatures and other bacterial rots of onion have not been previously reported. In addition, three and

five weeks preharvest in PA and NY, respectively, roughly correspond with the physiological onset of

bulbing, which relates well to results reported by Schwartz et al., where high temperatures at bulbing

were associated with initial onset of Xanthomonas leaf streak in onion (2003). In the PA-2011 dataset, an

interaction between soil temperature three weeks preharvest and levels of foliar N existed, but when

investigated more fully through simple slopes analysis (Aiken and West, 1991), it was predicted that soil

temperature would only play a role in increasing bacterial disease incidence at average and above-average

81

levels of foliar N at midseason (Fig. 4.1). At below-average levels of foliar N, it was predicted that total

bacterial disease incidence would always be high, regardless of soil temperatures three weeks preharvest

(Fig. 4.1). The potential interaction between soil temperatures five weeks preharvest and midseason soil

NO3 was not significant in the combined NY model (Table 4.3). These results relate well to the influence

of soil temperature on bacterial disease incidence in the use of different types of plastic mulches. Through

several replicated trials, it was shown that plots with plastic mulches that kept soils cooler also had lower

incidence of bacterial rots than plots with high-soil temperature mulches (Gugino et al., 2011).

Since the datasets discussed here are largely observational, results may be used to develop more

targeted replicated field trials in the future, with the overall goal of improving management

recommendations for onion growers. The relationships between midseason foliar N and C, soil NO3, and

total incidence of bacterial rots of onion (Tables 4.1, 4.2, 4.3, 4.4) indicate further research into the type

and timing of nitrogen fertility is necessary. The positive relationship between soil temperatures in PA-

2011, NY-2011/2012, and bacterial rot incidence has been indicated in several replicated trials, where

plastic mulches that reduced soil temperatures were shown to result in lower disease incidence (Gugino

et al., 2011). These datasets have resulted in revisions to production guides such that black biodegradable

plastic mulches are now recommended to help moderate soil temperatures, particularly after midseason.

Acknowledgements

Soil nitrate, ammonium, and PMN were processed in Dr. Jason Kaye’s lab in the Department of Ecosystem Resource Management at Penn State, with the assistance of Dr. Kaye, Sara Eckert, and Kaye lab members.

Foliar and bulb tissue N and C content were processed in the Soils Research Cluster Lab at Penn State with the assistance of Dr. Ephraim Govere.

Technical assistance was provided by Dr. Michele Mansfield, Tim Grove, Ilse Huerta, Evan Stover, Jill Pollok, Robert, Andrew Hower, Khanh Nguyen, Lizzie King’ang’i, Rosemary Schwegel, Marie Ebner, Anna Testen, Laura Ramos, Laura del Sol Bautista, and Andy Kelly.

Many thanks to our truck benefactor, Dr. Scott Isard.

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Tables and Figures

Table 4.1. Field-averaged results of multiple linear regression analysis of PA-2011 dataset. All variables were placed in a stepwise model selection procedure (α to add = 0.15, α to remove = 0.2), with total bacterial rot incidence as the dependent variable. For this model, R2 = 0.557; adj. R2 = 0.480; P = 0.001.

Predictor Coefficient SE of Coefficient T value P value

Constant 1582.5 610.8 2.59 0.016 Foliar N, midseasona -468.9 186.5 -2.51 0.019 Average soil T, 3 wk preharvestb -41.81 20.23 -2.07 0.050 Foliar C, midseasona -9.63 4.50 -2.14 0.043 Foliar N * 3 wk soil T interaction 17.02 7.30 2.33 0.029

a The fifth leaf from ten equidistantly spaced plants was collected at the midseason visit, bulked by plot, dried, homogenized, and analyzed for total C and N via dry combustion. Three replicate plots were averaged by field prior to analysis. b Soil temperatures 3-in. beneath the soil surface, beneath the plastic mulch, were recorded hourly throughout the growing season. Datasets were normalized by harvest date, then weekly averages were calculated; this variable represents the time period 14-21 days preharvest.

Fig. 4.1. Simple slopes analysis of projected relationships between average soil temperature three weeks preharvest and the incidence of total bacterial rot of onion, given different levels of foliar N, from PA-2011. Points of each line were calculated based on the covariance matrix of the multiple regression model in Table 1 (Aiken and West, 1991). Foliar N values (2.41% N [low], 2.75% N [avg], 3.09% N [high]; ±1 standard deviation from the sample mean) were chosen, then projected bacterial disease estimates were calculated based on chosen average soil temperatures three weeks preharvest (23.79, 24.29, 24.79°C; ± 0.5 °C from the sample mean). Simple slopes were compared to H0 = 0; for average and high foliar N lines, t was significant at P = 0.03.

83

Table 4.2. Field-averaged results of multiple linear regression analysis of PA-2012 dataset. All variables were placed in a stepwise model selection procedure (α to add = 0.25, α to remove = 0.3), with a logistic transformation of total bacterial rot incidence as the dependent variable. For this model, R2 = 0.314; adj. R2 = 0.212; P = 0.052.

Predictor Coefficient SE of Coefficient T value P value

Constant 7.513 2.971 2.53 0.020 Foliar N, midseason a -0.377 0.147 -2.56 0.018 Foliar C, midseason a -0.136 0.071 -1.91 0.070 Early-season soil nitrate b 0.004 0.002 1.98 0.062

a The fifth leaf from ten equidistantly spaced plants was collected at the midseason visit, bulked by plot, dried, homogenized, and analyzed for total C and N via dry combustion. Three replicate plots were averaged by field prior to analysis. b Soil from the first farm visit was analyzed for nitrate using the VCl3 protocol.

Fig. 4.2. Total bacterial disease incidence by foliar C/N ratio, combined data from PA-2011 and PA-2012. Ten leaves per plot were co-mingled, dried, homogenized, and analyzed for total C and N via dry combustion. Total bacterial disease incidence was the sum of the percentages of symptomatic bulbs at harvest and from storage as a total of the bulbs harvested per plot. Three plots were averaged for each field value; each point represents one field.

Table 4.3. Field-averaged results of multiple linear regression analysis of combined NY-2011 and 2012 datasets. Independent variables were observed in 22 and 32 fields, respectively. All variables were placed in a stepwise model selection procedure (α to add = 0.15, α to remove = 0.2), with a square root transformation of total bacterial rot incidence for each field as the dependent variable. For this model, R2 = 0.161; adj. R2 = 0.126; P = 0.019.

Predictor Coefficient SE of Coefficient T value P value

Constant -7.138 3.884 -1.84 0.073 Midseason soil nitrate a 0.003 0.001 2.51 0.016 Average soil T, 5 wk preharvest b 0.112 0.052 2.17 0.035

a Soil from the second farm visit was analyzed for nitrate using the CNAL protocol. b Soil temperatures 3-in. beneath the soil surface, were recorded hourly throughout the growing season. Datasets were normalized by harvest date, then weekly averages were calculated; this variable represents the time period 28-35 days preharvest.

84

Fig. 4.3. Total bacterial rot incidence by cultivar grown, NY-2011 and NY-2012. Data were analyzed using a one-way ANOVA in Minitab 16.2, error bars represent the standard error of the mean, and letters above each bar indicate statistically significant differences by Fisher’s LSD (α = 0.05).

Table 4.4. Field-averaged results of multiple linear regression analysis of combined PA datasets. All independent variables observed in 54 fields were placed in a stepwise model selection procedure (α to add = 0.05, α to remove = 0.1), with a log transformation of total bacterial rot incidence as the dependent variable. For this model, R2 = 0.179; adj. R2 = 0.147; P < 0.001.

Predictor Coefficient SE of Coefficient T value P value

Constant 5.657 1.477 3.83 <0.001 Foliar N, midseasona -0.391 0.122 -3.21 0.002 Foliar C, midseasona -0.081 0.031 -2.59 0.012

a The fifth leaf from ten equidistantly spaced plants was collected at the midseason visit, bulked by plot, dried, homogenized, and analyzed for total C and N via dry combustion. Three replicate plots were averaged by field prior to analysis.

References

Aiken, L. S., West, S. G. 1991. ‘Interactions between Continuous Predictors in Multiple Regression’ in: Multiple Regression: Testing and Interpreting Interactions. SAGE Publications, Inc: Thousand Oaks, CA. pp. 12-14. Brewster, J. L., Butler, H. A. 1989. Effects of nitrogen supply on bulb development in onion Allium cepa L. Journal of Experimental Botany 40:1155-1162. Bull, C. T., De Boer, S. H., Denny, T. P., Firrao, G., Fischer-Le Saux, M., Saddler, G. S., Scortichini, M., Stead, D. E., Takikawa, Y. 2010. Comprehensive list of names of plant pathogenic bacteria, 1980 – 2007. Journal of Plant Pathology 92: 551 – 592. Carr, E. A., Zaid, A. M., Bonasera, J. M., Lorbeer, J. W., Beer, S. V. 2013. Infection of onion leaves by Pantoea ananatis leads to bulb infection. Plant Disease 97:1524-1528.

85

Coenye, T., Vandamme, P. 2003. Diversity and significance of Burkholderia species occupying diverse ecological niches. Environmental Microbiology 5: 719-729. Conover, R. A., Gerhold, N. R. 1981. Mixtures of copper and maneb or mancozeb for control of bacterial spot of tomato and their compatibility for control of fungus diseases. Proceedings of the Florida State Horticultural Society 94: 154-156.

Coutinho, T. A., Venter, S. N. 2009. Pantoea ananatis: an unconventional plant pathogen. Molecular Plant Pathology 10: 325-335.

Daroub, S. H., Snyder, D. H. 2007. ‘The Chemistry of Plant Nutrients in Soil’ in: Mineral Nutrition and Plant Disease. Editors: L. E. Datnoff, W. H. Elmer, D. M. Huber. APS Press: St. Paul, MN.

Diaz-Perez, J. C., Purvis, A. C., Paulk, J. T. 2002. Bolting, yield, and bulb decay of sweet onion as affected by nitrogen fertilization. Journal of the American Horticultural Society 128:144-149.

Doane, T. A., Horwath, W. R. 2003. Spectrophotometric determination of nitrate with a single reagent. Analytical Letters 36: 2713-2722. Elmer, W. H. 2000. Comparison of plastic mulch and nitrogen form on the incidence of Verticillium wilt of eggplant. Plant Disease 84:1231-1234. Elmer, W. H., LaMondia, J. A. 1999. Influence of ammonium sulfate and rotation crops on strawberry black root rot. Plant Disease 83:119-123. Gent, D. H., Schwartz, H. F. 2008. ‘Bacterial Stalk and Leaf Necrosis’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 66-67.

Gent, D. H., Schwartz, H. F. 2005. Management of Xanthomonas leaf blight of onion with a plant activator, biological control agents, and copper bactericides. Plant Disease 89:631-639.

Gitaitis, R., Walcott, R., Culpepper, S., Sanders, H., Zolobowska, L., Langston, D. 2003. Recovery of Pantoea ananatis, causal agent of center rot of onion, from weeds and crops in Georgia, USA. Crop Protection 21: 983-989.

Gitaitis, R. D., Walcott, R. R., Sanders, H. F., Zolobowska, L., Diaz-Perez, J. C. 2004. Effects of mulch and irrigation system on sweet onion: II. The epidemiology of center rot. Journal of the American Society of Horticultural Science 129: 225-230. Gitaitis, R. D., Gent, D. H., Schwartz, H. S. 2008. ‘Leaf streak and bulb rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 59. Gugino, B. K., Hoepting, C. A., Stoltzfus, J., Mansfield, M. A., Klotzbach, K., Reid, J. E. 2011. Management of onion bacterial diseases using alternative mulches and plant spacing. Phytopathology 101: S65. Kosuge, T., Kimpel, J. A. 1982. ‘Altered Metabolism: Response to Infection’ in Phytopathogenic Prokaryotes, Volume 1. Edited by M. Mount and G. H. Lacy. Academic Press, Inc: New York, NY. pp 366-368.

86

Maekawa, S., Sato, T., Asada, Y., Yasuda, S., Yoshida, M., Chiba, Y., Yamaguchi, J. 2012. The Arabidopsis ubiquitin ligases ATL31 and ATL6 control the defense response as well as the carbon/nitrogen response. Plant Molecular Biology 79:217-227.

Mohan, S. K. 2008. ‘Other Bacterial Soft Rots’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 62.

Mulvaney, R., Sparks, D., Page, A., Helmke, P., Loeppert, R., Soltanpour, P., Tabatabai, M., Johnston, C., Sumner, M. 1996. Nitrogen-Inorganic Forms. Methods of Soil Analysis. Part 3-Chemical Methods. pp. 1123–1184.

Nault, B. A., Shelton, A. M. 2010. Impact of insecticide efficacy on developing action thresholds for pest management: a case study of onion thrips (Thysanoptera: Thripidae) on onion. Journal of Economic Entomology 103: 1315 – 1326.

Nischwitz, C., Gitaitis, R., Sanders, H., Langston, D., Mullinix, B., Torrance, R., Boyhan, G., Zolobowska, L. 2007. Use of fatty acid methyl ester profiles to compare copper-tolerant and copper-sensitive strains of Pantoea ananatis. Phytopathology 97: 1298-1304. Preacher, K. J. 2003. ‘A primer on interaction effects in multiple linear regression.’ Vanderbilt University, accessed online July 27, 2014: http://www.quantpsy.org/interact/interactions.htm Rotenberg, D., Cooperband, L., Stone, A. 2005. Dynamic relationships between soil properties and foliar disease as affected by annual additions of organic amendment to a sandy-soil vegetable production system. Soil Biology and Biochemistry 37:1343-1357. Russo, V. M. 2008. Plant density and nitrogen fertilizer rate on yield and nutrient content of onion developed from greenhouse-grown transplants. HortScience 43: 1759-1764. Sanchez, E., Elkner, T. E., Lamont, W. J., Demchak, K., Orzolek, M. D., Gugino, B. K., Halbrendt, J. M., Fleischer, S. J., LaBorde, L., Hoffman, K., San Julian, G. J. 2014. Commercial Vegetable Production Recommendations – Pennsylvania 2014. Penn State Cooperative Extension, Pennsylvania Agricultural Experiment Station, and The Pennsylvania State University, University Park, PA. 329 pp. Sato, T., Maekawa, S., Yasuda, S., Sonoda, Y., Katoh, E., Ichikawa, T., Nakazawa, M., Seki, M., Shinozaki, K., Matsui, M., Goto, D. B., Ikeda, A., Yamaguchi, J. 2009. CNI1/ATL31, a RING-type ubiquitin ligase that functions in the carbon/nitrogen response for growth phase transition in Arabidopsis seedlings. The Plant Journal 60: 852–864.

Schwartz, H. F., Otto, K. L., Gent, D. H. 2003. Relation of temperature and rainfall to development of Xanthomonas and Pantoea leaf blights of onion in Colorado. Plant Disease 87:11-14.

Thompson, I. A., Huber D. M. 2007. ‘Manganese and Plant Disease’ in: Mineral Nutrition and Plant Disease. Edited by L.E. Datnoff, W.H. Elmer, D. M. Huber. APS Press: St. Paul, MN.

Westerveld, S. M., McKeown, A. W., Scott-Dupree, C. D., McDonald, M. R. 2003. How well do critical nitrogen concentrations work for cabbage, carrot, and onion crops? HortScience 38: 1122-1128.

