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Title:Nitrogen recommendation systems, weather effects on nitrogen response, and the prediction of nitrogen response in Illinois
Author(s):Febrer, Daniel
Advisor(s):Villamil, Maria; Nafziger, Emerson D.
Department / Program:Crop Sciences
Discipline:Crop Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Nitrogen
Nitrogen response
Corn
Weather
Yield
Regression
Classification and regression tree (CART)
Maximum return to nitrogen (MRTN)
Economically optimal N rates (EONR)
Illinois
Abstract:ABSTRACT 1 Nitrogen rate determination by corn producers entails both environmental and economic risk. Over-application increases production costs and causes environmental damage, whereas under-application reduces food production and farm revenue. Several recommendation methodologies have been proposed to provide fixed N recommendations to maximize profits. The maximum return to nitrogen (MRTN) system, currently in use in Illinois and other Corn Belt states, fits an appropriate function (linear, quadratic, or quadratic + plateau) to each N response, calculates a predicted return to N at each N rate, then averages these net return responses over all responses in the database. The MRTN rate is that rate producing the predicted maximum return to N across all responses. This is a departure from previous approaches, in which yield data were typically averaged across a set of experiments to form a single response function, from which an optimum N rate was derived. Using data from N rate trials run on corn following corn and corn following soybeans at seven sites in Illinois over 10 years (1999-2008), we evaluated this approach in comparison to both the conventional approach and one using different functional forms of N response. It was determined that the logistic function is the most suitable model for corn N response in Illinois. MRTN rates derived from the logistic function did not perform better than those derived from the quadratic + plateau function. MRTN recommendations from averaged annual response curves generally resulted in higher revenue than those derived from a single response curve. ABSTRACT 2 Nitrogen application in intensive corn production systems is a source of both environmental and economic risk. Over-application of N is economically wasteful, and is a source of point and nonpoint pollution affecting the health of humans and ecosystems alike. Under-application of N decreases yield and profitability. While advances have been made in the development of guidelines for N rates, the ability to predict site-specific economically optimal N rates (EONR) that change based on expected or observed weather remains elusive. Being able to predict N response will allow producers to adjust N application to be closer to economically optimal given expected growing conditions, increasing profitability while reducing environmental impact. N rate studies were conducted at seven sites in Illinois for 10 years, from 1999 to 2008. Weather variables were evaluated for their ability to predict the parameters governing N response over the experimental period. Average precipitation in July, average soil temperature at 10 cm depth during silking, and average soil temperature at 20 cm depth during June were most predictive of N response. Early season weather variables were also evaluated for their ability to predict N response parameters. Average soil temperature at 20 cm depth during April, simulated average soil moisture at 135 cm depth during April, and average precipitation in January were most predictive of N response. However, when significant selected variables were entered into simple linear regression, use of predicted EONR for corn following soy resulted in lower revenues than the maximum return to nitrogen (MRTN) system, while results were mixed for corn following corn.
Issue Date:2015-01-21
URI:http://hdl.handle.net/2142/72812
Rights Information:Copyright 2014 Daniel Febrer
Date Available in IDEALS:2015-01-21
Date Deposited:2014-12


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