Improving in-season wheat yield prediction using remote sensing and additional agronomic traits as predictors

The development of accurate grain yield (GY) multivariate models using normalized difference vegetation index (NDVI) assessments obtained from aerial vehicles and additional agronomic traits is a promising option to assist, or even substitute, laborious agronomic in-field evaluations for wheat varie...

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Detalles Bibliográficos
Autores principales: Gracia-Romero, Adrian, Rufo, Rubén, Gómez-Candón, David, Soriano, José Miguel, Bellvert, Joaquim, Yannam, Venkata Rami Reddy, Gulino, Davide, Lopes, Marta S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106603/
https://www.ncbi.nlm.nih.gov/pubmed/37077632
http://dx.doi.org/10.3389/fpls.2023.1063983

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106603/
https://www.ncbi.nlm.nih.gov/pubmed/37077632
http://dx.doi.org/10.3389/fpls.2023.1063983

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