Active-Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt Bean, G. M. Kitchen, N. R. Sawyer, John Camberato, J. J. Ferguson, R. B. Fernandez, F. G. Franzen, D. W. Laboski, C. A. M. Nafziger, E. D. Sawyer, J. E. Scharf, P. C. Schepers, J. Shanahan, J. S.
dc.contributor.department Agronomy 2018-11-10T18:44:24.000 2020-06-29T23:05:57Z 2020-06-29T23:05:57Z 2018-01-01
dc.description.abstract <p>Uncertainty exists with corn (<em>Zea mays</em> 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<sup>–1</sup> on 45 kg ha<sup>–1</sup>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<sup>–1</sup> of EONR > 50% of the time. Average recommendations differed from EONR 81 to 147 kg N ha<sup>–1</sup> with no N applied at planting and 74 to 118 kg N ha<sup>–1</sup> with 45 kg of N ha<sup>–1</sup> 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.</p>
dc.description.comments <p>This article is published as Bean, G. M., 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, and J. S. Shanahan. 2018. Active-Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt. Agron. J. 110 (2018): 2552-2558. doi: <a href="" target="_blank">10.2134/agronj2018.03.0217</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 1581
dc.identifier.contextkey 13253509
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath agron_pubs/532
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 00:51:11 UTC 2022
dc.source.uri 10.2134/agronj2018.03.0217
dc.subject.disciplines Agriculture
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Soil Science
dc.title Active-Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 17ce8a78-56b3-47be-abcb-b22968be40f2
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
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