Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

60-5 Soil and Environmental Factors Affecting Internal N Efficiency of Maize.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Outcomes of an Innovative Public-Industry Corn Nitrogen Research Partnership

Monday, October 23, 2017: 10:28 AM
Marriott Tampa Waterside, Room 2

James Camberato1, Matt Shafer2, Paul R. Carter3, Richard B. Ferguson4, Fabián G. Fernández5, David Franzen6, Newell R Kitchen7, Carrie A.M. Laboski8, Emerson D. Nafziger9, Robert L. Nielsen1, John Shanahan10 and John E. Sawyer11, (1)Agronomy, Purdue University, West Lafayette, IN
(2)Agronomy Dept., Purdue University, West Lafayette, IN
(3)DuPont Pioneer, Johnston, IA
(4)Department of Agronomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE
(5)Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN
(6)North Dakota State University, Fargo, ND
(7)243 Agricultural Engineering Bldg, USDA-ARS, Columbia, MO
(8)Soil Science, University of Wisconsin-Madison, Madison, WI
(9)W301 Turner Hall, 1102 S. Goodwin, University of Illinois-Urbana-Champaign, Urbana, IL
(10)Fortigen (Tetrad Corp.), Lincoln, NE
(11)Department of Agronomy, Iowa State University, Ames, IA
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 grain dry matter per kg plant N with a mean and standard deviation of 54 and 7 kg grain kg-1 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.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Outcomes of an Innovative Public-Industry Corn Nitrogen Research Partnership