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首页> 外文期刊>Food Analytical Methods >Feasibility Research on Rapid Detection of Prochloraz in Green Tea Soft Drink by Near-Infrared Spectroscopy
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Feasibility Research on Rapid Detection of Prochloraz in Green Tea Soft Drink by Near-Infrared Spectroscopy

机译:近红外光谱法快速检测绿茶软饮料中敌百虫的可行性研究

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摘要

A rapid and non-destructive method, based on near-infrared spectroscopy (NIRS) was established for screening prochloraz in green tea soft drink. Two chemometric methods, including partial least-squares discriminant analysis (PLS-DA) and least-squares support vector machines (LS-SVM), were used to establish the calibration model for full-spectrum classification. The results of LS-SVM outperformed those of PLS-DA, with the classification accuracy of 100 % for the calibration set and the prediction set when the two parameters, γ and σ 2, were 454.994 and 1,057.77, respectively, while the classification accuracy of PLS-DA for the calibration set and the prediction set is 99.1 and 94.8 %, respectively. In order to avoid model overfitting, the procedure was applied to the analysis of prochloraz residue in other four kinds of green tea soft drinks. Good results were also received. Due to the small difference between the blank samples and the contaminated ones, an interval, not a threshold, was set. The samples in the interval are suspicious which should be detected by chromatographic method. Thus, after screening by NIRS and the further chemometric analysis, the appearance of false negative samples was avoided, and workload could be greatly reduced.
机译:建立了一种基于近红外光谱(NIRS)的快速无损检测方法,用于筛查绿茶软饮料中的原虫。两种化学计量学方法,包括部分最小二乘判别分析(PLS-DA)和最小二乘支持向量机(LS-SVM),用于建立全光谱分类的校准模型。 LS-SVM的结果优于PLS-DA,当两个参数γ和σ2分别为454.994和1,057.77时,校准集和预测集的分类精度为100%。校准集和预测集的PLS-DA分别为99.1%和94.8%。为避免模型过度拟合,该方法用于分析其他四种绿茶软饮料中的前杀菌剂残留。也收到了良好的结果。由于空白样品和受污染样品之间的差异很小,因此设置了一个间隔而不是一个阈值。间隔内的样品可疑,应通过色谱法进行检测。因此,通过NIRS筛选并进行进一步的化学计量分析后,避免了假阴性样品的出现,并且可以大大减少工作量。

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