An untargeted metabolomics approach based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) fingerprinting was applied to investigate the metabolic differences of black pepper among three geographical origins (Sri Lanka, Vietnam, and Brazil) and two post-harvest processing (sterilized and non-sterilized spice). Principal component analysis (PCA) was employed to assess the overall clustering of samples, whereas supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was effectively used for discrimination purposes. OPLS-DA models were fully validated (R²Y and Q² values > 0.5) and the variable importance in projection (VIP) approach was employed to provide valuable data about differential metabolites with high discrimination potential (8 markers were putatively identified). For origin differentiation, three markers were highlighted with VIP values > 1.5 (i.e. reynosin, artabsinolide D, and tatridin B). Fatty acid derivates were the most frequent markers within the metabolites annotated for processing discrimination (e.g. 10,16-dihydroxyhexadecanoic acid and 9-hydroperoxy-10E-octadecenoic acid). Additionally, different combinations of mid-level data fusion of chromatographic-mass spectrometric techniques (UHPLC and gas chromatography coupled to HRMS) and proton nuclear magnetic resonance spectroscopy (¹H NMR) were evaluated for the first time for geographical and processing discrimination of black pepper. The NMR-UHPLC-GC mid-level fused model was preferred among the tested fusion approaches since good sample clustering and no misclassification were achieved. Enhanced correct classification rate was achieved by mid-level data fusion compared with the findings obtained for one of the individual techniques (¹H NMR fingerprinting) (from 92% to 100% of samples correctly classified). This study opens the path to new metabolomics approaches for black pepper authentication and quality control.

Thyme is an aromatic herb traditionally used for food purposes due to its organoleptic characteristics and medicinal properties, which is highly susceptible to food fraud. In this study, GC-HRMS-based fingerprinting was applied for the first time to determine the geographical traceability of thyme based on different origins (Spain, Poland, and Morocco), as well as to assess its processing by comparing sterilized vs. non-sterilized thyme. Unsupervised chemometric methods (PCA and HCA) revealed a predominant influence of the geographical origin on thyme fingerprints rather than processing effects. Supervised PLS-DA and OPLS-DA were used for discrimination purposes, revealing high predictive ability for further samples (100%), and allowing the identification of differential compounds (markers). A total of 24 markers were putatively identified (13 metabolites were confirmed) belonging to different classes: monoterpenoids, diterpenoids, sesquiterpenoids, alkenylbenzenes, and other miscellaneous compounds. This study outlines the potential of combining untargeted analysis by GC-HRMS with chemometrics for thyme authenticity and traceability.

Black pepper is one of the most consumed spices all over the world. Due to its high demand and nutritional value, a metabolomics approach based on GC-Orbitrap-HRMS fingerprinting and chemometrics was applied to assess its geographical traceability and processing authenticity. GC-HRMS-based fingerprints were obtained using a simple ultrasound-assisted extraction method, which may be easily implemented in routine activities of quality control. Unsupervised methods, such as principal component analysis (PCA), were performed for sample overview according to the investigated origins (Brazil, Vietnam, and Sri Lanka) and processing (sterilized vs nonsterilized samples). Further orthogonal partial least squares discriminant analysis (OPLS-DA) models were validated by cross- and external validation, providing satisfactory performance for geographical and processing authentication, as well as excellent predictive ability for further samples. Furthermore, reliable putative identification of 12 key metabolites (markers) was performed, highlighting the feasibility of combining untargeted GC-HRMS analysis with chemometrics for quality control of black pepper.

Thyme is a culinary herb highly susceptible to increasing mislabeling occurring in the spice industry. In this study, proton nuclear magnetic resonance spectroscopy (¹H NMR) combined with multivariate statistics was successfully applied with two authenticity purposes: (1) tracing thyme metabolic differences among three relevant geographical regions (Morocco, Spain, and Poland), and (2) assessing the influence of sterilization processing on the metabolic fingerprint. Multivariate data analysis provided six and seven key geographical and processing markers, respectively, including thymol, organic acids, chlorogenic acid, and some carbohydrates (e.g., sucrose). Additionally, for the first time, a mid-level data fusion approach was tested for thyme authenticity combining three complementary and synergic analytical platforms: gas and liquid chromatography coupled with high-resolution mass spectrometry, and ¹H NMR spectroscopy, providing a comprehensive metabolomics insight into the origin and processing effects on thyme fingerprinting, and opening the path to new metabolomics approaches for quality control in the spice industry.