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Chapter 5: Efficacy of plant defense-inducing and growth-promoting products for the management of center rot of onion, caused by Pantoea ananatis and P. agglomerans

Abstract

Center rot, caused by the bacteria Pantoea ananatis and Pantoea agglomerans, is an emerging

disease of onion in Pennsylvania. Growers primarily manage onions for bacterial diseases using copper

mixed with ethylene-bis-dithiocarbamate fungicides, however, low efficacy has been reported for this

practice. A number of plant defense-inducing and growth-promoting products are labeled for onion,

however, little data on the efficacy of these products was available. To determine the efficacy of these

products for the management of center rot of onion, replicated field trials were undertaken in two

locations in 2011 and 2012, using two different inoculation techniques. The 2012 inoculation technique

effectively resulted in disease pressure at three different levels. In low inoculum pressure plots, the

grower standard copper-EBDC, hydrogen peroxide, harpin alternated with copper-EBDC, and acibenzolar-

S-methyl treatments resulted in lower disease incidence than the untreated control, but no treatments

were effective in the untreated plots at higher inoculum pressures. Though not statistically significant,

plants treated with Bacillus subtilis GB03 consistently had lower disease incidences than other treatments.

Introduction

Pennsylvania growers may suffer yield losses of 50% or more due to bacterial diseases of onion

(Allium cepa L.), including center (caused by Pantoea ananatis Serrano and Pantoea agglomerans

Beijerinck) and soft rots (caused by Pectobacterium carotovorum subsp. carotovorum Jones and

Pseudomonas marginalis pv. marginalis Stevens). Center rot symptoms typically develop following the

infection of a single leaf, with the bacteria progressively moving proximally into the corresponding

enlarged scale in the onion bulb (Carr et al., 2013). The primary chemical management strategy for

bacterial diseases of onions is the use of preventative applications of copper hydroxide combined with

ethylene-bis-dithiocarbamate (EBDC) fungicides, which are reported to increase the efficacy of copper

(Conover and Gerhold, 1981; Gent and Schwartz, 2005). EBDC fungicides, such as mancozeb, have been

shown to be class B-2 carcinogens, were cancelled for selected uses in 1992, including green onion

(EXTOXNET, 1992), and are not permissible for use in organic production systems, which has led some

growers to call for alternative chemical management strategies for onion production. Most importantly,

even under conscientious management using the copper - EBDC grower standard, extensive losses due to

bacterial disease may still occur.

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Some interest has been expressed in plant defense-inducing compounds as alternatives to

traditional copper-EBDC treatments for the management of bacterial bulb rots of onion. Several different

types of plant defense-inducing compounds have been suggested as effective management tools for plant

disease, particularly viral and bacterial diseases (Gent and Schwartz, 2005; Louws et al., 2001; Romero et

al., 2001). In addition, commercial plant growth-promoting products have been suggested to activate

induced systemic resistance (ISR) or systemic acquired resistance (SAR), which increase plants’ natural

defenses against pathogens and insects (van Wees et al., 2000; Walters et al., 2005; Siddiqui, 2006).

Salicylic acid (SA), a defense signaling molecule that naturally occurs in plants, activates systemic

acquired resistance (SAR), which provides nonspecific, long-lasting, systemic control against plant

pathogens as part of pathogen associated molecular pattern (PAMP)- and effector- triggered immunity

(Jones and Dangl, 2007; van Wees et al., 2000; Walters et al., 2005; Walters et al., 2009). SA biosynthesis

and SA-induced genes have been shown to be activated in response to plant infection with biotrophic

pathogens (Spoel et al., 2007), and implicated in interactions between Pseudomonas syringae pv. tomato

and tomato (Solanum lycopersicum; Thaler et al., 2002), and a number of other pathosystems.

Acibenzolar-s-methyl (ASM), a synthesized analog of SA, is one of an increasing group of plant defense-

inducing products marketed to conventional vegetable growers, particularly those who suspect resistance

to copper-based treatments (Gugino, pers. comm.) In a study on the onion foliar pathogen X. axonopodis

pv. allii Hasse, Gent and Schwartz (2005) evaluated combinations of plant defense activators and

biological control agents along with traditional copper applications in the management of onion leaf

blight. Reduced-copper applications combined with ASM were comparable or more effective for leaf

blight control compared to a traditional copper - EBDC spray program (Gent and Schwartz, 2005).

Harpin protein, a pathogenicity factor isolated from Erwinia amylovora (Wei et al., 1992), was first

found to elicit a hypersensitive response, and later, to activate systemic acquired resistance (SAR) in

Arabidopsis (Dong et al., 1999). Harpin protein homologues have been shown to be synthesized by several

plant pathogenic strains of bacteria, including causal agents of soft rots (Nasser et al., 2005) and Pantoea

stewartii subsp. stewartii (Ahmad et al., 2001), which is fairly closely related to P. ananatis. By utilizing

transgenic E. coli, harpin protein is now mass-produced and marketed commercially as a plant defense

inducing product (EPA, 2011).

The potential for acibenzolar-S-methyl (ASM) and harpin protein to assist in managing bacterial

disease in onion bulbs suggests these products are worth further investigation. Currently, ASM is

marketed in the US as Actigard 50WG (Syngenta Crop Protection, Greensboro, NC) and onions are

included on the product label. Purified harpin protein (Employ or ProAct; Plant Health Care, Inc.,

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Pittsburgh, PA) is marketed as a preventative treatment for a variety of diseases on virtually any crop.

While ASM functions as a mimic of salicylic acid (SA), harpin protein triggers plants to naturally produce

SA (EPA, 2011). These types of plant-induced defenses may come at the cost of yield as a result of a

potential deficit in metabolic resources, due to maintenance of high levels of defense proteins (Gent and

Schwartz, 2005; Louws et al., 2001; Romero et al., 2001; Walters and Fountaine, 2009). This ‘yield-drag’

effect may be especially pronounced, as both product labels warn, during periods of plant stress.

Mitigation of this effect has been reported by the use of plant-growth promoting rhizobacteria (PGPR) in

amaranthus (Nair et al., 2006) and tomato (Obradovic et al., 2005), so combinations of SAR inducers and

plant-growth promoters present potential to manage bacterial disease while still producing profitable

yields.

Plant growth-promoting rhizobacteria (PGPR) have been shown to induce positive effects on

plants in a number of ways, including nitrogen fixation, phosphate solubilization (Lugtenberg and

Kamilova, 2009; Van Loon, 2007), soil pollutant remediation (Kuiper et al., 2001), and the stimulation of

root hair growth (Brazelton et al., 2008; Dodd et al., 2010). As biocontrol agents of soilborne pathogens,

PGPR may exclude pathogens from the rhizosphere by resource competition, inhabiting facultative

pathogen niches, or by producing secondary metabolites, such as antibiotic compounds or siderophores

(Kokalis-Burelle et al., 2003; Lugtenberg and Kamilova, 2009; Van Loon, 2007). Others suggest that PGPR

may interfere with pathogen quorum sensing systems (Lin et al., 2003), which help coordinate pathogen

infection of potential hosts. The most notable effect of PGPR, however, in terms of plant disease, may be

the positive regulation of induced systemic resistance (ISR). ISR is similar to SAR in its result (heightened

plant defenses against a variety of plant pathogens), but the two types of resistance differ in terms of

signaling molecules, genetic determinants, and inducing organisms (Siddiqui, 2006).

Arbuscular mycorrhizal fungi (AMF) function in a similar relationship to some PGPR: AMF are

fungal symbionts that form associations with terrestrial plants and have been shown to reduce the

incidence and severity of diseases caused by soilborne fungi, oomycetes, and nematodes (Whipps, 2004).

Some studies have also examined the role of AMF in reducing foliar bacterial diseases in tomato and alfalfa

(Garcia-Garrido and Ocampo, 1988; Liu et al., 2007). Specifically, Liu et al. recorded an overall increase in

stress and defense-associated gene expression in Medicago truncatula shoots and roots following the

development of mycorrhizal associations, which was coordinated with an overall reduction in foliar

symptoms caused by Xanthomonas campestris pv. alfalfae (2007). The authors concluded the M.

truncatula response to the formation of mycorrhizal associations was homologous to induction of ISR (Liu

et al., 2007); this is supported by the results that AMF associations with plants are mediated by the same

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signaling molecules as PGPR-induced ISR (Pozo and Azcon-Aguilar, 2007). Rather than its effects on plant

defenses, however, the majority of horticultural studies on AMF focus on their ability to improve water

and nutrient uptake, especially phosphorus, in arid or nutrient-poor soils (Borowicz, 2001; Simard and

Durall, 2004). In this way, PGPR and AMF may alternatively serve to reduce plant nutrient stress by way

of their suggested roles of enhancing nutrient uptake. These additional nutrients could mitigate yield

reduction effects when used in combination with plant defense-inducers.

In addition to the previously mentioned plant defense-inducing and plant growth-promoting

products, a number of growers have begun to use surface-sterilizing type treatments to manage bacterial

diseases in their onions. In particular, OxiDate (active ingredient hydrogen dioxide, BioSafe Systems,

Glastonbury, CT) is marketed to growers as a broad-spectrum bactericide/fungicide, and is an OMRI-listed

product approved for organic production systems. The product is labeled for onion for the management

of Botrytis, downy mildew, powdery mildew, and in particular, has some efficacy data available for

management of Xanthomonas leaf blight. In addition, the product label lists two concentrations for

product use on onion, ‘preventative,’ and ‘curative,’ both on a 5-7 day spray interval; curative is simply

the maximum concentration, while preventative is a reduced concentration. Several PA growers have

already begun treating their onion crops using hydrogen peroxide, however, efficacy data for

management of typical PA diseases, such as center rot, are lacking overall.

With expressed grower interest in the aforementioned foliar plant defense-inducing products, soil

treatments for induced disease resistance, and surface sterilizants, replicated studies of selected

commercial products were undertaken on two university research farms in 2011 and 2012. Two

inoculation protocols were explored, and in-season growth and disease estimates were recorded in

addition to harvest yields and disease incidence.

Materials and Methods

Field trial establishment and maintenance

In 2011 and 2012, replicated research trials were established at the Russell E. Larson Agricultural

Research and Education Center in PA Furnace, PA (Rock Springs), and the Southeast Agricultural Research

and Extension Center in Manheim, PA (Landisville); soil in both fields were Hagerstown silt loam. The fields

were plowed and prepared following standard commercial production practices. Raised beds with 1.0 or

1.5-mil standard black plastic mulch and a double row of drip-irrigation tape were formed using a raised-

bed plastic mulch layer (Rain-Flo Irrigation Inc., East Earl, PA). Beds were spaced on 2.4 or 3 m centers

depending on the year and trial location. ‘Candy’ onion transplants (Dixondale Farms, Carrizo Springs, TX)

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were spaced 15.2 cm apart in the row and 15.2 cm apart between rows, with four rows across an approx.

1 m bed. Plots were one bed wide and 3.7 or 4.3 m long with 0.3 or 1.5 m breaks between plots, depending

on year and location. Insects were managed using Radiant SC (0.44 -0.73 L / ha, Dow AgroSciences,

Indianapolis, IN) and/or Warrior 1EC (0.19 – 0.28 L / ha, Syngenta Crop Protection, Greensboro, NC) as

necessary and weeds were hand-pulled within the row and mowed between rows. Onions were fertilized

through drip irrigation weekly with a water-soluble 30% liquid urea fertilizer (Helena Chemical Co.,

Collierville, TN, USA) following standard commercial production practices, typically application of 16.8 kg

/ ha per week, to a field rate of nitrogen of 168 - 196 kg / ha for the season.

In 2011, onions were transplanted on April 19 and 21 at research farms in Rock Springs and

Landisville, respectively, and arranged in a randomized block design with four replicates in each trial;

untreated controls were included as treatments in this design. In 2012, onions were transplanted on April

17 and 19 at Rock Springs and Landisville, respectively, and treatments were arranged in a randomized

block design, but each treatment plot was split into uninoculated and inoculated subplots in order to

account for yield fluctuations that may occur by the use of the products in the absence of disease.

Treatments

In 2011, the treatments included acibenzolar-S-methyl (ASM; Actigard 50WG, Syngenta Crop

Protection, Greensboro, NC, USA), harpin protein (harpin; Employ, Plant Health Care, Pittsburgh, PA, USA),

Glomus intraradices (GI; Myke Pro WG, Premier Tech Biotechnologies, Rivière-du-Loup, Québec, Canada),

and Bacillus subtilis GB03 (GB03; Companion, Growth Products, Ltd., White Plains, NY, USA). GB03 and GI

were applied as a drench at the base of the plant two days after planting at concentrations of 8.19 mL / L

and 36 spores / 150 mL (159 g / L), respectively, using a backpack sprayer with a concentrated spigot tip.

After sprayer calibration, the application was estimated at 150 mL / plant. At Rock Springs, foliar

treatments were applied using a tractor mounted, CO2-powered side boom sprayer calibrated to deliver

206 L / ha at 24 psi through three TX-18 nozzles, while at Landisville treatments were applied using a Solo

backpack sprayer. Weekly foliar applications of copper hydroxide (Kocide 3000; Dupont, Wilmington, DE,

USA; 1.68 kg / ha) tank-mixed with mancozeb (Penncozeb 75DF; Cerexagri-Nisso LLC, King-of-Prussia, PA,

USA; 1.68 kg / ha) was applied as a grower standard. Harpin was applied at a rate of 146 mL / ha per

treatment, while ASM was applied at 5.5 mL / ha per treatment following the application schedules in

Tables 5.1 and 5.2 for 2011 and 2012, respectively.

In 2012, ASM, harpin, GB03, hydrogen peroxide, and the current grower standard copper

hydroxide + EBDC were applied singly or in combination. ASM and harpin were applied at concentrations

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consistent with the label and listed above. Hydrogen peroxide (Oxidate, Biosafe Systems Inc., Glastonbury,

CT, USA) was applied weekly at two concentrations, preventative (9.3 L / ha for three weekly applications,

then 2.9 L / ha weekly after) and curative (9.3 L / ha weekly). Treatment dates and rates are outlined in

Table 5.1.

Leaf length

On June 10, 2011, the number of leaves as well as the longest leaf of each of five plants per plot

were measured (cm) as a measure of vigorous growth, which is one of the additional product claims.

Inoculation

In 2011, onion plants were inoculated on June 21 with 108 colony-forming units (CFU) /mL

suspension of six isolates of bacterial species P. ananatis (isolates PA1a, PA1b, and 09-082) and P.

agglomerans (isolates 10-009, 10-022, and 09-063) in a 0.1% Silwet solution. All isolates were initially

isolated from symptomatic onions from PA farms in 2008, 2009, or 2010 and are part of the Gugino Lab

bacterial isolate collection. Plants were sprayed to run-off less than 1 hr before sunset with a backpack

sprayer on June 21. Four leaves from each treatment were sampled the next morning, placed individually

in plastic bags, each shaken in 100 mL buffer, and plated on PA20, a semi-selective medium for Pantoea

spp. (Goszczynska et al., 2006). Epiphytic bacterial populations remained at least 106 CFU / mL (data not

shown).

In 2012, onion plants were inoculated June 13 with a 108 CFU / mL mix of two strains of P. ananatis

(isolates PA1a and PA1b) and two strains of P. agglomerans (isolates 2010-009 and 2009-063). A toothpick

was dipped into the bacterial suspension, and the fourth and fifth or fifth and sixth leaves of the interior

two rows of plants in the bed were punctured with the toothpick less than 15.2 cm from the onion neck

(modified from Gent and Schwartz, 2005; Carr et al., 2012; Fig. 5.1). Based on a laboratory simulation (not

shown), this inoculation protocol results in approx. 10 µL of suspension delivered through each punctured

leaf, for an inoculation of approx. 106 CFU applied per wound. Two leaves were inoculated per plant, and

the two exterior rows of plants in the four-row raised bed were left uninoculated, as were full-size 3.7 m

plots; this represented three levels of inoculum pressure: low (uninoculated), medium (adjacent-to-

inoculated), and high (inoculated).

