1-s2.0-S0167198704000388-main

Soil & Tillage Research 78 (2004) 151170

Least limiting water range indicators of soil qualityand corn production, eastern Ontario, Canada

D.R. Lapen a,, G.C. Topp a, E.G. Gregorich a, W.E. Curnoe ba Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food Canada, Ottawa, Ont., Canada K1A 0C6

b Directors Office, University of Guelph-Kemptville College, Kemptville, Ont., Canada K0G 1J0

Abstract

The least limiting water range (LLWR) attempts to incorporate crop-limiting values of soil strength, aeration, and watersupply to plant roots into one effective parameter (on the basis of soil water content). The LLWR can be a useful indicator ofsoil quality and soil physical constraints on crop production. This study focused on assessing dynamic cultivation zone LLWRparameters between different cropping/tillage/trafficked clay loam plots at Winchester, Ont., to identify potential managementimpact on surficial soil physical conditions for contrasting growing seasons. This study also evaluated dynamic cultivationlayer LLWR variables as indicators of corn (Zea mays L.) plant establishment and corn yield. The results suggest that no-tillsoils had lower average air-filled porosities (AFP) and O2 concentrations than respectively managed tilled plots for both yearsof study. Potential trafficking effects on aeration properties were most evident in no-till relative to till; preferentially traffickedno-tilled plots had lower AFP and O2 concentrations than respective non-preferentially trafficked no-till plots for both yearsof study. Corn establishment and yield variability were principally explained by cumulative differences between daily AFPand aeration threshold values, and the cumulative number of days daily AFP was below an AFP aeration threshold for specificcorn growth stage periods. Lower AFP was linked to lower yields and plant establishments. Soil strength, as measuredby cone penetration resistance, was important over certain sites, but not as important globally as AFP in predicting cropproperties. Overall, conventional tilled soils that were not preferentially trafficked had most favorable aeration properties, andsubsequently, greatest corn populations and yields. No-till soils were at greater risk of aeration limiting conditions, especiallythose in continuous corn and preferentially trafficked.Crown Copyright 2004 Published by Elsevier B.V. All rights reserved.

Keywords: Least limiting water range; Aeration; Cone resistance; Tillage; Trafficking; Corn; Clay loam; CART

1. Introduction

Optimal crop rooting soil physical conditions are aresult of complex interactions between soil strength(mechanical impedance) and oxygen and water supplyto plant roots. The least limiting water range (LLWR)

Corresponding author. Tel.: +1-613-759-1537;fax: +1-613-759-1515.E-mail address: [email protected] (D.R. Lapen).

incorporates crop-limiting values of these factors intoone effective parameter, on the basis of soil water con-tent (WC) (Letey, 1985; Topp et al., 1994; da Silva andKay, 1997a). For instance, water contents associatedwith cone penetration resistance (PR) values >2 MPa(Bengough and Mullins, 1990; Greacen, 1986), andmore conservatively >3 MPa (Horn and Baumgartl,2000), are generally accepted to limit root growth.A critical aeration limit is often assumed to occurat an air-filled porosity (AFP) of approximately 10%

0167-1987/$ see front matter Crown Copyright 2004 Published by Elsevier B.V. All rights reserved.doi:10.1016/j.still.2004.02.004

152 D.R. Lapen et al. / Soil & Tillage Research 78 (2004) 151170W

ater

cont

ent (m

3 m

-3 )

0.0

0.1

0.2

0.3

0.4

0.5

0.6

LLWR

Porosity

Wilting Point

2 MPa Cone Pen. Res. Limit

Aeration Limit

Fig. 1. Conceptual diagram of LLWR.

vol. for most agricultural crops. For AFPs

D.R. Lapen et al. / Soil & Tillage Research 78 (2004) 151170 153

-50 0 50E-W axis (m)

320

420

520

620

N-S a

xis

(m)

72.3

72.5

72.7

72.9

m

BNTCC

01

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00

BNTC

01

BTC

BTCC

00

BTC

WTCC

01

WTC

00

WTC

01

WNTC

WNTCC

00

WNTC

Fig. 2. Study field. Locations of soil measurement sites (solid blackdiamonds) and in situ O2 concentration measurement sites (hollowdiamond for 2000 and hollow triangle for 2001) are overlaid onelevation map of field. Plots run NS and treatment names/yearsare given at top of map.

for tilled plots. A field trafficking treatment (i.e.,worst management) was conducted by making sin-gle wheel-beside-wheel passes with a 7710 Fordtractor (5400 kg total mass; front and rear tires13.6R24 at 137 kPa and 18.4R34 at 124 kPa, respec-tively) over the length of selected plots when thesoil was at or slightly above the upper plastic limit

Table 1Description of plot treatments

Plot Tillage Trafficking Cropa,b

BNTCC No-till Best Cont. cornBNTC No-till Best 1 year cornBTCC MB plow Best Cont. cornBTC MB plow Best 1 year cornWNTCC No-till Worst Cont. cornWNTC No-till Worst 1 year cornWTCC MB plow Worst Cont. cornWTC MB plow Worst 1 year corn

MB: mouldboard plow.a Cornsoybeanwheat rotation for 1 year corn plots.b Fourth year corn for 2000 and fifth year corn for 2001.

(0.35 Mg Mg1) as seeding time approached eachyear. Preferential trafficking was done prior to springsecondary tillage operations (cultivator) and seedingactivities. This treatment was employed to simulatesoil structural degradation, such as increased strength,densities, and surface sealing, imposed by wheel traf-fic during wet soil conditions. Best management wasnormal field operations when cultivation soils wereat water contents generally less than 0.3 Mg Mg1.Fertilizer for all plots was applied in spring at ratesof 155 and 150 kg N ha1 as ammonium nitrate for2000 and 2001, respectively; there was no side dress-ing. The same corn planter was used on all plots. Ameteorological station at the site provided informa-tion on incoming radiation, relative humidity, windspeed/direction, total precipitation and air and soiltemperature.

