@article{sripada_farrer_weisz_heiniger_white_2007, title={Aerial color infrared photography to optimize in-season nitrogen fertilizer recommendations in winter wheat}, volume={99}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2006.0258}, abstractNote={Remote sensing in the form of aerial color infrared (CIR) photography has been shown to be a useful tool for in‐season N management in winter wheat (Triticum aestivum L.). The objectives of this study were (i) to develop a methodology for predicting in‐season optimum fertilizer N rates for winter wheat at growth stage (GS) 30 directly from aerial CIR photography and (ii) to quantify how the relationships between these optimum N rates and spectral indices respond to different levels of biomass of the wheat crop. Field studies were conducted for three winter wheat growing seasons (2002–2004) over a wide range of soil conditions across North Carolina using a split‐split plot randomized complete block design. Different planting date–seeding rate (PDSR) combinations were applied to create a range of biomass levels at GS 30. Different levels of N were applied at GS 25 (N25) to create a range of N supply and winter wheat radiance, and at GS 30 (N30) to measure grain yield response to N30. Aerial CIR photographs were obtained at each site at GS 30 before N applications. Significant biomass response to PDSR and yield response to N25 and N30 were observed. Optimum N30 ranged from 0 to 124 kg ha−1 with a mean of 55 kg ha−1. Better prediction of optimum N30 rates were obtained with spectral indices calculated relative to high‐N reference strips compared to absolute bands or spectral indices. Biomass measured at GS 30 influenced the strength of the relationship between optimum N30 and spectral indices. When the GS‐30 biomass was >1000 kg ha−1, the best predictor of optimum N30 (R2 = 0.85) was a quadratic model based on measured winter wheat radiance relative to mean radiance in the G band for the high N reference strip (Rel GS).}, number={6}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Sripada, Ravi P. and Farrer, Dianne C. and Weisz, Randy and Heiniger, Ronnie W. and White, Jeffrey G.}, year={2007}, pages={1424–1435} }
 @article{williams_crozier_white_sripada_crouse_2007, title={Comparison of soil nitrogen tests for corn fertilizer recommendations in the humid southeastern USA}, volume={71}, ISSN={["0361-5995"]}, DOI={10.2136/sssaj2006.0057}, abstractNote={Environmental concerns about increasing NO3 levels in watersheds in North Carolina and elsewhere indicate the need for better N fertilizer management. Nitrate levels might be reduced if N rates could be adjusted based on field‐ or site‐specific knowledge of corn (Zea mays L.) response to N fertilization. Currently, there is no effective soil N test for the humid southeastern USA. This study was conducted to compare three soil N tests for practicality, precision, and ability to correlate with economic optimum N rate (EONR) and fertilizer response on southeastern U.S. soils. The soil N tests were the Illinois soil N test (ISNT), the gas pressure test (GPT), and the incubation and residual N test (IRNT). Soil samples were collected from the sites of 16 N‐response trials from 2001 to 2003 where different mineralizable and residual N levels were expected. The ISNT was determined to be the most practical test because it was the easiest to perform and could be completed in 1 d. The ISNT and GPT had better precision (lower CV) than the IRNT (9 and 13 vs. 61%, respectively). All three tests were related to EONR; ISNT had the strongest linear relationship (r2 = 0.90) when consideration was restricted to sites on mineral soils. The ISNT and GPT were related to delta yield (maximum yield minus check yield; r2 = 0.49 and 0.60, respectively) and fertilizer response (r2 = 0.31 and 0.51, respectively). These results indicate the potential of the ISNT and GPT to account for mineralizable and residual soil N levels and thus improve current corn N recommendations in the humid southeastern USA.}, number={1}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={Williams, Jared D. and Crozier, Carl R. and White, Jeffrey G. and Sripada, Ravi P. and Crouse, David A.}, year={2007}, pages={171–180} }
 @article{williams_crozier_white_heiniger_sripada_crouse_2007, title={Illinois soil nitrogen test predicts southeastern US corn economic optimum nitrogen rates}, volume={71}, ISSN={["0361-5995"]}, DOI={10.2136/sssaj2006.0135}, abstractNote={An accurate and quick soil N test is needed for N fertilizer recommendations for corn (Zea mays L.) for the humid southeastern USA. The Illinois soil N test (ISNT) has been used to distinguish fertilizer-responsive from unresponsive sites in Illinois. We determined relationships between economic optimum N rates (EONR) and ISNT levels in representative southeastern soils in 35 N-response trials in the Piedmont (n = 4) and Middle (n = 8) and Lower (n = 23) Coastal Plains of North Carolina from 2001 to 2004. The ISNT was strongly correlated with EONR for well or poorly drained sites (r 2 = 0.87 [n = 20] and 0.78 [n = 10], respectively); data were insuffi cient for establishing correlations for very poorly drained or severely drought-stressed sites. Expressing ISNT on a mass per unit volume basis vs. EONR improved the correlations slightly (r 2 = 0.88 and 0.79 for well and poorly drained sites, respectively), but these improvements would not justify the necessary soil bulk density determinations. Regressions of ISNT vs. minimum, average, and maximum EONR based on different N-fertilizer cost /corn price ratios (11.4:1, 7.6:1, and 5:1, respectively) showed strong correlations with EONR for well-drained sites (r 2 = 0.77, 0.87, and 0.87, respectively) and poorly drained sites (r 2 = 0.84, 0.78, 0.70, respectively). The ISNT–EONR correlations were different among the cost/price ratios for well-drained sites, but not different for poorly drained sites. Because ISNT predicted EONR robustly to different cost/price ratios, ISNT has the potential to modify or replace current N recommendation methods for corn. Abbreviations: EONR, economic optimum nitrogen rate; HM, humic matter; ISNT, Illinois soil nitrogen test; RYE, realistic yield expectation.