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Foliar disease ratings

In 2012, disease ratings were recorded weekly post-inoculation on a 0 to 7 scale (Fig. 5.2). Since

two leaves per plant were inoculated, the leaf expressing higher severity was rated. The scale is as follows:

0 – no lesion, asymptomatic (uninoculated plants only); 1 – local lesion (2.5 cm x 2.5 cm or less); 2 –

expanded lesion, but less than ¼ of leaf; 3 – up to ½ of the inoculated leaf is chlorotic or bleached; 4 –

more than ½ of the inoculated leaf is chlorotic or bleached, but uninoculated leaves do not show

symptoms; 5 – entire inoculated leaf and a portion of an uninoculated leaf are symptomatic; 6 – multiple

fully symptomatic leaves; 7 – ≥50% bleached and/or collapsed leaves (Fig. 5.2). A total of four foliar disease

ratings were recorded at Rock Springs in 2012 on June 26 (one week postinoculation), July 2, July 11, and

July 17. A single foliar disease severity rating was recorded at Landisville using the same scale on July 9.

Notes on the topography of the field in Landisville were also recorded (Fig. 5.3).

Harvest evaluation

In 2011, plots were harvested individually, the number and total weight of bulbs with bacterial

disease symptoms were recorded, and marketable bulbs were graded by size. Briefly, the size categories

are considered the following: small, < 6.4 cm in diameter; medium, 6.4 – 7.6 cm; jumbo, 7.6 – 10.2 cm;

colossal, > 10.2 cm. One-gram samples of tissue were excised from 20% of the symptomatic bulbs for

bacterial pathogen isolation as well as lyophilized and extracted for multiplex PCR detection of all bacterial

species present; both samples were placed in 1.8 mL tubes. In 2012, plots were harvested individually and

separated by inoculation pressure: low (uninoculated), medium (outer rows directly adjacent-to-

inoculated), and high (inoculated). Symptomatic bulbs were culled for bacterial pathogen identification

using the two-sample microbiological and molecular protocols described above. Marketable bulbs were

graded by size, counted, and weighed.

Data analysis

Data were analyzed using one-way ANOVA and Levene’s test in Minitab 16.2 (Minitab, State

College, PA, USA), in addition to post-hoc mean comparisons using Fisher’s LSD (α = 0.05).

Results

Marketable yield and plant growth – 2011

At Landisville in 2011, distributions of bulb sizes were subject to a blocking effect, such that plots

in blocks 1 and 4 had a significantly greater proportion of large-size (combined jumbo and colossal; >7.6

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cm diameter) bulbs than block 3 (Fig. 5.4; blue bars). At Rock Springs, a blocking effect was again present;

block 1 had significantly fewer large-size bulbs than the other three blocks (data not shown). When block

1 was removed from the Rock Springs analysis, no differences were indicated between any of the

treatment groups, so groups were compared based on their combinations of products. Earlier that season,

growth estimates indicated the harpin, harpin and GI, GB03, and GB03/ASM treatments averaged longer

leaves than untreated controls (Table 5.1).

Disease management - 2011

In 2011, harvest disease incidence in onion bulbs from Landisville averaged 12.9% loss across all

plots. However, these data were subject to a blocking effect such that the lowest-lying area of the field

(block 3; Fig. 5.3) was significantly different from blocks 2 and 1 (Fig. 5.4). In addition, the slightly lower

area of the field (block 4) was significantly different from the highest area, block 1 (Fig. 5.4, red bars; Fig.

5.3). This prevented effective use of ANOVA to compare treatment means since disease incidence was not

uniform across blocks.

At Rock Springs in 2011, disease incidence was overall much lower, at an experiment-wise average

of 2.4% loss across all plots. These data very nearly violated the assumption of equal variances by Levene’s

test (P = 0.06) between treatments; it appeared that very inconsistent disease incidence in the untreated

inoculated control contributed to this, with one block averaging 18% disease incidence and the remaining

three blocks with 0% disease incidence, as indicated by variance within the treatment (Table 5.1). As a

result of the unequal variances, data were not analyzed further.

Marketable yield - 2012

In 2012, a different inoculation technique was used in which plants were subjected to three levels

of inoculum pressure, low (uninoculated), medium (adjacent-to-inoculated), and high (toothpick-

inoculated). In Fig. 5.5, the proportion of marketable bulbs that were large (> 7.6 cm diameter) in the low

and medium inoculum pressure plots was greater than the proportion of large bulbs in the high inoculum

pressure plots, which was apparent at both research farms (P < 0.001; Fig. 5.5).

Bacterial disease management – 2012

In both Landisville and Rock Springs in 2012, only a few statistically significant differences existed

in disease incidence between product treatments within each inoculation group. At Landisville in 2012, in

the medium inoculum pressure plots, the hydrogen peroxide preventative rate treatment had higher

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bacterial rot incidence than the uninoculated plots, however, no other statistically significant differences

occurred (Fig. 5.6). However, numerically, treatments with the lowest disease incidence included the

curative rate of hydrogen peroxide in low inoculum plants and GB03 in high inoculum pressure plants (Fig.

5.6). For plants under medium inoculum pressure (adjacent-to-inoculated), the lowest average disease

incidences were in the untreated control and GB03-treated plots (Fig. 5.6).

At Rock Springs in 2012, 20 inoculated plants in each inoculated plot were rated for foliar disease

for four weeks after inoculation using the scale described in Fig. 5.2. Three weeks post-inoculation, plots

treated with GB03 had an average severity rating of 4.55, which was significantly less than the grower

standard (copper + mancozeb) severity rating of 4.97 (P = 0.001), with other treatments ranging in severity

from 5.0 to 5.3 (Fig. 5.7). However, when plots were rated for severity immediately prior to harvest the

following week, this difference was no longer observed (Fig. 5.7). At Landisville, a single foliar rating was

recorded 17 days post-inoculation, and the harpin treatment averaged a severity rating of 4.1, which was

significantly higher than the preventative hydrogen peroxide, uninoculated, and ASM treatments with

averages of 3.3, 3.3, and 3.2 disease severity, respectively (P < 0.05; data not shown). In addition, these

foliar disease ratings were correlated with the bacterial disease incidence recorded at harvest in

Landisville (data not shown, P < 0.001, R2 = 0.66).

In terms of disease incidence at harvest, statistically significant differences between treatments

administered at Rock Springs only occurred at the low level of inoculum (Fig. 5.8). The grower standard

copper - EBDC mixture, in addition to the alternative H2O2 (preventative rate), ASM, and Harpin alternated

with copper – EBDC all were lower in disease incidence than the untreated plots (Fig. 5.8; P < 0.05). While

no statistically significant results were indicated at either the medium or high inoculum levels, numerically

the grower standard Cu-EBDC, hydrogen peroxide (curative rate), and GB03 were the treatments with the

lowest disease incidence (Fig. 5.8).

In summary, bacterial disease incidence was low (Rock Springs) or variable (Landisville) in the 2011

research farm trials. With the change of the inoculation protocol, bacterial disease incidence was higher

in 2012, yet few significant differences were present among the treatments included in these trials. Data

from the two locations could not be combined as a result of the variability between sites (Fig. 4.9),

reiterating the general need for product evaluation at multiple sites.

Discussion

Onions have been grown commercially as a trademarked crop in Pennsylvania for approximately

15 years, so the elucidation of a relatively consistent inoculation protocol was a significant result from this

96

work. The 2011 inoculation protocol, in which plants were sprayed to run-off with 108 CFU / mL Pantoea

spp. in 0.1% Silwet, had been shown to induce bacterial disease in growth chamber studies (not shown),

but did not induce consistent disease under field conditions (Table 5.1; Fig. 5.4), even though bacterial

populations were maintained on the plants overnight. The 2012 inoculation protocol, in which plants were

inoculated by puncturing two full-size, inner leaves with a toothpick dipped in a bacterial suspension

containing 108 CFU / mL, was more effective overall in inducing consistent center rot symptoms (Figs. 5.6,

5.8, 5.9). In fact, the 2012 protocol allowed observation of inoculum pressure at three levels, low

(uninoculated), medium (adjacent-to-inoculated) and high (inoculated); which was statistically significant

when inoculum levels at both field locations were grouped (Fig. 5.9; data not shown). When Rock Springs

and Landisville were combined, the incidence of center rot averaged 12.9%, 17.9%, and 27.5% for low,

medium, and high inoculum pressures, respectively.

Few recommendations can be deduced from the 2011 cropping season alone, however, one trend

that became apparent was the association of high disease incidence and low proportions of large (> 7.6

cm diameter) bulbs. This may suggest that even if bulbs are not symptomatic at harvest, high inoculum

pressure may still result in smaller asymptomatic onions (Fig. 5.4), perhaps as a result of latent foliar

infection and reduced movement of photosynthate to onion bulbs. Work with 14C-urea injections into

onion leaves has indicated that each leaf blade primarily nourishes its corresponding bulb scale; when the

leaf blade is removed, portions of photosynthate from both older and younger blades are then shared

with the ‘orphaned’ scale (Mann, 1983). In addition, through leaf removal experiments simulating storm

damage, it was suggested that reduced yield of onions with removed leaf blades may also be attributed

to a later onset of bulbing, due to the reduction in total numbers of light receptors (Bartolo et al., 1995).

Results from both locations in 2012 lend strength to this hypothesis, which indicated more large-size bulbs

in low and medium inoculum plots compared to the high inoculum plots when considering only the

marketable bulbs (Fig. 5.6; P < 0.001). However, other environmental variables, such as field topography,

may also play roles in disease pressure and marketable yields, with Landisville in 2011 as an example; in

this dataset, the lowest areas of the field recorded the highest disease incidence, as indicated in Fig. 5.4.

Some trends may be suggested by combining disease and growth estimates from 2011 and 2012,

which may be pursued in future work. GB03-treated plots were consistently among those with the lowest

disease incidence at harvest (Fig. 5.6 and 5.8), even though these results were not statistically significant.

GB03 - treated plots also had slower foliar disease development (Fig. 5.7) and longer leaves in 2012 (Table

5.1). Similar results have been shown in other bacteria-vegetable pathosystems, such as Pseudomonas

syringae pv. lachrymans on watermelon, muskmelon, and cucumber (Raupach and Kloepper, 1998;

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Kokalis-Burelle et al., 2003). Bacillus subtilis GB03 is recommended as an at-planting soil drench, and may

be an economically viable disease management treatment as a result of the efficacy of its single

application. In this study, treatment occurred shortly after transplanting, which would reduce overall

management costs compared to weekly foliar applications of copper – EBDC fungicide by tractor or

backpack. Disease incidence in GB03-treated plots was consistently no different from the copper - EBDC

standard (Figs. 5.6 and 5.8), and the product has short re-entry (4 hr) and 0 day pre-harvest intervals.

Conversely, the collective data presented here suggest harpin may not be effective for bacterial

disease management in onion. In 2011, two treatments that included harpin had significantly longer

leaves than control treatments (Table 5.1), which supports a potential growth promotion effect. However,

harpin-treated plots (without copper – EBDC) had the highest disease incidence at both locations in 2012

(Figs. 5.6 and 5.8). Other research has indicated poor bacterial disease management using a harpin

protein-based product (Obradovic et al., 2005), so products with this active ingredient, applied on the

same schedule, may not be the most effective management tools.

The plots receiving plant defense-inducing and growth-promoting products had similar

marketable yields and disease incidences compared to the grower standard in two replicated research

trials in 2012, however, most treatments were also similar to the untreated controls in these studies.

Therefore, it is recommended that selected products be tested for a third year using the 2012 inoculation

protocol and the repetitions of each experimental block are increased which may increase the power of

these experiments and ideally allow more customized recommendations based on perceived inoculum

pressure in grower fields. In summary, plant defense-inducing products, particularly GB03, have some

potential to serve as alternatives to the grower standard copper-EBDC treatments for the management

of bacterial rots of onion.

Acknowledgements

John Stepanchak, Jim Bollinger, Alyssa Collins, and Michele Mansfield offered essential technical

assistance.

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Tables and Figures

Table 5.1. Treatments, treatment schedule, and 2011 growth and disease incidence results from Rock Springs, 2011. Similar treatments and application schedules were conducted in the 2011 trial in Landisville as well the 2012 trials in Rock Springs and Landisville. Longest leaf means were separated using Fisher’s LSD (P ≤ 0.05); different letters following the means indicate statistically significant differences.

Treatment and rate Applications (days post-transplant)

2011 longest leaf (cm)

2011 Disease incidence (% ± std. deviation)

Untreated 53.1c 2.8 ± 3.7

Untreated, inoculated 53.1c 4.5 ± 9.2

Copper, 1.68 kg / ha Mancozeb, 1.68 kg / ha

55, 62, 69, 76, 83, 90 55, 62, 69, 76, 83, 90

54.9bc

0.6 ± 0.7

Harpin, 146 mL / ha Copper, 1.68 kg / ha Mancozeb, 1.68 kg / ha

55, 76 62, 69, 83, 90 62, 69, 83, 90

57.6abc

4.0 ± 2.8

ASM, 5.5 mL / ha 55, 62, 69, 76, 83, 90 55.9abc 1.4 ± 2.0

GI, 159 g / L 0 (at planting) 58.2ab 3.3 ± 3.4

Harpin, 146 mL / ha 55, 76 60.1ab 1.4 ± 2.0

GB03, 8.19 mL / L 0 (at planting) 60.7a 3.0 ± 3.5

Harpin, 146 mL / ha GI, 159 g / L

55, 76 0 (at planting)

59.2ab

4.1 ± 4.2

Harpin, 146 mL / ha GB03, 8.19 mL / L

55, 76 0 (at planting)

55.1bc

0.6 ± 0.7

ASM, 5.5 mL / ha GI, 159 g / L

55, 62, 69, 76, 83, 90 0 (at planting)

56.1bc

1.9 ± 1.9

ASM, 5.5 mL / ha GB03, 8.19 mL / L

55, 62, 69, 76, 83, 90 0 (at planting)

59.1ab

2.0 ± 1.7

ASM, 5.5 mL / ha Copper, 1.68 kg / ha Mancozeb, 1.68 kg / ha

55, 69, 83 62, 76, 90 62, 76, 90

53.7c

3.5 ± 5.2

Harpin, 146 mL / ha ASM, 5.5 mL / ha

55, 76 62, 69, 83, 90

52.9c

0.7 ± 0.8

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Rep 1

Rep 2

Rep 3

Rep 4

Fig. 5.1. 2012 inoculation diagram with locations of high (red, center front), medium (orange, flanking red), and low (yellow, center rear) inoculum. pressure sections of each plot.

Fig. 5.3. Photograph of Landisville field showing topography of blocks.

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Fig. 5.2. Foliar disease symptom rating scale. Foliar ratings are as follows: 0 – no lesion, asymptomatic (uninoculated

plants only); 1 – local lesion (2.5 cm x 2.5 cm or less); 2 – expanded lesion, but less than ¼ of leaf; 3 – up to ½ of the

inoculated leaf is chlorotic or bleached; 4 – more than ½ of the inoculated leaf is chlorotic or bleached, but

uninoculated leaves do not show symptoms; 5 – entire inoculated leaf and a portion of an uninoculated leaf are

symptomatic; 6 – multiple fully symptomatic leaves; 7 – ≥50% bleached and/or collapsed leaves.

5 6 7

1 2 3 4

101

Fig. 5.4. Average center rot incidence and percentage of marketable large-size (>7.6 cm diameter) onions by treatment block, Landisville, 2011. Block was analyzed as a random factor in order to control for natural variation within the onion field; the arrow roughly indicates the topography of the field (low-lying, on left, to high-ground, on right). Data were analyzed using PROC GLM in SAS 9.2, with post-hoc comparisons completed using Fisher’s LSD (α = 0.05); statistically significant differences are indicated by different letters above each set of bars (disease incidence [red bars] = a-c; large bulbs [blue bars] = x-z). Bars represent the experiment-wide standard error.

