CAJ | 학술논문

应用表面增强拉曼光谱（surface‐enhanced Raman spectroscopy ，SERS）技术，结合线性回归算法，开展蜂蜜乐果中农药残留快速定量分析方法研究。含乐果农药残留的益母草蜂蜜样品30个作为被测对象，划分成建模集（20个）和预测集（10个）。采用具有规则倒四角锥体结构的Klarite基底作为增强基底，提高特征拉曼位移峰的相对强度。通过含乐果农药残留蜂蜜样品的SERS光谱与乐果标准品的常规拉曼光谱间的对比分析，找到了蜂蜜中乐果农药残留对应的四个特征拉曼位移峰867，1065，1317和1453 cm －1。采用线性回归方法，建立了蜂蜜中乐果农药残留对应的四个特征拉曼位移峰强与乐果浓度间的线性回归模型。10个未参与建模的预测集样品，评价了模型的预测能力。经比较，采用867 cm －1处特征拉曼位移峰强建立的线性回归模型预测结果最优，模型预测相关系数为0.984，预测均方根误差为0.663 ppm。检测限达到2 ppm ，接近我国农药残留最大限量标准的检测限。实验结果表明采用表面增强拉曼光谱技术结合线性回归算法实现蜂蜜中乐果农药残留的快速定量分析是可行的。可为其他农产品的农药残留快速定量分析提供参考依据。
응용표면증강랍만광보（surface‐enhanced Raman spectroscopy ，SERS）기술，결합선성회귀산법，개전봉밀악과중농약잔류쾌속정량분석방법연구。함악과농약잔류적익모초봉밀양품30개작위피측대상，화분성건모집（20개）화예측집（10개）。채용구유규칙도사각추체결구적Klarite기저작위증강기저，제고특정랍만위이봉적상대강도。통과함악과농약잔류봉밀양품적SERS광보여악과표준품적상규랍만광보간적대비분석，조도료봉밀중악과농약잔류대응적사개특정랍만위이봉867，1065，1317화1453 cm －1。채용선성회귀방법，건립료봉밀중악과농약잔류대응적사개특정랍만위이봉강여악과농도간적선성회귀모형。10개미삼여건모적예측집양품，평개료모형적예측능력。경비교，채용867 cm －1처특정랍만위이봉강건립적선성회귀모형예측결과최우，모형예측상관계수위0.984，예측균방근오차위0.663 ppm。검측한체도2 ppm ，접근아국농약잔류최대한량표준적검측한。실험결과표명채용표면증강랍만광보기술결합선성회귀산법실현봉밀중악과농약잔류적쾌속정량분석시가행적。가위기타농산품적농약잔류쾌속정량분석제공삼고의거。
The feasibility of a combination method of surface‐enhanced Raman spectroscopy (SERS) technology and linear re‐gression algorithm was investigated for rapid quantitative analysis of pesticide residues in honey .The total of 30 samples was ap‐plied in the experiment with dimethoate pesticide residues range from 1 ppm to 10 ppm .The samples were divided into calibra‐tion set (20) and prediction set (10) .The substrate of Klarite with an inverted pyramidal structure was adopted for improvement of the relative intensity of the majority of Raman shift peaks .The comparative analysis was carried out between SERS spectra of dimethoate pesticide residues in honey samples and conventional Raman spectra of dimethoate standard sample .And four charac‐teristic Raman shift peaks at the wavenumbers of 867 ,1 065 ,1 317 and 1 453 cm -1 were found ,which were related with the vi‐brational information of dimethoate molecule .The relationship was developed by linear regression algorithm between the intensi‐ty of Raman shift and the concentration of dimethoate pesticide residues .The 10 new samples in the prediction set were applied to evaluate the performance of the models .By comparison ,the optimal model was obtained with the characteristic Raman shift peak of 867 cm-1 .The higher correlation coefficient of prediction of 0.984 and lower root mean square error of prediction of 0.663 ppm were obtained .The detection limit of this method was 2 ppm ,which was close to the maximum levels of pesticide residue detection limits .Experimental results showed that it was feasible to rapidly analyze quantitative of pesticide residues in honey with the combination method of SERS technology and linear regression algorithm .Compared with the conventional method coupled with the suitable pretreatment ,the combination method of SERS technology and linear regression method could analyze the dimethoate pesticide residues in honey ,and it also provided an optional method for rapid quantitative analysis pesticide resi‐dues in other agricultural products .