Non-destructive prediction of isoflavone and starch by hyperspectral imaging and deep learning in Puerariae Thomsonii Radix

Accurate assessment of isoflavone and starch content in Puerariae Thomsonii Radix (PTR) is crucial for ensuring its quality. However, conventional measurement methods often suffer from time-consuming and labor-intensive procedures. In this study, we propose an innovative and efficient approach that...

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Detaylı Bibliyografya
Asıl Yazarlar:	Huiqiang Hu, Tingting Wang, Yunpeng Wei, Zhenyu Xu, Shiyu Cao, Ling Fu, Huaxing Xu, Xiaobo Mao, Luqi Huang
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Frontiers Media S.A. 2023-10-01
Seri Bilgileri:	Frontiers in Plant Science
Konular:	Puerariae Thomsonii Radix isoflavones and starch content hyperspectral imaging deep learning one-dimensional convolutional neural network
Online Erişim:	https://www.frontiersin.org/articles/10.3389/fpls.2023.1271320/full
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Non-destructive prediction of isoflavone and starch by hyperspectral imaging and deep learning in Puerariae Thomsonii Radix

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