|Vories, Earl - Earl|
Submitted to: Asian Conference on Precision Agriculture
Publication Type: Abstract Only
Publication Acceptance Date: 3/31/2013
Publication Date: 6/25/2013
Citation: Tremblay, N., Bouroubi, M.Y., Belec, C., Mullen, R.L., Kitchen, N.R., Thomason, W.E., Ebelhar, S.A., Mengel, D.B., Raun, W.R., Francis, D.D., Vories, E.D., Ortiz-Monasterio, I. 2013. Adjustment of corn nitrogen in-season fertilization based on soil texture and weather conditions: a Meta-analysis of North American trials [Abstract]. Asian Conference on Precision Agriculture. 52-53. Interpretive Summary:
Technical Abstract: Soil properties and weather conditions are known to affect soil nitrogen (N) availability and plant N uptake. However, studies examining N response as affected by soil and weather sometimes give conflicting results. Meta-analysis is a statistical method for estimating treatment effects in a series of experiments to explain the sources of heterogeneity. In this study this technique was used to examine the influence of soil and weather parameters on N responses of corn (Zea mays L.) across 51 studies involving the same N rate treatments which were carried out in a diversity of North American locations between 2006 and 2009. Results showed that corn response to added N was significantly greater in fine-textured soils than in coarse-textured soils. A new metric called “abundant and well-distributed rainfall” and, to a lesser extent, accumulated corn heat units enhanced N response. At high N rates corn yields increased by a factor of 1.6 (over the unfertilized control) in coarse-textured soils and 2.7 in fine-textured soils. Subgroup analyses were performed on the fine-textured soil class based on weather parameters. Rainfall patterns had an important effect on N response in this soil texture class, with yields being increased 4.5-fold by in-season N fertilization under conditions of abundant and well-distributed rainfall. These findings could be useful for developing N fertilization algorithms that would allow for N application at optimal rates taking into account rainfall pattern and soil texture, which would lead to improved crop profitability and reduced environmental impacts.