Validation of an Eco-Friendly Automated Method for the Determination of Glucose and Fructose in Wines
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Published:2023-07-22
Issue:14
Volume:28
Page:5585
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ISSN:1420-3049
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Container-title:Molecules
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language:en
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Short-container-title:Molecules
Author:
Dini Irene1ORCID, Tuccillo Dario2, Coppola Daniele2, De Biasi Margherita-Gabriella1ORCID, Morelli Elena1ORCID, Mancusi Andrea3ORCID
Affiliation:
1. Department of Pharmacy, University of Naples Federico II, Via Domenico Montesano 49, 80131 Napoli, Italy 2. Lcm Laboratorio Chimico Merceologico, Corso Meridionale, 80143 Napoli, Italy 3. Department of Food Microbiology, Istituto Zooprofilattico Sperimentale del Mezzogiorno, Via Salute 2, 80055 Portici, Italy
Abstract
Fermentable sugar dosage helps oenologists to establish a harvest’s moment and control the fermentation process of the musts. The official analyses recommended for their determination are long, laborious, and must be carried out by specialized personnel. On the contrary, instrumental analysis automation limits human errors, increases precision, and reduces the time and cost of the analyses. In the food production sector, to use methods other than those recommended by supranational bodies in official reports, it is necessary to validate the analytical processes to establish the conformity of the results between the new methods and the reference ones. This work validated an automated enzymatic apparatus to determine the sum of glucose and fructose levels in wine samples. The validation was carried out on wine samples (dry red wine, dry white wine, moderately sweet wine, and sweet wine) containing different sugar concentrations by comparing data obtained using the OIV-MA-AS311-02 method performed by a specialized operator (reference method) and the same method performed by an automated apparatus. The difference between the results’ means obtained with the two procedures was significant. Nevertheless, the automated procedure was considered suitable for the intended use since the differences between the averages were lower than the measurement uncertainty at the same concentration, and the repeatability results were better for the automated procedure than the reference method.
Subject
Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science
Reference27 articles.
1. Barbosa, C., Ramalhosa, E., Vasconcelos, I., Reis, M., and Mendes-Ferreira, A. (2022). Machine Learning Techniques Disclose the Combined Effect of Fermentation Conditions on Yeast Mixed-Culture Dynamics and Wine Quality. Microorganisms, 10. 2. (2009). Commission Regulation (EC) No 607/2009 Laying down certain detailed rules for the implementation of Council Regulation (EC) No 479/2008 as regards protected designations of origin and geographical indications, traditional terms, labelling and presentation of certain wine sector products. J. Eur. Union, 22, 60–139. 3. Vyshkvarkova, E., Rybalko, E., Marchukova, O., and Baranova, N. (2021). Assessment of the Current and Projected Conditions of Water Availability in the Sevastopol Region for Grape Growing. Agronomy, 11. 4. Chemical hazards in grapes and wine, climate Change and challenges to face;Ubeda;Food Chem.,2020 5. A Climate Change Impact Assessment (CCIA) of Key Indicators and Critical Thresholds for Viticulture and Oenology in the Fraser Valley, British Columbia, Canada;Beech;Weather Clim. Soc.,2021
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