WANG Mohan, GAO Ming, LI Yali, et al. Traceability Technology of Milk Origin Based on Stable Isotope and Mineral Elements[J]. Science and Technology of Food Industry, 2022, 43(3): 284−290. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021060282.
Citation: WANG Mohan, GAO Ming, LI Yali, et al. Traceability Technology of Milk Origin Based on Stable Isotope and Mineral Elements[J]. Science and Technology of Food Industry, 2022, 43(3): 284−290. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021060282.

Traceability Technology of Milk Origin Based on Stable Isotope and Mineral Elements

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  • Received Date: July 01, 2021
  • Available Online: December 02, 2021
  • With the development of the dairy industry, the safety of milk quality had attracted much attention. Top-brand dairy products with specific origins or grass-fed claims were emerging in an endless stream, so the traceability of the milk origin had also become an urgent need. In this study, four stable isotope ratios of δ13C, δ15N, δ2H, δ18O in milk samples of Heilongjiang Province, Yunnan Province, Hebei Province, Gansu Province and Inner Mongolia Autonomous Region were determined respectively, as well as three mineral elements mass concentration of calcium, iron and zinc. Data models combined with multivariate statistical analysis of 5 milk regions was established. This research explored the application prospects of stable isotopes and mineral elements in the milk traceability and developed a milk traceability technology based on them. The results showed that the stable isotope ratios δ13C, δ15N, δ2H, δ18O and the mineral elements calcium and zinc in milk had significant differences based on regions (P<0.05), which could be used as the basis for the identification of breeding mode and origin, while the difference in iron had no significant (P>0.05). Cluster analysis and principal component analysis could effectively distinguish the samples from Gansu Province, but there was a certain crossover among other regions. All regions could be effectively distinguished through discriminant analysis, the original discrimination rate was 100% and 96% in cross-validation. Traceability technology of milk origin developed by this research could realize effective origin traceability, and provide strong technical support for controlling milk sources and boosting consumer confidence.
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