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

应用拉曼光谱技术结合化学计量学方法能有效的实现果蔬中农药残留的定性定量分析。本研究借助实验室自主研发的拉曼光谱检测系统，对苹果中溴氰菊酯和啶虫脒的快速无损识别和检测进行了探索。定性分析时将拉曼峰574 和843 cm-1分别作为识别溴氰菊酯和啶虫脒的拉曼指纹，当苹果中的溴氰菊酯和啶虫脒残留的含量分别为0.78和0.15 mg·kg-1时，两种农药的特征峰仍清晰可见。定量分析首先对光谱进行多种预处理（Savitzky-Golay平滑、一阶导、二阶导、基线校准、标准正态变量变换），结合偏最小二乘法分别建立苹果中溴氰菊酯和啶虫脒含量的定量模型。结果表明，采用8次多项式拟合进行基线校准的预处理方法效果最好，对于溴氰菊酯，偏最小二乘模型预测值与气相色谱法测定值的相关系数和预测均方根误差分别为0.94和0.55 mg·kg-1，对于啶虫脒，其偏最小二乘模型的相关系数与预测均方根误差分别为0.85和0.12 mg·kg-1。本研究证实了利用拉曼技术对苹果农残进行无损检测的可行性，使用该方法进行检测时，在光谱测定前不需要进行前处理，光谱测定后样品无任何损伤，该技术实现了果蔬农残的现场检测，可在检测部门、果蔬加工企业、超市、市场等场所得到推广使用，为果蔬品质安全提供了一种无损、快速和环保的检测方法。

Research on Identification and Determination of Pesticides in Apples Using Raman Spectroscopy

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 (R_p) 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 R_p 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.