Tegillarca granosa ( T. granosa ) is susceptible to heavy metals, which may pose a threat to consumer health. Thus, healthy and polluted T. granosa should be distinguished quickly. This study aimed to rapidly identify heavy metal pollution by using laser-induced breakdown spectroscopy (LIBS) coupled with linear regression classification (LRC). Five types of T. granosa were studied, namely, Cd-, Zn-, Pb-contaminated, mixed contaminated, and control samples. Threshold method was applied to extract the significant variables from LIBS spectra. Then, LRC was used to classify the different types of T. granosa . Other classification models and feature selection methods were used for comparison. LRC was the best model, achieving an accuracy of 90.67%. Results indicated that LIBS combined with LRC is effective and feasible for T. granosa heavy metal detection.

中文翻译：

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激光诱导击穿光谱法和线性回归法鉴定重金属污染的Tegillarca granosa

Tegillarca granosa（T. granosa）易受重金属污染，这可能对消费者健康构成威胁。因此，应迅速区分健康和污染严重的T. granosa。这项研究旨在通过使用激光诱导击穿光谱法（LIBS）和线性回归分类（LRC）来快速识别重金属污染。研究了五种T. granosa，即Cd，Zn，Pb污染，混合污染和对照样品。采用阈值法从LIBS光谱中提取出显着变量。然后，使用LRC对T. granosa的不同类型进行分类。其他分类模型和特征选择方法用于比较。LRC是最好的模型，准确率达到90.67％。结果表明LIBS联合LRC治疗T是有效可行的。