2.2. Soil and crop measurements

Cone penetration resistance was used as the cultiva-tion zone (average: 0.060.12 m depth increment) soilstrength indicator in our LLWR analyses. The mea-surement methods were made using the TerraPointcombination penetration resistance/water content in-strument (Young et al., 2000; Topp et al., 2001) atsoil measurement sites (Fig. 2) located down theun-trafficked (for secondary tillage, planting, fer-tilizer, and herbicide activities) center of each plot(between-row) at various stages of plant developmentfrom planting to post-harvest. The water contentsensor on the TerraPoint uses a time domain trans-missivity (TDT) approach, which is similar to TDRexcept that the signal for TDT is measured as it istransmitted, rather than reflected.

In situ soil WC and O2 concentrations were mea-sured at one measurement site per plot (Topp et al.,2000) from 1997 to 2001. For each plot O2 concen-trations were measured in duplicate at depths of 0.05,0.10, 0.20, and 0.30 m using double-membrane oxy-gen cathodes and a model P5 oxygen sensor (JensenInstruments, Tacoma, WA). The O2 sensor voltagewas recorded on a 21X datalogger (Campbell Scien-tific Canada Ltd., Edmonton, Alta.) as hourly aver-ages of six measurements. The O2 sensors, installedeach year just after emergence, were placed directlybeneath two adjacent corn rows at selected locationswithin each plot (Fig. 2). At the same four depths, soil

154 D.R. Lapen et al. / Soil & Tillage Research 78 (2004) 151170

WC was measured using a TDR instrument (modelMP917) (Environmental Sensors Inc., Victoria, BC).The 0.20 m length TDR probes were centered beneaththe corn rows by insertion horizontally from a soil pitwith vertical faces parallel to each instrumented cornrow and 0.10 m from the row location. Into the samevertical face, copperconstantan thermocouples werealso inserted at the same depth, and with the junctiondirectly beneath the corn row, to measure hourly soiltemperatures. The pit was back-filled after installationof equipment. Soil water content measurements, to amaximum depth of 0.4 m, were also determined at PRmeasurement sites using the TerraPoint TDT-basedmethods described in Topp et al. (2001).

Bulk densities at each depth increment at the insitu O2 concentration measurement sites were sampledin duplicate via vertically driven soil corers (76 mmlength and 47 mm i.d.) centered at O2 concentrationdepths. Bulk densities at other soil measurement siteswere made in triplicate from 0 to 0.15 m depth us-ing vertically driven soil corers (47 mm i.d.). Rela-tive soil compaction was determined for each samplesite (00.15 m depth) by estimating empirically max-imum bulk densities using soil texture information(Diaz-Zorita et al., 2001) and measured bulk densities.

Soil cores (76 mm length and 76 mm i.d.) for des-orption curve analysis were collected by verticallydriving a soil corer into surface soils near yearly O2measurement sites; four measurements per plot weretaken. The pressure plate methods used to provide in-formation on soil water desorption to matric potentialsof 1.5 MPa are described in Topp et al. (1993).

Spring cultivation layer residual soil NO3-N +NH4-N (00.15 m depth) were determined at eachmeasurement site for each plot. Pre-fertilizer soilsamples were taken approximately 15 and 10 daysprior to planting for 2000 and 2001, respectively.Three composited samples (18 mm diameter) weretaken at each soil sample location. The field moistsamples were immediately extracted with 2 M KCl.Residual soil NO3-N and NH4-N concentrationswere analyzed using a TRAACS 800 Autoanalyzer(Bran-Luebbe Analyzing Technologies, Elmsford,NY).

Total plant counts for the two harvested center rowswere made along each plot approximately 1 monthafter planting date. The corn plots were harvested witha plot combine fitted with a grain weighing system.

The plot combine was stopped every 10 m along thelength of each plot and the total yield was measuredover the previous 10 m of travel.

2.3. LLWR approach

Dwyer et al. (1988) noted that for soils similar intextural composition as those in this study, 62 and20% of maximum corn root length occurred in the00.15 and 0.150.30 m depth increment of the soil,respectively. Moreover, Ritchie et al. (1993) illustratedthat the critical growing point (stem apex) of corntypically occurs in the surface zone during criticalVE (emergence) and V3 (three-leaf stage) vegetativestages of plant growth. Notwithstanding lower depthimpact on corn growth, this study focused on LLWRparameters derived from water content informationin the top 0.15 m of the soil profile where most rootactivity typically occurs and where compaction andcultivation effects on soil structure at the site are moststrongly expressed (Lapen et al., 2002a; Topp et al.,2003). Cultivation zone LLWR parameters were de-termined for each plot treatment for wetter-cooler(2000) and drier-warmer (2001) conditions fromplanting to corn maturity.

2.3.1. Estimating daily soil water contentsTDT- and TDR-based soil WC measurements were

not made continuously over the 2000 and 2001 grow-ing seasons. Therefore, a soil water model (Tsuji et al.,1994), used in a companion study, was used to predictdaily soil WC at respective depths over the growingseasons using on-site soil, crop, and meteorologicalinformation as input. Linear regressions were thendeveloped to predict site-specific daily WC using thedaily Tsuji et al. (1994) model predictions as inde-pendent data, and the TDT and TDR site measures asdependent data.

