Abstract：Raman spectroscopy combined with chemometric methods has been thought to an efficient method for identification and determination of pesticide residues in fruits and vegetables. In the present research, a rapid and nondestructive method was proposed and testified based on self-developed Raman system for the identification and determination of deltamethrin and acetamiprid remaining in apple. The peaks of Raman spectra at 574 and 843 cm-1 can be used to identify deltamethrin and acetamiprid, respectively, the characteristic peaks of deltamethrin and acetamiprid were still visible when the concentrations of the two pesticides were 0.78 and 0.15 mg·kg-1 in apples samples, respectively. Calibration models of pesticide content were developed by partial least square (PLS) algorithm with different spectra pretreatment methods (Savitzky-Golay smoothing, first derivative transformation, second derivative transformation, baseline calibration, standard normal variable transformation). The baseline calibration methods by 8th order polynomial fitting gave the best results. For deltamethrin, the obtained prediction coefficient (Rp) value from PLS model for the results of prediction and gas chromatography measurement was 0.94; and the root mean square error of prediction (RMSEP) was 0.55 mg·kg-1. The values of Rp and RMSEP were respective 0.85 and 0.12 mg·kg-1 for acetamiprid. According to the detect performance, applying Raman technology in the nondestructive determination of pesticide residuals in apples is feasible. In consideration of that it needs no pretreatment before spectra collection and causes no damage to sample, this technology can be used in detection department, fruit and vegetable processing enterprises, supermarket, and vegetable market. The result of this research is promising for development of industrially feasible technology for rapid, nondestructive and real time detection of different types of pesticide with its concentration in apples. This supplies a rapid nondestructive and environmentally friendly way for the determination of fruit and vegetable quality and safety.
翟 晨，彭彦昆*，李永玉，DHAKAL Sagar，徐田锋，郭浪花 . 基于拉曼光谱的苹果中农药残留种类识别及浓度预测的研究 [J]. 光谱学与光谱分析, 2015, 35(08): 2180-2185.
ZHAI Chen, PENG Yan-kun*, LI Yong-yu, DHAKAL Sagar, XU Tian-feng, GUO Lang-hua . Research on Identification and Determination of Pesticides in Apples Using Raman Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(08): 2180-2185.
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