Application of Hyperspectral Imaging as a Nondestructive Technology for Identifying Tomato Maturity and Quantitatively Predicting Lycopene Content

Application of Hyperspectral Imaging as a Nondestructive Technology for Identifying Tomato Maturity and Quantitatively Predicting Lycopene Content

Maturity is a crucial indicator in assessing the quality of tomatoes, and it is closely related to lycopene content. Using hyperspectral imaging, this study aimed to monitor tomato maturity and predict its lycopene content at different maturity stages. Standard normal variable (SNV) transformation w...

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Bibliographic Details
Main Authors: Chunxia Dai, Jun Sun, Xingyi Huang, Xiaorui Zhang, Xiaoyu Tian, Wei Wang, Jingtao Sun, Yu Luan
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Foods
Subjects:
hyperspectral imaging technology
tomato maturity
lycopene content
classification
regression model
visualization
Online Access:https://www.mdpi.com/2304-8158/12/15/2957

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