偏最小二乘回归
荧光光谱法
光谱学
残留物(化学)
杀虫剂
多效唑
荧光
分析化学(期刊)
农药残留
色谱法
生物系统
化学
化学计量学
检出限
数学
光学
物理
统计
生态学
生物
农学
量子力学
生物化学
作者
Rendong Ji,Shicai Ma,Hua Yao,Yue Han,Xiao Yang,Ruiqiang Chen,Yinshang Yu,Xiaoyan Wang,Dongyang Zhang,Tiezhu Zhu,Haiyi Bian
出处
期刊:Applied Optics
[Optica Publishing Group]
日期:2020-01-08
卷期号:59 (6): 1524-1524
被引量:10
摘要
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.
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