Chemometric Discrimination of Typical Regional Chinese Baijiu Using Multielement Indicators and Multivariate Statistical Analysis

Baijiu, a traditional Chinese distilled spirit with cultural and economic significance, faces authenticity challenges from counterfeiting and lacks systematic studies of elemental fingerprints and health risks. In this study, 15 mineral elements in Baijiu samples from Beijing, Shandong, and Guizhou were analyzed using ICP-OES and ICP-MS. Multivariate statistical methods (ANOVA, PCA, PLS-DA, OPLS-DA) identified Mn, Na, Zn, Ca, Mg, and Sr as the major contributors to sample discrimination, with PLS-DA achieving 79.6% classification accuracy. By applying the THQ model, this study assessed heavy metal risks under both moderate and excessive drinking scenarios for males and females. All calculated THQ values were well below the safety threshold of 1.0, indicating negligible health risks regardless of sex or consumption level. This work emphasizes regional provenance, offering fresh insights into how soil and water geochemistry shape Baijiu’s elemental profiles. By integration of elemental-based classification with risk assessment, this study provides a dual-purpose framework for authenticity verification and consumer protection.