The Recognition of Biological Pesticide Adulteration by Attenuated Total Reflection Infrared Spectroscopy
文献类型: 外文期刊
作者: Li Xiao-ting 1 ; Wand Dong 1 ; Zhu Da-Zhou 3 ; Ma Zhi-hong 1 ; Pan Li-gang 1 ; Wang Ji-hua 1 ;
作者机构: 1.Beijing Res Ctr Agr Stand & Testing, Beijing 100097, Peoples R China
2.Shanghai Jiao Tong Univ, Sch Agr & Biol, Shanghai 200240, Peoples R China
3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词: Infrared spectroscopy;Attenuated total reflection;Partial least squares;Biological pesticides;Adulteration
期刊名称:JOURNAL OF PURE AND APPLIED MICROBIOLOGY ( 影响因子:0.073; )
ISSN:
年卷期:
页码:
收录情况: SCI
摘要: Rapid qualitative and quantitative determination of biological pesticide (Avermectin) adulterated with highly toxic pesticide (Chlorpyrifos) were completed by ATR-FTIR technology. The IR absorbance spectra, the second derivative spectra, the comparative analysis of peak intensity and similarity comparison were used for qualitative analysis. The results showed that with the increase of the proportions of Chlorpyrifos which was adulterated into Abamectin, the number of characteristic absorption peaks belonged to Abamectin decreased, and the peak intensity gradually weakened. Conversely, the number of characteristic absorption peaks attributed to Chlorpyrifos increased, andhe peak intensity gradually strengthened. The quantitative prediction models ofAbamectin EC adulterated with Chlorpyrifos were established by partial least squares regression method and optimized. And then the external validation sets was used to validate the model performance. The results showed that ATR-FTIR technology can accurately determine the content of Abamectin EC adulterated with Chlorpyrifos. The model of prediction precision was improved through spectrum pretreatment, outliers diagnosis and modeling parameters optimization. In addition, the predicted values and the real values had no significant differences. The determination coefficient (R2) was 99.88%. The root mean square error of calibration (RMSEC), the root mean square error of cross-validation (RMSECV) and the root mean square error of prediction (RMSEP) was 0.44, 0.79 and 0.70, respectively. The present study provided a new method for the rapid identification of biological pesticides mixed with chemical pesticides. It also laid a foundation for the application of ATR-FTIR technology to detect biological pesticides.
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