Fig. 5.5. Proportion of total marketable bulbs that were categorized as large (> 7.6 cm diameter) bulbs across all treatments grouped by pathogen pressure based on inoculation status (low, medium, and high) from Rock Springs and Landisville, 2012. Analysis was completed using PROC GLM in Minitab 16 with post-hoc comparisons using Fishers LSD (α = 0.05). Letters above each bar indicate statistical significance.

a

ab

z yz

xy x

c

bc

Lowest Highest

a a

b b

a a

Inoculum pressure

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Fig. 5.6. Center rot incidence by treatment under varying levels of inoculum pressure, Landisville, 2012. Center rot incidence at harvest was recorded for different areas of plots for each treatment. Inoculum pressure within plots includes low (uninoculated), medium (adjacent to inoculated), and high (inoculated) treatments. Error bars represent experiment-wide standard error. Different letters above each bar of the same inoculum pressure indicate statistically significant differences by Fisher’s LSD (α = 0.05).

Fig. 5.7. Weekly foliar disease severity ratings post-inoculation, from Rock Springs in 2012. For each treatment, 20 inoculated plants per plot were rated for disease severity following the scale in Fig. 5.2. * indicates a statistically significant difference between GB03 and the grower standard Cu-EBDC treatment (Fisher’s LSD; α = 0.05).

*

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Fig. 5.8. Center rot incidence by treatment under varying levels of inoculum pressure, Rock Springs, 2012. Bacterial disease incidence at harvest was recorded for different areas of plots for each treatment. Inoculum pressure within plots includes low (uninoculated), medium (adjacent to inoculated), and high (inoculated) treatments. Error bars represent experiment-wide standard error. Different letters above each bar of the same inoculum pressure indicate statistically significant differences by Fisher’s LSD (α = 0.05).

Fig. 5.9. Center rot incidence on research farms in 2012. Bars indicate the mean of each inoculation level on each farm, regardless of in-season treatment, and error bars indicate standard error of each mean. Statistically significant differences are indicated by different letters above the bars (Fisher’s LSD; α = 0.05).

a

b b

c

bc

d

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References Ahmad, M., Majerczak, D. R., Pike, S., Hoyos, M. E., Novacky, A., Coplin, D. L. 2001. Biological activity of Harpin produced by Pantoea stewartii subsp. stewartii. Microbe-Plant Molecular Interactions 14: 1223-1234. Bartolo, M. E., Schwartz, H. F., Schweissing, F. C. 1994. Yield and growth response of onion to simulated storm damage. HortScience 29:1465-1467. Bonaterra, A., Marib, M., Casalinib, L., Montesinosa, E. 2003. Biological control of Monilinia laxa and Rhizopus stolonifer in postharvest of stone fruit by Pantoea agglomerans EPS125 and putative mechanisms of antagonism. International Journal of Food Microbiology 84: 93-104. Borowicz, V. 2001. Do arbuscular mycorrhizal fungi alter plant-pathogen relations? Ecology 82: 3057-3068. Brazelton, J. N., Pfeufer, E. E., Sweat, T. A., McSpadden Gardener, B. B., Coenen, C. 2008. 2,4-diacetylphloroglucinol alters plant root development. Microbe-Plant Molecular Interactions 21: 1349-1358. Carr, E. A., Zaid, A. M., Bonasera, J. M., Lorbeer, J. W., Beer, S. V. 2013. Infection of onion leaves by Pantoea ananatis leads to bulb infection. Plant Disease 97:1524-1528. Conover, R. A., Gerhold, N. R. 1981. Mixtures of copper and maneb or mancozeb for control of bacterial spot of tomato and their compatibility for control of fungus diseases. Proceedings of the Florida State Horticultural Society 94: 154-156. Dodd, I. C., Zinovkina, N. Y., Safronova, V. I., Belimov, A. A. 2010. Rhizobacterial mediation of plant hormone status. Annals of Applied Biology 157: 361-379. Dong, H., Delaney, T. P., Bauer, D. W., Beer, S. V. 1999. Harpin induces disease resistance in Arabidopsis through the systemic acquired resistance pathway mediated by salicylic acid and the NIM1 gene. The Plant Journal 20: 207 – 215. Environmental Protection Agency (EPA). Harpin Protein (006477) Fact Sheet. Updated December 8, 2010. Accessed online, January 31, 2011: http://www.epa.gov/pesticides/biopesticides/ingredients/factsheets/factsheet_006477.htm . EXTOXNET Pesticide Information Notebook. EBDCs (General Information) Mancozeb Research Report. Accessed online 18 March 2014: http://pmep.cce.cornell.edu/profiles/fung-nemat/aceticacid-etridiazole/edbc/index.html . Garcia-Garrido, J. M., Ocampo, J. A. 1988. Interaction between Glomus mosseae and Erwinia carotovora and its effects on the growth of tomato plants. New Phytologist 110: 551-555. Gent, D. H., Schwartz, H. F. 2005. Management of Xanthomonas leaf blight of onion with a plant activator, biological control agents, and copper bactericides. Plant Disease 89: 631 - 639.

105

Goszczynska, T., Venter, S. N., Coutinho, T. A. 2006. PA20, a semi-selective medium for isolation and enumeration of Pantoea ananatis. Journal of Microbiological Methods 64: 225 – 231. Herrera Medina, M. J., Gagnon, H., Piche, Y., Ocampo, J. A., Garcia Garrido, J. M., Vierheilig, H. 2003. Root colonization by arbuscular mycorrhizal fungi is affected by the salicylic acid content of the plant. Plant Science 164: 993-998. Kokalis-Burelle, N., Vavrina, C.S., Reddy, M.S., Kloepper, J.W. 2003. Amendment of muskmelon and watermelon transplant media with plant growth-promoting rhizobacteria: effects on seedling quality, disease, and nematode resistance. HortTechnology 13:476-482. Kuiper, I., Lagendijk, E. L., Bloemberg, G. V., Lugtenberg, B. J. J. 2004. Rhizoremediation: A Beneficial Plant-Microbe Interaction. Microbe-Plant Molecular Interactions 17:6-15. Lang, J. M., Gent, D. H., and Schwartz, H. F. 2007. Management of Xanthomonas leaf blight of onion with bacteriophages and a plant activator. Plant Disease 91:871-878. Lin, Y. H., Xu, J. L., Hu, J., Wang, L. H., Ong, S. L., Leadbetter, J. R., Zhang, L. H. 2003. Acyl-homoserine lactone acylase from Ralstonia strain XJ12B represents a novel and potent class of quorum-quenching enzymes. Molecular Microbiology 47: 849-860. Liu, J., Maldonado-Mendoza, I., Lopez-Meyer, M., Cheung, F., Town, C. D., Harrison, M. J. 2007. Arbuscular mycorrhizal symbiosis is accompanied by local and systemic alterations in gene expression and an increase in disease resistance in the shoots. The Plant Journal 50: 529-544. Louws, F. J., Wilson, M., Campbell, H. L., Cuppels, D. A., Jones, J. B., Shoemaker, P. B., Sahin, F., Miller, S. A. 2001. Field control of bacterial spot and bacterial speck of tomato using a plant activator. Plant Disease 85:481-488. Lugtenberg, B., Kamilova, F. 2009. Plant growth-promoting rhizobacteria. Annual Reviews of Microbiology 63: 541-556. Mann, J. D. 1983. Translocation of photosynthate in bulbing onions. Australian Journal of Plant Physiology 10: 515-521. Nair, C. B., Anith, K. N., Sreekumar, J. 2007. Mitigation of growth retardation effect of plant defense activator, acibenzolar-S-methyl, in amaranthus plants by plant growth-promoting rhizobacteria. World Journal of Microbiological Technology 23: 1183-1187. Nasser, W., Reverchon, S., Vedel, R., Boccara, M. 2005. PecS and PecT coregulate the synthesis of HrpN and pectate lyases, two virulence determinants in Erwinia chrysanthemi 3937. Molecular Plant-Microbe Interactions 18:1205-1214. Obradovic, A., Jones, J. B., Momol, M. T., Olson, S. M., Jackson, L. E., Balogh, B., Guven, K., Iriarte, F. B. 2005. Integration of biological control agents and systemic acquired resistance inducers against bacterial spot on tomato. Plant Disease 89:712-716.

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Pozo, M. J., Azcon-Aguilar, C. 2007. Unraveling mycorrhiza-induced resistance. Current Opinion in Plant Biology 10: 393-398. Romero, A. M., Kousik, C. S., Ritchie, D. F. 2001. Resistance to bacterial spot in bell pepper induced by acibenzolar-S-methyl. Plant Disease 85:189-194. Siddiqui, Z. 2006. PGPR: Prospective biocontrol agents of plant pathogens. PGPR: Biocontrol and Biofertilization. Springer Netherlands: Pp. 111-142. Simard, S. W., Durall, D. M. 2004. Mycorrhizal networks: a review of their extent, function, and importance. Canadian Journal of Botany 82: 1140-1165. Raupach, G. S., Kloepper, J. W. 1998. Mixtures of plant growth-promoting rhizobacteria enhance biological control of multiple cucumber pathogens. Phytopathology 88: 1158-1164. Thaler, J. S., Fidantsef, A. L., Bostock, R. M. 2002. Antagonism between jasmonate- and salicylate-mediated induced plant resistance: Effects of concentration and timing of elicitation on defense-related proteins, herbivore, and pathogen performance in tomato. Journal of Chemical Ecology 28:1131 – 1159. van Wees, S. C. M., de Swart, E. A. M., van Pelt, J. A., van Loon, L. C., Pieterse, C. M. J. 2000. Enhancement of induced disease resistance by simultaneous activation of salicylate- and jasmonate-dependent defense pathways in Arabidopsis thaliana. Proceedings of the National Academy of Science 97: 8711-8716. Walters, D. R., Fountaine, J. M. 2009. Practical application of induced resistance to plant diseases: an appraisal of effectiveness under field conditions. Journal of Agricultural Science 147: 523 – 535. Walters, D., Walsh, D., Newton, A., Lyon, G. 2005. Induced resistance for plant disease control: Maximizing the efficacy of resistance elicitors. Phytopathology 95:1368-1373. Wei, Z. M., Laby, R. J., Zumoff, C. H., Bauer, D. W., He, S. Y., Collmer, A., Beer, S. V. 1992. Harpin, elicitor of the hypersensitive response produced by the plant pathogen Erwinia amylovora. Science 257: 85-88.

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Chapter 6: Effects of nitrogen fertilizer on growth characteristics, center rot incidence and severity, and other nutrient status in ‘Candy’ onion

Abstract

Center rot of onion, caused by Pantoea ananatis and P. agglomerans, is an emerging disease in

onion production regions across the United States, but economic losses can be especially severe in

Pennsylvania, where large amounts of inputs are integrated into these highly managed systems. As a

result of poor efficacy of chemical controls, commercial growers are interested in the impact of fertility

programs on bacterial disease management. From 2011 and 2012, intensive surveys suggested a weak

relationship between early-season levels of soil NH4 and the incidence of bacterial disease at harvest, and

in 2013, preliminary growth chamber studies suggested delayed center rot progression in plants fertilized

primarily with (NH4)2SO4 compared to Ca(NO3)2 or a 1:1 mixture of the two fertilizers. A small-plot

randomized block trial was conducted during the 2013 growing season in which ‘Candy’ onion plants were

fertilized at the same concentrations with either Ca(NO3)2 or (NH4)2SO4 on two different application

schedules, half-season (recommended N fertility applied weekly prior to bulbing) or full-season

(recommended N fertility applied weekly through the growing season). Consistent differences were

indicated between inoculated and uninoculated plants, with a possible interaction with the timing of N

application, and some pairwise differences in inoculated plants. Additionally, the inclusion of early-season

foliar Ca and mid-season foliar N were significant factors in ANCOVAs with center rot incidence as the

dependent variable when treatment was included as a factor; in particular, early-season foliar Ca was

negatively related to center rot incidence. Fertilization with (NH4)2SO4 resulted in onion bulbs with

significantly higher levels of sulfur, a major component in onion pungency and a restrictive factor in

marketing onion bulbs in PA. Taken together, these results suggest the timing of N fertility applications in

onion fields may have implications for bacterial disease management, foliar Ca may be influential in

slowing the spread of bacterial pathogens from infected foliage to onion bulbs, and using (NH4)2SO4 as the

sole N fertility source should be avoided by growers involved in the PA Simply Sweet® marketing program.

Introduction

Bacterial rots of onion (Allium cepa L.), including center rot, are the most significant diseases

affecting commercial production of the crop in Pennsylvania. Center rot is caused by Pantoea ananatis

Serrano and P. agglomerans Beijerinck, which are considered recently emerging bacterial pathogens

(Gitaitis and Gay, 1997; Edens et al., 2006). Growers attempt to manage center rot using copper-based

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fungicides tank-mixed with ethylene-bis-dithiocarbamate, hydrogen dioxide, and cultural methods like

alternative mulches, some of which have efficacy against bacterial diseases (Sanchez et al., 2014; Gugino

et al., 2011). The majority of onions in PA are grown in small, frequently rotated, highly managed fields

on raised beds with plastic mulch and drip irrigation. Some growers contract with commercial fertilizer

companies or consultants for their fertigation programs, spending as much as $1600 per hectare on crop

fertility (J. Stoltzfus, pers. comm.). Data on the efficacy of these fertility programs in ensuring high yields,

however, is lacking, and high N fertility has been suggested to increase bacterial disease in onion (Diaz-

Perez et al., 2003; Mohan, 2008; Gitaitis et al., 2008).

Nitrogen (N) is the most frequently studied elemental nutrient in horticultural production and

plant disease management (Huber and Thompson, 2007). A number of studies have been conducted

investigating relationships between N and plant disease; in particular, different plant-available forms of

N, specifically NO3 and NH4, have been implicated in complex relationships with disease management and

plant uptake of other macro- and micronutrients. In work with eggplant, strawberry, rice, and wheat,

fertilizing with NH4-N was demonstrated to increase uptake of manganese, which in turn is implicated in

pathogen inhibition and plant physical defenses (Elmer, 2000; Elmer and LaMondia, 1999; Huber and

McCay-Buis, 1995). However, relationships between macro- and micronutrients, the environment,

pathogens, and their host plants are generally pathosystem-specific, as management of other diseases

appears to favor NO3 nutrition (Huber and Thompson, 2007). Research completed in the onion-white rot

(Sclerotium rolfsii) pathosystem indicated decreases in disease following NH4 nutrition (Huber and

Graham, 1999), in addition to similar relationships shown in many soilborne pathosystems (Huber and

Thompson, 2007), however, the pathogens primarily investigated here are foliar (Pfeufer and Gugino,

unpublished; Carr et al., 2013).

Results from an observational study of 54 farms in PA suggested that foliar N at midseason had a

strong negative relationship to the total incidence of bacterial rots of onion at harvest and from storage

(Chapter 3), and a weak negative relationship was suggested between soil NH4 shortly after transplanting

and the incidence of bacterial rot at harvest (Pfeufer and Gugino, unpublished). In analyses on the same

dataset, early-season soil NH4 was positively associated with onion foliar N at midseason, as was the silt

content of soil (Chapter 3; Table 5.1). In contrast, horticultural studies on NO3 and NH4 nutrition have been

completed for onion in a modified hydroponic system, which indicated reduced plant canopy, early onset

of bulbing, reduced water usage, and low bulb weight when onions were fertilized solely with NH4

(Gamiely et al., 1991). While different N sources were included in another horticultural study concerning

critical N concentrations in Canada, the combination of N source data from this research indicates no

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significant differences between the type of N used and the overall yield in those plots (Westerveld et al.,

2003a; 2003b).

Investigations into the timing of N fertility in onion concluded reduced yield and delayed bulb

ripening when onions were underfertilized early in the season, but sufficient early-season N combined

with N reduction later in the season had no effect on horticultural yields (Brewster and Butler, 1989).

While no statistical significance was indicated, Westerveld et al. (2003a) reported highest onion yields on

mineral soils in Ontario when the N fertility concentration was either equally split between pre- and in-

season applications (2000) or when no additional N fertility was added besides the pre-plant application

(2001). These yield studies complement the result that higher incidence of storage losses due to several

bacterial onion pathogens were recorded when plants were fertilized late in the season (Wright, 1993).

