Qi Fang, Liu Xing, Deng Zhongsheng, Lu Yangyang, Chen Yijiao, Geng Hao, Zhang Qicai, Rao Qinxiong, Song Weiguo
Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China.
College of Food Sciences, Shanghai Ocean University, Shanghai 201306, China.
Foods. 2023 Jul 10;12(14):2655. doi: 10.3390/foods12142655.
Accurate identification of the rational and standardized use of pesticides is important for the sustainable development of agriculture while maintaining a high quality. The insecticides thiamethoxam and fenvalerate and the vegetables spinach, cabbage, and lettuce were used here as study objects. Descriptive analysis and primary reaction kinetic equations were used to analyze the changes in metabolic residues of the two insecticides after different numbers of application in three vegetables. The effects of pesticide residue levels on the C, N, H, and O values of vegetables were analyzed by one-way analysis of variance and correlation analysis. Partial least squares discriminant analysis (PLS-DA) was applied to build discrimination models of the vegetables with different pesticide residues based on stable isotopes. The results showed that the first degradation residues of thiamethoxam and fenvalerate in spinach, cabbage, and lettuce conformed to primary reaction kinetic equations, but the degradation half-lives were long, and accumulation occurred in the second application. The differences in the four stable isotope ratios in the control group of the three vegetables were statistically significant, and two-thirds of the stable isotope ratios in the three vegetables with different numbers of pesticide applications were significantly different. The C and N values of spinach, the C, N, and H values of cabbage, and the C, N, H, and δO values of lettuce were significantly correlated with different residues of thiamethoxam and/or fenvalerate applications. The control groups of the three vegetables, spinach-thiamethoxam-first, spinach-thiamethoxam-second, cabbage-thiamethoxam-second, cabbage-fenvalerate-first, and lettuce-thiamethoxam-first, were fully identified by PLS-DA models, while the identification models of other vegetables containing pesticide residues still need to be further improved. The results provide technical support for identifying the rational use of pesticides in vegetables and provide a reference method for guaranteeing the authenticity of green and organic vegetables.
准确识别农药的合理与规范使用对于农业可持续发展并保持高品质至关重要。本文以杀虫剂噻虫嗪和氰戊菊酯以及蔬菜菠菜、白菜和生菜为研究对象。采用描述性分析和一级反应动力学方程分析两种杀虫剂在三种蔬菜中不同施药次数后的代谢残留变化。通过单因素方差分析和相关性分析研究农药残留水平对蔬菜碳、氮、氢和氧值的影响。应用偏最小二乘判别分析（PLS-DA）基于稳定同位素建立不同农药残留蔬菜的判别模型。结果表明，噻虫嗪和氰戊菊酯在菠菜、白菜和生菜中的首次降解残留符合一级反应动力学方程，但降解半衰期较长，第二次施药时出现累积现象。三种蔬菜对照组的四种稳定同位素比率差异具有统计学意义，三种不同施药次数蔬菜中三分之二的稳定同位素比率存在显著差异。菠菜的碳和氮值、白菜的碳、氮和氢值以及生菜的碳、氮、氢和δO值与噻虫嗪和/或氰戊菊酯不同残留量显著相关。PLS-DA模型能够完全识别三种蔬菜的对照组，即菠菜-噻虫嗪-首次、菠菜-噻虫嗪-第二次、白菜-噻虫嗪-第二次、白菜-氰戊菊酯-首次和生菜-噻虫嗪-首次，而其他含农药残留蔬菜的识别模型仍需进一步改进。研究结果为识别蔬菜中农药的合理使用提供了技术支持，为保障绿色和有机蔬菜的真实性提供了参考方法。
