Iowa Falls, IA, United States
Iowa Falls, IA, United States

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Kyveryga P.M.,On Farm Network | Tao H.,On Farm Network | Morris T.F.,University of Connecticut | Blackmer T.M.,University of Connecticut
Agronomy Journal | Year: 2010

Past studies on N management in corn (Zea mays L.) have shown insurmountable difficulties predicting N supply from soil and fertilizer sources. New tools are needed for collecting feedback about the N status of corn from large areas at a low cost. We used adaptive management to compare major N management practices by organizing many grower groups across Iowa and conducting a guided corn stalk nitrate survey of 683 fields in 2006 and 824 in 2007. Aerial images of corn canopy taken in late August were used to select three sampling areas, one within each predominant soil type within a field. Ordinal logistic regressions (OLRs) were used to calculate the cumulative probability of a stalk sample to test in a higher stalk test category and to identify important factors affecting stalk test values. The analyses revealed significant differences in corn N status among management categories based on combinations of forms and timing of fertilizer and manure applications, previous crop, and soil drainage classes. In both years, fields receiving spring anhydrous ammonia (AA) were more likely to test higher than fields receiving fall liquid swine (Sus scrofa) manure (LSM), spring urea-ammonium nitrate (UAN) solution, or fall AA. The large amounts of rainfall in June 2006 and cumulative spring rainfall in 2007 significantly decreased the likelihood to test in a higher stalk test category. A guided corn stalk nitrate survey as part of an adaptive management program allows documenting relatively efficient management practices within large areas of spatially variable soils and rainfall patterns. © 2010 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 | Morris T.F.,University of Connecticut
Journal of Soil and Water Conservation | Year: 2011

Precision agriculture technologies offer potential economic and environmental benefits from site-specific management of nitrogen (N) fertilizer and animal manure sources for corn (Zea mays L.). However, lack of knowledge and reliable methodology for developing and evaluating site-specific N fertilizer recommendations are the major obstacles for realizing these potential benefits. The objective of this study was to evaluate corn N status at the field scale and across many fields using late-season digital aerial imagery and the end-of-season corn stalk nitrate test in large-scale on-farm evaluation studies. About 30 groups of farmers, lead by agronomists and crop consultants, were formed across Iowa to evaluate different N management practices. Late-season color digital aerial imagery and digital soil maps were used to guide the collection of the corn stalk nitrate test samples within 683 cornfields in 2006, 824 fields in 2007, and 828 fields in 2008. Four areas-one from each of the three predominant soil types and one within a target-deficient area-were sampled in each field. Multilevel binary logistic regressions were used to quantify the relationship between green reflectance of the corn canopy and corn N status, expressed as deficient and sufficient (a combination of marginal, optimal, and excessive categories of the corn stalk nitrate test), within and across the fields. Percentages of areas within fields with deficient and sufficient N status were estimated using distributions of pixel counts of green reflectance of the corn canopy. Multiple regression analysis was used to identify factors affecting percentage-deficient area within the fields. Results showed that N management category (a combination of N form and timing of application) and early season rainfall (May, June, or cumulative from March through June) had the largest effects on percentage-deficient area. Fields with liquid swine manure applied in the fall or urea-ammonium nitrate solution applied in the spring (before planting) or urea-ammonium nitrate solution applied at sidedress had larger areas of N deficiency than fields with anhydrous ammonia applied in the spring. Larger early season rainfalls also increased percentage-deficient area during each year. The results of large-scale evaluations can be used to develop more accurate site-specific N recommendations based on knowledge of differences between management practices and effects of soil properties and rainfall on N status within fields. Future evaluations can identify areas that persistently have excessive N status and quantify potential N fertilizer reductions within those areas or fields. © 2011 Soil and Water Conservation Society. All rights reserved.


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 | 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.


Kyveryga P.M.,On Farm Network | Blackmer T.M.,On Farm Network
Precision Agriculture | Year: 2014

Nitrification inhibitors (NI) can be used with liquid swine manure (LSM) to decrease potential NO3 losses, but knowledge specifying when and where NI can increase corn (Zea mays L.) yields is limited. Eleven on-farm evaluation trials (OET) were conducted in 2009 and 15 in 2010 to identify site-specific factors for using Instinct (an encapsulated form of nitrapyrin) with LSM in Iowa. Farmers injected LSM in the fall in at least three field-long strips with and without NI. Yield responses (YR) to NI were calculated by dividing yield monitor data into 50-m cells within each field. Hierarchical models were used to estimate predictive probabilities of profitable YR for two categories of monthly average rainfall and soil drainage. On average, NI produced no YR in relatively normal 2009 and a 0.15 Mg ha-1 YR in extremely wet 2010. The NI did not change late-season corn N status but half of corn stalk nitrate test (CSNT) samples were N deficient in 2009 and about 65 % in 2010. Fields receiving >90 cm March through August rainfall in 2010 were predicted 65 % more likely to have economic YR (>0.13 Mg ha-1) than fields receiving <90 cm rainfall. Within-field variability in YR was about four times greater than among-field variability, but within field-level factors had no significant effects on YR. The NI effects may not have lasted long enough to increase yields across all OET and predictive probabilities suggest that NI may produce profitable YR only when spring and summer rainfall exceed the long-term averages by more than 40 %. © 2013 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.


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).

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