Detection of paralytic shellfish toxins by near-infrared spectroscopy based on a near-Bayesian SVM classifier with unequal misclassification costs

文献类型： 外文期刊

第一作者： Liu, Yao

作者： Liu, Yao;Xiong, Jianfang;Qiao, Fu;Qiao, Fu;Xu, Lele;Xu, Zhen;Liu, Yao

作者机构：

关键词： near-infrared spectroscopy; paralytic shellfish toxins; near-Bayesian SVM; unequal misclassification costs; imbalanced classification

期刊名称：JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE （ 影响因子：4.1； 五年影响因子：4.2 ）

ISSN： 0022-5142

年卷期： 2023 年

页码：

收录情况： SCI

摘要： BACKGROUND: Paralytic shellfish poisoning caused by human consumption of shellfish fed on toxic algae is a public health hazard. It is essential to implement shellfish monitoring programs to minimize the possibility of shellfish contaminated by paralytic shellfish toxins (PST) reaching the marketplace.RESULTS: This paper proposes a rapid detection method for PST in mussels using near-infrared spectroscopy (NIRS) technology. Spectral data in the wavelength range of 950-1700 nm for PST-contaminated and non-contaminated mussel samples were used to build the detection model. Near-Bayesian support vector machines (NBSVM) with unequal misclassification costs (u-NBSVM) were applied to solve a classification problem arising from the fact that the quantity of non-contaminated mussels was far less than that of PST-contaminated mussels in practice. The u-NBSVM model performed adequately on imbalanced datasets by combining unequal misclassification costs and decision boundary shifts. The detection performance of the u-NBSVM did not decline as the number of PST samples decreased due to adjustments to the misclassification costs. When the number of PST samples was 20, the G-mean and accuracy reached 0.9898 and 0.9944, respectively.CONCLUSION: Compared with the traditional support vector machines (SVMs) and the NBSVM, the u-NBSVM model achieved better detection performance. The results of this study indicate that NIRS technology combined with the u-NBSVM model can be used for rapid and non-destructive PST detection in mussels. (c) 2023 Society of Chemical Industry.

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