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| An experimental study on rapid detection of the biopesticide avermectin using spectroscopy combined with stoichiometric analysis |
| Received:December 14, 2022 Revised:March 03, 2023 |
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| KeyWord:avermectin;ultraviolet/visible absorption spectra;stoichiometry methods;rapid detection;quantitative analysis |
| Author Name | Affiliation | E-mail | | LI Yanfen | College of Engineering, South China Agricultural University, Guangzhou 510642, China | | | MA Ruijun | College of Engineering, South China Agricultural University, Guangzhou 510642, China | maruijun_mrj@163.com | | CHEN Yu | College of Engineering, South China Agricultural University, Guangzhou 510642, China | chenyu219@126.com | | HUANG Li | College of Engineering, South China Agricultural University, Guangzhou 510642, China | | | YAN Zhenfeng | College of Engineering, South China Agricultural University, Guangzhou 510642, China | | | CAI Xiang | College of Engineering, South China Agricultural University, Guangzhou 510642, China | |
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| Abstract: |
| The biopesticide abamectin is a highly toxic insecticide that is slightly soluble in water. It exhibits a broad spectrum of application and high efficiency. Abamectin shows excellent performance in controlling rice borers and rice leaf rollers, however, it is highly toxic to aquatic organisms. To test the feasibility of rapid detection of avermectin in water through spectroscopy, absorption spectral data of different concentrations in the ultraviolet/visible wavelength range were measured, and a rapid and effective quantitative analysis model was established. Spectroscopic data of avermectin pesticide samples in a certain concentration range were collected with different optical path cuvettes for comparison, and the best spectral data were used for subsequent quantitative processing and analyses. Spectral data with a wavelength range of 200-500 nm were preprocessed using the Savitzky-Golay convolutional smoothing(S-G smoothing)method, and original spectral data and spectral data preprocessed through S-G smoothing were used to divide the samples set according to different proportions using sample set partitioning based on a joint x-y distance(SPXY)algorithm, and PLS models for comparison were established. Then, the spectral data selected after dividing the sample set were selected through principal component analysis(PCA)combined with a Mahalanobis Distance(MD)(PCA-MD)algorithm to eliminate abnormal samples. After removing abnormal samples, the spectral data were screened using the competitive adaptive reweighted sampling(CARS)method to screen the characteristic wavelength variables, and the quantitative analysis model of S-G smoothing-SPXY-(PCA-MD)-CARS-PLS was established. Spectral data results obtained from 100 mm optical path cuvettes were the best, and the characteristic absorption peak of avermectin was at 245.4 nm. The quantitative model established after S-G smoothing preprocessing, SPXY dividing of the sample set, removing abnormal samples by PCA-MD, and screening characteristic wavelength variables by CARS was optimal; the model evaluation coefficient R2p was 0.998 8, RMSEP was 0.061 1, and RPD was 29.589 4. The model was effectively simplified, and its accuracy and robustness were improved. The UV/Vis absorption spectral data of the biopesticide avermectin combined with chemometric analysis can be used to quantify avermectin concentrations. |
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