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An Integrated Approach for Managing Fusarium head blight and
Deoxynivalenol in Wheat: Lessons Learned After 12 Years of Multistate Research
Dr. Pierce A. PaulAssociate Professor
2
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
• Fusarium graminearum• Infection
– Warm, humid weather– Anthesis and early grain-fill– Shriveled light-weight kernels– Fusarium damaged kernels (FDK)
• Grain yield and quality losses– Low test weight and grain grade
Fusarium Head Blight (FHB)
• Grain contamination with mycotoxin- DON (Vomitoxin), 3A-DON, 15A-DON, and NIV- Livestock health concerns
• Flour yield and milling and baking quality
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
• Components of FHB-related lossesLower grain yield, price discounts due to DON contamination, Fusarium damaged kernels (FDK), and low test weight. • Costs associated with FHB management To minimize losses due to FHB and DON, growers are advised to implement management strategies such as: Tillage, crop rotation, cultivar resistance, and timely fungicide application, as well as grain harvesting strategies.• Impact on gross cash income (GCI)
FHB-related Losses
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
• Costs associated with management are not always offset by gains in grain yield and quality.
• Fungicides only provide about 50% control and the benefit of applying a fungicide is not always sufficient to offset application cost.
• Resistant varieties are not always high-yielding. • Modifying combine harvester configurations to
remove diseased kernels during harvest improves grain quality, but it may also reduce expected yield.
• Benefits depend on yield, baseline FHB and DON levels, grain prices and price discounts due to poor grain quality.
Factors Affecting Decision making
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
National Coordinated Project
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
National Coordinated Project
Integrated Management• Core Treatments
o Resistance (S, MS, MR)o Fungicide application
Prosaro (Tebuconazole+Prothioconazole)
o Inoculation• Cropping sequence/Rotation• Responses
o FHB Incidence and Severityo FDK,DON, NIV
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
National Coordinated Project
Treatment Prosaro Resistance Code
1 (Check) NO Susceptible S_UT
2 Yes Susceptible S_TR
3 NO Moderately Susceptible MS_UT
4 Yes Moderately Susceptible MS_TR
5 NO Moderately Resistant MR_UT
6 Yes Moderately Resistant MR_TR
Fungicide/Resistance treatment Combinations
8
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
National Coordinated Project
MS_UT MR-UT S_TR MS_TR MR_TR
Per
cen
t C
on
tro
l
-80
-60
-40
-20
0
20
40
60
80
100
MS_UT MR-UT S_TR MS_TR MR_TR-60
-40
-20
0
20
40
60
80
100
• Lots of data and highly variable results
• Lots of questionso How effective?o Is the combined effect additive?o How stable is the effect?o Is it economical?
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Efficacy and Additivity
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
10
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Efficacy: Overall Percent Control
100-
_
___
UTS
TRMRUTSTRMR X
XXC
UTS
TRMRTRMR X
XR
_
__
100)-1( __ TRMRTRMR RC
Measures of efficacy (effect size)
TRMRUTSTRMR XXD ___ -
11
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Efficacy: Overall Percent Control
i
ii
w
zw
A formal probabilistic approach for synthesizing evidence from multiple sources
Estimated Mean Percent
Control
Individual Percent Control
22ˆ1
ii sw
Meta-Analysis: Quantitative Research Synthesis
12
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Efficacy: Overall Percent Control
iii uz Effect size for study i(the result from study i
becomes a data point in the meta-analysis)
Expected effect size, overall
Among-study variability term.
Random effect of study i on the effect size.
i ~ N (0, 2)
Within-study variability term; residual or
“sampling variation”.Assume known.i ~ N (0, s2)
Meta-Analysis: The Model
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• Estimate and its sampling variance,
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Efficacy: Overall Percent ControlLog of R as effect size: PROC Mixed
𝑺𝑳𝟐=𝑽
𝒏 ( 𝟏𝑿𝑪𝑲
𝟐 −𝟏
𝑿𝑴𝑮𝑴𝑻𝟐 )
𝑳=𝒍𝒏 (𝑹)=𝒍𝒏 (𝑿𝑴𝑮𝑴𝑻 /𝑿 𝑪𝑲 )=𝒍𝒏 (𝑿𝑴𝑮𝑴𝑻 )− 𝒍𝒏 (𝑿𝑪𝑲 )
𝑳=𝒍𝒏 (𝑹)
• From each study obtain treatment means, and residual variance, V 𝑿 𝒊
𝑺𝑳𝟐
• Back-transform to obtain 𝐶𝐿
𝑪=[𝟏−𝒆𝒙𝒑 (𝑳) ]𝐱𝟏𝟎𝟎
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Efficacy: Overall Percent Control
15
Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
Additivity of the integrated effectAdditive: Observed C(F+R) = Expected C(F+R)
D|R = (1 – CR) = (1 – 0.54) = 0.46
C(F+R) = CR + CF (1 – CR) = 0.54 + 0.24 = 0.78
CF|R = CF (1 – CR) = 0.53 x 0.46 = 0.24
CR = 0.54
CF = 0.53
Observed C(F+R) = 0.76
Expected C(F+R) = 0.78
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
So, what have we learned?1. Combining resistance with fungicide is more
efficacious than either approach alone; 2. Relative to fungicide alone, the integrated
approach leads to comparable levels of index and DON reduction;
3. There is an additive effect of fungicide and resistance on both index and DON;
4. The integrated approach is more stable across environment; and
5. The integrated approach is more economically beneficial for a range of baseline FHB levels, grain prices and fungicide application costs.
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Ohio Agricultural Research and Development CenterDepartment of Plant Pathology
L. Madden and K. Willyerd (OSU)G. Milus (University of Arkansas)C. Bradley (University of Illinois)G. Bergstrom (Cornell)M. McMullen (NDSU)J. Ransom (NDSU)K. Wise (Purdue)B. Padgett (LSU)S. Wegulo (UNL)L. Osborne (SDSU)L. Sweets (University of Missouri)P. Esker (University of Wisconsin)W. Bockus (Kansas State University)D. Hershman (University of Kentucky)A. Grybauskas (University of Maryland)R. Dill-Mackey (University of Minnesota)
U.S. Wheat & BarleyScab Initiative
"This material is based upon work supported by the U.S. Department of Agriculture, under Agreement No. 59-0790-4-112. This is a cooperative project with the U.S. Wheat & Barley Scab Initiative. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture."
Acknowledgments
Dr. JD Salgado
Dr. KT Willyerd