Multiple kinds of pesticide residue detection using fluorescence spectroscopy combined with partial least-squares models
Rendong Ji, Shicai Ma, Hua Yao, Yue Han, Xiao Yang, Ruiqiang Chen, Yinshang Yu, Xiaoyan Wang, Dongyang Zhang, Tiezhu Zhu, Haiyi Bian
Abstract
Compared with high-performance liquid chromatography and mass spectroscopy, fluorescence spectroscopy has attracted considerable attention in the field of pesticide residue detection due to its practical advantages of providing rapid, simultaneous analysis and non-destructive detection. However, given that the concentration of pesticide residue detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescences. Multiple partial least-squares (PLS) models are introduced in this work to overcome this disadvantage and achieve the concentration of zhongshengmycin, paclobutrazol, boscalid, and pyridaben, whose fluorescences are overlapping. The R squares of the models for zhongshengmycin, paclobutrazol, boscalid, and pyridaben were 0.9942, 0.9912, 0.9913, and 0.9847, respectively. Results indicated that fluorescence spectroscopy combined with multiple PLS models can be used to detect multiple kinds of pesticides in the water.