期刊
FOOD ANALYTICAL METHODS
卷 12, 期 11, 页码 2572-2581出版社
SPRINGER
DOI: 10.1007/s12161-019-01610-8
关键词
Saffron; Elemental analysis; Classification; Class-modeling; Authentication
PDO (protected designation of origin) Zafferano dell'Aquila (AQ), Iranian (IR), and commercial (CS) saffron samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The ICP-MS data of 30 elements were handled by unsupervised (principal component analysis (PCA)) and supervised (linear discriminant analysis (LDA)) multivariate statistical methods to identify a subset of discriminant variables useful for geographical classification. Moreover, class modeling of AQ saffron was performed by both UNEQ (unequal disperses classes) and SIMCA (soft independent modeling of class analogy) methods. A good differentiation of the AQ, IR, and CS samples was obtained by the LDA based on four selected elements: Sr, Ca, Mo, and Fe. A UNEQ class model for the PDO AQ saffron based on the above four elements provided 100% sensitivity (all authentic AQ saffron were accepted) and 100% specificity (all IR and CS were rejected), while slightly worse results were obtained using the SIMCA (89% sensitivity and 96% specificity).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据