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Featured researches published by Giovanna Fia.


Chemical Senses | 2009

Saliva Characteristics and Individual Sensitivity to Phenolic Astringent Stimuli

Caterina Dinnella; Annamaria Recchia; Giovanna Fia; Mario Bertuccioli; Erminio Monteleone

Astringency sensation is due to interactions between salivary proteins and phenols and is based on an increased-friction mechanism. Modifications to the profile of salivary proteins and their concentration could affect tannin/protein reactions and hence the intensity of perceived astringency. Salivary characteristics of 65 subjects were compared after abstention from phenol-containing food and immediately after ingestion of tannic acid. The effect of stimulation on saliva characteristics was expressed in terms of D value, computed as the arithmetic difference between values found in saliva samples from the 2 conditions. Based on D values, subjects were clustered in two groups. Cluster 1 (Cl1, 53 cases) was characterized by low D values thus indicating that the basal saliva condition was quickly restored in these subjects. Cluster 2 (Cl2) was composed of 12 subjects whose basal salivary condition was not quickly restored, particularly in terms of salivary protein concentration and profile and saliva haze-forming capacity. Sensory data showed that subjects capable of maintaining constant saliva characteristics were less sensitive to astringent stimuli than subjects in which the same stimulations induced significant saliva modifications. The results suggest that a large proportion of the population are able to maintain their salivary protein concentration and simultaneously intercept and inactivate dietary tannins.


Antioxidants | 2018

A Naturally Occurring Antioxidant Complex from Unripe Grapes: The Case of Sangiovese (v. Vitis vinifera)

Giovanna Fia; Claudio Gori; Ginevra Bucalossi; Francesca Borghini; Bruno Zanoni

The wine industry is well known for its production of a large amount of wastes and by-products. Among them, unripe grapes from thinning operations are an undervalued by-product. Grapes are an interesting source of natural antioxidants such as flavonoids, non-flavonoids and stilbenes. A potential strategy to exploit unripe grapes was investigated in this study. Juice from unripe grapes, v. Sangiovese, was obtained by an innovative technique of solid-liquid extraction without the use of solvents. The juice was dried by a spray-drying technique with the addition of arabic gum as support to obtain powder; juice and powder were characterized for antioxidant activity, phenolic concentration and profile. Phenolic acids, flavonols, flava-3-ols, procyanidins and resveratrol were detected in the juice and powder. The powder was used as anti-browning additive in white wine to test the potential re-use of the unripe grapes in the wine industry. The results indicated that the antioxidant complex from unripe grapes contributed to increasing the anti-browning capacity of white wine. Other applications, such as food and nutraceutical products development, can be considered for the antioxidant complex extracted from unripe grapes. In conclusion, the method proposed in this study may contribute to the exploitation of unripe grapes as a by-product of the winemaking process.


American Journal of Enology and Viticulture | 2017

A Multivariate Methodological Approach to Relate Wine to Characteristics of Grape Composition: The Case of Typicality

Valentina Canuti; Monica Picchi; Bruno Zanoni; Giovanna Fia; Mario Bertuccioli

Typicality is defined as the characteristics of a Protected Designation of Origin (PDO) wine related to a terroir. In the context of a PDO, a typicality assessment can be used to assess the global quality of a PDO wine. This study used a two-phase method to identify the distinctive characteristics of a PDO wine and then apply those findings to a case study of Chianti Montespertoli DOCG wine, where DOCG is the Italian acronym for PDO. A panel of wine professionals evaluated the typicality of a series of selected PDO wine samples, and a partial least squares (PLS) regression model was used to associate wine typicality and chemical composition. The model was used to predict wine typicality from the chemical composition of experimental wines (2009, 2010, and 2011 vintages) produced from grapes growing in the PDO area. Finally, regression coefficients of the PLS model were analyzed to select which grape chemical parameters were significant in describing the typicality of the wine. These highlight the most important factors to manage during winemaking to ensure the typicality of this wine.


Australian Journal of Grape and Wine Research | 2003

Influence of different pH values and inoculation time on the growth and malolactic activity of a strain of Oenococcus oeni

Iolanda Rosi; Giovanna Fia; Valentina Canuti


International Journal of Food Science and Technology | 2014

Evaluation of potential side activities of commercial enzyme preparations used in winemaking

Giovanna Fia; Valentina Canuti; Iolanda Rosi


Food Chemistry | 2009

Prediction of grape polyphenol astringency by means of a fluorimetric micro-plate assay.

Giovanna Fia; Caterina Dinnella; Mario Bertuccioli; Erminio Monteleone


European Journal of Lipid Science and Technology | 2016

Direct quantitative indices for ripening of olive oil fruits to predict harvest time

Serena Trapani; Marzia Migliorini; Chiara Cherubini; Lorenzo Cecchi; Valentina Canuti; Giovanna Fia; Bruno Zanoni


Australian Journal of Grape and Wine Research | 2016

Side activities of commercial enzyme preparations and their influence on the hydroxycinnamic acids, volatile compounds and nitrogenous components of white wine

Giovanna Fia; V. Olivier; A. Cavaglioni; Valentina Canuti; Bruno Zanoni


Agriculture and Agricultural Science Procedia | 2016

A New Technique for Exploitation of Wine Lees

Giovanna Fia; Bruno Zanoni; Claudio Gori


Lwt - Food Science and Technology | 2018

Beta-glucosidase and esterase activity from Oenococcus oeni: Screening and evaluation during malolactic fermentation in harsh conditions

Giovanna Fia; Valentina Millarini; Lisa Granchi; Ginevra Bucalossi; Simona Guerrini; Bruno Zanoni; Iolanda Rosi

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