Detection of mussels contaminated with cadmium by near-infrared reflectance spectroscopy based on RELS-TSVM

文献类型： 外文期刊

第一作者： Liu, Yao

作者： Liu, Yao;Qiao, Fu;Xu, Zhen

作者机构：

关键词： cadmium contamination; least squares twin support vector machine; mussel; near-infrared spectroscopy; robustness

期刊名称：JOURNAL OF FOOD SCIENCE （ 影响因子：3.4； 五年影响因子：4.1 ）

ISSN： 0022-1147

年卷期： 2024 年 89 卷 12 期

页码：

收录情况： SCI

摘要： Eating mussels contaminated with cadmium (Cd) can seriously harm health. In this study, a non-destructive and rapid detection method for Cd-contaminated mussels based on near-infrared reflectance spectroscopy was studied. The spectral data of Cd-contaminated and non-contaminated mussels were collected in the range of 950-1700 nm. The model based on a robust energy-based least squares twin support vector machine (RELS-TSVM) was established to detect Cd-contaminated mussels. The influence of parameters on the RELS-TSVM model was analyzed, and the most suitable parameters were determined. The average accuracy of the proposed RELS-TSVM model in detecting Cd-contaminated mussels reached 99.92%, which was better than other twin support vector machine-derived models. For test datasets with different kinds of spectral noises (Gaussian noise, baseline shift, stray light, and wavelength shift), the RELS-TSVM model had a high robustness for noise disturbance. The results show that near-infrared spectroscopy combined with the RELS-TSVM model can realize the detection of Cd-contaminated mussels, which can provide technical support for the monitoring of heavy metals in shellfish.

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