2.3.2. Soil aeration, permanent wilting point, andsoil strength LLWR limits

Meyer and Barrs (1991) noted that the aeration sta-tus of the soil is more adequately described by totalO2 concentrations incorporating gaseous and dis-solved states, than merely a simple gas-filled porositycriterion (Glinski and Stepniewski, 1985). Exper-imental results for a variety of agricultural crops,including cotton (Gossypium spp.), wheat (Triticum


spp.), and corn, indicated that roots cease to grow atO2 concentrations below 0.01 kg O2 m3 soil; aera-tion constraints were likely restrictive around valuesof 0.02 kg O2 m3 soil (Meyer et al., 1987; Meyerand Barrs, 1991). For each treatment in this study,the highest observed growing season AFP (0.10 mdepth), associated with O2 concentrations (at 0.10 mdepth) less than 0.02 kg O2 m3 soil, was assumed torepresent an aeration limiting AFP. Thus, soil WC as-sociated with these AFPs were assumed to be aerationWC limits in the LLWR.

It was hypothesized that there would be general in-crease in cultivation zone bulk density (i.e., decreasein porosity) over the growing season, in particularfor tilled plots (Lapen et al., in press). Therefore,bulk densities (00.15 m depth at 10 m sample spac-ings over 300 m length of plots (un-trafficked andbetween-row)) were collected periodically over grow-ing seasons from planting to post-harvest from 1997to 2001 over tilled and no-till plots. Multivariate adap-tive regression splines (Friedman, 1991) were used todescribe statistical changes in bulk density from plant-ing to post-harvest. The permanent wilting point wasconsidered to serve as a lower WC limit in the LLWR,provided it was greater than the WC at which PR ex-ceeded the root growth limiting value.

Root growth is usually considered to be reduced byhalf at PR values between 2 and 3 MPa, whereas forvalues greater than 3 MPa, root growth is generallyprevented (Bengough and Mullins, 1990; Horn andBaumgartl, 2000). For this study, WC values associ-ated with a PR value of 2.5 MPa were selected as soilstrength WC limits in the LLWR. Due to non-linearassociations between observed PR and soil WC overthe growing season for tilled plots (Lapen et al., inpress), empirical models were developed, using multi-variate adaptive regression splines (Friedman, 1991),to predict daily cultivation zone PR from cultivationzone soil WC (tilled soils) and the number of daysafter planting (DAP). Linear regressions were used topredict daily PR from daily soil WC for no-till plots(Lapen et al., in press).

2.3.3. Statistical approachA suite of indicator variables were developed

(Table 2) to assess the relevance of planting-to-V6stage LLWR and soil temperature factors on plantestablishment. These indicators expressed the

cumulative number of days a soil variable exceededa designated LLWR threshold, the cumulative dif-ference between an estimated variable value and itsLLWR threshold, and cumulative daily soil tempera-tures. An additional variable was years in corn pro-duction (ROT). A non-parametric, binary, recursivepartitioning procedure described in Breiman et al.(1984) and Steinberg and Colla (1995) called regres-sion tree analysis (RTA) was used to predict plantcounts (establishment) from these LLWR and soiltemperature variables.

The goal of this RTA approach is to partition de-pendent data on the basis of independent variable splitcriteria into a suite of low variance dependent variablegroups. The dependent variable mean value of each re-sulting group is typically used as the predicted value.The RTA procedure begins by conducting tests usingthe entire group of input data (root parent node) todetermine which independent variable value best (interms of greatest reduction of variance due to split,i.e., improvement score) splits the dependent variableinto two subsequent groups or child nodes (primarysplit for that node of data). This optimal splitting pro-cess continues for each child node until user-definedstopping rules are met. Cross-validation can be usedto measure the goodness of fit, and mean-square erroris the criterion by which trees of different sizes areranked. Generally, this criterion can be expressed asthe cross-validated relative error (CVRE). The lowerthe value is for a specific sized tree, the more statisti-cally accurate the tree model is relative to other testedtrees. The specific RTA approach employed here isdiscussed in more detail in Lapen et al. (2001). Inthis study, cross-validation was employed using a 90%learning and a 10% testing approach. Independentvariable importance for a selected tree model was de-termined as improvement scores associated with eachvariable in its role as a primary and surrogate split.The values of these improvements are summed overeach of the trees nodes and totaled, and are scaledrelative to the best performing variable. A surrogatevariable split mimics a primary split on a case by casebasis, but has improvement scores less than or equal tothe primary split score. Surrogate splits are ranked byan association algorithm discussed in Breiman et al.(1984). Surrogate splits provide additional informa-tion on variable masking effects, multicollinearity, andpotential for spurious predictions.


Table 2Descriptions of variables used in statistical analyses

Variable description (AFPthr = threshold AFP value in LLWR for treatment)AFP variables

V6AFPa,b Cumulative daily AFP AFPthr from planting to V6 (m3 m3 day)V6AFPDAYa,b No. of days AFP below AFPthr from planting to V6R1AFPb Cumulative daily AFP AFPthr from planting to R1 (m3 m3 day)R1AFPDAYb No. of days AFP below AFPthr from planting to R1R6AFPb Cumulative daily AFP AFPthr from planting to R6 (m3 m3 day)R6AFPDAYb No. of days AFP below AFPthr from planting to R6R1-V6AFPb Cumulative daily AFP AFPthr from V6 to R1 (m3 m3 day)R1-V6AFPDAYb No. of days AFP below AFPthr from V6 to R1R6-R1AFPb Cumulative daily AFP AFPthr from R1 to R6 (m3 m3 day)R6-R1AFPDAYb No. of days AFP below AFPthr from R1 to R6

