Monitoring the metabolite content of seasoned zucchinis during storage by NMR-based metabolomics

This study applied 1H NMR metabolomics to monitor the metabolite content of baked and seasoned zucchinis packaged in both compostable and plastic trays. Polar extracts of samples stored at 4 °C up to 35 days were investigated to check for metabolite changes upon shelf life. The evolution of the integral values of only the main metabolites responsible for sample differentiation (lactate, acetate, malate, α and β glucose and sucrose) were further analysed and compared. In particular, the evaluation of lactate and acetate amount, considered markers of fermentation progress, showed a comparable performance for the two types of packaging in preserving the freshness of seasoned zucchinis, confirming the maintenance of food product composition within the declared shelf life period in the recommended storage conditions. Albeit preliminary, the results support the NMR metabolomics as a tool for identifying candidate metabolites to monitor the shelf life of foods, thereby improving the understanding of molecular changes during storage.

NMR-Based Metabolomic Study on Phaseolus vulgaris Flour Fermented by Lactic Acid Bacteria and Yeasts

In recent years, fermented foods have attracted increasing attention due to their important role in the human diet, since they supply beneficial health effects, providing important sources of nutrients. In this respect, a comprehensive characterization of the metabolite content in fermented foods is required to achieve a complete vision of physiological, microbiological, and functional traits. In the present preliminary study, the NMR-based metabolomic approach combined with chemometrics has been applied, for the first time, to investigate the metabolite content of Phaseolus vulgaris flour fermented by different lactic acid bacteria (LAB) and yeasts. A differentiation of microorganisms (LAB and yeasts), LAB metabolism (homo- and heterofermentative hexose fermentation), LAB genus (Lactobacillus, Leuconostoc, and Pediococcus), and novel genera (Lacticaseibacillus, Lactiplantibacillus, and Lentilactobacillus) was achieved. Moreover, our findings showed an increase of free amino acids and bioactive molecules, such as GABA, and a degradation of anti-nutritional compounds, such as raffinose and stachyose, confirming the beneficial effects of fermentation processes and the potential use of fermented flours in the production of healthy baking foods. Finally, among all microorganisms considered, the Lactiplantibacillus plantarum species was found to be the most effective in fermenting bean flour, as a larger amount of free amino acids were assessed in their analysis, denoting more intensive proteolytic activity.

The potentiality of NMR-based metabolomics in food science and food authentication assessment

In the last years, there was an increasing interest on nuclear magnetic resonance (NMR) spectroscopy, whose applications experienced an exponential growth in several research fields, particularly in food science. NMR was initially developed as the elective technique for structure elucidation of single molecules and nowadays is playing a dominant role in complex mixtures investigations. In the era of the "omics" techniques, NMR was rapidly enrolled as one of the most powerful methods to approach metabolomics studies. Its use in analytical routines, characterized by rapid and reproducible measurements, would provide the identification of a wide range of chemical compounds simultaneously, disclosing sophisticated frauds or addressing the geographical origin, as well as revealing potential markers for other authentication purposes. The great economic value of high-quality or guaranteed foods demands highly detailed characterization to protect both consumers and producers from frauds. The present scenario suggests metabolomics as the privileged approach of modern analytical studies for the next decades. The large potentiality of high-resolution NMR techniques is here presented through specific applications and using different approaches focused on the authentication process of some foods, like tomato paste, saffron, honey, roasted coffee, and balsamic and traditional balsamic vinegar of Modena, with a particular focus on geographical origin characterization, ageing determination, and fraud detection.

HR MAS 1H NMR and chemometrics as useful tool to assess the geographical origin of cocoa beans - Comparison with HR 1H NMR

Chocolate and cocoa-based products are among the goods with higher added value. A current trend of the cocoa market is to offer to the consumers high quality cocoa products, namely mono-origin cocoa. However, a reliable analytical method able to trace the geographical origin of cocoa is lacking. In this work we tested the capability of HR MAS ¹H NMR combined with chemometrics to assess the geographical origins of 60 fermented and dried cocoa beans of 23 different cocoa producing countries from the three major crop-growing areas (Africa, Central/South America, Asia/Oceania). Metabolic profiling was determined by HR MAS ¹H NMR directly on cocoa powder after the method optimization. The same samples were also subjected to extraction and analysis with HR ¹H NMR. HR MAS ¹H NMR, as ¹H NMR analysis, allowed the simultaneous detection of amino acids, polyalcohols, organic acids, sugars, methylxanthines, catechins. Moreover, HR MAS allows the detection of lipids, not present in the aqueous extract utilized for ¹H NMR. The data set obtained is therefore representative of all classes of cocoa compounds. Untargeted HR MAS ¹H NMR and ¹H NMR datasets were utilized as fingerprint of the samples and elaborated with multivariate statistical methods. A targeted quantitative approach of selected metabolites was possible only with HR ¹H NMR data, because HR MAS ¹H NMR does not give reliable quantitative results. All the approaches adopted showed a discrimination of the cocoa origins. HR MAS presents the advantages to obtain a very rapid picture of the samples, comprising both lipophilic and hydrophilic components, avoiding any sample manipulation.

