Determining the geographical origin of milk by multivariate analysis based on stable isotope ratios, elements and fatty acids. Issue 22 (20th May 2021)

• Record Type: Journal Article
• Authors: Xu, Siyan; Zhao, Chaomin; Deng, Xiaojun; Zhang, Runhe; Qu, Li; Wang, Min; Ren, Shuo; Wu, Hao; Yue, Zhenfeng; Niu, Bing
• Is Part Of: Analytical methods. Volume 13:Issue 22(2021)
• Page Start: 2537
• Page End: 2548
• Publication Date: 2021-05-20
• Subjects: Chemistry, Analytic -- Periodicals; Analytical biochemistry -- Periodicals; Chemical laboratories -- Standards -- Periodicals; 543.1905
• DOI: 10.1039/d1ay00339a
• Languages: English
• ISSNs: 1759-9660

Abstract

Abstract : Based on three types of variables (stable isotope ratios, elements and fatty acids), a robust OPLS-DA model that is capable of classifying origin countries of milk samples could be built. Abstract : To construct a reliable discrimination model for determining milk geographical origin, stable isotope ratios including δ 13 C, δ 15 N and δ 18 O, 51 elements and 35 fatty acids (FAs) in milk samples from Australia, New Zealand and Austria were detected and analyzed. It is found that all of the stable isotope ratios in the milk samples of Australia are the highest, followed by those of the samples from New Zealand and Austria. In addition, 14 elements and 8 FAs show different contents in the samples of different countries at the significance level of P < 0.05. Based on these results, a multivariate model with good robustness and predictive ability for authenticating milk origin ( R 2 X = 0.693, Q 2 = 0.854) was successfully constructed. Element contents and stable isotope ratios are more reliable variables for milk origin discrimination and Rb, δ 18 O, Tl, Ba, Mo, Sr, δ 15 N, Cs, As, Eu, C20:4n6, Sc, C13:0, K, Ca and C16:1n7 are the critical markers in the multivariate model for verifying milk origin.