Dairy flavor is a product of the synergistic interaction between microbial metabolism and processing techniques, with its unique sensory characteristics being critical determinants of product competitiveness and quality control. This review systematically summarizes the formation mechanism of dairy flavor and the principles and applications of major identification, screening, and quality evaluation technologies, with a focus on the advantages, limitations, and complementary relationships of gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, near-infrared (NIR) spectroscopy, nuclear magnetic resonance, and intelligent sensory technologies. Based on a systematic comparison of existing techniques, a “technology characteristic-detection objective-application scenario” matching framework is proposed, aiming to shift the current research paradigm from reliance on “single-technology identification” toward an integrated approach based on “multi-technology fusion perception”. This shift provides a theoretical foundation and technical support for establishing a standardized and intelligent dairy flavor evaluation system. Future developments are expected to focus on the construction of multi-technology collaborative platforms, in-depth interpretation of complex data using artificial intelligence algorithms, and online quality control enabled by miniaturized devices.

For geographical traceability and breed discrimination of lamb meat in Southern Xinjiang, inductively coupled plasma-mass spectrometry was used to analyze the differences in the contents of 25 mineral elements in lamb meat from four local breeds in this region. Characteristic elements were determined by analysis of variance, orthogonal partial least squares-discriminant analysis (OPLS-DA), hierarchical clustering analysis (HCA), and linear discriminant analysis (LDA). The results showed that there were significant differences in the contents of 16 mineral elements including Na, Mg, K, Ca, P, Fe, Zn, Rb, V, Cu, Cr, Se, Sr, Cd, Ag, Cs among lamb meat from different breeds. Furthermore, Se, Mg, P, Sr, and Ag were selected as the characteristic mineral elements for traceability and discrimination. Se, Mg, Sr, and Ag were determined as the characteristic mineral elements in Hetian lamb, P in Celle black lamb, Mg and Sr in Duolang lamb, and Sr in Hetian white lamb. Based on these characteristic elements, a discriminant model was established, and the overall accuracy rate was 100% in both cross-validation and back-validation tests, demonstrating that the five selected mineral elements are effective for distinguishing the lamb meat from four local breeds in Southern Xinjiang, confirming the validity of this model. Therefore, the analytical method based on mineral element differences allows traceability and identification of lamb meat from four local breeds in Southern Xinjiang, which is of great significance for the protection of local specialty sheep breeds in Xinjiang.