A 1D-SP-Net to Determine Early Drought Stress Status of Tomato (<i>Solanum lycopersicum</i>) with Imbalanced Vis/NIR Spectroscopy Data

A 1D-SP-Net to Determine Early Drought Stress Status of Tomato (<i>Solanum lycopersicum</i>) with Imbalanced Vis/NIR Spectroscopy Data

Detection of the early stages of stress is crucial in stabilizing crop yields and agricultural production. The aim of this study was to construct a nondestructive and robust method to predict the early physiological drought status of the tomato (<i>Solanum lycopersicum</i>); for this pur...

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Bibliographic Details
Main Authors: Yuan-Kai Tu, Chin-En Kuo, Shih-Lun Fang, Han-Wei Chen, Ming-Kun Chi, Min-Hwi Yao, Bo-Jein Kuo
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Agriculture
Subjects:
tomato
drought stress
early detection
residual block
GC block
convolutional neural network (CNN)
Online Access:https://www.mdpi.com/2077-0472/12/2/259

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