Predicting wheat yield and grain quality with UAV multispectral imagery and deep learning

Bread wheat (Triticum aestivum L.) is a major staple crop, and timely, in-season prediction of grain yield (GY) and grain quality traits, grain protein content (GP), and grain test weight (TW), is critical for informed management and field-based high-throughput phenotyping (HTP). Unmanned Aerial Veh...

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Auteurs principaux:	Mohammad Maruf Billah, Maitiniyazi Maimaitijiang, Swas Kaushal, Bruce Millett, Shahid Nawaz Khan, Jyotirmoy Halder, Jonathan Kleinjan, Sunish K. Sehgal
Format:	Artigo
Langue:	Inglês
Publié:	Frontiers Media S.A. 2026-05-01
Collection:	Frontiers in Plant Science
Sujets:	deep learning (DL) high-throughput phenotyping (HTP) protein and test weight estimation unmanned aerial vehicles (UAV) wheat yield
Accès en ligne:	https://www.frontiersin.org/articles/10.3389/fpls.2026.1812052/full
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