PR variablesV6PRa,b Cumulative daily PR 2.5 MPa from planting to V6 (MPa day)V6PRDAYa,b No. of days PR below 2.5 MPa from planting to V6R1PRb Cumulative daily PR 2.5 MPa from planting to R1 (MPa day)R1PRDAYb No. of days PR below 2.5 MPa from planting to R1R6PRb Cumulative daily PR 2.5 MPa from planting to R6 (MPa day)R6PRDAYb No. of days PR below 2.5 MPa from planting to R6R1-V6PRb Cumulative daily PR 2.5 MPa from V6 to R1 (MPa day)R1-V6PRDAYb No. of days PR below 2.5 MPa from V6 to R1R6-R1PRb Cumulative daily PR 2.5 MPa from R1 to R6 (MPa day)R6-R1PRDAYb No. of days PR below 2.5 MPa from R1 to R6

Soil temperature variablesV6STEMPa,b Cumulative daily soil temperature (0.1 m depth) from planting to V6 (C day)R1SOILTEMPb Cumulative daily soil temperature (0.1 m depth) from planting to R1 (C day)R6SOILTEMPb Cumulative daily soil temperature (0.1 m depth) from planting to R6 (C day)

Crop variablesROTa,b First year corn (coded 1) and fifth (2000) and sixth (2001) year corn (coded 0)YIELDc Final corn yield (10 m footprint) (t ha1)COUNTc Plant establishment (two-row average) (no. of plants m1 row)

AFP: air-filled porosity; PR: cone penetration resistancea Independent variables in COUNT analyses.b Independent variables in YIELD analyses.c Dependent variables in multivariate statistical analyses.

Regression tree analysis was also used in themanner described above, to predict YIELD fromLLWR, temperature, and cropping variables givenin Table 2. This analysis was intended to: (i) un-cover important growth-stage specific links betweenYIELD and LLWR variables, and (ii) identify ap-propriate yield-integrating LLWR indicators oftillage/trafficking/cropping effects on soil physicalproperties for different seasonal conditions. Simplenon-parametric correlation analyses using inter-nodaldependent and independent data were also used to helpgain insights into variable interactions and processes.

3. Results and discussion

3.1. Weather conditions for 2000 and 2001

Year 2000 and 2001 were considered effectivelywetter and cooler and warmer and drier, respec-tively (Figs. 3 and 4). Average minimum and max-imum temperatures between DAPs 1 and 130 were11.1 and 22.8 C, respectively, for 2000, and 11.9 and25.2 C, respectively, for 2001. Total precipitation forthis period was 288 mm for 2000 and 205 mm for2001. Droughty conditions occurred roughly between


2000

preci

pita

tion

(mm

)

& air

tem

pera

ture

(o C)

0

10

20

30

40

50

60

Days after planting0 50 100 150

2001

preci

pita

tion

(mm

)

& air

tem

pera

ture

(o C)

0

10

20

30

40

50

60

Precip.Max. temp.Min. temp.

Planting

MaturityPlanting

Killing frost

Fig. 3. Weather information collected at Winchester site (2000 and 2001).

DAP 65 and DAP 135 for 2001. The corn heat units(CHU) at V6, R1, and R6 stages of corn developmentfor 2000 and 2001 are given in Table 3.

3.2. Corn establishment and yield

In 2000, planting was delayed to day of year(DOY) 152 as a result of wet soil conditions just priorto planting (Fig. 3). Plant establishment (COUNT)reflected relative corn yield (YIELD) differences be-tween treatments (Fig. 5). The correlation betweenCOUNT and YIELD for 2000 was 0.69 (significance0.05 level). Moreover, plant establishment, henceyield, was generally greater for tilled treatments thanno-tilled treatments. Yields were also consistently

Table 3Corn heat units (CHUa) at various stages of corn development for 2000 and 2001Growth stage DAP 2000 DAP 2001 CHU 2000 CHU 2001

V6 (sixth leaf) 39 51 773 941R1 (silking) 77 79 1672 1597R6 (maturity) 118b 125 2391b 2633

a CHU = (1.8(daily min. temp 4.4)+ 3.3(daily max temp 10) 0.084(daily max temp 10)2)/2.b Corn did not really mature naturally due to killing frost on DAP (days after planting) 118.

lower in the worst managed treatments, relative torespective (till, no-till) best managed treatments.

For 2001, planting occurred on DOY 129, and plant-ing conditions were considered by the farm managers(B. Dow and M. Edwards, personal communication,2001) to be excellent. The COUNT versus YIELD cor-relation for 2001 was 0.33 (significance 0.05 level).Highest relative yields in 2001 could be found in bothtilled and no-till sites.

3.3. Soil water estimation, porosity, O2concentrations, and LLWR threshold values

Desorption curve data indicated that a WC of0.11 m3 m3 was an effective PWP for all plots.


Tota

l pre

cip.

(mm

)

0

50

100

1502000 2001 normal

Min

.

daily

tem

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(Co)

0

5

10

15

2020002001normal

May June July Aug

Max

.

daily

tem

p.

(Co)

0

10

20

30

4020002001normal

Fig. 4. Comparisons of site-observed precipitation and temperature data with Environment Canada normals (19712000) for Kemptville(latitude 4500, longitude 7538) weather station.

BNTCC BNTC BTC BTCC WNTCC WNTC WTC WTCC

Corn

yield

(t ha

-1 )

and

Esta

blish

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plan

ts

(coun

t m-1

row

lengt

h)

0

2

4

6

8

10Yield (2000)Yield (2001)Establish. (2000)Establish. (2001)

N=8 sites per plot

Fig. 5. Average and standard deviation of corn grain yields and corn plant establishment (measured approximately 1 month after planting)at in situ soil O2 measurement plus additional soil sampling sites.


