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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Huiqiang Hu, Tingting Wang, Yunpeng Wei, Zhenyu Xu, Shiyu Cao, Ling Fu, Huaxing Xu, Xiaobo Mao, Luqi Huang
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2023-10-01
Schriftenreihe:Frontiers in Plant Science
Schlagworte:
Puerariae Thomsonii Radix
isoflavones and starch content
hyperspectral imaging
deep learning
one-dimensional convolutional neural network
Online-Zugang:https://www.frontiersin.org/articles/10.3389/fpls.2023.1271320/full
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