Analytical method for assessing exposure of greenhouse applicators to procymidone by gas chromatography and whole body dosimetry

Summary An analytical method for the determination of the potential and actual exposure of agricultural workers to procymidone has been developed. The methodology is based on the whole body technique, using Tyvek Pro-Tech and Sontara as sampling media, and uses hexane extraction, GC-ECD analysis and GC-MSD confirmation. The validation of the analytical method has been carried out incorporating the matrix of coverall in all steps when calculating parameters such as retention time window, limits of detection and quantification, linear ranges and precision. A field sampling strategy has also been developed and the method has been applied to the evaluation of the potential and actual dermal exposure of an applicator and an assistant in normal working conditions.     

Comparison of Multicomponent Determination of Iprodione,Procymidone and Chlorothalonil by Partial Least Squares Modelling Using Spectrophotometric and High-Performance Liquid Chromatography Data

Abstract

A Partial Least Squares (PLS) calibration method was applied to the simultaneous determination of iprodione, procymidone and chlorothalonil in mixtures, by uv-vis absorption spectrophotometry and by high performance liquid chromatography (HPLC). Signals and first-derivative (¹D) signals were used to optimize the calibration matrices by the PLS-1 method. Quantitative results are presented for synthetic mixtures and for extracts from soil and groundwater samples. Significant improvements were achieved by using the PLS-1 method built with first-derivative chromatograms, in the determination of iprodione, procymidone and chlorothalonil in environmental samples.     

共线双脉冲LIBS结合变量筛选定量检测腐霉利含量

腐霉利（Procymidone）作为一种新型的农产品杀菌剂,具有防止农产品受病虫害的作用,但其在施药过程中容易使用不当危害环境和人的健康。为加强对腐霉利农药的检测,本研究应用共轴双脉冲激光诱导击穿光谱技术（LIBS）对溶液中的腐霉利含量进行定量检测研究。为配置不同浓度的腐霉利样品,将有效成分含量为98%腐霉利粉末与二甲苯按照不同比例混合并完全溶解。由于液体样品在激光击打的过程中容易将液体溅出,具有一定的危险性。因此,实验将液体样品转化为固体样品,利用石墨吸附腐霉利溶液,然后采用八通道高精度光谱仪采集样品的LIBS光谱,并利用不同预处理方法对光谱数据进行预处理。为提高腐霉利的检测精度,选择氯元素信号最强的两通道（744.555~935.843,893.107~1 057.058 nm）光谱数据,分别采用归一化函数（normalization）、基线校正（baseline correction）、标准正态变量变换（SNV）、多元散射校正（MSC）方法进行光谱预处理,并应用PLS方法建模。通过比较各预处理方法数据后,综合考虑,选择Baseline方法为最佳预处理方法。在baseline预处理方法的基础上使用无信息变量消除算法(UVE) 联合竞争性自适应重加权采样(CARS)算法剔除无信息的波长变量,筛选与腐霉利相关的重要波长变量,最后应用偏最小二乘回归建立溶液中腐霉利含量的定量预测模型。建模结果表明：经光谱预处理和UVE-CARS方法优选后,可将原4096个波长变量个数减少至13个,变量压缩率为99.68%;经UVE-CARS变量优选后建立的PLS模型的校正集的决定系数和均方根误差分别为0.990 5和0.66,预测集的决定系数和均方根误差分别为0.990 3和0.67,其模型性能优于原始光谱建立的PLS模型。结果表明,利用共轴双脉冲LIBS技术定量检测溶液中的腐霉利含量具有一定的可行性,经UVE和CARS方法筛选后可以有效提取腐霉利的特征变量及相关影响变量,剔除冗余及噪声影响变量,简化定量分析模型且提高了定量分析模型的稳定性。     

近红外光谱技术结合变量选择方法定性检测食用植物油中的腐霉利

利用近红外光谱技术对食用植物油中的腐霉利进行定性检测研究。以国家标准规定的腐霉利最大残留限量为界线,将不同腐霉利含量的食用植物油样本分为合格组和不合格组。采用QualitySpec台式近红外光谱仪采集两类样本的光谱,利用无信息变量消除 (UVE)和子窗口重排分析(SPA)方法进行波长变量筛选,并应用线性判别分析(LDA)、偏最小二乘-线性判别分析(PLS-LDA)及判别偏最小二乘(DPLS)方法建立两类样本的分类模型。结果表明,近红外光谱技术可以对两类样本进行分类。UVE方法可以有效筛选有用波长变量,提高分类模型的性能。UVE-DPLS所建立的分类模型性能最优,其预测集样本的分类正确率、灵敏度及特异性分别为98.7%,95.0%和100.0%。