Table 4Greatest air-filled porosities (m3 m3) observed with O2 concen-trations


Fig. 6. Measured air-filled porosity vs. O2 concentrations at in situ soil O2 concentration measurement sites for each plot at 0.1 m depthduring 2000 and 2001.

The linear regressions used to predict site-specificmeasured soil WC at non-O2 measurement sites(0.060.12 m) from soil water model predictions(0.060.12 m) (Tsuji et al., 1994) had generally highR2 values and modest standard errors (Table 6). Forcomparison purposes in subsequent analyses, dailysoil WC at each O2 measurement site were predictedvia the manner described above. Water content sup-port information for linear regression modeling wasgreater, relative to non-instrumented sites, for eachsite (N > 35) for each plot for each year. The R2between modeled (Tsuji et al., 1994) and observeddaily soil WC for all sites were >0.85 with standarderrors


TN1Avg.=2.2 (1.2)

N=9

TN2Avg.=3.4 (1.3)

N=35

N3: V6AFP -1.1Avg.=3.1(1.3)

N=44

TN4Avg.=5.0 (0.3)

N=10

N2: V6TEMP

677.0Avg.=3.5 (1.4)

N=54

TN3Avg.=4.9 (0.5)

N=34

TN5Avg.=5.4 (0.5)

N=40

N4: V6AFP4.8Avg.=5.1 (0.6)

N=74V6AFPDAY>2.0 (9%)

N1: V6AFP1.9Avg.=4.4 (1.3)

N=128V6AFPDAY>6 (55%)

V6AFPDAY>38 (68%)

V6AFPDAY 41 (18%)

Fig. 7. Regression tree predicting COUNT (nodal average (standard deviation) and N = number of observations) from LLWR, cropping,and soil temperature information. Observations that meet node splitting definitions (bold) occur in subsequent left-hand observation group(node); rest of observations go to subsequent right-hand node. N1, N2, N3, etc. refer to node numbers. TN1, TN2, TN3, etc. refer toterminal nodes (no further splitting of observations occurs). Terminal node numbers are based on ranking the COUNT averages for allterminal nodes so that the lowest average is for TN1 and highest average is for TN5. Surrogate variable split definitions for nodes are initalics, and surrogate split improvement scores are presented as a percentage of the primary split improvement score for that node.

model (Fig. 7) had an R2 of approximately 0.62 andthe second lowest CVRE (0.60), relative to the lowestCVRE (0.58) produced by a four-terminal node model(considered to simplistic for heuristic purposes) inthe tree building procedure. Surrogate variable splitsin the tree had modest improvement scores relative toassociated primary variable splitting criteria.

Fig. 7 indicates that the 128 initial COUNT ob-servations used as model input were initially spliton the basis of V6AFP = 1.9 m3 m3 day. The R2at this step in tree was 0.40. Sites in N4 with val-ues >1.9 m3 m3 day (higher average daily AFP) hadan average COUNT of 5.1 (standard deviation =0.6) plants m1 row, while for node 2 (V6AFP 1.9 m3 m3 day), the average and standard deviationof COUNT was 3.5(1.4) plants m1 row. The correla-tion coefficient between COUNT and V6AFP for allsites was 0.58 (significance 0.05 level) (R = 0.64 for2000 and 0.46 for 2001). AFP was clearly more lim-iting on establishment during the wetter year. Cornplants < V2 stage (two-leaf) are sensitive to low AFPand can be severely injured if subjected to near-zero

O2 concentrations for more than 24 h. Node 4 (N4) ob-servations split on the basis of V6AFP = 4.8 m3 m3day, and TN3 and TN5 had COUNT averages of 4.9(0.5) and 5.4 (0.5) plants m1 row, respectively. On aglobal basis, sites with V6AFP > 4.8 m3 m3 day hadthe highest average COUNT for both years of study.The N2 split criteria, V6TEMP = 677 C day, effec-tively subdivided N2 observations into cooler (2000)(N3) and warmer (2001) (TN4) soil temperature datasets. Reduced soil temperatures during emergenceperiods can increase time required for seedling emer-gence (Hayhoe et al., 1993), which can potentiallydecrease establishment via longer seed exposure timeto soil pathogens. Node 3 data split on the basis ofV6AFP = 1.1 m3 m3 day where sites with V6AFPvalues below or equal to this split value had the low-est average COUNT in the tree model. Sites in TN2had a marginally better average COUNT than TN1.

For each V6AFP split in the tree model, COUNTaverages were exclusively lower for sites with V6AFPvalues lower than the associated split value, relativeto those for sites with V6AFP values above the split


value. Stand establishments can be reduced under con-ditions of cool soil temperatures and high soil wa-ter contents (Herner, 1986). These results suggest thatV6AFP and to a lesser extent V6AFPDAY (domi-nant surrogate split variable in tree model) are po-tentially important indicators of establishment risk forclay loam soils in eastern Ontario. Evidently, PR andROT were not as important statistically as AFP onplant establishment in the tree model.

Table 7 summarizes how COUNT observations foreach treatment were delineated on the basis of regres-sion tree terminal nodes. Observations in TN1 andTN2 are exclusively 2000 data. Approximately, 78%of TN1 observations occur in WNTCC. About 63%of all TN2 observations were in no-till, and approxi-mately 31% of TN2 observations were in WTC andWTCC. For TN3, about 59% of the data were from2001 and every treatment had observations representedwithin it. Modal TN3 observations for 2001 originatedexclusively from no-till data sets indicating greater po-tential for poorer plant establishment, relative to tilledplots, during the more optimal planting and plant es-tablishment conditions in 2001. TN4 contained 2001data exclusively, but no clear treatment associationswere evident. Approximately 75 and 50% of all (bothyears) respective BTC and BTCC observations werein TN5. Interestingly, 100% of WTCC 2001 data

Table 7Number of COUNT observations (large font numbers) that occur in each terminal node (TN) in Fig. 7 for each corn management treatmentfor both years of observation

Bolded and underscored large font numbers = modal nodal group for each respective treatment/year.Double horizontal line = delineation of terminal nodes with below site average (above line) and above site average (below line) COUNTvalues.Smaller font values = average and standard deviations () of total residual spring soil N for respective sites (kg ha1).

occurred in TN5, albeit 88% of WTCC 2000 dataoccurred in TN2.

