Beyond assimilation of leaf area index: Leveraging additional spectral information using machine learning for site-specific soybean yield prediction.

ABSTRACT.- Assimilating external observations of crop state in cropping system models is essential for making spatially explicit predictions of crop variables relevant in precision agriculture. Satellite-based leaf area index (LAI) estimates have been the most frequent variable used as a proxy of ac...

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Bibliographic Details

Main Author:	GASO, D. (author)
Other Authors:	PAUDEL, D. (author), DE WIT, A. (author), PUNTEL, L.A. (author), MULLISSA, A. (author), KOOISTRA, L. (author)
Format:	article
Language:	English
Published:	2024
Subjects:	Crop modeling Data assimilation Machine learning Remote sensing Soybean Sustainable Development Goals (SDGs) Zero hunger - Goal 2 Partnership for the goals - Goal 17 Crops models
Online Access:	https://ainfo.inia.uy/consulta/busca?b=pc&id=64621&biblioteca=vazio&busca=64621&qFacets=64621
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