Author
CAMBERATO, J. - Purdue University | |
SHAFER, M. - Purdue University | |
CARTER, P. - Dupont Pioneer Hi-Bred | |
FERGUSON, R. - University Of Nebraska | |
FERNANDEZ, F. - University Of Minnesota | |
FRANZEN, D. - North Dakota State University | |
Kitchen, Newell | |
LABOSKI, C. - University Of Wisconsin | |
NAFZIGER, E. - University Of Illinois | |
NIELSON, R. - Purdue University | |
SHANAHAN, J. - Fortigen | |
SAWYER, J. - Iowa State University |
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only Publication Acceptance Date: 9/6/2017 Publication Date: 10/22/2017 Citation: Camberato, J.J., Shafer, M., Carter, P.R., Ferguson, R.B., Fernandez, F.G., Franzen, D.W., Kitchen, N.R., Laboski, C.A., Nafziger, E.D., Nielson, R.L., Shanahan, J., Sawyer, J.E. 2017. Soil and environmental factors affecting internal N efficiency of maize. ASA-CSSA-SSSA Annual Meeting, October 22-25, 2017. Tampa, Florida. Paper #108990. Interpretive Summary: Technical Abstract: The inverse of internal N efficiency (IE), N needed per quantity of grain produced, is used in yield-goal based N recommendations to determine the target quantity of N needed to attain a chosen maize yield. Often the value of IE is considered static, irrespective of environment. Evaluation of 47 site-years of data across the U.S. Corn Belt demonstrated variation in IE at the economically optimum N rate (IEE). IEE ranged from 38 to 73 kg dry grain/kg plant N with a mean and standard deviation of 54 and 7 kg grain kg/kg N. A linear model based on soil properties determinable at planting (texture, organic matter, and pH) explained only 16% of the variation in IEE. Just prior to sidedress at growth stage V9, 38% of the variation in IEE was explained by soil texture, soil nitrate-N, and NDVI. Considering all variables at the end of the season, including soil, weather, and crop parameters, only about 60% of the variation in IEE was explained by linear models. Unpredictable variation in IEE introduces meaningful variation in yield-goal based N recommendations. |