The average spring total residual soil N was cal-culated for each subset of observations identified inTable 7. Likely due to wetter pre-plant conditionsin 2000, average 2000 residual total N was in allcases lower, relative to 2001, for respective treatments.Although not tested, the formative impact of totalresidual soil N on plant establishment was likely notstrong.

While no-till can be desirable with respect tominimizing soil degradation, reducing erosion, andsequestering of carbon, for example (Carter, 1994),these results suggest that fall mouldboard plowingand spring cultivation fostered better plant establish-ment on these cool and moist clay loam soils thatdominate much of eastern Ontario. For instance, 63%of BTC observations during 2000 occurred in areasthat maintained the highest daily AFPs. The bestmanaged tilled plots were the only plots that did nothave modal nodal observations (Table 7) for 2000 and2001 in TN1 and TN2. There is generally higher riskof poor plant establishment in the worst managedtilled plots, relative to the best managed tilled plots,irrespective of the potential for the worst managedplots to achieve relatively good plant establishmentduring drier conditions.


The essential findings above are supported by plotsof estimated daily AFPs at the in situ O2 measure-ment sites (Fig. 8). On average, AFPs at the no-tillsites between planting and V6 were lower, relativeto tilled sites. Worst managed tilled estimates tendedon average to have lower AFPs than best managedtilled plots. The preferential trafficking that occurredover the worst managed plots during conditionswhen farmers in the region often work their fieldsaugmented the potential of the soil to achieve lowerrelative AFPs by increasing surface bulk densitiesas well as reducing air/water transmission propertiesthrough surface sealing/smearing of the soil surface(Wang et al., 1985; G.C. Topp, unpublished data).With respect to bulk densities, relative soil com-paction (measured/estimated maximum) was notablyhigher in worst managed plots for specific tillagetreatments, compared to respective best managedplots (Table 8). Moreover, no-till had higher averagerelative compaction ratios than tilled plots. It shouldbe noted that maximum bulk densities for these soilsare achieved at water contents around 0.22 Mg Mg1,whereas preferential trafficking was performed ataround a water content of 0.35 Mg Mg1; thus traf-ficking soils during wet, but not maximum bulk den-sity optimal conditions, achieved undesirable effects(smearing and sealing of surface) on surface soilaeration and strength. Correlating evidence of soilcompaction over worst managed plots, relative to bestmanaged plots, was also presented by Lapen et al.(2002a) where it was found that highest observed PR

Table 8Rounded average and standard deviations (parenthesis) of relative compaction for plots for 2000 and 2001Plot Planting (2000) Planting (2001) R6 (2000) R6 (2001)No-till

BNTCC 0.91 (0.02) 0.84 (0.05) 0.91 (0.02) 0.84 (0.05)BNTC 0.85 (0.02) 0.91 (0.02) 0.85 (0.02) 0.91 (0.02)WNTC 0.92 (0.01) 0.88 (0.05) 0.92 (0.01) 0.88 (0.05)WNTCC 0.95 (0.01) 0.94 (0.02) 0.95 (0.01) 0.94 (0.02)

TillBTCC 0.82 (0.02) 0.82 (0.04) 0.85 (0.02) 0.83 (0.04)BTC 0.80 (0.01) 0.83 (0.02) 0.82 (0.01) 0.85 (0.02)WTC 0.84 (0.02) 0.85 (0.04) 0.90 (0.02) 0.90 (0.04)WTCC 0.86 (0.02) 0.84 (0.02) 0.91 (0.02) 0.88 (0.02)

Values are averages of observed bulk densities divided by an estimated maximum bulk density (approximately 1.56 Mg m3). Bold values= highest ratios for given year, growth stage, and tillage treatment. N = 24 observations per value. Note: no-till bulk densities wereexclusively R6 values as they were statistically indifferent from those at planting.

values recorded over corn plots (0.050.10 m depth)were predominately associated with worst managedplots.

3.5. Growing season LLWR versus final yieldrelationships

The R2 of the selected regression tree model (Fig. 9)was 0.88 with the lowest observed CVRE in thetree-building process. All YIELD data were initiallysubdivided by R6-R1AFPDAY into lower yielding(>11 days) and higher yielding (11 days) groups.Given that V6AFP processes were linked to COUNT,the correlation between YIELD and V6AFPDAY, andV6AFPDAY and R6-R1AFPDAY was 0.52 and0.67 (significance 0.05 level), respectively. The domi-nant N1 surrogate variable (R6AFPDAY) underscoresassociations of growing season AFP conditions onYIELD. Node 2 observations were subdivided byyears in corn. The YIELD average for 1 year corn ob-servations was approximately 1.6 t ha1 greater thanthat for the continuous corn group. Node 2 representedmodest surrogate split variable improvement scoresand absolute correlation coefficients between YIELDand independent variables for N2 observations were

164 D.R. Lapen et al. / Soil & Tillage Research 78 (2004) 151170AF

P (m

3 m-3 )

0.0

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6

7AFP 2000AFP 2001PR 2000PR 2001

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(MPa

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7BNTC

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(m3 m

-3 )

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(MPa

)

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(m3 m

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(m3 m

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Fig. 8. Estimated daily AFP and PR trends at in situ O2 measurement sites for 2000 and 2001.


