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Multispectral imaging for predicting the water status in mushroom during hot‐air dehydration
Author(s) -
Younas Shoaib,
Liu Changhong,
Qu Hao,
Mao Yu,
Liu Wei,
Wei Liyang,
Yan Ling,
Zheng Lei
Publication year - 2020
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/1750-3841.15081
Subject(s) - multispectral image , partial least squares regression , water content , dehydration , environmental science , support vector machine , water activity , remote sensing , computer science , artificial intelligence , machine learning , chemistry , engineering , geography , biochemistry , geotechnical engineering
In‐depth understanding of the shifting of water status during dehydration is crucial for obtaining better quality of dried food. In this work, we report a nondestructive method to measure the water status in hot‐air dried mushroom via multispectral imaging (MSI) technology combined with chemometric methods. The low‐field nuclear magnetic resonance (LF‐NMR) measurements were performed as reference. During drying process, the moisture content changed dramatically with notable migration and conversion of different water phases. Partial least squares (PLS), back propagation neural network (BPNN), and least squares‐support vector machine (LS‐SVM) models were applied to develop quantitative models. Among all, BPNN model showed considerably better performance of prediction with coefficient of determination R 2 c = 0.9829, R 2 p = 0.9639. The results demonstrated that MSI technology combined with chemometric methods is an impressive approach for determination of the water status in hot‐air dried mushrooms, which would facilitate infield of food processing by providing applicable and appropriate platform. Practical Application Experimental investigation of different water status during food processing. Assessment of the potential of multispectral imaging to predict water status. Usage of novel measurement method for food processors.