Geographical differentiation of garlic based on HS-GC-IMS combined with multivariate statistical analysis

Garlic is famous for its unique flavor and health benefits. An effective means of authenticating garlic's origin is through the implementation of the Protected Geographical Indication (PGI) scheme. However, the prevalence of fraudulent behavior raises concerns regarding the reliability of this system. In this study, garlic samples from six distinct production areas (G1: Cangshan garlic, G2: Qixian garlic, G3: Dali single clove garlic, G4: Jinxiang garlic, G5: Yongnian garlic, and G6: Badong garlic) underwent analysis using HS-GC-IMS. A total of 26 VOCs were detected in the samples. The differences in VOCs among the different garlic samples were visually presented in a two-dimensional topographic map and fingerprint map. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to demonstrate the capacity of the HS-GC-IMS method for effectively distinguishing garlic samples from different geographical sources. Further screening based on the p-value and VIP score threshold identified 12 different aroma substances, which can be utilized for the identification of garlic from different producing areas. The fusion of HS-GC-IMS with multivariate statistical analysis proved to be a rapid, intuitive, and efficient approach for identifying and categorizing garlic VOCs, offering a novel strategy for ascertaining garlic origin and ensuring quality control. In this work, HS-GC-IMS combined with multivariate modeling was used to characterize the PGI garlic source.