Combining corn N recommendation tools for an improved economical optimal nitrogen rate estimation

Abstract

Improving corn (Zea mays L.) nitrogen (N) rate fertilizer recommendation tools can improve farmers' profits and mitigate N pollution. Numerous approaches have been tested to improve these tools, but to date improvements for predicting economically optimum N rate (EONR) have been modest. This work's objective was to use ensemble learning to improve our estimation of EONR (for a single at-planting and split N application timing) by combining multiple corn N recommendation tools. The evaluation was conducted using 49 corn N response trials from eight states in the US Corn Belt and three growing seasons (2014)(2015)(2016). Elastic net and decision tree approaches regressed EONR against three unique tools for each N application timing. Tools used in various combinations included a yield goal method, two soil nitrate tests (pre-plant and late season), a computer simulation crop model (Maize-N), and canopy reflectance sensing. Any combination of two or three N recommendation tools improved or maintained performance metrics (R 2 , root-mean square error , and number of sites close to EONR). The best results for a single at-planting recommendation occurred when combining the three at-planting N recommendation tools (including interactions) with an elastic net regression model. This combined recommendation tool had a significant linear relationship with EONR (R 2 = 0.46), an increase of 0.27 over the best tool evaluated alone. Combining multiple tools increased the implementation cost, but it did not reduce profitability and, sometimes, improved profitability. These results show tools can be combined to better match EONR, and thus could aid farmers in improving N management.Abbreviations: cEONR, reasonably close to the economical optimal N rate; EONR, economical optimal N rate; LSNT, late-spring soil nitrate test; MRTN, maximum return to N; PPNT, pre-plant soil nitrate test; RMSE, root mean square error; YG, yield goal.

Note on the unparallel vertical distribution of nitrate and sulfate in Mollisols

“…Soil Science Society of America Journal © 2024 Soil Science Society of America. et al, 2018;Ransom et al, 2023). Most of them are based on the pre-plant concentration of soil nitrate, typically measured at depths of 15, 30, or 60 cm (Correndo, Gutiérrez-Boem et al, 2021;Ransom et al, 2021;and references therein).…”

“…Worldwide, numerous methods have been developed to diagnose soil N availability, aiming to enhance farmers' profits and mitigate N pollution (e.g., Herrera et al., 2016; Morris et al., 2018; Ransom et al., 2023). Most of them are based on the pre‐plant concentration of soil nitrate, typically measured at depths of 15, 30, or 60 cm (Correndo, Gutiérrez‐Boem et al., 2021; Ransom et al., 2021; and references therein).…”

Economic and Environmental Feasibility of Variable Rate Nitrogen Application in Potato by Fusion of Online Visible and Near Infrared (Vis-NIR) and Remote Sensing Data

“…In traditional agricultural practices, spatial variability within a field is ignored and fields are considered as a single unit, whose soil characteristics, topography and environmental factors are spatially homogeneous [11]. Consequently, applying a uniform rate of N fertilization on entire field area may results in over and under-application of N, potentially leading to significant environmental pollution and poor crop yield [12].…”

Economic and Environmental Assessment of Variable Rate Nitrogen Application in Potato by Fusion of Online Visible and Near Infrared (Vis-NIR) and Remote Sensing Data

“…In traditional agricultural practices, spatial variability within a field is ignored, and fields are considered as a single unit whose soil characteristics, topography, and environmental factors are spatially homogeneous [11]. Consequently, applying a uniform rate of N fertilization on the entire field area may result in over and under-application of N, potentially leading to significant environmental pollution and poor crop yield [12].…”