Literature suggests N deficiency is only indicated when plants respond to increased levels of N fertilizer

(Lorenz and Tyler, 1976; cited by Rumpel et al., 2004), so the lack of response at the later tissue sampling

dates suggests N fertilizer did not need to be applied on these dates. More locally, one experienced PA

grower has anecdotally shared that he never fertilizes through drip irrigation after the first week of June,

and simply waters his onions until harvest in early- to mid-July (pers. comm., to Pfeufer). The effects of

the timing of N fertility on the incidence of center rot of onion, therefore, have not been explicitly

addressed and are relevant to PA growers.

In addition, N levels in plant foliage have been suggested to be influential in insect pest preference

for plants, and this relationship has previously been demonstrated with onion thrips (Thrips tabaci

Lindeman; Malik et al., 2009), which are considered the major insect pest of onions in PA. Onion thrips

have been shown to vector Pantoea spp. to previously uninfected onion plants (Dutta et al., 2014), so the

role of N in thrips pressure was also briefly investigated. In one study on the impact of the role of N

fertility in onion thrips damage completed in Ontario, the authors observed no differences in thrips counts

between differentially-fertilized onions (Westerveld et al., 2003b). However, in another study in Utah,

authors demonstrated that 1/3 the recommended season concentration of fertilizer N reduced onion

thrips by 23 – 31% (Buckland et al., 2013).

Intensive survey support

Results from a two-year observational study in which different management factors were

investigated for associations to bacterial rot disease incidence suggested strong relationships between

foliar N and C at midseason and high disease incidence (see Chapter 3). These data were further mined

with midseason foliar N as a dependent variable, using variables previously investigated or unchanging

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over the observation time as independent variables. When farm was treated as a sample, these results

indicated the level of early-season soil NH4 was positively associated with foliar N content at midseason,

along with the silt content of each field’s soil (Table 6.1).

Table 6.1. Multiple linear regression between foliar carbon (C), early-season soil ammonium (NH4), and silt content of soil to the foliar nitrogen (N) content from leaves collected at midseason, from 54 Pennsylvania onion fields over two yearsa.

Predictora Coefficient SE of Coefficient T value P value

Constant 7.607 1.053 7.22 <0.001 Foliar C, midseason -0.140 0.026 -5.44 <0.001 Early-season soil NH4 0.010 0.004 2.38 0.021 Silt content of soil 0.014 0.005 2.60 0.012

a R2 = 0.232; adj. R2 = 0.200; P = 0.002.

The present study was planned based on the results from preliminary observational studies and

local interest by growers coupled with concerns about over-fertilization and the expense of proprietary

fertility programs. As an emerging disease of onion, there is a general absence of data in the present

published literature on the effects of N fertility on center rot, caused by P. ananatis and P. agglomerans.

A randomized, replicated field trial was conducted at the Russell E. Larson Agricultural Research and

Education Center, Pennsylvania Furnace, PA in 2013 in order to determine the effects of N source and N

fertility timing on onion growth, onion thrips pressure, micronutrient content, and center rot incidence at

harvest.

Materials and Methods

Preliminary growth chamber assays

In two growth chamber assays, ‘Candy’ seeds were sown in a flat eight weeks prior to

transplanting, which was watered 2-3 times per week and placed under growth lamps with a 16-hr light

period. Plants had 2-4 leaves when transplanted into 7.62 cm diameter round clay pots with pasteurized

Metro-Mix 360 (Sun Gro Horticulture, Agawam, MA), then were allowed to grow for two more weeks

prior to fertilizer applications. Applications were composed of Ca(NO3)2, NH4(SO4)2, or a 1:1 mixture of

the two nitrogen sources. Final concentrations of N applied were the equivalent of 84 kg N / ha per

application, which occurred weekly. Two experiments were performed; one in which plants were

fertilized at and after inoculation, and another where plants were fertilized for two weeks prior to

inoculation, then weekly thereafter. Plants were bottom-watered to prevent nutrient leaching.

Inoculations were performed in the growth chamber where a toothpick was used to puncture

the longest leaf of the growing plant approx. midway up the leaf. This toothpick was dipped in 108 colony-

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forming units (CFU) / mL mixture of P. ananatis (strain PA1a) and P. agglomerans (strain 10-009).

Uninoculated controls were punctured with a sterile, dry toothpick. Lesions were measured on two axes

each week, with the axes multiplied to calculate symptomatic area. The total number and length of the

longest leaf of each plant was also recorded. Replicate plants (twelve or fifteen, depending on

experiment) of each treatment were blocked within the growth chamber and treatments were

randomized within the block.

Field trial setup and maintenance

Based on a soil test, field nitrogen levels were brought to 112.1 kg N / ha using urea prior to field

preparation, while levels of other nutrients met or exceeded recommendations for onion (soil test on

file, from Penn State Agricultural Analytical Services Lab). Small plots were established on a Hagerstown

silt loam in four rows with standard black plastic mulch and two lines of drip irrigation. Each plot was

1.83 m long and approximately 1 m wide across the top of the raised bed. ‘Candy’ onion transplants

(Dixondale Farms, Carrizo Springs, TX) were planted at 15.24 cm spacing on April 25, 2013. In-season

fertilizer treatments were arranged in a randomized block configuration with unfertilized, half-season

NO3, full-season NO3, half-season NH4, and full-season NH4 treatments; half-season treatments were

twice as concentrated as full-season treatments. Uninoculated and inoculated plots were maintained for

each of the previous treatments. Fertility was applied as a sidedress approx. weekly for four or eight

weeks, depending on the treatment, to a total, season-long field concentration of 179.4 kg N / ha, except

unfertilized plots which received only 112.1 kg N / ha broadcast prior to bed preparation, which is similar

to some recommended fertility rates for onion for the total season (transplant supplier recommendation;

Rumpel et al., 2008; Diaz-Perez et al., 2003). Nitrogen sources were Ca(NO3)2 or (NH4)2SO4, which were

special ordered from Peters Fertilizer (Allentown, PA). A calibrated backpack sprayer was used to

administer approx. 100 mL of concentrated liquid fertilizer directly to the side of each onion plant. If

necessary, plastic mulch was loosened around the necks of each onion plant in order to apply fertilizer

treatments. Weeds were managed by tilling between raised beds and hand weeding within the bed;

there was no insect management in these plots.

Plants in the appropriate treatments were inoculated by puncturing the fifth non-senescing leaf

approx. 15 cm from the leaf whorl with a sterile toothpick dipped in a mixture of three P. ananatis (12-

766, 12-980, and 12-1764) and three P. agglomerans strains (12-823, 12-835, and 12-2058), all

originating from symptomatic onions sampled from PA farms in 2012, and similar to Carr et al. (2013).

Inoculum was prepared by streaking two large (15 x 100 mm) King’s B (King et al., 1954) plates with a

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single strain, then flooding each plate with 2 mL phosphate buffer the following day, using a sterile plastic

scraper to dislodge the cells, and removing this liquid to six 50-mL tubes containing 6 mL sterile

phosphate buffer, one for each strain. One milliliter was removed from each of these tubes, combined

with 10 mL phosphate buffer, vortexed, and this mixture was aliquoted into sterile 1 mL Eppendorf tubes

for field inoculations. The final concentration of inoculum was 7.6 x 1013 CFU / mL, and estimates suggest

approx. 10 µL inoculum is delivered per puncture. Tubes were gently agitated in the field by inverting

several times prior to inoculations, which occurred on June 22, 2013. Plants were observed over several

days, and since symptoms did not progress quickly, the same leaf per plant was inoculated again on June

29, 2013 using 9.2 x 1013 CFU / mL mixture of P. ananatis strains PA1a and 10-082, and P. agglomerans

strains 09-009 and 10-063. Second inoculation strains were collected from symptomatic bulbs from PA

in 2008, 2009, and 2010 and are part of the Gugino lab bacterial isolate collection. Center rot symptoms

progressed quickly following the second inoculation.

Data collection

At three points in the season (May 13, May 31, and June 12; 18, 35, and 47 days after

transplanting [dap]), the longest leaf, bulb diameter, and number of thrips were recorded for ten plants

per replicate plot. Onion foliage, which was the total green tissue above the onion neck, from three

random plants in the plot was comingled in a paper bag on May 29 (33 dap) and June 22 (57 dap), then

dried for at least 72 hr in a 60⁰C forced-air drying oven. Bulbing estimates, as a ratio of the bulb diameter

at its widest point to the neck diameter from the narrowest point of the plant to (B:N ratio), were

recorded from the same three plants from which foliar tissue was sampled. In addition, at harvest, two

asymptomatic onion bulbs were split, comingled by plot, and dried for at least 72 hr in a 60⁰C drying

oven. Foliar and bulb tissue samples were submitted to Penn State Agricultural Analytical Services Lab,

University Park, PA for tissue grinding and complete analysis for N, P, K, and micronutrients via total acid

digest.

Plants were rated weekly for center rot symptoms after the second inoculation using the 0-7

point scale described in Chapter 4. Plots were harvested on July 16, 2013. Bulbs were initially rated for

bacterial disease by removing those with discolored scales in the neck or macerated area on their surface,

then marketable bulbs were graded by size into the categories small (< 6.35 cm diameter), medium (6.35

– 7.62 cm diameter), jumbo (7.62 – 10.2 cm diameter), and colossal (> 10.2 cm diameter).

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Data analysis

Data were analyzed using the one-way ANOVA and Correlation procedures in Minitab 16.2

(Minitab Inc., State College, PA) with disease severity, harvest incidence of center rot, sulfur content, leaf

length, thrips density, and neck diameter as dependent variables. Using the General Linear Model

procedure, treatment, fertilizer timing, and fertilizer type were input as class variables, while macro- and

micronutrient data were included as covariates in some analyses. Post-hoc comparisons were completed

using Fisher’s LSD (ANOVA) or Tukey’s HSD (ANCOVA), α = 0.05.

Results

In preliminary growth chamber assays with onion seedlings, plants fertilized with (NH4)2SO4 had

smaller (P < 0.05) lesions after bacterial inoculation than inoculated plants fertilized with Ca(NO3)2 (12

days post-inoculation [dpi] and 19 dpi; Fig. 6.1) or a 1:1 mix of Ca(NO3)2:(NH4)2SO4 (19 dpi). Likely due to

high variation, the statistically significant differences were not present at a final disease severity

measurement at 26 dpi (Fig. 6.1), and no significant differences in either leaf length or in number of leaves

were indicated between any of the treatments (data not shown). In a replicate experiment where plants

were fertilized with the same concentrations of N fertilizer prior to inoculation, the average lesion size of

(NH4)2SO4- fertilized plants was smaller at 7 dpi compared to both the Ca(NO3)2 and Ca(NO3)2 - (NH4)2SO4

– fertilized plants. Seven days later, however, lesion sizes among the treatments did not differ (data not

shown).

In a replicated field trial in 2013, uninoculated and inoculated plants were rated weekly for

bacterial symptom development on two dates following the second inoculation. Significant differences

were indicated by inoculation status, that is, uninoculated plants developed symptoms more slowly than

inoculated treatments (data not shown). No differences were suggested based on N source and

application timing. As a result, treatments were grouped according to inoculation status and fertility

timing; at 9 dpi, inoculated, full-season N fertilized plants had a higher average foliar disease severity

rating than inoculated, half-season N fertilized plants (Fig. 6.2).

Midseason growth and thrips pressure estimates were recorded two (B:N ratio) or three (all other

estimates) times during the 2013 onion growing season. No differences in B:N ratio were indicated

between treatments on either of the data collection dates (Table 6.2). The number of thrips per leaf 35

dap, was numerically largest in the unfertilized treatments (A and B), which was statistically significant

when compared to the half-season fertilized plants, but not the full-season fertilized plants, which each

averaged fewer thrips per leaf at that timepoint (Table 6.2). This difference was not apparent in the data

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from the other two data collection dates, which flank the date described. When neck diameter of ten

plants was recorded at the narrowest point on ten onion plants’ necks from each replicate plot 47 dap,

the full-season fertilized plants had significantly larger neck diameters compared to the unfertilized and

half-season fertilized plants (Table 6.2).

Center rot incidence at harvest, the percent of bulbs with center rot symptoms out of total bulbs

per plot, was numerically highest in the full-season Ca(NO3)2 fertilized plots, and was numerically lowest

in the uninoculated, unfertilized plots (Fig. 6.3). Disease incidence was generally higher in inoculated

plants than in uninoculated plants. Within only inoculated treatments, the full-season Ca(NO3)2 fertilized

plants had significantly higher center rot incidence than both the half-season Ca(NO3)2 fertilized plants

and the full-season (NH4)2SO4 fertilized plants, but there was no significant difference compared to the

half-season Ca(NO3)2 fertilized plants (Fig. 6.3). When treatments were combined by fertilizer application

timing and inoculation status (Fig. 6.4), the uninoculated, unfertilized plots as well as the uninoculated,

full-season fertilized plots had lower center rot incidence at harvest than the inoculated, full-season

fertilized plots, which was statistically significant (Fig. 6.4). Analysis indicated inoculation status

(uninoculated vs. inoculated) was a highly significant factor determining center rot incidence, and

suggested a nearly-significant interaction existed between inoculation status and timing of fertilizer

application (P = 0.15; data not shown).

A series of two foliar tissue tests 35 dap and 57 dap, in addition to a bulb nutrient test on

asymptomatic harvested onions, were conducted to determine potential roles of micro- and

macronutrient status on center rot incidence in onion at harvest. Asymptomatic, jumbo-size bulbs from

plots fertilized with (NH4)2SO4 had higher levels of sulfur, the primary component in onion pungency, as

compared to sulfur levels in bulbs from unfertilized and Ca(NO3)2 treated plots. This occurred regardless

of the timing of (NH4)2SO4 fertilization (Fig. 6.5).

Calcium levels in foliar tissue sampled 35 dap (after three weekly fertilizer treatments) showed a

weak negative relationship to the incidence of center rot at harvest, and when Ca was included as a

covariate in an ANCOVA, both treatment (P = 0.012) and 35 dap foliar Ca (P = 0.020) were significant

factors influencing center rot at harvest. Estimated means based on the inclusion of this late-May foliar

Ca as a covariate are shown in Fig. 6.6, where inoculated treatments trend toward higher disease

incidence. The model including treatment as a factor and 35 dap foliar Ca as a covariate with a negative

relationship with center rot incidence had an adjusted R2 = 0.403 pertaining to Fig. 6.6). In the 57 dap

tissue test, foliar N levels were weakly positively correlated to the incidence of center rot at harvest, and

when N was included as a covariate in ANCOVA, treatment (P = 0.02) and 57 dap foliar N (P = 0.09) were

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significant or nearly-significant factors influencing center rot at harvest (data not shown). Estimated

means based on the inclusion of N as a covariate are shown in Fig. 6.7, where again, inoculated treatments

trend toward higher disease incidence. The model including treatment as a factor and 57 dap foliar N as

a covariate with a positive relationship with center rot incidence gave a model with an adjusted R2 = 0.353

(pertaining to Fig. 6.7). Combining treatment as a factor and both the 35 dap foliar Ca and 57 dap foliar N

as covariates indicated a model with an adjusted R2 = 0.417 (data not shown). Interestingly, a multiple

linear regression model not including treatment as a factor indicated the same, strong (P = 0.032) positive

relationship between center rot incidence and 57 dap foliar N, but the negative relationship with 35 dap

foliar Ca was diminished (P = 0.37; data not shown).

When harvest center rot incidence was averaged by inoculation status and N fertility timing, and

displayed by the amount of N fertilizer applied prior to midseason, there appear to be linear relationships

between N fertilizer applied prior to bulbing and disease incidence, which differ according to inoculum

pressure (Fig. 6.8). Analysis of N status in each of the tissue tests indicated higher levels of N in foliage in

plants fertilized at the 179.4 kg N / ha rate than the 112.1 kg N / ha concentration, but this difference was

only apparent at 35 dap tissue sample, where plants had at that point received the equivalents of 50.4

and 25.2 kg N / ha additional N over unfertilized and full-season fertilized plots, respectively (data not

shown).

