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Identification and detection of pesticide in chard samples by laser-induced breakdown spectroscopy using chemometric methods
Spectrochimica Acta Part B: Atomic Spectroscopy ( IF 3.2 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.sab.2020.106031
Lucila J. Martino , Cristian A. D'Angelo , Claudia Marinelli , Rosana Cepeda

Abstract Pesticide residues in food represent a significant threat to consumers. However, the fast detection of traces directly in samples involves a complex task. In this work, we explore the potential application of the Laser-Induced Breakdown Spectroscopy (LIBS) technique for the rapid measurement of pesticide residues in chard leaves by identifying them from the signal recording of the emission lines of P, S, C and Cl. They are subsequently jointly described through a principal components analysis (PCA) and grouping of the samples according to their pesticide was corroborated by means of a linear discriminant analysis (LDA) with an error rate of less than 9.5%. Moreover, differences can be observed in the classification of groups with a 95% confidence level. There is thus clear evidence of the applicability of this technique as a potential tool for the study of pesticide residues in food matrices.

中文翻译:

化学计量学方法通过激光诱导击穿光谱法鉴定和检测甜菜样品中的农药

摘要 食品中的农药残留对消费者构成重大威胁。然而,直接在样品中快速检测痕量涉及一项复杂的任务。在这项工作中,我们探索了激光诱导击穿光谱 (LIBS) 技术通过从 P、S、C 和 Cl 发射谱线的信号记录中识别它们来快速测量甜菜叶中农药残留的潜在应用。随后通过主成分分析 (PCA) 对它们进行联合描述,并通过线性判别分析 (LDA) 证实根据农药对样品进行分组,误差率小于 9.5%。此外,可以在具有 95% 置信水平的组分类中观察到差异。
更新日期:2021-03-01
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