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SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits.

Plant cell reports - 9 Jun 2024

Jeong Seok Won, Lyu Jae Il, Jeong HwangWeon, Baek Jeongho, Moon Jung-Kyung, Lee Chaewon, Choi Myoung-Goo, Kim Kyoung-Hwan, Park Youn-Il

Abstract excerpt

KEY MESSAGE: Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes. Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this...

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PMID: 38852113
DOI: 10.1007/s00299-024-03249-0
PMCID: PMC11162974

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