Discussion

Grower interest in fertility programs as a component of integrated bacterial disease management

in onion, in addition to anecdotal evidence and preliminary data from observational studies, prompted

more thorough investigation of the roles of N fertility in onion growth, micronutrient status, disease

severity and incidence and thrips pressure in ‘Candy’ onion produced in PA. In two growth chamber

studies, it was indicated that plants fertilized only with (NH4)2SO4 [AmmINC] had smaller lesions than

plants fertilized with Ca(NO3)2 [NitINC] (at two timepoints, Fig. 6.1) or plants fertilized with an (NH4)2SO4

– Ca(NO3)2 mixture [ConINC] (at one timepoint) following inoculation with P. ananatis and P. agglomerans

(Fig. 6.1). This result, however, was temporary when compared later in the season, where there were no

differences in disease severity between differentially fertilized plants. Since bulb symptoms typically take

two to three weeks to develop following foliar inoculation (Pfeufer and Gugino, unpublished; Carr et al.,

2013), and in PA, an onion forms a bulb over a period of three to four weeks, even a temporary delay in

disease progression may produce higher marketable yields with a carefully timed harvest.

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A small-plot, replicated field trial was set up to determine the effects of different N sources and

application timings on onion growth, micronutrient status, center rot incidence at harvest and thrips

pressure. No differences in disease progression were indicated by the type of N source used, however,

ten days after inoculation, plants fertilized on the half-season schedule (that is, no N applications after

mid-season) had lower foliar disease severity than plants that were fertilized on the full-season application

schedule. This difference was not present at the later severity rating, immediately prior to harvest (Fig.

6.2). Growth estimates and thrips counts were completed at several points prior to inoculation, and in

contrast to other published work (Gamiely et al., 1991), there were no significant differences indicated in

B:N ratio when treatments were grouped according to N source (Table 6.1). In that previous study, on

hydroponically-fed onions, plants fertilized with mostly NH4-N bulbed precociously compared to plants

fertilized with ratios higher in NO3-N, even though the authors concluded that precocious bulbing

ultimately had no impact on final bulb fresh weight (Gamiely et al., 1991).

At the May 31 rating, 35 dap, thrips densities were higher on unfertilized plants than on plants

fertilized on the half-season schedule (Table 6.1), which conflicts with other published results which

suggested that high N fertility promotes thrips pressure in onions (Buckland et al., 2013; Malik et al.,

2009), but is in agreement with another published report where onion thrips pressure was highest on

unfertilized plants (Westerveld et al., 2003a). However, no differences were observed 18 or 47 dap, so it

may be that high densities temporarily developed for a different reason, such as a lack of pressure on

thrips populations by natural predators. Neck diameter at 47-dap (June 12) was significantly larger in

plants fertilized on the full-season schedule compared to the unfertilized and half-season fertilized plants

(Table 6.1). This result was expected based on previously published work with onion (Wright, 1993) and

is significant because as the center rot pathogens infect onion leaves and subsequently bulbs (Carr et al.,

2013), logic follows that bulbs with smaller necks will dry down faster and halt this bacterial advance

(Wright, 1993), potentially resulting in reduced incidence of center rot in storage.

Inoculated plants as a group had significantly higher disease incidence than uninoculated plants,

however, the only statistically significant differences within inoculation type were between full-season

Ca(NO3)2 fertilized plants and each of half-season Ca(NO3)2 and full-season (NH4)2SO4 plants (Fig. 6.3).

Combining treatments by fertilizer application timing suggested a nearly-significant interaction between

inoculation status and timing of fertilizer application (P = 0.15), and when compared in a different format,

where total kg N / ha applied at roughly midseason is the only independent variable considered, well-fit

(R2 > 0.8) linear relationships with opposing slopes are indicated by this same dataset (Fig. 6.8). Taken

together, these suggest that the optimal timing of fertilizer application depends on the inoculum pressure

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within a field, and it may be advantageous for growers to err on the side of half-season N fertility

applications if they are concerned about bacterial diseases. (Figs. 6.4 and 6.8). These results have not been

previously reported for management of center rot of onion, although sources recommend restricting N

fertilization late in the season (Dixondale Farms website), or note high levels of bacterial decay when

onions are fertilized at above-optimal levels (Diaz-Perez et al., 2002).

Foliar nutrients were analyzed in Pearson’s correlations with the incidence of harvested onions

with center rot symptoms, and correlated nutrients were included initially as covariates in ANCOVA

analyses. From the 35 dap foliar tissue test following three weeks of fertility applications, Ca was

suggested to be negatively correlated with the incidence of center rot at harvest (P = 0.02; data not

shown). This is intriguing because Ca plays primary roles in cell membrane integrity, plant defense

signaling, and the maintenance of plant tissue structure through the middle lamella (Rahman and Punja,

2007). In research completed in another bacteria-vegetable pathosystem, a negative relationship was

demonstrated between tuber Ca levels and severity of soft rot due to Erwinia carotovora pv. atroseptica

(now Pectobacterium carotovorum pv. atrosepticum) in potato (McGuire and Kelman, 1984). Including Ca

as a covariate in an ANCOVA with treatment as a factor indicated significant differences between adjusted

means of several inoculated and uninoculated treatments (Fig. 6.6). While NH4+ in soil solution has been

suggested to depress uptake of Ca ions (Rahman and Punja, 2007), no differences between fertilizer

treatments and Ca levels in foliage was indicated in the present study (data not shown). Since Ca has been

shown to accumulate in foliage as compared to other potato tissues (McGuire and Kelman, 1984; Rahman

and Punja, 2007) and Ca nutrition has been implicated in firmer onion bulbs and decreased pungency

(Coolong and Randle, 2009), one suggestion for the center rot – onion pathosystem is that Ca’s role in

strengthening foliar tissue structure may also slow the movement of the Pantoea spp. from inoculation

point to onion bulbs; however, additional replicated trials would be necessary to definitively demonstrate

this relationship and define critical Ca levels that confer its effect.

From the 57 dap foliar tissue test, following six weeks of fertility applications and immediately

prior to the first inoculation, N was suggested to be positively correlated to the incidence of center rot at

harvest (data not shown). This observation is not consistent with the survey results reported in Chapter

4, however, it is consistent with reports that over-fertilization promotes bacterial disease in onion (Diaz-

Perez et al., 2003; Mohan, 2008; Gitaitis et al., 2008). Including 57 dap foliar N as a covariate resulted in

only one significant difference between tested treatments (Fig. 6.7), and including the same variable in an

ANCOVA already containing treatment as a factor and 35 dap foliar Ca as a covariate only marginally

improved the model (R2 value increased 1.2%; data not shown). The interaction term between covariates

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was not significant to the model (data not shown), which suggests that 35 dap foliar Ca and 57 dap foliar

N are either explaining the same variation in the model, or that each covariate’s explanatory power is

diminished by inclusion of the other variable in the model. When Ca and N were used as dependent

variables with treatments grouped by N source as the independent variable, the type of fertilizer was not

a significant factor in determining the content of these nutrients in onion foliar tissue (data not shown).

This suggests that while these foliar nutrients may influence disease development, the treatments applied

here were not the only factors dictating foliar nutrient content. Overall, relationships between

micronutrients, macronutrients, and the incidence of center rot of onion are complicated, and repeated

experiments are necessary to identify if these relationships are consistent before detailed interpretation

and conclusions are to be drawn.

Asymptomatic onion bulb tissue was dried and analyzed for total sulfur (S), soil levels of which

have been shown to influence S accumulation in sweet onions (Randle et al., 1999). In the present study,

plants fertilized with (NH4)2SO4 had significantly higher levels of S in their bulbs, regardless of fertilizer

application timing, than unfertilized plants or plants fertilized with Ca(NO3)2 (Fig. 6.5), which is consistent

with other publications (Randle et al., 1999). While total tissue S does not directly correlate with

enzymatically-developed pyruvic acid (the determining factor in onion pungency), and onion varieties vary

in their partitioning of S as a nutrient (Randle et al., 1999), the sensitivity of sweet onions to soil S levels

and the result of higher pungency when onions are fertilized solely with (NH4)2SO4 (Gamiely et al., 1991)

may suggest growers participating in the PA Simply Sweet® program should avoid (NH4)2SO4 as their

primary N source. Indeed, crops intended for marketing through the Simply Sweet® program have been

turned away if their pungency levels are too high (J. Stoltzfus, pers. comm.). This may result in an economic

loss to growers who paid membership fees to participate in the program prior to the season, and

additional effort is required to find an alternative market for the crop.

Several conclusions are suggested by the results of the study presented here; among them, a

trend emerges in which full-season fertilizer applications may result in larger onion necks in late-season

(Table 6.1), as well as higher center rot incidence (Figs. 6.3, 6.4, 6.8) as compared to half-season fertilizer

applications, particularly in plants under high inoculum pressure. Since uninoculated plants in unfertilized

plots, which received only 63% of the full season concentration, had the highest marketable yields (data

not shown), and generally, plants’ failure to respond to additional nutrients may suggest adequate N

availability (Lorenz and Tyler, 1976; cited by Rumpel et al., 2004), this suggests that N fertility

concentrations lower than current recommendations may be feasible for PA growers while maintaining

current yields. While the full-season Ca(NO3)2 treatment on inoculated plants had significantly higher

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disease incidence than both the half-season Ca(NO3)2 and the full-season (NH4)2SO4 treatments, the lack

of relationship between this treatment and the half-season (NH4)2SO4 treatment (Fig. 6.3) necessitates at

least another year of replicated trials, preferably in multiple locations with different soil types. In these

further trials, an alternative NH4 source would be advantageous to include, since fertilizing onions with

(NH4)2SO4 increases bulb S and likely increases onion pungency (Fig. 6.5). In addition, the roles of foliar

nutrient levels in center rot progression may be manipulated through plant nutrition applications as an

additional disease management approach, given that foliar Ca and N were significant variables in the

models presented here (Figs. 6.6 and 6.7).

Acknowledgements

The authors thank Tim Grove and Michele Mansfield for technical assistance in field maintenance and inoculations.

Tables and Figures

Fig. 6.1. Lesion development in differentially-fertilized onion seedlings after foliar inoculation with P. ananatis in a growth chamber assay. Inoculated plants are indicated by INC. Means at each date were compared between treatments using ANOVA with Fisher’s LSD; * indicates a statistically significant difference between the Nitrate and Ammonium-fertilized, inoculated plants, while ** indicates a statistically significant difference between inoculated control and nitrate fertilizer treatments compared to the ammonium-only fertilizer treatment. Error bars represent standard error of the mean.

*

**

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Fig. 6.2. Disease progression over time by fertilizer application timing in inoculated plants in the field. N treatments were combined within the timing variable since no differences were apparent between N types. Means within each type of timing were compared using a one-way ANOVA and Fisher’s LSD (α = 0.05). * indicates a statistically significant difference in disease severity between the full-season and half-season fertilized treatments.

Table 6.2. Midseason growth estimates and thrips pressure by fertilizer treatment prior to inoculation in 2013.

Treatment by fertilizer type and timinga Treatment by application timingb

None Half NO3 Full NO3 Half NH4 Full NH4 None Half Full B:N (35 dap)c 1.84 1.88 1.84 1.83 1.96 1.84 1.86 1.90 B:N (52 dap)c 1.52 1.52 1.49 1.49 1.45 1.52 1.50 1.47 Thrips/leaf (18 dap) 0.10 0.10 0.07 0.12 0.22 0.12 0.20 0.12 Thrips/leaf (35 dap) 0.22 0.13 0.14 0.14 0.17 0.22a 0.13b 0.15ab Thrips/leaf (47 dap) 1.16 1.08 1.26 1.11 0.96 1.16 1.10 1.11 Neck D (18 dap)d 5.57 5.46 5.73 5.61 5.58 5.57 5.53 5.65 Neck D (35 dap)d 8.81 8.68 8.81 8.89 8.86 8.81 8.79 8.83 Neck D (47 dap)d 13.4c 13.6bc 14.4ab 14.2abc 14.4a 13.4b 13.9b 14.4a

a Treatments were as follows: unfertilized (none); half-season fertilized with Ca(NO3)2; full-season fertilized with Ca(NO3)2; half-season fertilized with (NH4)2SO4; full-season fertilized with (NH4)2SO4.

b Groups in application timing are combined regardless of N source. Different letters following measurements within the row indicate statistical significance via Fisher’s LSD (α = 0.05).

c Ratio of the bulb diameter, at its widest point, to the neck diameter, at its narrowest point, for three plants per replicate plot. (N = 8 reps for unfertilized plots; N = 16 for fertilized plots).

d Neck diameter in mm.

*

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Fig. 6.3. Center rot at harvest by inoculation status, N fertilizer source and application timing. Bars indicate the average of four replicate plots, error bars represent standard error of the mean. Bars with different letters indicate statistical significance by Fisher’s LSD (α = 0.05).

Fig. 6.4. Center rot incidence at harvest based on inoculation status and fertilizer application timing. Bars indicate the average of the plots within each category (N = 4 [unfertilized plots] or N = 8 [half- or full-season fertilized plots, regardless of N source]). Error bars represent standard error of the mean and different letters above each bar indicate statistical significance by Fisher’s LSD (α = 0.05).

0

5

10

15

20

25

30

Cen

ter

rot

inci

den

ce a

t h

arve

st (

%)

Uninoculated Inoculated

UnfertilizedHalf-season NO3Full-season NO3Half-season NH4Full-season NH4

UnfertilizedHalf-season Ca(NO3)2

Full-season Ca(NO3)2

Half-season (NH4)2SO4

Full-season (NH4)2SO4

d

cd

bcd bcd

bcd bcd

bcd

abc ab a

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Fig. 6.5. Sulfur content of asymptomatic bulbs at harvest by N fertilizer type and timing. Bars indicate averages by treatment group; different letters above bars indicate statistical significance by Fisher’s LSD (α = 0.05).

Fig. 6.6. Analysis of covariance estimates with treatment (listed under each bar with the timing and form of inorganic N) as a main effect and calcium in foliage after three weekly fertilizer treatments as a covariate. Inoculated treatments are solid color bars, uninoculated treatments are hatched. Dark blue indicates full-season application (N fertility applied weekly throughout the season), medium blue indicates half-season application (N fertility applied weekly prior to midseason), and light blue indicates no additional N fertility. Means shown are estimates with early-season foliar Ca included as a covariate in the model. Bars with different letters are significantly different by Tukey’s test (α = 0.05).

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Fig. 6.7. Analysis of covariance estimates with treatment (listed under each bar with the timing and form of inorganic N) as a main effect and nitrogen in foliage after six weekly fertilizer applications as a covariate. Inoculated treatments are solid color bars, uninoculated bars are hatched. Dark blue bars indicate full-season fertilizer application, medium blue bars indicate half-season fertilizer application, and light blue bars indicate no fertilizer application. Means shown are estimates with N included in the model. Bars with different letters are significantly different by Tukey’s test (α = 0.05).

Fig. 6.8. Center rot incidence at harvest compared to amount of N fertilizer of either type applied by midseason. Statistically significant differences only exist between means in different inoculation categories. Error bars indicate standard error of the mean.

Full None Half Full Half Half Full Half Full None NO

3

NH

4 NH

4 NO

3 NH

4 NO

3 NO

3

NH4

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References Buckland, K., Reeve, J. R., Alston, D., Nischwitz, C., Drost, D. 2013. Effects of nitrogen fertility and crop rotation on onion growth and yield, thrips densities, Iris yellow spot virus, and soil properties. Agriculture, Ecosystems and Environment 177: 63 – 74. Carr, E. A., Zaid, A. M., Bonasera, J. M., Lorbeer, J. W., Beer, S. V. 2013. Infection of onion leaves by Pantoea ananatis leads to bulb infection. Plant Disease 97:1524 - 1528. Coolong, T. W., Randle, W. M. 2008. The effects of calcium chloride and ammonium sulfate on onion bulb quality at harvest and during storage. HortScience 43: 465 – 471.

