Fabiano Reniero

Botanical and geographical characterization of green coffee (Coffea arabica and Coffea canephora): chemometric evaluation of phenolic and methylxanthine contents.

Green coffee beans of the two main commercial coffee varieties, Coffea arabica (Arabica) and Coffea canephora (Robusta), from the major growing regions of America, Africa, Asia, and Oceania were studied. The contents of chlorogenic acids, cinnamoyl amides, cinnamoyl glycosides, free phenolic acids, and methylxanthines of green coffee beans were analyzed by liquid chromatography coupled with UV spectrophotometry to determine their botanical and geographical origins. The analysis of caffeic acid, 3-feruloylquinic acid, 5-feruloylquinic acid, 4-feruloylquinic acid, 3,4-dicaffeoylquinic acid, 3-caffeoyl-5-feruloylquinic acid, 3-caffeoyl-4-feruloylquinic acid, 3-p-coumaroyl-4-caffeoylquinic acid, 3-caffeoyl-4-dimethoxycinnamoylquinic acid, 3-caffeoyl-5-dimethoxycinnamoylquinic acid, p-coumaroyl-N-tryptophan, feruloyl-N-tryptophan, caffeoyl-N-tryptophan, and caffeine enabled the unequivocal botanical characterization of green coffee beans. Moreover, some free phenolic acids and cinnamate conjugates of green coffee beans showed great potential as means for the geographical characterization of coffee. Thus, p-coumaroyl-N-tyrosine, caffeoyl-N-phenylalanine, caffeoyl-N-tyrosine, 3-dimethoxycinnamoyl-5-feruloylquinic acid, and dimethoxycinnamic acid were found to be characteristic markers for Ugandan Robusta green coffee beans. Multivariate data analysis of the phenolic and methylxanthine profiles provided preliminary results that allowed showing their potential for the determination of the geographical origin of green coffees. Linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLS-DA) provided classification models that correctly identified all authentic Robusta green coffee beans from Cameroon and Vietnam and 94% of those from Indonesia. Moreover, PLS-DA afforded independent models for Robusta samples from these three countries with sensitivities and specificities of classifications close to 100% and for Arabica samples from America and Africa with sensitivities of 86 and 70% and specificities to the other class of 90 and 97%, respectively.

1H NMR as a tool for the analysis of mixtures of virgin olive oil with oils of different botanical origin

1H NMR spectroscopy provides a possible alternative to conventional chromatographic methods for determining the composition of oils. In this study, various oils from olive, hazelnut and sunflower were analysed by 1H NMR spectroscopy. Experimental conditions were chosen in order to have a short experimental time. It was demonstrated that multivariate statistical methods, in particular discriminant analysis, applied to selected predominant peaks in the 1H NMR spectra of oils resulted in a good separation between these three oils of different botanical origin and permitted the detection of their mixtures. Copyright

Asthma severity in childhood and metabolomic profiling of breath condensate

Asthma is a heterogeneous disease and its different phenotypes need to be better characterized from a biochemical‐inflammatory standpoint. This study aimed to apply the metabolomic approach to exhaled breath condensate (breathomics) to discriminate different asthma phenotypes, with a particular focus on severe asthma in children.

Virgin Olive Oil Authentication by Multivariate Analyses of 1H NMR Fingerprints and δ13C and δ2H Data

(1)H NMR fingerprints of virgin olive oils (VOOs) from the Mediterranean basin (three harvests) were analyzed by principal component analysis, linear discriminant analysis (LDA), and partial least-squares discriminant analysis (PLS-DA) to determine their geographical origin at the national, regional, or PDO level. Further delta(13)C and delta(2)H measurements were performed by isotope ratio mass spectrometry (IRMS). LDA and PLS-DA achieved consistent results for the characterization of PDO Riviera Ligure VOOs. PLS-DA afforded the best model: for the Liguria class, 92% of the oils were correctly classified in the modeling step, and 88% of the oils were properly predicted in the external validation; for the non-Liguria class, 90 and 86% of hits were obtained, respectively. A stable and robust PLS-DA model was obtained to authenticate VOOs from Sicily: the recognition abilities were 98% for Sicilian oils and 89% for non-Sicilian ones, and the prediction abilities were 93 and 86%, respectively. More than 85% of the oils of both categories were properly predicted in the external validation. Greek and non-Greek VOOs were properly classified by PLS-DA: >90% of the samples were correctly predicted in the cross-validation and external validation. Stable isotopes provided complementary geographical information to the (1)H NMR fingerprints of the VOOs.

