Zhang Yan-nan, Chen Lan-zhen, Xue Xiao-feng, Wu Li-ming, Li Yi, Yang Juan
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Sep;35(9):2536-9.
At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.
目前,大米糖浆作为一种价格低廉的甜味剂常被掺入刺槐蜂蜜中,掺假蜂蜜在蜂蜜市场上销售,而目前尚无合适且快速的方法来鉴别掺有大米糖浆的蜂蜜。本研究采用近红外光谱(NIR)结合化学计量学方法来鉴别蜂蜜的真伪。制备了来自不同蜂蜜产区的20个未加工刺槐蜂蜜样品,将其与不同比例的大米糖浆混合,形成包括121个样品的7种不同浓度梯度。分别使用近红外光谱(NIR)仪器和光谱处理软件对掺假样品进行光谱扫描和数据转换。然后通过主成分分析(PCA)和典型判别分析方法进行分析,以鉴别掺假蜂蜜。结果表明,主成分分析后,前两个主成分占总变异的97.23%,但前两个主成分得分图的地域特征不明显,因此采用典型判别分析进行进一步判别,所有样品均被正确判别,前两个判别函数在六个典型判别函数中占91.6%,不同浓度的掺假样品也能被正确判别,说明近红外光谱结合典型判别分析方法对于快速、有效地鉴别刺槐蜂蜜中大米糖浆掺假不仅可行而且实用。