近红外透反射光谱用于检测蜂蜜加入麦芽糖浆掺假

Detection of honey adulteration by addition of maltose syrup using near-infrared transflectance spectroscopy

为实现蜂蜜掺假的快速检测,利用近红外光谱法(NIRS)对蜂蜜用麦芽糖浆掺假进行了研究。从121个真蜂蜜样本中任取8个不同品种掺假,共得80个掺假样本。另取两个真蜂蜜样本(油菜蜜和向日葵蜜)掺假,各自得到50个掺假样本。KS法划分校正集和验证集。偏最小二乘-线性判别分析法(PLS-LDA)鉴别真假蜂蜜,校正集和验证集的识别正确率都达100%。用CARS(competitive adaptive reweighted sampling)-偏最小二乘法(CARS-PLS)对掺假量定量校正,80个掺假样本的结果不理想,而50个掺假样本的结果令人满意:交互验证均方差(RMSECV)、交互验证决定系数(Q2)、预测均方差(RMSEP)、预测决定系数(R2),掺假油菜蜜模型分别为0.2529、0.9995、0.1851、0.9996;掺假向日葵蜜模型分别为0.1141、0.9999、0.1673、0.9997。因此,NIRS具有对蜂蜜用麦芽糖浆掺假快速检测的能力。

Near infrared spectroscopy（NIRS） was used to detect honey adulteration by addition of maltose syrup.8 different varieties of 121 authentic honey samples were adulterated with maltose syrup,thus producing 80 adulterated honey samples.Two other authentic honey samples（rape honey and sunflower honey） were also adulterated,thus respectively producing 50 adulterated honey samples.Kennard-stone（KS） was used to divide calibration and validation.Partial least squares-line discriminant analysis（PLS-LDA） was used to identify honeys as authentic or adulterated honey samples,the corrected identification rate of calibration and validation were all 100%.Competitive adaptive reweighted sampling-partial least squares regretssion（CARS-PLS） was used to predict the adulteration level,The model results of 80 adulterated honey samples was unfavorable,but the models results of 50 adulterated honey samples were all favorable： RMSECV,Q2,RMSEP and R2 were respectively 0.2529,0.9995,0.1851 and 0.9996 for 50 adulterated rape honey samples,while for 50 adulterated sunflower honey samples,respectively 0.1141,0.9999,0.1673 and 0.9997.The results demonstrated that NIRS had a ability to detect honey adulteration by addition of maltose syrup.