Identification of pesticide residues in lettuce leaves based on near infrared transmission spectroscopy
Identification of pesticide residues in lettuce leaves based on near infrared transmission spectroscopy
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基于近红外透射光谱法鉴定生菜叶片农药残留
DOI：
10.1111/jfpe.12816
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发表时间：
2018-10-01
影响因子：
3
通讯作者：
Yang, Ning
中科院分区：
文献类型：
--
作者：
Sun, Jun;Ge, Xiao;Yang, Ning
为探索蔬菜中农药残留的无损、准确的定性检测方法，以生菜叶为载体，以氰戊菊酯和毒死蜱为研究对象。利用NIRez近红外光谱仪（950-1,650 nm）采集生菜叶片的近红外光谱数据，分别采用SNV算法和SG-SNV组合算法对数据进行预处理。分别采用连续投影算法（SPA）、竞争自适应加权采样（汽车）、迭代保留信息变量（IRIV）以及两者结合的方法从预处理后的光谱数据中选择特征波长。采用支持向量机对生菜叶片中农药残留进行分类。由于支持向量机的分类性能受参数c（惩罚系数）和g（核函数参数）的影响，因此采用引力搜索算法（GSA）对支持向量机的参数c和g进行优化。最后，分别建立了全波长和选定特征波长的识别模型。最终结果表明，CARS-IRIV-GSA-SVM模型的分类性能最好，训练集和预测集的分类准确率分别达到100%和98.33%。因此，近红外透射光谱技术可应用于生菜叶片中农药残留的定性检测。
To explore the nondestructive and accurate qualitative detection method of pesticide residues in vegetables, lettuce leaves were taken as carrier and pesticides (fenvalerate and chlorpyrifos) were taken as research object. The near infrared spectral data of lettuce leaves was collected by using near infrared spectrometer NIRez (950-1,650 nm), then it was preprocessed by SNV algorithm and SG-SNV combination, respectively. The successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), iteratively retaining informative variables (IRIV), and combination of two of them were used to select characteristic wavelengths from the preprocessed spectral data, respectively. In this study, support vector machine (SVM) was used to classify pesticide residues in lettuce leaves. Because the classification performance of SVM was influenced by parameters c (penalty coefficient) and g (kernel function parameter), so the parameters c and g of SVM were optimized by gravitational search algorithm (GSA). Finally, identification models were built on the full wavelengths and the selected characteristic wavelengths, respectively. Final result showed that CARS-IRIV-GSA-SVM model had the best performance, and the classification accuracy of training set and predication set reached 100 and 98.33%. Therefore, near infrared transmission spectroscopy can be applied to the qualitative detection of pesticide residues in lettuce leaves.