Rapid Determination of Cadmium Contamination in Lettuce Using Laser-Induced Breakdown Spectroscopy

文献类型： 外文期刊

第一作者： Shen, Tingting

作者： Shen, Tingting;Kong, Wenwen;Liu, Fei;Chen, Zhenghui;Yao, Jingdong;Wang, Wei;Peng, Jiyu;He, Yong;Shen, Tingting;Liu, Fei;Wang, Wei;He, Yong;Kong, Wenwen;Chen, Huizhe

作者机构：

关键词： cadmium contamination; lettuce; laser-induced breakdown spectroscopy; multivariate analysis; genetic algorithm

期刊名称：MOLECULES （ 影响因子：4.411； 五年影响因子：4.587 ）

ISSN： 1420-3049

年卷期： 2018 年 23 卷 11 期

页码：

收录情况： SCI

摘要： Quick access to cadmium (Cd) contamination in lettuce is important to supervise the leafy vegetable growth environment and market. This study aims to apply laser-induced breakdown spectroscopy (LIBS) technology for fast determination of Cd content and diagnosis of the Cd contamination degree in lettuce. Emission lines Cd II 214.44 nm, Cd II 226.50 nm, and Cd I 228.80 nm were selected to establish the univariate analysis model. Multivariate analysis including partial least squares (PLS) regression, was used to establish Cd content calibration models, and PLS model based on 22 variables selected by genetic algorithm (GA) obtained the best performance with correlation coefficient in the prediction set Rp(2) = 0.9716, limit of detection (LOD) = 1.7 mg/kg. K-Nearest Neighbors (KNN) and random forest (RF) were used to analyze Cd contamination degree, and RF model obtained the correct classification rate of 100% in prediction set. The preliminary results indicate LIBS coupled with chemometrics could be used as a fast, efficient and low-cost method to assess Cd contamination in the vegetable industry.

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