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Nondestructive determination of the total mold colony count in green tea by hyperspectral imaging technology
Author(s) -
Cao Yan,
Li Haoran,
Sun Jun,
Zhou Xin,
Yao Kunshan,
Nirere Adria
Publication year - 2020
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.13570
Subject(s) - hyperspectral imaging , partial least squares regression , preprocessor , support vector machine , mathematics , artificial intelligence , pattern recognition (psychology) , computer science , statistics
In the process of tea production and storage, mold is constantly multiplying due to improper production methods and environmental conditions. To realize the nondestructive detection of the total mold colony count in green tea, an accurate and rapid method based on visible–near‐infrared (431–962 nm) hyperspectral image was proposed. Firstly, the spectral data extracted from hyperspectral images was preprocessed and partial least squares regression model based on different preprocessing methods was established to determine the best preprocessing method. Then, competitive adaptive reweighted sampling (CARS) and variable combination population analysis were used to select the characteristic wavelengths and support vector regression (SVR) was introduced to establish quantitative detection model. Because the parameter setting of SVR directly affects the effect of the model, a combination of genetic algorithm (GA) and particle swarm optimization (PSO) was adopted to optimize the parameters c (penalty factor) and g (kernel function parameter). The results showed that based on the wavelength selected by CARS, the SVR model optimized by GA‐PSO (CARS‐GA‐PSO‐SVR) achieved accuracy with R P 2 of 0.9577 and root mean square error of prediction set of 0.1140 lg(CFU/g). Therefore, hyperspectral imaging technology can realize the nondestructive determination of the total mold colony count in green tea. Practical applications Some molds, such as aspergillus and penicillium, are the main factors of tea mildew. These molds can produce mycotoxins such as aflatoxin and citreoviridin, which can not only cause damage to the tea quality, but also threaten the health of tea drinkers. In this paper, the total mold colony count of green tea was studied based on hyperspectral imaging technology. The experiment result indicated that the use of hyperspectral imaging technology can achieve accurate, nondestructive, and rapid detection of the total mold colony count in green tea. This research provides an effective solution to the quantitative detection of the total mold colony count in green tea.