Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China

Ruting Zhao,Yan Zhao,Ailiang Chen,Shuming Yang,Meicheng Su,Gang Chen

doi:10.3390/foods10051119

Abstract

Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R2 = 0.716, Q2 = 0.614; fatty acid-binding isotopes: R2 = 0.760, Q2 = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R2 = 0.771, Q2 = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting.

Highlights

With the great improvement of people’s living standard, China’s dairy farming industry has greatly developed, and has become the third largest producer in the world
Single or multiple chemical parameter data were analyzed by principal component analysis (PCA) to study any possible milk clustering based on origin
PCA results (Supplementary Materials Figure S1A,B) showed that there was no obvious grouping in the score plots for interprovincial samples, whether a single chemical parameter or the analysis with a combination of chemical parameters; other PCA models had no obvious classification

Summary

Introduction

With the great improvement of people’s living standard, China’s dairy farming industry has greatly developed, and has become the third largest producer in the world. Milk has high nutritional value, and its quality is considered to be related to the geographical location of pasture, forage, water source and other factors. Consumers pay increasingly more attention to the origin of milk, resulting in the economic value of origin information. Traceability of milk origin in China is conducive to the implementation of the protection of regional products. It can effectively prevent the spread of food safety incidents and recall products. The traceability of China is of high importance. The traceability of milk utilizes fatty acids, stable isotopes and mineral elements to identify the geographical origins of dairy products

Methods

Results

Conclusion