Department of Food Science and Technology, Faculty of Agriculture, Urmia University, Urmia, Iran.
Department of Food Science and Technology, Faculty of Agriculture, Urmia University, Urmia, Iran.
Food Chem. 2017 Jun 1;224:390-397. doi: 10.1016/j.foodchem.2016.12.025. Epub 2016 Dec 29.
In this research, honey samples were adulterated with date syrup (DS) and invert sugar syrup (IS) at three concentrations (7%, 15% and 30%). 102 adulterated samples were prepared in six batches with 17 replications for each batch. For each sample, 32 parameters including color indices, rheological, physical, and chemical parameters were determined. To classify the samples, based on type and concentrations of adulterant, a multivariate analysis was applied using principal component analysis (PCA) followed by a linear discriminant analysis (LDA). Then, 21 principal components (PCs) were selected in five sets. Approximately two-thirds were identified correctly using color indices (62.75%) or rheological properties (67.65%). A power discrimination was obtained using physical properties (97.06%), and the best separations were achieved using two sets of chemical properties (set 1: lactone, diastase activity, sucrose - 100%) (set 2: free acidity, HMF, ash - 95%).
在这项研究中，蜂蜜样品被掺入了枣糖浆（DS）和转化糖浆（IS），浓度分别为 7%、15%和 30%。共制备了 102 个掺假样品，分为 6 批，每批有 17 个重复。对于每个样品，测定了 32 个参数，包括颜色指数、流变学、物理和化学参数。为了根据掺杂物的类型和浓度对样品进行分类，应用主成分分析（PCA）和线性判别分析（LDA）进行多元分析。然后，在五组中选择了 21 个主成分（PC）。使用颜色指数（62.75%）或流变学性质（67.65%）可以正确识别大约三分之二的样品。使用物理性质可以获得较高的判别能力（97.06%），而使用两组化学性质（第 1 组：内酯、酶活性、蔗糖-100%）（第 2 组：游离酸度、HMF、灰分-95%）可以获得最佳的分离效果。