Recent developments in honey characterization

Advanced analytical techniques in honey characterization.

NMR characterization of saccharides in Italian honeys of different floral sources

The saccharide profiles of 5 different botanical species in 86 Italian honey samples were investigated by ¹H and ¹H-¹³C NMR spectroscopy. Nineteen saccharides were identified in the aqueous extracts, namely, fructose, glucose, gentiobiose, isomaltose, kojibiose, maltose, maltulose, melibiose, nigerose, palatinose, sucrose, turanose, erlose, isomaltotriose, kestose, maltotriose, melezitose, raffinose, and maltotetraose. PCA performed on NMR spectral regions, in particular between 4.400 and 5.700 ppm and the fructose signal at 4.050 ppm, revealed a partial sample grouping. The score contribution plots derived from PCA performed using the mean values for the buckets of the anomeric region for each floral source allowed the identification of saccharides characterizing different honeys. OPLS-DA models were further evaluated to confirm the previous findings. OPLS-DA models were also built to highlight differences between polyfloral and high mountain polyfloral honeys and between high mountain polyfloral and rhododendron honeys, both collected at high altitude; S-plots highlighted the characteristic saccharides.

NMR based geographical characterization of roasted coffee

The increasing attention for food quality and safety led to develop several analytical techniques suitable to address these demands. Coffee has been already demonstrated to represent a worldwide appreciated beverage and its high economical value could induce frauds or adulteration practices involving both compositional and geographical aspects. In the last years, metabolic profiling revealed to be suitable to face the quality determination of food matrices and NMR confirmed its potentiality in metabolites characterization. The present study reports the capability of NMR spectroscopy to investigate the metabolite content of roasted Coffea arabica samples from the three main production areas, America, Africa and Asia. OPLS-DA models performed on (1)H NMR data led to a clear separation of samples according to their origin: fatty acids, chlorogenic acids and lactate and finally acetate and trigonelline resulted the main compounds characterizing the American, African and Asian samples respectively. The analytical approach here presented confirmed the potentiality of the joined NMR analysis and statistical treatments in quality determination of food matrices.

Evaluation of the production year in Italian and Chinese tomato paste for geographical determination using O2PLS models

Nuclear magnetic resonance (NMR) is nowadays largely used as valid tool in metabolomic applications. In this study, the metabolite content of Italian and Chinese tomato paste at different concentration rates of two production years (2007 and 2008) was investigated with the aim of building a robust geographical differentiation statistical model. A total of 119 tomato paste samples were analyzed by (1)H NMR and multivariate data analysis tools, in particular using bidirectional orthogonal projection to latent structures-discriminant analysis (O2PLS-DA). This technique is well-suited for noisy and correlated variables and was recently adopted to obtain robust classification models, having a clear interpretation of the systematic variation useful to characterize each class. In the present study, the analysis of latent space underlying the classification model allowed us to understand the role played by the production year on geographical discrimination. The O2PLS-DA model performed considering only tomato paste samples of 2007 was capable of predicting the geographical origin of all analyzed samples. The effect of the production year therefore resulted in not affecting the geographical origin discrimination.

Nuclear magnetic resonance and chemometrics to assess geographical origin and quality of traditional food products

In this globalization era, the opening of the markets has put at almost everybody's disposal a wide variety of foods, allowing everybody to taste food flavors and aromas from different nations. Notwithstanding this opportunity, countries try to preserve their markets by developing protection policies. A few countries have adopted different denominations to label their "typical food" products in order to give them additional value. Besides, the term "typical food" is widely thought of as something anchored to the local traditions, with geographical meaning and made with typical raw materials. Then a "typical food" starts to be considered "traditional" when it is made following specific and old recipes. As a matter of fact, these products acquire particular organoleptic characteristics that are not reproducible when produced in different places. In this review, NMR studies coupled to multivariate statistical analysis are presented with the aim of determining geographical origin and key quality characteristics.

Triple concentrated tomato paste: discrimination between Italian and Chinese products

(1)H NMR spectroscopy was applied to discriminate triple concentrated tomato paste coming from two different countries. Notwithstanding different tomato cultivars and ripening stages employed to obtain the final product, significant discrimination between Italian and Chinese samples was obtained by combining NMR data and principal component analysis. Supervised orthogonal projection to latent structure discriminant analysis (OPLS-DA) technique was used to build robust classification models, while S-plot was employed to identify statistically significant variables responsible for class separation. Citrate content resulted in being the most relevant chemical compound for Chinese and Italian sample differentiation. In order to highlight other compounds able to contribute to sample differentiation, citrate content was excluded, and a new classification model was built. This latter model indicated aspartate, glutamine, and sugars as important variables in sample differentiation.