Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning

Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather, and management conditions is challenging. Strategies using multi-source data are hypothesized to perform significantly better than approaches using crop sensing information alone. The objective of this study wa...

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Detalhes bibliográficos

Principais autores:	Dan Li, Yuxin Miao, Curtis J. Ransom, Gregory Mac Bean, Newell R. Kitchen, Fabián G. Fernández, John E. Sawyer, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Carrie A. M. Laboski, Emerson D. Nafziger, John F. Shanahan
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-01-01
coleção:	Remote Sensing
Assuntos:	nitrogen status diagnosis machine learning normalized difference red edge (NDRE) data fusion
Acesso em linha:	https://www.mdpi.com/2072-4292/14/2/394
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