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

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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Bibliographic Details
Main Authors: Adrian Gracia-Romero, Rubén Rufo, David Gómez-Candón, José Miguel Soriano, Joaquim Bellvert, Venkata Rami Reddy Yannam, Davide Gulino, Marta S. Lopes
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-04-01
Series:Frontiers in Plant Science
Subjects:
wheat
grain yield
prediction models
UAV
NDVI
plant height
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2023.1063983/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2023.1063983/full

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