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• RSM was applied for optimizing the extraction process of minor curcuminoids. • MRM parameters including DP and CE for each curcuminoid were optimized. • The established method could discriminate turmeric samples from different origins. • This study was useful for discriminating other geo-authentic and non-authentic herbs. In this research, a three-step strategy was utilized for discriminating turmeric samples from different provinces and regions in China. Firstly, MRM-based UPLC-MS/MS method for chemical profiling of curcuminoids in turmeric samples was established. Then, response surface methodology was applied for optimizing the extraction process of targeted curcuminoids. Finally, multivariate analysis was conducted for systematic characterization of 66 curcuminoids in turmeric. Principal component analysis (PCA) and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) revealed that turmeric samples from Sichuan and other regions could be classified into two distinct groups. Turmeric samples from the same group had similar curcuminoids content distribution. 25 differential curcuminoids were discovered through OPLS-DA, among which most curcuminoids were more abundant in Sichuan. Furthermore, turmeric samples from different provinces could be clearly discriminated based on hierarchical cluster analysis (HCA) using the screened differential curcuminoids. [ABSTRACT FROM AUTHOR]

• For the first time, GC×GC-TOFMS was used to classify strong aroma-type baijiu (SAB) from different regions. • The SAB samples from two different basins in China were clearly separated in PCA score plots. • The predictive ability of the PLS-DA model was excellent, correctly classifying 100% of the unknown SAB samples. • Twenty-three potential markers were identified using standard compounds. • The HCA result showed that the selected markers offered strong discrimination power. A metabolomics strategy was developed to differentiate strong aroma-type baijiu (SAB) (distilled liquor) from the Sichuan basin (SCB) and Yangtze-Huaihe River Basin (YHRB) through liquid–liquid extraction coupled with GC×GC-TOFMS. PCA effectively separated the samples from these two regions. The PLS-DA training model was excellent, with explained variation and predictive capability values of 0.988 and 0.982, respectively. As a result, the model demonstrated its ability to perfectly differentiate all the unknown SAB samples. Twenty-nine potential markers were located by variable importance in projection values, and twenty-four of them were identified and quantitated. Discrimination ability is closely correlated to the characteristic flavor compounds, such as acid, esters, furans, alcohols, sulfides and pyrazine. Most of the marker compounds were less abundant in the SCB samples than in the YHRB samples. The quantitated markers were further processed using hierarchical cluster analysis for targeted analysis, indicating that the markers had great discrimination power to differentiate the SAB samples. [ABSTRACT FROM AUTHOR]