Codi de projecte: AGL2015-70106-R, AEI/FEDER, UE
Paraules clau: Wine fermentation Wine Vibrational spectroscopy Trends Process monitoring Process analytical technology Process analytical technologies Parameters Malolactic fermentation contamination Grape Diversity Attenuated total reflectance Atr-mir Alcoholic fermentation
Data d'alta del registre: 2023-12-16
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Referència a l'article segons font original: Food Control. 109 (UNSP 106947):
Referència de l'ítem segons les normes APA: Cavaglia, Julieta; Schorn-Garcia, Daniel; Giussani, Barbara; Ferre, Joan; Busto, Olga; Acena, Laura; Mestres, Montserrat; Boque, Ricard; (2020). ATR-MIR spectroscopy and multivariate analysis in alcoholic fermentation monitoring and lactic acid bacteria spoilage detection. Food Control, 109(UNSP 106947), -. DOI: 10.1016/j.foodcont.2019.106947
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Acrònim: EnoPAT
Tipus de publicació: Journal Publications
Codi de projecte 3: 2020 FISDU 00221
Autor segons l'article: Cavaglia, Julieta; Schorn-Garcia, Daniel; Giussani, Barbara; Ferre, Joan; Busto, Olga; Acena, Laura; Mestres, Montserrat; Boque, Ricard;
Departament: Química Analítica i Química Orgànica
Autor/s de la URV: Aceña Muñoz, Laura / Boqué Martí, Ricard / Busto Busto, Olga / Cavaglia Pietro, Julieta / Ferré Baldrich, Joan / Giussani, Barbara / Mestres Solé, Maria Montserrat / Schorn García, Daniel
Resum: Wine production processes still rely on post-production evaluation and off-site laboratory analyses to ensure the quality of the final product. Here we propose an at-line methodology that combines a portable ATR-MIR spectrometer and multivariate analysis to control the alcoholic fermentation process and to detect wine fermentation problems. In total, 36 microvinifications were conducted, 14 in normal fermentation conditions (NFC) and 22 intentionally contaminated fermentations (ICF) with different lactic acid bacteria (LAB) concentrations. ATR-MIR measurements were collected during alcoholic and malolactic fermentations and relative density, pH, and L-malic acid were analyzed by traditional methods. Partial Least Squares Regression could suitably predict density and pH in fermenting samples (root mean squared errors of prediction of 0.0014 g mL(-1) and 0.06 respectively). With regard to ICF, LAB contamination was detected by multivariate discriminant analysis when the difference in L-malic acid concentration between NFC and ICF was in the order of 0.7-0.8 g L-1, before the end of malolactic fermentation. This methodology shows great potential as a fast and simple at-line analysis tool for detecting fermentation problems at an early stage.
Acció del programa de finançament 2: Ayudas para la contratación de personal investigador novel (FI-2018)
Àrees temàtiques: Zootecnia / recursos pesqueiros Saúde coletiva Química Nutrição Medicina veterinaria Medicina ii Materiais Interdisciplinar Geociências Food science & technology Food science Farmacia Ensino Engenharias iii Engenharias ii Engenharias i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Biotecnología Biotechnology & applied microbiology Biotechnology Biodiversidade Astronomia / física Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 09567135
Adreça de correu electrònic de l'autor: barbara.giussani@urv.cat laura.acena@urv.cat olga.busto@urv.cat ricard.boque@urv.cat montserrat.mestres@urv.cat joan.ferre@urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat
Identificador de l'autor: 0000-0001-5942-9424 0000-0002-2318-6800 0000-0001-7311-4824 0000-0001-9805-3482 0000-0001-6240-413X 0000-0003-0997-2191 0000-0003-0997-2191 0000-0003-0997-2191
Acció del programa de finançament 3: Ayudas de apoyo a departamentos y unidades de investigación universitarios para la contratación de personal investigador predoctoral en formación (FI SDUR 2020)
Codi del projecte 2: FI_B100154
Programa de finançament 2: Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR)
Enllaç font original: https://www.sciencedirect.com/science/article/abs/pii/S0956713519305365
Programa de finançament: Programa estatal de Investigación, Desarrollo e Innovación orientada a los Retos de la Sociedad, en el marco del Plan estatal de investigación científica y técnica y de innovación 2013-2016
Programa de finançament 3: Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR)
DOI de l'article: 10.1016/j.foodcont.2019.106947
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2020
Acció del programa de finançament: Ciencias y tecnologías de los alimentos