基于OMWTTFA的豇豆多农药残留非靶向检测方法研究

A non-targeted detection method of multi-pesticide residues in cowpea based on OMWTTFA

针对豇豆多农药残留检测难度不断增大的问题,在移动窗口目标转换因子分析(MWTTFA)算法基础上增加了自适应迭代重加权惩罚最小二乘计算步骤,提出一种优化移动窗口目标转换因子分析(OMWT-TFA)算法,结合气相色谱-质谱(GC-MS)联用技术,建立一种豇豆多农药残留非靶向检测新方法。通过建立500种常见农药MS数据库,利用OMWTTFA算法对豇豆GC-MS数据进行高通量解析,采用实际豇豆样品及加标样品对该方法进行验证。结果表明:该方法可在30.00 min保留时间内实现两组豇豆加标样品中所有农药残留的非靶向检测,实际豇豆样品中未检出农药残留;检出组分的匹配度均超过800‰,准确性优于MWTTFA算法,有望成为果蔬多农药残留非靶向高通量检测的新途径。

To the increasing difficulty of the detection of multi-pesticide residues in cowpea,optimized moving window target conversion factor analysis(OMWTTFA)algorithm was proposed,in which an adaptive iterative re-weighted penalized least squares calculation had been added to the moving window target transfer factor analysis(MWTTFA)algorithm.And a new method for non-targeted detection of multi-pesticide residues in cowpea was established by combining with gas chromatography-mass spectrometry(GC-MS).A mass spectrometry database of 500 common pesticides was established and high throughput analysis of cowpea GC-MS data was realized by using OMWTTFA algorithm.The method was verified with actual cowpea and spiked samples.The results showed that the method could realize non-targeted detection of all pesticide residues in the two groups of spiked cowpea samples within 30 min retention time,while no pesticide residues were detected in the actual cowpea samples.The matching values of all components were larger than 800‰,and this method was more accurate than MWTTFA algorithm.The above results showed that this method promised to become a new way for non-targeted and high-throughput detection of multi-pesticide residues in fruits and vegetables.