基于表面增强拉曼光谱技术的柑橘表皮咪鲜胺和抑霉唑农药残留检测

doi:10.3964/j.issn.1000-0593(2023)10-3052-07

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摘要：咪鲜胺和抑霉唑是柑橘类水果常用的保鲜剂，二者混用可有效降低致病细菌抗药性，达到更好的保鲜效果，但农残过量会影响食用者健康。基于表面增强拉曼光谱技术，以丑橘为基质，咪鲜胺和抑霉唑混合农药为研究对象，结合化学计量学方法，建立一种快速准确检测柑橘表皮农药残留的方法。为了对比金、银溶胶的增强效果，分别将金、银溶胶用于浓度为10 mg·L^-1的咪鲜胺、抑霉唑标准溶液及橘皮萃取液中的混合农药，采集其拉曼光谱。结果表明，咪鲜胺和抑霉唑的单独标准溶液中金溶胶较优，在橘皮萃取液中的混合农药溶液中银溶胶效果更佳。为了获得最佳增强效果，通过不同比例试验对比，最终确定溶胶增强基底与两种农药标准溶液体积比为1∶1，团聚剂NaCl浓度为1 mol·L^-1。按照浓度从高到低的方向，分别采集咪鲜胺标准溶液及抑霉唑标准溶液在不同浓度情况下的光谱，检出限分别低于1和0.5 mg·L^-1，达到国标规定的最大残留限5 mg·L^-1。在咪鲜胺和抑霉唑混合农药的定量分析实验中，以橘皮萃取液为基质，用增强效果较好的银溶胶作为增强基底，采集含有梯度浓度的咪鲜胺和抑霉唑混合农药(5~42 mg·L^-1)的表面增强拉曼光谱，采用多种预处理方法优化光谱数据，对比支持向量回归(SVR)、灰狼算法优化的支持向量回归(GWO-SVR)、粒子群算法优化的支持向量回归(PSO-SVR)、遗传算法优化的支持向量回归(GA-SVR)四种回归模型的建模效果选择最佳算法建立定量模型。结果表明：通过一阶微分预处理方法，选取829和1 168 cm^-1处的特征峰强度建立灰狼算法优化的支持向量机回归(GWO-SVR)模型得到的预测效果最佳，其校正相关系数(R_C)为0.978，校正集均方根误差(RMSEC)为1.655 mg·L^-1，预测相关系数(R_P)为0.967，预测集均方根误差(RMSEP)为2.227 mg·L^-1。研究结果表明，该方法可对柑橘表皮咪鲜胺和抑霉唑混合农药进行定性与定量检测，可为柑橘农残检测提供新思路。

关键词：表面增强拉曼光谱；柑橘；咪鲜胺；抑霉唑；支持向量机回归

Abstract：Prochloraz and imazalil are commonly used preservative fungicides for citrus fruits. The mixture of the two pesticides can effectively reduce pathogenic bacteria' drug resistance and achieve better preservative effects. However, the high concentration of pesticide residues on the surface of fruits and vegetables will affect consumers' health. In this paper, a rapid and accurate method for detecting pesticide residues in the citrus epidermis was established based on the combination of surface-enhanced Raman spectroscopy and chemometrics methods by taking ugly orange as matrix, prochloraz and imazalil mixed pesticides as the research object. In order to compare the enhancement effects of the gold sol and silver sol, they were respectively used on prochloraz standard solution, imazalil standard solution and mixed pesticide solution of prochloraz and imazalil based on orange peel extract at the concentration of 10 mg·L^-1 respectively. Then the Raman spectra of the prepared sample solutions were collected. The results showed that the enhancement effect of gold sol in prochloraz standard solution orimazalil standard solution was better, while silver sol in prochloraz and imazalil mixed pesticides was good. Additionally, to obtain the best reinforcing effect of gold sol substrate, a comparative test was carried out, which determined that the volume ratio of gold sol reinforced substrate to two standard pesticide solutions is 1∶1, and the concentration of agglomerating agent NaCl is 1 mol·L^-1. According to the direction from high to low, the spectra of prochloraz standard solutions and imazalil standard solutions at different concentrations were collected. The detection limits were lower than 1 mg·L^-1 and 0.5 mol·L^-1 respectively, within the maximum pesticide residue limit of 5 mg·L^-1 for citrus crops stipulated by the state. In the quantitative analysis experiment of mixed pesticides with prochloraz and imazalil, taking orange epidermis extract as matrix and silver sol with better enhancement effect as enhancement substrate, the surface enhanced Raman spectra of mixed pesticides including prochloraz and imazalil with gradient concentration (5~42 mg·L^-1) were collected. Then, various pretreatment methods were used to optimize the spectral data, and four regression models containing support vector regression (SVR), support vector regression optimized by the Grey Wolf (GWO-SVR)algorithm, support vector regression optimized by particle swarm optimization (PSO-SVR)and support vector regression optimized by genetic (GA-SVR) algorithm were compared to establish anaccurate and reliable quantitative model. The results showed that the best prediction effect was achieved on the regression model which was established by support vector regression optimized by Grey Wolf (GWO-SVR) algorithm with the characteristic peak intensities of 829 and 1 168 cm^-1 as input after the first-order difference preprocessing. The corrected correlation coefficient (R_C), the root mean square error (RMSEC) of the correction set, the predicted correlation coefficient (R_P), and the root mean square error (RMSEP) of the correction predicted were 0.978, 1.655 mg·L^-1, 0.967 and 2.227 mg·L^-1 respectively. In conclusion, the proposed method was proved to be effectively applied for the qualitative and quantitative detection of mixed pesticides with prochloraz and imazalil in the citrus epidermis. It could provide a new approach for detecting pesticide residues in citrus.

Key words：Surface enhanced Raman spectroscopy; Citrus; Prochloraz; Imazalil; Support vector machine regression

收稿日期: 2022-01-25 修订日期: 2022-11-17

中图分类号:

O657.3

基金资助: 国家重点研发计划项目（2019YFD1001402，2020YFD1000101），现代农业(柑橘)产业技术体系建设专项(CARS-26)，中央高校基本科研业务费专项(2762020GXPY012)资助

通讯作者: 龙长江 E-mail: lcjflow@163.com

作者简介: 李雯雯，女，1998年生，华中农业大学工学院硕士研究生 e-mail: 1831907347@qq.com

引用本文:

李雯雯，龙长江，李善军，陈红. 基于表面增强拉曼光谱技术的柑橘表皮咪鲜胺和抑霉唑农药残留检测[J]. 光谱学与光谱分析, 2023, 43(10): 3052-3058.
LI Wen-wen, LONG Chang-jiang, LI Shan-jun, CHEN Hong. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in Citrus Epidermis by Surface Enhanced Raman Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058.

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