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Prairie City, IA, United States

Kyveryga P.M.,On Farm Network | Blackmer T.M.,On Farm Network | Caragea P.C.,Iowa State University
Agronomy Journal | Year: 2011

Despite growing interests in variable-rate nitrogen (VRN) fertilizer applications, we still lack basic knowledge and practical methodology for identifying major factors that can be used to guide VRN application to corn (Zea mays L.). The objective was to develop a methodology for identifying a predictable relationship between economic yield response (YR) to N and commonly measured soil and terrain attributes in the presence of spatial dependence. Six 30-ha no-till fields in central Iowa were studied during 6 yr. Urea-ammonium nitrate solution was sidedressed at 112 and 140 kg N ha-1 in alternating strips replicated from 10 to 22 times. Yield responses to the high rate were calculated in a 20 by 25 m grid pattern and classified into profitable and nonprofitable categories within each field. Autologistic models were used to identify which (if any) of the following factors economically affected YR: elevation, apparent soil electrical conductivity (ECa), slope, topographic wetness index (TWI), or digital soil map units. Significant effects of some of the factors were found within 8 of 15 site-years. Within five of these site-years, well-drained areas with lower ECa and TWI, and higher elevation and slope had the higher probability of profitable YR, but these effects were not stable over time. Within the proposed methodology, a high spatial resolution of YR is used that increases the ability to identify areas profitable to N, and farmers can explore VRN possibilities by applying a small fertilizer increment below or above a uniform optimal rate in many alternating strips across fields. © 2011 by the American Society of Agronomy.

Zhang J.,Temple University | Blackmer A.M.,Iowa State University | Blackmer T.M.,On Farm Network | Kyveryga P.M.,On Farm Network
Communications in Soil Science and Plant Analysis | Year: 2010

Nitrogen (N) applied in bands across cornfields often induces differences in plant height, leaf color, and growth stage of corn (Zea mays L.). Especially during wet springs, plants growing immediately over the bands are often noticeably taller and greener for a short period. Plants growing between the bands experience N deficiency until their roots reach the bands. The impacts of such short periods of N deficiency on plant early growth have received little attention. We studied the effects of tracks left by fertilizer applicator on corn growth stage, plant height, and leaf chlorophyll meter readings (CMRs) in a field where conditions seemed favorable for a fertilizer-induced advancement in growth stage. Measurements showed that the reduced plant height or leaf color attributable to a temporary N deficiency was mainly associated with the delay of growth stages and might have little influence on final grain yield. © Iowa State University and Iowa Soybean Association.

Kyveryga P.M.,On Farm Network | Caragea P.C.,Iowa State University | Kaiser M.S.,Iowa State University | Blackmer T.M.,On Farm Network
Agronomy Journal | Year: 2013

Current systems for developing N recommendations for corn (Zea mays L.) lack methods to quantify the effects of factors influ- encing yield responses to N and quantify the uncertainty in N recommendations. We utilized hierarchical modeling and Bayes- ian analysis to quantify the risk from reducing N to corn using on-farm observations. Across Iowa, farmers conducted 34 trials in 2006 and 22 trials in 2007. Each trial had a farmer's normal N rate alternating with a reduced rate (by about 30% less) in three or more replications. Yield losses (YLs) from reduced N were calculated at 35-m intervals. Posterior distributions were used to identify across-field and within-field factors affecting YL and to quantify the risk of economic YL (>0.31 Mg ha-1) from reducing N in unobserved fields. In 2006 (dry May and June), the economic YL for corn after soybean (C-S) was predicted to be 20% larger than that for corn after corn. Also in 2006, C-S fields with above-normal June rainfall had economic YLs 35% larger than those with below-normal June rainfall, and sidedress applications were about 20% riskier than spring applications. In 2007 for C-S, N reductions with above-normal spring rainfall were riskier than with below-normal spring rainfall. Areas with higher soil organic matter (SOM) had economic YLs about 20% smaller than those with lower SOM. Many on-farm trials can be conducted across the state and the use of the proposed statistical methodology can improve decisions on where to reduce N applications across and within fields. © 2013 by the American Society of Agronomy.

Kyveryga P.M.,On Farm Network | Blackmer T.M.,On Farm Network | Pearson R.,Southern Illinois University at Edwardsville
Precision Agriculture | Year: 2012

Using uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) status of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Late-season DAI is more accurate for identifying areas deficient in N than early-season imagery. Even so, the quantitative use of the imagery across many fields is still limited because DAI is often not radiometrically calibrated. This study tested whether spectral characteristics of corn canopy derived from normalized uncalibrated late-season DAI could predict final corn N status. Color and near-infrared (NIR) imagery was collected in late August or early September across Iowa from 683 corn fields in 2006, 824 in 2007, and 828 fields in 2007. Four sampling areas (one within a target-deficient area) were selected within each field for conducting the end-of-season corn stalk nitrate test (CSNT). Each image was enhanced to increase the dynamic range within each field and to normalize reflectance values across all fields within a year. The reflectance values of individual bands and three vegetation indices were used to predict corn N status expressed as Deficient and Sufficient (a combination of marginal, optimal, and excessive CSNT categories) using a binary logistic regression (BLR). The green reflectance had the highest prediction rate, which was 70, 64, and 60% in 2006, 2007, and 2008, respectively. The results suggest that the normalized (enhanced) late-season uncalibrated DAI can be used to predict final corn N status in large-scale on-farm evaluation studies. © 2011 The Author(s).

Kyveryga P.M.,On Farm Network | Blackmer T.M.,On Farm Network
Agronomy Journal | Year: 2012

Properly calibrated diagnostic tools are needed to evaluate the performance of different N management practices for corn (Zea mays L.). Until now, mostly controlled studies were used for such calibrations. We utilized on-farm evaluation studies to verify current and identify new N status categories using the corn stalk nitrate test (CSNT) and late-season digital aerial imagery of the corn canopy. From 2007 through 2010, producers conducted 125 trials across Iowa. Each trial had treatments of a producer's normal N rate alternated with a rate that was about one-third lower or higher. Categorical yield response (YR), expressed as profitable and unprofitable, was related to green reflectance (GR), relative green reflectance (RGR), or CSNT sampled within nine areas in each trial. Multilevel binary logistic regressions were used to estimate the probability of receiving profitable YR for a range of CSNT, RGR, and GR values. Among the three diagnostics, RGR performed slightly better but required applying at least two N rates within producers' fields. For CSNT, the identified optimal category was almost the same as that currently recommended in Iowa (700-2000 mg NO3-N kg-1), even when corn and N prices deviated from their long-term averages by 30%. Due to the uncertainty in N availability, however, the critical CSNT value for fall manure treatments was about 3000 mg NO3-N kg-1 higher than that for fall anhydrous NH3, spring urea-NH4NO3, or sidedress N. On-farm studies can be used to calibrate late-season N diagnostic tools for evaluating management practices that differ in rates, forms, and timing of N applications. Copyright © 2012 by the American Society of Agronomy.

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