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

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.

Microwave-Assisted Digestion Using Dilute Nitric Acid and Hydrogen Peroxide for Multielement Determination in Wheat Flour by ICP-MS

“…Multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), is used to process a large amount of data, assisting in the interpretation of the results [21]. In food analysis, these techniques are often used in classifcation, determination of the geographic origin, and evaluation of the viability of samples according to their chemical properties [21][22][23][24][25][26][27].…”

Stable Isotope and Element Profiling for Determining the Agroclimatic Origin of Cow Milk within a Tropical Country

“…Further, another feasibility study conducted in New Zealand has shown that the δ 13 C and δ 15 N isotopes of milk casein reflect the inherent geo-climatic variation across dairy farms sampled in the south and north islands [17]. Several studies conducted with milk samples collected from various provinces in China have successfully shown the ability of stable isotopes to verify the geographic origin [18,19].…”

Proposing Two Local Modeling Approaches for Discriminating PGI Sunite Lamb from Other Origins Using Stable Isotopes and Machine Learning

“…In order to protect the PGI products, researchers have put forward a fingerprint tracing method, that is, using chemical parameters to build the fingerprint of geographical indication products [ 4 ] and comparing it with the fingerprint of the testing sample to determine whether the testing sample is the geographical indication product. At present, the chemical parameters used in the traceability of animal-origin food include stable isotopes [ 5 ], mineral elements [ 6 ], fatty acid content [ 7 , 8 ], amino acid content [ 9 ], and metabolites [ 10 ]. Stable isotopes are commonly used to characterize geographical origin information and to describe agricultural products’ origin information, where δ 2 H and δ 18 O can be used to distinguish altitude, δ 15 N can be used to determine the type of grazing vegetation, and δ 13 C can determine the type of animal feed [ 11 ].…”