Visible and near-infrared hyperspectral imaging as an intelligent tool for parasite detection in sashimi

文献类型： 外文期刊

第一作者： Xu, Sai

作者： Xu, Sai;Fan, Changxiang;Qiu, Guangjun;Liang, Xin;Peng, Jian;Xu, Sai;Fan, Changxiang;Qiu, Guangjun;Liang, Xin;Peng, Jian;Xu, Sai;Lu, Huazhong;Ference, Christopher

作者机构：

关键词： Sashimi; Parasite; Grass carp; Visible and near-infrared hyperspectral imag; ing; Intelligent detection

期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：6.0； 五年影响因子：6.0 ）

ISSN： 0023-6438

年卷期： 2023 年 181 卷

页码：

收录情况： SCI

摘要： There are parasites found on sashimi which can cause a series of health problems to those who consume them. Because the parasites are too small to be visible to the naked eye, the labor and time-consuming use of a microscope is required for detection. This study proposes a visible and near-infrared (VIS/NIR) hyperspectral imaging method to quickly and intelligently detect parasites in sashimi. The research results show that the VIS/NIR spectrums for fish meat and parasite images were different at certain wavelengths. The ability of a probabilistic neural network (PNN) combined with multiple detection models was better than that of partial least squares regression (PLSR) combined with a single detection model for the true positive detection of parasites on sashimi. A synthesis between PNN and a combination of detection models, including Savitzky-Golay, standard normal variate, and first derivative pre-processing, is able to optimally detect parasites in sashimi. Using this strategy, the detection accuracy of the validation set for Anisakis nematodes on the top and bottom of a sliced piece of sashimi were 91.67% and 82.14%, respectively. Thus, VIS/NIR hyperspectral imaging allows for intelligent, accurate, efficient, and rapid detection of Anisakis nematodes on sashimi.

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