Enhancing buckwheat maturity classification with generative adversarial networks for spectroscopy data augmentation

IntroductionThe optimal harvest period for buckwheat is challenging to determine due to its short growth cycle. Harvesting too early or too late can negatively affect the quality of the crop. Traditional harvest methods are labor-intensive and fail to account for the spatial variability in buckwheat...

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Bibliographic Details
Main Authors:	Huihui Wang, Xiaoxue Che, Jiaxuan Nan, Yuyuan Miao, Yaqi Wang, Wuping Zhang, Fuzhong Li, Jiwan Han
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-07-01
Series:	Frontiers in Plant Science
Subjects:	buckwheat spectroscopy machine learning generative adversarial networks NIR precision agriculture
Online Access:	https://www.frontiersin.org/articles/10.3389/fpls.2025.1604088/full
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Enhancing buckwheat maturity classification with generative adversarial networks for spectroscopy data augmentation

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