Determination of Chlorpyrifos Pesticide Residues in Wheat Based on Near Infrared Spectroscopy

FENG Zhen; LIU Xin; ZHANG Zhen; REN Shuanghe; GUO Zengwang; GUO Yanan; YIN Dong; GUO Liyuan; WANG Zhongjiang

doi:10.13386/j.issn1002-0306.2021020221

Volume 43 Issue 4

Feb. 2022

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Science and Technology of Food Industry > 2022 > 43(4): 271-277. > DOI: 10.13386/j.issn1002-0306.2021020221

FENG Zhen, LIU Xin, ZHANG Zhen, et al. Determination of Chlorpyrifos Pesticide Residues in Wheat Based on Near Infrared Spectroscopy[J]. Science and Technology of Food Industry, 2022, 43(4): 271−277. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021020221.

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Determination of Chlorpyrifos Pesticide Residues in Wheat Based on Near Infrared Spectroscopy

1.
Food College of Northeast Agricultural University, Harbin 150030, China
2.
Shenzhen Sino Assessment Grou, Shenzhen 518110, China
3.
Heilongjiang Puni Testing Technology Company, Harbin 150028, China

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Received Date: February 25, 2021
Available Online: December 17, 2021

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Abstract

Abstract

The identification model of chlorpyrifos pesticide residues in wheat was established based on near infrared spectroscopy and stoichiometry. Wheat samples with different chlorpyrifos residues were prepared by spraying method. Near infrared diffuse reflectance spectra of samples were collected, and qualitative prediction models of factorization method, Euclidean distance method and quantitative prediction model of partial least squares method were established. The results showed that: The qualitative discrimination rate of factorization method was higher than that of Euclidean distance method, the characteristic bands of construction conditions were 5543.68~4643.72, 7582.43~6510.28 cm⁻¹, the preprocessing method was second derivative+vector normalization+5-point smoothing, the discrimination rate could reach 96%. The characteristic bands of the construction conditions of partial least squares quantitative discrimination model were 5543.68~4643.72 cm⁻¹, 7582.43~6510.28 cm⁻¹, the preprocessing method was to eliminate the constant offset, the main component fraction was 7, the cross validation coefficient (R²) was 99.46, and the mean square residual (RMSECV) was 1.15. The correlation between the actual value and the predicted value was good, and the minimum detection limit was 1 mg/kg, which could accurately determine the pesticide of Chlorpyrifos in wheat. The above results showed that the discrimination rate of the qualitative analysis model established by the factorization method was as high as 96%, which could realize the qualitative analysis and identification of chlorpyrifos pesticide residues in wheat, and the partial least squares method could realize the quantitative analysis and identification with good reproducibility.
- near infrared spectroscopy,
- wheat,
- chlorpyrifos,
- Euclidean distance,
- factorization method,
- partial least squares method

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