A Low-Cost RGB-Based Image Processing Method for High-Throughput Assessment of Rice Grain Chalkiness

Although numerous rice genotypes have been developed worldwide, post-harvest evaluation of chalkiness, a key grain trait, remains a significant challenge in breeding programs. Conventional phenotyping methods rely on manual grain separation and analysis, which limit the speed and performance of deci...

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Главные авторы:	Jardel da SILVA SOUZA, Sandra Helena UNEDA-TREVISOLI, Felipe DALLA LANA, Roberto FRITSCHE-NETO
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2026-05-01
Серии:	Rice Science
Предметы:	Oryza sativa grain trait chalkiness degree hyperspectral high-throughput phenotyping
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S1672630826000041
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