TN6Avg.=5.6 (0.7)

N=28

TN4Avg.=4.3 (0.8)

N=13

N3: V6PR -41.5Avg.=5.2 (0.9)

N=41V6PRDAY6 (70%)

TN7Avg.=5.8 (0.8)

N=15

TN5Avg.=4.8 (0.3)

N=7

N5: V6PR -44.5Avg.=5.5 (0.9)

N=22V6AFP1.2 (54%)

TN8Avg.=7.3 (0.6)

N=32

TN9Avg.=8.2 (0.7)

N=8

N6: R6AFP 25.5Avg.=7.5 (0.7)

N=40V6AFP7.2 (87%)

N4: R6-R1AFP4.5Avg.=6.8 (1.2)

N=62R6AFP9.4 (68%)

N2: ROT=0Avg.=6.2 (1.4)

N=103R6PRDAY>72 (26%)

TN1Avg.=0.3 (0.5)

N=4

TN3Avg.=4.2 (0.5)

N=9

TN2Avg.=2.9 (0.5)

N=9

N8: R6-R1AFPDAY15.5Avg.=3.6 (0.8)

N=18V6PR>-60.5 (35%)

N7: R1AFP -2.0Avg.=3.0 (1.5)

N=22V6AFP-2.2 (66%)

N1: R6-R1AFPDAY11Avg.=5.6 (1.8)

N=125R6AFPDAY


was 5 (9) and 27 (13) days, respectively, and the cor-relation between V6AFPDAY and R6-R1AFPDAYwas 0.67 (significance 0.05 level)). The top five vari-ables (out of 24 independent variables) in the treemodel, in order of standardized importance were:R6AFP (100%), R6-R1AFPDAY (95%), R6-R1AFP(93%), V6AFP (79%), and R6AFPDAY (73%). Inseveral cases, indicators including R1-to-R6 condi-tions effectively delineated 2000 (wetter and loweryielding) and 2001 (drier and higher yielding) data.

Table 9 indicates that TN1 observations wereexclusively in WNTCC (2000), while 78% of TN2observations were in BNTCC (2000). Terminal node3 observations were dominated by WTCC (2000),suggesting that surface compaction/sealing and con-tinuous corn can potentially restrict aeration of con-ventional tilled soils. The TN4 group represented thelowest average yields for 2001, which were primarilyin BNTCC (31% of observations) and WNTCC (54%

Table 9Number of YIELD observations that occur in each terminal node (TN) in Fig. 9 for each corn management treatment for both years ofobservation

Bolded and underscored large font numbers = modal nodal group for each respective treatment/year.Double horizontal line = delineation of terminal nodes with below site average (above line) and above site average (below line) YIELDvalues.Smaller font values = average and standard deviations () of total residual spring soil N for respective sites (kg ha1).Note: 2 missing data for BNTCC for 2001.

of observations). For lower occurrences of exceedinglater season daily AFP thresholds (N1 split), thesetillage/cropping practices were associated, in a rel-ative sense, with lower yielding corn, as apparentlyassociated with soils of higher relative strength earlyin the growing season. Negative spatial associationsbetween PR patterns and corn yield/plant establish-ment at the site were documented by Turpin et al.(2003) and Lapen et al. (2001); higher PR areas withhigher relative water contents were lower yieldingsites. Seed soil contact after planting was also prob-lematic in these harder soil areas as noted by farmmanagers. Terminal node 5 observations were exclu-sively located in WTC (2000), where planting-to-V6PR was generally higher than that for the TN7 groupof data (primarily BNTC (2000) and WNTC (2000)data). For TN6, a majority of observations occurredin BTCC (2000, 2001) (57% of all observations) andWTCC (2001) (29% of observations).


Terminal nodes 7, 8, and 9 represented groups ofobservations, exclusively for corn in rotation, withYIELD averages above the total site-wide YIELD av-erage of 5.6 t ha1. Residual spring total N was notdramatically different between continuous and cornin rotation for the treatments for both years of study.However, nitrate reduction dramatically increases atAFP values of 0.1 m3 m3 (Pilot and Patrick, 1972)and lower soil temperatures, lower crop heat units, andleaching of N in 2000 likely constrained final yields(Turpin et al., 2003).

Vyn and Raimbault (1993) noted that for long-termcorn monoculture soils in no-till, higher soil resistance,higher bulk densities, and lower proportions of fine ag-gregates were observed relative to mouldboard plow-ing. Wang et al. (1985) noted that monoculture of cornfor >5 years usually produced marked compaction at0.100.25 m depth on clayey soils. Terminal node 7was represented primarily by no-till corn in rotationobservations for both trafficking treatments (87% ofobservations). Terminal node 8 effectively representedthe highest yields of 2000 (in BTC where AFP con-straints on aeration were not considerable) and aboveaverage yields for 2001. Thus, even for drier growingseasons, AFP appeared to be statistically importantwith respect to crop performance even for traffickedtilled plots. The highest nodal YIELD average was pri-marily composed of BTC (2001) observations whereAFP conditions over the entire growing season wereeffectively highest. The essential findings in Table 9

BNTCC BNTC BTC BTCC WNTC WNTCC WTC WTCC

R6AF

P (m

3 m

-3 )

and

R6A

FPD

AY

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)

-100

102030405060708090

100110

R6AFP (2000) R6AFPDAY (2000) R6AFP (2001) R6AFPDAY (2001)

N=8 sites per plotper year observation.

