College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
School of Chinese Material Medica, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Aug 5;257:119759. doi: 10.1016/j.saa.2021.119759. Epub 2021 Apr 1.
Contamination of agricultural plants and food in the environment caused by pesticide residues has gained great attention of the world. Pesticide residues on vegetables constitute a potential risk to human health. A visible/near-infrared (Vis/NIR) spectroscopy combined with chemometric methods was employed to quantitatively determine chlorpyrifos and carbendazim residues in the cabbage (Brassica chinensis L.). Preprocessing methods were used for spectra denoising. Partial least squares regression (PLSR) and least squares-support vector machine (LS-SVM) were applied as the quantification models. Feature variables were selected by successive projection algorithms (SPA), random frog and regression coefficients in PLSR. As for the samples with chlorpyrifos residues, LS-SVM models based on the global spectra achieved best model performance. The best performance for carbendazim content prediction was achieved by the LS-SVM models based on the original global spectra. And modeling with SPA selected feature variables for carbendazim determination was as good as modeling with the global spectra. The results indicated that Vis/NIR spectroscopy coupled with chemometrics could be an efficient way for the assessment of the pesticide residues in vegetables, and was significant for detection of environmental pollution and ensuring food safety.
环境中农药残留对农作物和食品的污染引起了全世界的高度关注。蔬菜上的农药残留对人类健康构成潜在威胁。本研究采用可见/近红外（Vis/NIR）光谱结合化学计量学方法定量测定了甘蓝（Brassica chinensis L.）中的毒死蜱和多菌灵残留。采用预处理方法对光谱进行去噪。偏最小二乘回归（PLSR）和最小二乘支持向量机（LS-SVM）被用作定量模型。通过连续投影算法（SPA）、随机青蛙和 PLSR 中的回归系数选择特征变量。对于含有毒死蜱残留的样品，基于全局光谱的 LS-SVM 模型取得了最佳的模型性能。基于原始全局光谱的 LS-SVM 模型对多菌灵含量预测的性能最佳。基于 SPA 选择特征变量进行多菌灵测定的建模与基于全局光谱的建模一样好。结果表明，Vis/NIR 光谱结合化学计量学可以作为评估蔬菜中农药残留的有效方法，对检测环境污染和保障食品安全具有重要意义。