Stable carbon isotope content in ethanol of EC data bank wines from Italy, France and Germany

In the present work we discuss the usefulness of carbon isotope analysis of wine ethanol for the assignment of origin and the proof of adulteration of Italian, French and German wines. At first the comparability of the results from three laboratories is demonstrated by the results of inter-laboratory comparison measurement and by tests of the distillation procedures applied to the same samples. Furthermore, a close correlation of carbon isotope content in sugars from must and ethanol from the related wine could be found for samples from all countries. Using the δ13C values of EC data bank wines from 1991 to 1993 for Italy, France and Germany, we describe and discuss the main factors of influence which are responsible for the variation of those values. By examination of spiked samples, the usefulness of the δ13C analysis in the detection of certain types of wine enrichment is demonstrated; especially if the carbon isotope analysis by13C-8 isotope ratio mass spectrometry is employed as an additional tool for improving the security of the already officially performed determination of the site-specific hydrogen isotope content in wine ethanol by2H-NMR.

Oxygen‐18 measurement by continuous flow pyrolysis/isotope ratio mass spectrometry of vegetable oils

Stable isotopes are now increasingly used for the control of the origin or authenticity of food products. Among these techniques, the measurement of the 18O content of organic compounds has rarely been carried out because of technical difficulties in the preparation and measurement of the samples. Recently a few laboratories have worked on the setting up of on-line methods to allow easier access to the information that can be obtained from 18O/16O ratios. In this work, such a technique was developed by modifying an elemental analyser device for carrying out the pyrolysis of organic matter. This device is coupled to an isotope ratio mass spectrometer for 18O determination in the CO resulting from the pyrolysis of the compound to be analysed, with good results. The relationship between the 18O content of various oils and their geographical origins is discussed.

Characterization of Italian durum wheat semolina by means of chemical analytical and spectroscopic determinations

ABSTRACT Proton high-resolution magic angle spinning nuclear magnetic resonance (1H HR-MAS NMR) has been applied for the analysis of two cultivars of durum wheat produced in different Italian geographical areas. Furthermore, on the same samples, isotopic ratios were measured by mass spectrometry (IRMS). The application of chemometrics to these results permitted the discrimination of semolina by cultivar and geographical origin. A similar approach has been applied to the results obtained from chemical analyses. The comparison showed that NMR spectroscopy can provide a faster method for the detection of differences among the durum wheat semolina according to geographical and varietal origin. Furthermore, IRMS data are suitable to provide information about the geographical origin of samples. This present investigation is part of an extensive research project to find a scientific method capable of classifying wheat foods for the assignment of a “denomination of origin” trademark.

Metabolomics: moving towards personalized medicine

In many fields of medicine there is a growing interest in characterizing diseases at molecular level with a view to developing an individually tailored therapeutic approach. Metabolomics is a novel area that promises to contribute significantly to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies. Based on analytical platforms such as mass spectrometry or NMR-based spectroscopy, the metabolomic approach enables a comprehensive overview of the metabolites, leading to the characterization of the metabolic fingerprint of a given sample. These metabolic fingerprints can then be used to distinguish between different disease phenotypes and to predict a drugs effectiveness and/or toxicity.Several studies published in the last few years applied the metabolomic approach in the field of pediatric medicine. Being a highly informative technique that can be used on samples collected non-invasively (e.g. urine or exhaled breath condensate), metabolomics has appeal for the study of pediatric diseases. Here we present and discuss the pediatric clinical studies that have taken the metabolomic approach.

Authentication of trappist beers by LC-MS fingerprints and multivariate data analysis.

The aim of this study was to asses the applicability of LC-MS profiling to authenticate a selected Trappist beer as part of a program on traceability funded by the European Commission. A total of 232 beers were fingerprinted and classified through multivariate data analysis. The selected beer was clearly distinguished from beers of different brands, while only 3 samples (3.5% of the test set) were wrongly classified when compared with other types of beer of the same Trappist brewery. The fingerprints were further analyzed to extract the most discriminating variables, which proved to be sufficient for classification, even using a simplified unsupervised model. This reduced fingerprint allowed us to study the influence of batch-to-batch variability on the classification model. Our results can easily be applied to different matrices and they confirmed the effectiveness of LC-MS profiling in combination with multivariate data analysis for the characterization of food products.

Synthesis and Inhibitory Activity of 7-Geranoxycoumarin against Penicillium Species in Citrus Fruit.

Abstract A naturally occurring compound with strong antifungal activity was isolated from the flavedo tissue of “Star Ruby” grapefruits (Citrus paradisi) and identified as 7-geranoxycoumarin. A high yield strategy for its synthesis was found and its antifungal activity against Penicillium italicum and P. digitatum assessed by in vivo and in vitro test.