Active-optical reflectance sensing corn algorithms evaluated over the United States midwest corn belt

G. M. Bean, N. R. Kitchen, J. J. Camberato, R. B. Ferguson, F. G. Fernandez, D. W. Franzen, C. A.M. Laboski, E. D. Nafziger, J. E. Sawyer, P. C. Scharf, J. Schepers, J. S. Shanahan

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Uncertainty exists with corn (Zea mays L.) N management due to year-to-year variation in crop N need, soil N supply, and N loss from leaching, volatilization, and denitrification. Active-optical reflectance sensing (AORS) has proven effective in some fields for generating N fertilizer recommendations that improve N use efficiency, but locally derived (e.g., within a US state) AORS algorithms have not been tested simultaneously across a broad region. The objective of this research was to evaluate locally developed AORS algorithms across the US Midwest Corn Belt region for making in-season corn N recommendations. Forty-nine N response trials were conducted across eight states and three growing seasons. Reflectance measurements were collected and sidedress N rates (45–270 kg N ha–1 on 45 kg ha–1 increments) applied at approximately V9 corn development stage. Nitrogen recommendation rates from AORS algorithms were compared with the end-of-season calculated economic optimal N rate (EONR). No algorithm was within 34 kg N ha–1 of EONR > 50% of the time. Average recommendations differed from EONR 81 to 147 kg N ha–1 with no N applied at planting and 74 to 118 kg N ha–1 with 45 kg of N ha–1 at planting, indicating algorithms performed worse with no N applied at planting. With some algorithms, utilizing red edge instead of the red reflectance improved N recommendations. Results demonstrate AORS algorithms developed under a particular set of conditions may not, at least without modification, perform very well in regions outside those within which they were developed.

Original languageEnglish (US)
Pages (from-to)2552-2565
Number of pages14
JournalAgronomy Journal
Volume110
Issue number6
DOIs
StatePublished - Nov 1 2018

Bibliographical note

Funding Information:
This project was funded and made possible by DuPont Pioneer. We thank producer cooperators for allowing us access to their farms. The authors would also like to thank all supporting scientists and field technicians involved in the collection and analysis of this dataset (Matt Yost, Kristen Veum, and Matt Volkmann [Missouri]; Dan Barker [Iowa]; Lakesh Sharma, Amitava Chatterjee, and Norm Cattanach [North Dakota]; Todd Andraski [Wisconsin]; Tim Hart [DuPont Pioneer]; Jason Niekamp and Joshua Vonk [Illinois]; Glen Slater [Nebraska]; Andrew Scobbie, Thor Sellie, Nicholas Severson, Darby Martin, and Erik Joerres [Minnesota]), and the cooperating farmers and research farm personnel.

Publisher Copyright:
© 2018 by the American Society of Agronomy 5585 Guilford Road, Madison, WI 53711 USA.

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