NMR-Based Approaches in the Study of Foods

NMR Metabolite Profiling and Antioxidant Properties of Spartan, Jewels, Misty, and Camelia Blueberries

The health-promoting properties of blueberries are widely recognized and are mainly attributed to anthocyanins. However, fruit's chemical composition includes also other components and strongly depends on varieties and climatic conditions. Here, 1H NMR metabolite profiling and biological activity of four blueberry cultivars (Spartan, Jewels, Misty, Camelia) grown in Central Italy over two years were reported. Untargeted and targeted NMR analyses allowed the quantification of sugars, organic acids, amino acids, anthocyanins, lipids, and other compounds. Spectrophotometric assays evaluated total phenolic and flavonoid content, antioxidant activity, and enzyme inhibitory activity toward cholinesterase, α-amylase, α-glucosidase, and tyrosinase. Statistical analysis showed a correlation between chemical composition and biological activity, revealing markers specific to blueberry cultivars (quinic acid, quercitrin, myo-inositol, myrtillin, and petunidin-3-O-glucoside). Almost all antioxidant assays were correlated with the chlorogenic acid levels. A strong effect of harvesting on chemical composition and biological activities was observed, with Misty cultivar having the highest antioxidant activity.

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

NMR Metabolomics and Chemometrics of Commercial Varieties of Phaseolus vulgaris L. Seeds from Italy and In Vitro Antioxidant and Antifungal Activity

The metabolite fingerprinting of four Italian commercial bean seed cultivars, i.e., Phaseolus Cannellino (PCANN), Controne (PCON), Vellutina (PVEL), and Occhio Nero (PON), were investigated by Nuclear Magnetic Resonance (NMR) spectroscopy and multivariate data analysis. The hydroalcoholic and organic extract analysis disclosed more than 32 metabolites from various classes, i.e., carbohydrates, amino acids, organic acids, nucleosides, alkaloids, and fatty acids. PVEL, PCON, and PCANN varieties displayed similar chemical profiles, albeit with somewhat different quantitative results. The PON metabolite composition was slightly different from the others; it lacked GABA and pipecolic acid, featured a higher percentage of malic acid than the other samples, and showed quantitative variations of several metabolites. The lipophilic extracts from all four cultivars demonstrated the presence of omega-3 and omega-6 unsaturated fatty acids. After the determination of the total phenolic, flavonoids, and condensed tannins content, in vitro antioxidant activity was then assessed using the DPPH scavenging activity, the ABTS scavenging assay, and ferric-reducing antioxidant power (FRAP). Compared to non-dark seeds (PCON, PCANN), brown seeds (PVEL, PON) featured a higher antioxidant capacity. Lastly, only PON extract showed in vitro antifungal activity against the sclerotia growth of S. rolfsii, by inhibiting halo growth by 75%.

From Nontargeted to Targeted Analysis: Feature Selection in the Differentiation of Truffle Species (Tuber spp.) Using 1H NMR Spectroscopy and Support Vector Machine

The price of different truffle types varies according to their culinary value, sometimes by more than a factor of 10. Nonprofessionals can hardly distinguish visually the species within the white or black truffles, making the possibility of food fraud very easy. Therefore, the identification of different truffle species (Tuber spp.) is an analytical task that could be solved in this study. The polar extract from a total of 80 truffle samples was analyzed by 1H NMR spectroscopy in combination with chemometric methods covering five commercially relevant species. All classification models were validated applying a repeated nested cross-validation. In direct comparison, the two very similar looking and closely related black representatives Tuber melanosporum and Tuber indicum could be classified 100% correctly. The most expensive truffle Tuber magnatum could be distinguished 100% from the other relevant white truffle Tuber borchii. In addition, signals for a potential Tuber borchii and a potential Tuber melanosporum marker for targeted approaches could be detected, and the corresponding molecules were identified as betaine and ribonate. A model covering all five truffle species Tuber aestivum, Tuber borchii, Tuber indicum, Tuber magnatum, and Tuber melanosporum was able to correctly discriminate between each of the species.

Multivariate Statistical Models for the Authentication of Traditional Balsamic Vinegar of Modena and Balsamic Vinegar of Modena on 1H-NMR Data: Comparison of Targeted and Untargeted Approaches

This work aimed to compare targeted and untargeted approaches based on NMR data for the construction of classification models for Traditional Balsamic Vinegar of Modena (TBVM) and Balsamic Vinegar of Modena (BVM). Their complexity in terms of composition makes the authentication of these products difficult, which requires the employment of several time-consuming analytical methods. Here, ¹H-NMR spectroscopy was selected as the analytical method for the analysis of TVBM and BVM due to its rapidity and efficacy in food authentication. ¹H-NMR spectra of old (>12 years) and extra-old (>25 years) TVBM and BVM (>60 days) and aged (>3 years) BVM were acquired, and targeted and untargeted approaches were used for building unsupervised and supervised multivariate statistical modes. Targeted and untargeted approaches were based on quantitative results of peculiar compounds present in vinegar obtained through qNMR, and all spectral variables, respectively. Several classification models were employed, and linear discriminant analysis (LDA) demonstrated sensitivity and specificity percentages higher than 85% for both approaches. The most important discriminating variables were glucose, fructose, and 5-hydroxymethylfurfural. The untargeted approach proved to be the most promising strategy for the construction of LDA models of authentication for TVBM and BVM due to its easier applicability, rapidity, and slightly higher predictive performance. The proposed method for authenticating TBVM and BVM could be employed by Italian producers for safeguarding their valuable products.

Investigation of Solid Phase Microextraction Gas Chromatography–Mass Spectrometry, Fourier Transform Infrared Spectroscopy and 1H qNMR Spectroscopy as Potential Methods for the Authentication of Baijiu Spirits

The baijiu spirit is often the focus of fraudulent activity due to the widely varying prices of the products. In this work, Solid Phase Microextraction Gas Chromatography (SPME GCMS), Fourier Transform Infrared (FTIR) Spectroscopy and 1H qNMR spectroscopy were evaluated as potential methods to authenticate baijiu samples. Data were collected for 30 baijiu samples produced by seven different distilleries. The data from the SPME GCMS and FTIR methods were treated by a Principal Component Analysis to identify clusters that would suggest chemical differences in the products from different distilleries. The results suggest that SPME GCMS has the potential to be a fully portable method for baijiu authentication. FTIR did not appear suitable for authentication but can be used to find the %ABV range of the sample. 1H quantitative NMR (1H qNMR) was utilized to quantify the ethanol concentrations and calculate the observable congener chemistry comprising ester, ethanol, methanol, fusel alcohol, and organic acids. Discrepancies in ethanol content were observed in three samples, and a lack of major congeners in two samples indicates the possible presence of a counterfeit product. Detailed and quantitative congener chemistry is obtainable by NMR and provides a possible fingerprint analysis for the authentication and quality control of baijiu style, producer, and the length of the ageing process.