Fig. 10. Average and standard deviation of planting-to-R6 LLWR AFP indicators for each plot for 2000 and 2001.

are supported by estimated AFP and PR growing sea-son trends at the in situ O2 measurement sites (Fig. 8),where it was found that the predicted BTC daily AFPsfor 2000 and 2001 never dropped below the aerationAFP value, implying that the BTC site, relative to theother plot sites, had most favorable aeration condi-tions. Of all plots, potential aeration constraints weremost strongly expressed at WNTCC.

Fig. 10 illustrates differences in planting-to-R6stage LLWR AFP indicators for the plots. No-till plotsfor respective traffic treatments exhibited greater po-tential for low AFP relative to respective conventionaltillage and cropping system counterparts. Moreover,75% of the continuous corn versus corn in rotationcomparisons for respective treatments for both yearsshowed that continuous corn plots had larger percent-ages of days where daily AFP was less than thresholdvalues, and also generally smaller cumulative dif-ferences between daily AFP and AFP thresholds.Nevertheless, these findings must be interpreted incontext of water uptake (or lack of it) by affectedcrops impacting AFP over the growing season, iden-tified context dependent soil physical limitations overthat period, and AFP controls on establishment.

3.6. Overview of the LLWR approach

The corn growth stage LLWR indicator approach,employing dynamic changes in bulk density andsoil strength over the growing season (Lapen et al.,


in press), was effective at identifying potential soilquality constraints to corn growth as a result of var-ious tillage, trafficking, and cropping systems. Thestatistical analyses consistently reinforced dominantcontext-dependent (spatially and temporally specific)positive associations between daily AFP and corngrowth properties, and negative associations betweensoil strength and corn properties.

In situ O2 concentration/soil water content mea-surements indicated that no-till soils had lower aver-age AFPs and O2 concentrations than respective tilledplots for both years of study. Potential trafficking ef-fects on aeration properties were most evident in no-tillrelative to till; worst managed no-tilled plots hadlower AFP and O2 concentration averages than re-spective best managed no-till plots for both years ofstudy. Overall, the best managed conventional tilledsoils had most favorable aeration properties.

Corn establishment limitations observed for drierand wetter planting-to-V6 stage soil conditionswere explained primarily from LLWR variables ex-pressing the cumulative difference between estimateddaily AFPs and LLWR aeration thresholds betweenplanting and V6 stage (best early season indicator).AFP was positively related to the establishment. Soilstrength factors were not found to be as statisticallyimportant as aeration constraints in plant establish-ment for the clay-silty loam field soils, although soilstrength indicators reflecting higher soil densities havebeen found to be spatially associated with aerationproblem areas (intrinsically higher water contents)at the site (Turpin et al., 2003). Higher risk (belowaverage establishments) management practices duringwetter conditions were found to be most stronglyassociated with (i) no-tilling and (ii) worst managedconventional tilling. For drier conditions, higherrisk management practices were predominately worstmanaged no-tilling. Tillage reduced the risk of lowerplant populations during drier early season conditions,but was less effective at increasing AFPs of traffickedsoils.

The LLWR indicators that best explained yieldvariability were based primarily on soil AFP condi-tions over many different primary (V6, R1, and R6)corn growth stages. Where cumulative differencesbetween predicted AFP and aeration thresholds wererelatively small or negative, and/or where the numberof days the daily AFP was lower than the aeration

limit was greater, yields were generally lower. Soilstrength (planting-to-V6) (negative PR versus YIELDrelationships) and years in corn (lower yields incontinuous corn) were statistically relevant factorspredicting yield, but were considerably less importantthan LLWR AFP indicators for both years of study.For wetter conditions, lower than average yieldswere most strongly associated with (i) no-tilling (con-tinuous corn), (ii) best managed conventional tilling(continuous corn), and (iii) worst managed conven-tional tilling. For drier conditions, lower than av-erage yields were most strongly associated with (i)no-tilling (continuous corn), (ii) best managed con-ventional tilling (continuous corn), and (iii) worstmanaged tilling (continuous corn). NotwithstandingN limitations to corn growth, for clay loam soils thatdominate much of the corn growing area in easternOntario, Canada, aeration limitations, even undertile-drained fields, can be problematic with respect toyield.

4. Conclusions

The data mining analyses indicated that the mostimportant LLWR indicators of yield were those thatexpressed, at a minimum, AFP conditions for time pe-riods between R1 and R6 stage. However, the impor-tance of these yield indicators was manifested via anunknown combination of plant water uptake relation-ships (higher yielding crops have greater uptake), andthe various establishment and post-establishment soilphysical limitations to corn growth. Specific identifi-cation of cause and effect relationships requires addi-tional analyses. This work does, however, suggest thatthe LLWR has great potential as an indicator of soilquality and crop production.

Acknowledgements

Funding for this project was provided in part byOntario Corn Producers Association. We wish tothank Mark Edwards, Bryan Dow, Mark Sunohara,Patrick St. George, Ulrica Stoklas, Karine Turpin,and Robyn Auld for field, technical, and laboratorysupport.


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Least limiting water range indicators of soil quality and corn production, eastern Ontario, CanadaIntroductionMaterials and methodsStudy site and treatmentsSoil and crop measurementsLLWR approachEstimating daily soil water contentsSoil aeration, permanent wilting point, and soil strength LLWR limitsStatistical approach

Results and discussionWeather conditions for 2000 and 2001Corn establishment and yieldSoil water estimation, porosity, O2 concentrations, and LLWR threshold valuesPlanting-to-V6 stage LLWR versus plant establishment relationshipsGrowing season LLWR versus final yield relationshipsOverview of the LLWR approach

ConclusionsAcknowledgementsReferences

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