Diaz-Perez, J. C., Purvis, A. C., Paulk, J. T. 2002. Bolting, yield, and bulb decay of sweet onion as affected by nitrogen fertilization. Journal of the American Horticultural Society 128: 144 - 149. Edens, D. G., Gitaitis, R. D., Sanders, F. H., Nischwitz, C. 2006. First report of Pantoea agglomerans causing a leaf blight and bulb rot of onions in Georgia. Plant Disease 90: 1551. Elmer, W. H. 2000. Comparison of plastic mulch and nitrogen form on the incidence of Verticillium wilt of eggplant. Plant Disease 84: 1231-1234. Elmer, W. H., LaMondia, J. 1999. Influence of ammonium sulfate and rotation crops on strawberry black root rot. Plant Disease 83: 119-123. Gamiely, S., Randle, W. M., Mills, H. A., Smittle, D. A., Banna, G. I. 1991. Onion plant growth, bulb quality, and water uptake following ammonium and nitrate nutrition. HortScience 26: 1061-1063. Gitaitis, R. D., Gay, J. D. 1997. First report of a leaf blight, seed stalk rot, and bulb decay of onion by Pantoea ananas in Georgia. Plant Disease 81: 1096. Gitaitis, R. D., Gent, D. H., Schwartz, H. S. 2008. ‘Leaf streak and bulb rot’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 59. Huber, D. M., Graham, R. D. 1999. ‘The role of nutrition in crop resistance and tolerance to diseases’ in: Mineral Nutrition of Crops: Fundamental Mechanisms and Implications. Food Products Press, New York. Pp. 169 – 204. Huber, D. M., McCay-Buis, T. S. 1995. A multiple component analysis of the take-all disease of cereals. Plant Disease 77: 437 – 446. Huber, D. M., Thompson, I. A. 2007. ‘Nitrogen and Plant Disease’ in: Mineral Nutrition and Plant Disease. APS Press: St. Paul, MN. Pp. 31 – 44. King, E. O., Ward, M. K., Raney, D. E. 1954. Two simple media for the demonstration of pyocyanin and fluorescin. Journal of Laboratory and Clinical Medicine 44, 301–307.

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Malik, M. F., Nawaz, M., Ellington, J., Sanderson, R., El-Heneidy, A. H. 2009. Effect of different nitrogen regimes on onion thrips, Thrips tabaci Lindemann, on onions, Allium cepa L. Southwestern Entomologist 34: 219 – 225. McGuire, R. G., Kelman, A. 1984. Reduced severity of Erwinia soft rot in potato tubers with increased calcium content. Phytopathology 74: 1250-1256.

Mohan, S. K. 2008a. ‘Other Bacterial Soft Rots’ in: Compendium of Onion and Garlic Diseases and Pests, 2nd edition. APS Press: St. Paul, MN. pp. 62.

Rahman, M., Punja, Z. K. 2007. ‘Calcium and Plant Disease’ in: Mineral Nutrition and Plant Disease. APS Press: St. Paul, MN. pp. 79 – 89.

Randle, W. M., Kopsell, D. E., Kopsell, D. A., Snyder, R. L. 1999. Total sulfur and sulfate accumulation in onion is affected by sulfur fertility. Journal of Plant Nutrition 22: 45 – 51.

Rumpel, J., Kaniszewski, S., Dysko, J. 2004. Effect of drip irrigation and fertilization timing and rate on yield of onion. Journal of Vegetable Crop Production 9: 65 – 73.

Westerveld, S. M., McDonald, M. R., Scott-Dupree, C. D., McKeown, A. W. 2003a. The effect of nitrogen on insect and disease pests of onions, carrots, and cabbage. Journal of Vegetable Crop Production 8 (2): DOI: 10.1300/J068v08n02_09.

Westerveld, S. M., McKeown, A. W., Scott-Dupree, C. D., McDonald, M. R. 2003b. How well do critical nitrogen concentrations work for cabbage, carrot, and onion crops? HortScience 38: 1122-1128.

Wright, P. J. 1993. Effects of nitrogen fertilizer, plant maturity at lifting, and water during field-curing on the incidence of bacterial soft rot of onions in store. New Zealand Journal of Crop and Horticultural Science 21: 377 – 381.

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Chapter 7: Revised best practices for onion production in Pennsylvania and future work

Pennsylvania onion growers participating in the Simply Sweet® program are faced with the

combined challenges of bacterial inoculum pressure, use of highly susceptible onion varieties, and

environmental conditions that favor development of bacterial disease. The advantages of participation in

the program include the fact that the supply of Simply Sweet® onions, the state’s only trademarked crop,

currently does not meet consumer demand, the timing of the onion growing season is convenient in

relation to other vegetable crops, and no specialized equipment is necessary. Thus, onions are an excellent

crop for vegetable growers to diversify their farm enterprises. Based on four years’ worth of intensive

sampling and observation, field experimentation, and data analysis, revisions to the current best practices

for onion production may be made to enhance the profitability and expansion of the crop in Pennsylvania.

While most commercial growers in Pennsylvania use plastic mulch and drip irrigation for weed

and disease suppression, respectively, individuals have additional production choices to consider as they

plan their onion fields. One recommendation, based on several years of replicated trials (Gugino,

unpublished) in addition to soil temperature data (Chapter 4), is to use biodegradable mulch to reduce

bacterial disease through moderation of soil temperatures. Early season soil warmth is important for

onion transplant establishment, however, soil temperatures, especially at and after bulbing, are positively

associated with bacterial disease (Chapter 4). Another early-season aspect of effective bacterial disease

management is preventing the introduction of bacterial inoculum into the onion crop. Onion transplants

should be carefully inspected for symptoms of bacterial disease, with only healthy plants planted into the

field. The majority of Pantoea agglomerans, Pectobacterium carotovorum, and Pseudomonas marginalis

isolates from transplants induce rotting symptoms in onion (Chapter 2), and analyses from 54 different

locations suggest this may particularly be the case with P. marginalis (Chapter 3). In the future, at-plant

treatments should be investigated for their potential to reduce bacterial inoculum from transplants;

suggested products to evaluate are surface-sterilizing treatments like hydrogen peroxide and biorational

products with Bacillus spp. as active ingredients, such as those used in Chapter 5. Pathogenic bacteria

have also been isolated from early-season soil (Chapter 2), so growers should choose a field with well-

drained soil that has not been planted to Alliums within the last two seasons, and low-lying areas should

be avoided (Chapter 5). There is evidence for antagonism between environmental (soil and weed-derived)

strains of Pantoea agglomerans and detections of the same bacterium in symptomatic onions (Chapter

3), which could be further investigated in laboratory and field experiments for potential biological control.

Some surface sterilants and plant defense-inducing products, such as those containing Bacillus

subtilis, were shown to be as effective as grower standard copper-mancozeb treatments in managing

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center rot of onion under low bacterial inoculum pressure (Chapter 5), so these products may play a role

in integrated disease management in the future. Additional experimentation on how best to integrate

these products for disease as well as potential copper resistance management is necessary before making

full recommendations, however. Weed control is also a potential in-season disease management strategy.

Bacterial isolates from weeds were shown to induce symptoms in pathogenicity tests, and one isolate of

Pantoea ananatis was obtained from both a midseason weed and a symptomatic onion bulb from storage,

from the same farm (Chapter 2). Additional work into the role of weeds as sources of bacterial inoculum

may be undertaken, such as the potential for pathogens of interest to be seedborne on weed seeds, the

timing of bacterial epiphytic and endophytic colonization of weeds, and the roles of weeds as potential

green bridges for inoculum movement from onion to onion. There may also be a role for onion thrips, the

most common insect pest of onions, in the epidemiology of bacterial rots (Appendix A), so thrips should

be managed on farms with high pest pressure. Additional research into the practical significance of these

insects is necessary to determine thresholds for management.

Onion growers participating in the Simply Sweet® program as well as other onion growers benefit

from producing a greater proportion of jumbo- and colossal-size bulbs compared to medium and small

bulbs, so fertigation programs are of significant interest to Pennsylvania growers. From one year of data,

it was suggested that while the primary form of supplied nitrogen (nitrate or ammonium) did not affect

center rot incidence, the timing of nitrogen application may play a role in center rot development. Using

the same fertilization rates, treatments where total nitrogen for the season was applied prior to bulbing

were similar between uninoculated and inoculated plots, but this was not the case for unfertilized and

full-season fertilized onion plots (Chapter 6). This suggests that in-season nitrogen application should be

completed in the early part of the season in addition to avoiding sulfur-containing products for the sole

fertilizer source, however, additional replicated experimentation is necessary to verify these preliminary

results. In addition, associations between foliar calcium and nitrogen levels suggest further investigation

of the role of these nutrients in center rot disease management (Chapter 6).

As the onion season draws to a close, growers are perennially faced with the question of when to

harvest their crops. Growers who observe high bacterial disease pressure often harvest early, trading bulb

size for the assurance of a larger proportion of asymptomatic onions. Other growers favor postponing

harvest to maximize bulb size, but at the cost of higher disease incidence. Current and ongoing work using

the disease rating scale (Chapter 5) in combination with regular scouting will help to identify a threshold

foliar disease severity value growers may use to determine when to harvest individual fields to maximize

yield with an economically tolerable level of bulbs with bacterial rot. Following harvest, rapid drying-down

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of onion necks can prevent the movement of leaf-infecting bacteria into onion bulbs, reducing postharvest

disease. Other future work includes an onion variety trial to identify less-susceptible cultivars and

repeated experiments into plant defense-inducing compounds and fertilizer programs for managing

bacterial disease. Combinations of these cultural and disease management practices will ideally increase

the profitability of producing onions in Pennsylvania, with some production practices broadly applicable

to reduce the incidence of bacterial disease in a variety of pathosystems.

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Appendix: Preliminary work with thrips identification by PCR primers and the impact of onion thrips

(Thrips tabaci) on center rot of onion (Allium cepa) in Pennsylvania

Introduction

Onion thrips, Thrips tabaci Lindeman, have been reported as the primary insect pest in onion

production in New York (Shelton et al., 2006), and varying levels of thrips damage were found on all 32

Pennsylvania farms surveyed in 2011 and 2012 (Pfeufer and Gugino, unpublished), but the prevalent

species in PA are unknown. Other thrips with potential to be found in Pennsylvania include western flower

thrips (Frankliniella occidentalis Pergande), tobacco thrips (F. fusca Hind), flower thrips (F. tritici Fitch),

and tomato thrips (F. schultzei Trybom; Felland et al., 1995; B. Nault, pers. comm.). Specifically, western

flower thrips and onion thrips have been previously demonstrated to vector P. ananatis and P.

agglomerans (Wells et al., 2002; Gitaitis et al., 2003; Dutta et al., 2012, 2014), in addition to serving as

vectors for iris yellow spot virus, which illustrate why thrips management for onions may have more

significant impacts than solely yield concerns in PA.

Western flower thrips, F. occidentalis, has been analyzed in terms of its gut bacteria, which

includes P. agglomerans, in several studies (de Vries et al., 2001; de Vries et al., 2004). These studies

suggested that western flower thrips became infested during larval stages, the bacteria reside in the

hindgut, and bacterial relationships with the insect change based on the food source (de Vries et al., 2001;

de Vries et al., 2004). The relationship between the insect and its gut symbionts was shown to be parasitic

when the insect food source was nutrient-rich, and beneficial when the food source was poor (de Vries et

al., 2004). In another publication, complicated interactions between F. occidentalis and chrysanthemum

nitrogen content demonstrated that the rate of increase in insect number was highest on plants grown in

high N, but that plant phenology was more influential overall in thrips population development (Chau et

al., 2005). Fertility management has been suggested to be an important factor affecting onion thrips

populations in multiple locations (Buckland et al., 2013; B. Nault and C. Hoepting, pers. comm.).

A comparison of F. occidentalis (western flower thrips) gut bacteria and T. tabaci (onion thrips)

gut bacteria based on 16S rDNA sequence and biochemical characteristics identified the type species of

four out of five T. tabaci gut bacterial populations as Erwinia herbicola (de Vries et al., 2008). In 1989,

however, it was suggested that E. herbicola isolates be placed into the P. agglomerans species, along with

the former Enterobacter agglomerans and Erwinia milletiae (Gavini et al., 1989). A different phylogenetic

analysis of several different F. occidentalis populations identified two consistent, distinct bacterial

symbionts associated with the insects. Both isolates were identified as members of the family

Enterobacteriaceae, with one grouping with Erwinia species, and the other into an unknown genus most

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closely related to E. coli and Enterobacter sakazakii (Chanbusarakum and Ullman, 2008). It is important to

note, however, that neither of the author groups used any Pantoea species in their analyses. In 2010 and

2011, P. agglomerans was successfully amplified from macerated F. occidentalis found feeding on onions

in the Penn State greenhouses (Pfeufer, unpublished).

Very recently, it has been shown that onion thrips have the ability to acquire as well as transmit

P. ananatis and P. agglomerans (Dutta et al., 2012, 2014). This research group showed that at least 92%

of onion thrips had acquired either bacterium after feeding for 48 hours on inoculated plants, and

transmission efficiency was approx. 60% for P. ananatis and 75% for P. agglomerans (Dutta et al., 2014).

While some PA growers manage thrips populations in their fields through the use of insecticides, it is

common for growers to discount the role of thrips in yield losses, and certainly in terms of disease

incidence in their crops (Pfeufer, unpublished). Little data exists pertaining to the impact of these insects

on yield losses due to bacterial rots of onion in PA. These lines of evidence suggest undertaking a more

thorough investigation into the potential role of thrips as field vectors of the Pantoea pathogens of onion.

Thrips may be identified to species using morphological keys, PCR, DNA fingerprinting,

sequencing, or combinations of methods. The use of morphological keys requires training, and can be

ambiguous because environmental conditions, such as temperature and moisture, can alter phenotypic

characteristics of thrips within the same species (Asokan et al., 2006). In addition, thrips larvae are

morphologically indistinguishable to the species level. RFLP-DNA fingerprinting methods generally

restriction-digest amplified copies of the cytochrome oxidase gene (CO1), generating banding patterns

that are species-specific (Brunner et al., 2002), however, restriction digest procedures are costly in terms

of time and materials. PCR identification methods are based on amplifying DNA of a known sequence

within the insect genome and generating DNA fragments of a specific size. PCR species identification

methods have been published for T. tabaci, T. palmi, and F. occidentalis (Asokan et al., 2006; Huang et al.,

2010; Toda and Komazaki, 2002), however, the use of some published primer sets and protocols has

produced inconsistent results (Pfeufer, unpublished).

To more clearly elucidate the impact of thrips on onion production in PA and determine the

potential for these insects to vector Pantoea ananatis and P. agglomerans, thrips were collected from

grower and research farms, visually identified to species, then bacterial isolates were generated from

these insects. Preliminarily, published PCR primers were tested for their specificity to Thrips tabaci, then

novel primers were designed in order to facilitate more rapid identification of onion thrips. These activities

were not continued past February 2013.