}, number={3}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={Williams, Jared D. and Crozier, Carl R. and White, Jeffrey G. and Heiniger, Ronnie W. and Sripada, Ravi P. and Crouse, David A.}, year={2007}, pages={735–744} }
 @article{weisz_sripada_heiniger_white_farrer_2007, title={In-season tissue testing to optimize soft red winter wheat nitrogen fertilizer rates: Influence of wheat biomass}, volume={99}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2006.0112}, abstractNote={In the southeastern USA, soft red winter wheat (Triticum aestivum L.) N fertilizer recommendations are based on growth stage (GS) 30 tissue testing and models that assume that the relationship between tissue N concentration (Ncon) and optimum N fertilizer rates (MaxN30) is stable across fields differing in GS‐30 biomass. However, previous research has indicated this may not be the case. Consequently, it was critical to re‐evaluate these models. Using a split‐split plot design, six experiments were conducted in North Carolina between 2002 and 2004. Main plots were planting date–seeding rate combinations that produced wheat with different GS‐30 biomass. Subplots and sub‐subplots were five N rates applied at GS‐25 and GS‐30, respectively. Wheat yield was responsive to fertilizer N at all site‐years. The overall relationship between MaxN30 and Ncon was weak (r2 = 0.43). The relationship between MaxN30 and N uptake (Ncon × biomass) was weaker (r2 = 0.27). However, when the data were divided into different biomass classes, the overall model improved (R2 = 0.75). For biomass < 340 kg ha−1, the Ncon at which no additional N fertilizer was required (Ncritical) was 70.0 g N kg−1. As biomass increased, Ncritical decreased to 33.2 g N kg−1. Intermediate classes had slopes of MaxN30 versus Ncon and Ncritical values that were similar to those previously reported. This study indicates that to use tissue testing to determine N fertilizer recommendations across a range of GS‐30 biomass conditions requires information regarding dry matter biomass.}, number={2}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Weisz, Randy and Sripada, Ravi P. and Heiniger, Ronnie W. and White, Jeffrey G. and Farrer, Dianne C.}, year={2007}, pages={511–520} }
 @article{sripada_heiniger_white_meijer_2006, title={Aerial color infrared photography for determining early in-season nitrogen requirements in corn}, volume={98}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2005.0200}, abstractNote={In‐season determination of corn (Zea mays L.) N requirements via remote sensing may help optimize N application decisions and improve profit, fertilizer use efficiency, and environmental quality. The objective of this study was to use aerial color‐infrared (CIR) photography as a remote‐sensing technique for predicting in‐season N requirements for corn at the V7 growth stage. Field studies were conducted for 2 yr at three locations, each with and without irrigation, in the North Carolina Coastal Plain. Experimental treatments were a complete factorial of four N rates at planting (NPL) and five N rates at V7 (NV7). Aerial CIR photographs were taken at each of the locations at V7 before N application. Optimum NV7 ranged from 0 to 207 kg N ha−1 with a mean of 67 kg N ha−1. Significant but weak correlations were observed between optimum NV7 rates and the band combinations relative green, Relative Green Difference Vegetation Index, and Relative Difference Vegetation Index as measured in CIR photos. High proportions of soil reflectance in the images early in the corn growing season (V7) likely confounded our attempts to relate spectral information to optimum NV7 rates. The primary obstacles to applying this technique early in the season are the use of relative digital counts or indices that require high‐N reference strips in the field and strong background reflectance from the soil. When the NPL treatments that were nonresponsive to NV7 (i.e., optimum NV7 = 0) were removed from the analysis, the normalized near infrared, the Green Difference Vegetation Index, the Green Ratio Vegetation Index, and the Green Normalized Difference Vegetation Index were the best predictors of optimum NV7 rate (r2 = 0.33).}, number={4}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Sripada, Ravi P. and Heiniger, Ronnie W. and White, Jeffrey G. and Meijer, Alan D.}, year={2006}, pages={968–977} }
 @article{sripada_heiniger_white_crozier_meijer_2006, title={Attempt to validate a remote sensing-based late-season corn nitrogen requirement prediction system}, ISBN={1543-7833}, journal={Crop Management}, author={Sripada, R. P. and Heiniger, R. W. and White, J. G. and Crozier, C. R. and Meijer, A. D.}, year={2006}, pages={1} }