For decades, agronomists have invested time and resources to identify the optimum nitrogen (N) rates for cereal crops. The most common method for estimating the agronomic optimum N rate (AONR) is to design a field experiment with several N fertilizer rates and fit a regression model to the yield observations. Here, we concentrate on its accuracy and precision given choices of experimental design and statistical analysis. Our first finding is that the choice of functional form has a large agronomic effect on the estimate of the AONR, and this depends on the data-generating model. Our second finding is that improving the precision and accuracy of AONR estimates will demand an increase in the number of N rates and replications. Finally, we propose that using either the best-fitting model or a weighted model is preferable to always choosing either the linear-plateau (negative bias) or quadratic-plateau (positive bias) models.
|Journal||Agricultural and Environmental Letters|
|State||Published - 2022|
Bibliographical noteFunding Information:
We would like to acknowledge the comments and feedback from the editor and two anonymous reviewers. FEM would like to acknowledge the support from USDA‐NIFA (award no. 2020‐67021‐32466), the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. IOW04614 supported by State of Iowa funds, and the Plant Science Institute. HP would like to acknowledge the support from the Agriculture and Food Research Initiative's Sustainable Agricultural Systems Coordinated Agricultural Projects (award no. 2019‐68012‐29818) from the United States Department of Agriculture (USDA) National Institute of Food and Agriculture and the USDA NC1195 multi‐state project.
© 2022 The Authors. Agricultural & Environmental Letters published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.
ASJC Scopus subject areas
- Agronomy and Crop Science
- Soil Science
- Management, Monitoring, Policy and Law