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Materials and Methods

Sample collection and identification

Thrips were collected from fourteen of the 26 farms visited for the observational study in 2012 by

removing an onion leaf very close to the plant neck and placing the tissue, along with the insect, into a 50

mL screwtop tube. Tubes were placed on ice in a cooler until return to the lab, where they were placed in

4⁰C storage. Within four weeks, thrips were removed from the tubes and tentatively identified to species

by inspecting them under at least 100x magnification for morphological characteristics. Both T. tabaci and

F. occidentalis are golden to gray-tan in color, adults 1-2 mm long, with two pairs of fringed-wings typical

of insects in the order Thysanoptera (UM Extension). Both species of thrips have lateral brown bands

alternated with yellow bands on the thorax. T. tabaci may vary more toward the grayish coloration and

are slightly smaller than F. occidentalis. Both species’ coloration can vary with environment, but the

following descriptive characters are consistent: T. tabaci have 7 antennal segments, 3 gray ocelli posterior

to the eyes, and shorter post-ocellar setae, while F. occidentalis have 8 antennal segments, 3 red ocelli

posterior to the eyes, and longer post-ocellar setae (UM Extension; Hoddle et al., 2012; Fig. A.1). T. tabaci

are more prevalent in the NY production system and can overwinter there (Nault, pers. comm), however,

F. occidentalis are a common greenhouse pest in PA, but seem to be found less frequently in the field

(Pfeufer, unpublished), perhaps as a result of difficulty in overwintering or poor competitorship.

Fig. A.1. Frankliniella occidentalis (left) and Thrips tabaci (right) as viewed at

100x magnification (E. Pfeufer).

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Sample preparation and bacterial isolation

After putative identification to species, insects were washed once in buffer (for epiphytic

bacteria), then washed twice in 70% ethanol, rinsed in sterile H20, then each was placed in a sterile tube

containing 20 µL of sterile buffer. Insects were macerated in this buffer using a sterile micropestle, then

five µL of buffer was used to inoculate culture tubes containing five mL of sterile nutrient broth (NB).

Tubes were incubated at 30⁰C with agitation (150 rpm) overnight, then broth was spread on King’s B

media, from which bacterial isolates were chosen. Isolates were generated by choosing a single colony

from KB with a sterile toothpick, then inoculating glass tubes containing five mL sterile Luria-Bertani broth

(Becton, Dickinson Co., Sparks, MD, USA), which was allowed to grow overnight before freezing at -20⁰C

in 15% glycerol.

Bacterial species identification

Bacterial isolates with phenotypic characteristics typical of Pantoea spp. (yellow on KB media)

were subjected to direct-colony multiplex PCR using the Pantoea ananatis and P. agglomerans primers

described in Chapter 2. PCR template was a toothpick touched to a single bacterial colony grown on KB.

In addition, a subset of unknown bacterial isolates were amplified for 16S rDNA sequencing, using the

primer sequences 530F and 1492R (Borneman et al., 1996). PCR reactions were cleaned using ExoSAP-it

(USB®, Cleveland, OH, USA), then 5 µL of reaction mixed with 1 µL of 590F primer was submitted to the

Penn State Nucleic Acid Core Facility for sequencing. Sequence data was edited, then NCBI BLAST was

used to identify the bacterial isolates to species.

Pathogenicity tests

A subset of isolates was tested for pathogenicity using aerobic and semi-anaerobic incubations

described in Chapter 2, where surface-sterilized pearl onion bulbs were inoculated with approx. 100 µL

overnight broth culture, then incubated one or two weeks, respectively. Symptom development was rated

according to the scale in Chapter 2.

Thrips species identifications

Previously published primers for T. tabaci (Asokan et al., 2007), F. occidentalis (Huang et al., 2010),

and Thrips palmi (Asokan et al., 2007; Table A.1) were tested for specificity using thrips collected from

onion fields as well as the Penn State greenhouses. Insects of the order Thysanoptera were putatively

identified to species based on morphological characteristics; no T. palmi were identified. Thrips were

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macerated in 20 µL sterile H20, then macerates were used as templates for PCR reactions composed of

12.5 µL TaqPRO Complete master mix (Denville Scientific, Metuchen, NJ), 1 µL species 1 forward primer

(10 mM), 1 µL species 2 forward primer (10 mM), 1 µL species 1 reverse primer (10 mM), 1 µL species 2

reverse primer (10 mM), and 7.5 µL PCR water. PCR conditions were as follows: (1) initial denaturation at

94°C for 3 min, followed by 40 cycles of (2) 94°C for 30 s; (3) 58°C (OT / MT) or 60°C (WFT) for 35 s, (4)

72°C for 1 min; then a final elongation at (5) 72°C for 20 min and storage at (6) 4°C continuous. PCR

amplicons were visualized by combining 10 µL reaction with 1.5 µL EZ-Vision Three dye (AMRESCO Inc.,

Solon, OH, USA) and electrophorescing in a 1.5% 1X TAE agarose gel for 45 min at 90V with either a 1kb

or 500 bp ladder (Denville, Metuchen, NJ, US).

Table A.1. Sequences, expected amplicon sizes, and sources of primers used to identify thrips collected from PA to species.

Primer Sequence Expected amplicon size

Source

T. tabaci F CGTTTTATCATTCAGGACC 298 bp Asokan et al., 2007

T. tabaci R AAGGTGTTGATATAAAACAGGGTCC

F. occidentalis F GTTTCCGTAGGTGAACCTGC 249 bp Modified from Huang et al., 2010 F. occidentalis R TGTTTTGGGCCATCTCCC

T. palmi F TTGACTTCTTCCACCCTCTTTAACTCTT 390 bp Asokan et al., 2007

T. palmi R TAGATGTTGATAAAGTACAGGATCT

Results and Discussion

Fig. A.2. Representative electrophoresis gel of PCR reactions using published Thrips tabaci (OT; expected amplicon size, 298 bp; Asokan et al., 2007), Frankliniella occidentalis (WFT; expected amplicon size, 249 bp; modified from Huang et al., 2010), and Thrips palmi (MT; expected amplicon size, 390 bp; Asokan et al., 2007) primer sets.

Several PCR reactions were attempted using published T. tabaci (Asokan et al., 2007), F.

occidentalis (Huang et al., 2010), and T. palmi (Asokan et al., 2007) primers to determine if these primer

sets would reliably differentiate the three species of thrips, forgoing morphological identification. F.

occidentalis was accurately identified in approx. 80% of successful reactions using visually identified,

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macerated F. occidentalis as the template, and failed reactions may have occurred as a result of

inappropriate cycling parameters. F. occidentalis primers did amplify some putatively identified T. tabaci,

though the fragment size was not the appropriate size (approx. 175 bp; Fig. A.2). Nevertheless, these

primers hold promise for the simple, rapid detection of F. occidentalis. Combining all three primer sets

and amplifying using the OT/MT PCR parameters still resulted in amplification of F. occidentalis at the

expected amplicon size, however, T. tabaci was no longer identified in the triplex reaction (Fig. A.2).

Visually identified T. tabaci were identified using the published T. tabaci primers in 50% of

reactions attempted (12 of 24; Fig. A.2). However, the amplicon generated was quite faint and was the

incorrect size; approximately 500 bp, when the expected amplicon size was 298 bp (Asokan et al., 2007).

Since the published primers were developed based solely on onion thrips from India, it may be that PA

populations of onion thrips have insertion(s) in the CO1 gene, resulting in larger than expected amplicon

sizes. However, additional PCR protocols would need to be completed in order to determine if this is the

case. The published T. palmi primers did not amplify any of the extracts used, which was expected, since

none of the extracted insects were visually identified as T. palmi (Fig. A.2).

Table A.2. Bacterial isolates from thrips tested for pathogenicity on onion through aerobic and semi-anaerobic pathogenicity tests. Ratios in each column pertain to the pathogenic isolates out of all isolates of that species tested; total columns indicate the total number of strains of each species in the collection.

Bacterial epiphytes (RS only) Bacterial endophytes (RS & grower farms)

Aerobic test Anaerobic test Total Aerobic test Anaerobic test Total

P. ananatis 3 / 5 10 1 / 2 1 / 2 4

P. agglomerans 0 / 2 1 / 2 3 3 / 4 3 / 4 4

Enterobacter sp. 3 1

Rahnella sp. 1 4

Other 5

Not yet identified 20 50

Total isolates 3 / 7 1 / 2 37 4 / 6 4 / 6 68

Pathogenicity tests of bacterial isolates from the surfaces and within the tissues of thrips sampled

from Rock Springs and selected grower farms indicated bacteria pathogenic to onion were isolated from

these insects (Table A.2). In particular, pathogenic P. ananatis and P. agglomerans were isolated in low

numbers, which supports previous reports of these insects vectoring the Pantoea spp. bacterial pathogens

(Dutta et al., 2014). However, significantly more evidence is necessary to determine the true impact of

thrips on bacterial rots of onion in PA. While onion thrips have recently been demonstrated to acquire

and transmit the Pantoea spp. in laboratory assays (Dutta et al., 2014), additional data is necessary

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pertaining to the frequency of thrips vectoring these pathogens in PA, the relative losses incurred by high

thrips pressure, both in terms of yield and disease, in addition to more basic information about the

prevalent species of thrips in and around onion fields in PA.

Acknowledgement

Caroline Black assisted E. Pfeufer initially in visually identifying thrips to species based on morphology.

References Alston, D. G., Drost, D. 2008. Onion thrips (Thrips tabaci). Utah Pests Fact Sheet, Utah State University Extension. Ent-117-08PR. Asokan, R., Krishna Kumar, N. K., Kumar, V., Ranganath, H. R. 2007. Molecular differences in the mitochondrial cytochrome oxidase I (mtCOI) gene and development of a species-specific marker for onion thrips, Thrips tabaci Lindeman, and melon thrips, T. palmi Karny (Thysanoptera: Thripidae), vectors of tospoviruses (Bunyaviridae). Bulletin of Entomological Research 97:461-470. Brunner, P. C., Fleming, C., Frey, J. E. 2002. A molecular identification key for economically important thrips species (Thysanoptera: Thripidae) using direct sequencing and a PCR-RFLP-based approach. Agricultural and Forest Entomology 4: 127-136. Chau, A., Heinz, K. M., Davies, F. T. 2005. Influences of fertilization on population abundance, distribution, and control of Frankliniella occidentalis on chrysanthemum. Entomologia Experimentalis et Applicata. 117:27-39. Chanbusarakum, L., Ullman, D. 2008. Characterization of bacterial symbionts in Frankliniella occidentalis (Pergande), western flower thrips. Journal of Invertebrate Pathology 99:318-325. de Vries, E. J., Jacobs, G., Breeuwer, J. A. J. 2001. Growth and transmission of gut bacteria in the western flower thrips, Frankliniella occidentalis. Journal of Invertebrate Pathology 77:129-137. de Vries, E. J., Jacobs, G., Sabelis, M. W., Menken, S. B. J., Breeuwer, J. A. J. 2004. Diet–dependent effects of gut bacteria on their insect host: the symbiosis of Erwinia sp. and western flower thrips. Proceedings of the Royal Society of London 271: 2171-2178. de Vries, E. J., van der Wurff, A. W. G, Jacobs, G., Breeuwer, J. A. J. 2008. Onion thrips, Thrips tabaci, have gut bacteria that are closely related to the symbionts of the western flower thrips, Frankliniella occidentalis. Journal of Insect Science 8:23 (11 pp., available online). Doda, S., Komazaki, S. 2002. Identification of thrips species (Thysanoptera: Thripidae) on Japanese fruit trees by polymerase chain reaction and restriction fragment length polymorphism of the ribosomal ITS2 region. Bulletin of Entomological Research 92: 359-363.

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Dutta, B., Gitaitis, R., Langston, Avci, U., Barman, A., Srinivasan, R. 2012. Acquisition and transmission of Pantoea ananatis and Pantoea agglomerans (causal agents of center rot of onion) by Thrips tabaci (Thysanoptera: Thripidae). Phytopathology S4:88. Dutta, B.., Barman, A. K., Srinivasan, R., Avci, U., Ullman, D., Langston, D. B., Gitaitis, R. 2014. Transmission of Pantoea ananatis and Pantoea agglomerans, causal agents of center rot of onion (Allium cepa L.) by onion thrips (Thrips tabaci Lindeman) through feces. Phytopathology 104: 812 – 819. Felland, C. M., Teulon, D. A. J., Hull, L. A., Polk, D. F. 1995. Distribution and management of thrips (Thysanoptera: Thripidae) on nectarine in the mid-Atlantic region. Journal of Economic Entomology 88(4):1004-1011. Hoddle, M.S., Mound, L.A., Paris, D.L. 2012. Thrips of California. CBIT Publishing, Queensland. Hoepting, C. A. Cornell University extension educator and onion specialist. Personal conversations, April 2012 – present. Huang, K. S., Lee, S. E., Yeh, Y., Shen, G. S., Mei, E., Chang, C. M. 2010. Taqman real-time quantitative PCR for identification of western flower thrip (Frankliniella occidentalis) for plant quarantine. Biology Letters 6:555-557. Morse, J. G., M. S. Hoddle. 2006. Invasion biology of thrips. Annual Review of Entomology 51: 67-89. Nault, B. Cornell University research and extension entomologist. Personal conversation, February 2012. Shelton, A. M., Zhao, J. Z., Nault, B. A., Plate, J., Musser, F. R., Larentzaki, E. 2006. Patterns of insecticide resistance in onion thrips (Thysanoptera: Thripidae) in onion fields in New York. Journal of Economic Entomology 99: 1798 - 1804. Toda, S., Kamazaki, S. 2002. Identification of thrips species (Thysanoptera:Thripidae) on Japanese fruit trees by polymerase chain reaction and restriction fragment-length polymorphism of the ribosomal ITS2 region. Bulletin of Entomological Research 92:359-363. Wells, M. L., Gitaitis, R. D., Sanders, F. H. 2002. Association of tobacco thrips, Frankliniella fusca (Thysanoptera: Thripidae), with two species of bacteria of the genus Pantoea. Annals of the Entomological Society of America 95: 719-723.

Emily E. Pfeufer VITA

Education Doctor of Philosophy in Plant Pathology .................................................................. expected August, 2014 Master of Science in Plant Pathology ....................................................................................... August, 2010 Bachelor of Science in Biology, cum laude ................................................................................... May, 2008

Awards Paul Hand Award for Graduate Student Teaching Achievement, Penn State .......................... March, 2014 2nd place, Life Sciences Division, 2013 Penn State Graduate Exhibition ..................................... April, 2013 1st place, Biological Sciences Division, 2013 PSU - GSD Graduate Research Competition .......... April, 2013 I.E. Melhus Graduate Student Symposium, American Phytopathological Society ............... February, 2013 Henry W. Popp Award, Penn State Department of Plant Pathology and Env. Micro. .............. August, 2012 Larry Jordan Endowment, Penn State Department of Plant Pathology and Env. Micro. .............. May, 2012 Henry W. Popp Award, Penn State Department of Plant Pathology and Env. Micro. ............... August, 2010 4th place, Biological Sciences Division, 2010 PSU – GSD Graduate Research Competition .......... April, 2010 Crouch Graduate Fellowship, Penn State College of Agricultural Sciences ............................. August, 2008 Alden Scholar, Allegheny College...................................................................... Academic terms, 2005-2008 Trustee Scholarship, Allegheny College ........................................................... Academic terms, 2004-2008 Peer-reviewed publications Pfeufer, E. E., Hoepting, C. A., Gugino, B. K. 2014. Environmental and management factors related to bacterial rots of onion in Pennsylvania and New York. Plant Disease; in preparation.

Mansfield, M. A., Pfeufer, E. E., Gugino, B. K. 2014. Diagnostic multiplex PCR method to detect onion bacterial pathogens in plant tissue and environmental samples. Plant Disease; in preparation. Ramos, L. S., Lehman, B. L., Sinn, J. P., Pfeufer, E. E., Halbrendt, N. O., McNellis, T. W. 2013. The fire blight pathogen Erwinia amylovora requires the rpoN gene for pathogenicity in apple. Molecular Plant Pathology 14: 838 – 843. Pfeufer, E. E., Ngugi, H. K. 2012. Orchard factors associated with resistance and cross-resistance to sterol demethylation inhibitor fungicides in populations of Venturia inaequalis from Pennsylvania. Phytopathology 102: 272-282. Brazelton, J., Pfeufer, E. E., Sweat, T., McSpadden Gardener, B., Coenen, C. 2008. 2,4-diacetylphloroglucinol alters plant root development. Molecular Plant Microbe Interactions 21: 1349-1358.