Riccardo Graziosi
University of Modena and Reggio Emilia
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Publication
Featured researches published by Riccardo Graziosi.
Journal of Agricultural and Food Chemistry | 2013
Giulia Papotti; Davide Bertelli; Riccardo Graziosi; Michele Silvestri; Lucia Bertacchini; Caterina Durante; Maria Plessi
Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.
Journal of Apicultural Research | 2018
Silvia Gardini; Davide Bertelli; Lucia Marchetti; Riccardo Graziosi; Diego Pinetti; Maria Plessi; Gian Luigi Marcazzan
The aim of this work was studying and identifying the main physicochemical properties and active constituents of Italian propolis derived from resident hives throughout the peninsula. The data, potentially useful to establish important propolis quality criteria, were compared to those typical of poplar type propolis and used to build a classification model to link the propolis characteristics to its ecoregion of origin. HPLC-ESI-TQ MS was used to quantify 21 phenolic compounds in propolis extracts. Considering the bioactive substances and the antioxidant activity, statistically significant characteristics can distinguish propolis from the considered Italian ecoregions: Mediterranean and temperate division and, due to the high presence of poplar trees, the Po plain province as part of temperate division. Chrysin is the most abundant flavonoid in all the samples followed by galangin and pinocembrin. Regarding phenolic acids the samples from temperate and Mediterranean ecoregions are characterized by high amount of ferulic and isoferulic acids. Composición química del propóleos italiano de diferente origen ecorregional El objetivo de este trabajo fue el estudio e identificación de las principales propiedades fisicoquímicas y componentes activos del propóleos italiano derivados de las colmenas residentes en toda la península. Los datos, potencialmente útiles para establecer importantes criterios de calidad del propóleos, se compararon con los típicos de los álamos y se utilizaron para construir un modelo de clasificación que vinculara las características del propóleos con su ecorregión de origen. Se utilizó HPLC-ESI-TQ MS para cuantificar veintiún compuestos fenólicos en extractos de propóleos. Considerando las sustancias bioactivas y la actividad antioxidante, las características estadísticamente significativas pueden distinguir al propóleos de las ecorregiones italianas consideradas: división mediterránea y templada y, debido a la alta presencia de álamos, la provincia de la llanura del Po como parte de la división templada. La crisina es el flavonoide más abundante en todas las muestras, seguido de la galangina y la pinocembrina. En cuanto a los ácidos fenólicos, las muestras de las ecorregiones templadas y mediterráneas se caracterizan por una elevada cantidad de ácidos ferúlicos e isoferúlicos.
Journal of Agricultural and Food Chemistry | 2017
Riccardo Graziosi; Davide Bertelli; Lucia Marchetti; Giulia Papotti; Maria Cecilia Rossi; Maria Plessi
The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, β-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.
Lwt - Food Science and Technology | 2015
Giulia Papotti; Davide Bertelli; Riccardo Graziosi; Annalisa Maietti; Paola Tedeschi; Andrea Marchetti; Maria Plessi
Food Analytical Methods | 2015
Davide Bertelli; Annalisa Maietti; Giulia Papotti; Paola Tedeschi; Gianpiero Bonetti; Riccardo Graziosi; Vincenzo Brandolini; Maria Plessi
XI Italian congress of Food Chemistry | 2016
Davide Bertelli; Riccardo Graziosi; Maria Plessi
XI Italian congress of FOOD CHEMISTRY | 2016
Davide Bertelli; Riccardo Graziosi; Lucia Marchetti; Maria Plessi
international symposium on bee products 3rd edition | 2014
Davide Bertelli; Riccardo Graziosi; Giulia Papotti; Maria Plessi; Gian Luigi Marcazzan; Silvia Gardini
X congresso natzionale di chimica degli alimenti | 2014
Davide Bertelli; Riccardo Graziosi; Giulia Papotti; Maria Plessi
Archive | 2014
Davide Bertelli; Maria Plessi; Federica Pellati; Flavio Forni; Giulia Papotti; Riccardo Graziosi