Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Tea trees are kept in shaded locations to increase their chlorophyll content, which influences green tea quality. Therefore, monitoring change in chlorophyll content under low light conditions is important for managing tea trees and producing high-quality green tea. Hyperspectral remote sensing is o...

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Bibliographic Details
Main Authors: Rei Sonobe, Yuhei Hirono, Ayako Oi
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Plants
Subjects:
deep belief nets
extreme learning machine
first derivative spectra
random forest
shade-grown tea
support vector machine
Online Access:https://www.mdpi.com/2223-7747/9/3/368

Internet

https://www.mdpi.com/2223-7747/9/3/368

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