journal article·2019-04-24Open access

A Correction Method of Mixed Pesticide Content Prediction in Apple by Using Raman Spectra

Yan Li, Yankun Peng, Jianwei Qin, Kuanglin Chao

Applied Sciences· Volume 9· Issue 8

Abstract

In the study, a new correction method was applied to reduce error during Raman spectral detection on mixed pesticide residue in apples. Combined with self-built pesticide residues detection system by Raman spectroscopy and the application of surface enhancement technology, rapid real-time qualitative and quantitative analysis of deltamethrin and acetamiprid residues in apples could be applied effectively. In quantitative analysis, compared with the intensity value of characteristic peaks of single pesticide with same concentration, the intensity value of characteristic peaks of the two pesticides decreased after mixing the pesticides, which affected the results severely. By comparing the difference in the intensity of characteristic peaks of single and mixed pesticides, a correction method was proposed to eliminate the influence of pesticides mixture. Characteristic peak intensity values of gradient concentration pesticide from 100 mg·kg−1 to 10−3 mg·kg−1 and Lagrangian interpolation were applied in the correction method. And a smooth surface was applied to describe the correction coefficient of characteristic peak intensity. Through detecting the characteristic peak intensity values of the mixed pesticide, correction coefficient would be obtained. Then real values of the peak intensity of pesticides and the content of each component of the mixed pesticide would be acquired by the correction method. Correlation coefficient of model validation exceeded 0.88 generally and Root Mean Square Error also decreased obviously after correction, which proved the reliability of the method.
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Research context

OpenAlex topics: Spectroscopy and Chemometric Analyses · Pesticide Residue Analysis and Safety · Spectroscopy Techniques in Biomedical and Chemical Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

National Research and Development Center for Agro-processing Equipment, College of Engineering, China Agricultural University, Beijing 100083, China

USDA-ARS Environmental Microbial and Food Safety Laboratory, Building 303, BARC-East, Beltsville, MD 20705, USA

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