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Monitoring wine fermentation deviations using an ATR-MIR spectrometer and MSPC charts

  • Identification data

    Identifier: imarina:6232181
    Authors:
    Cavaglia JSchorn-García DGiussani BFerré JBusto OAceña LMestres MBoqué R
    Abstract:
    © 2020 Despite the winemaker's efforts, deviations such as bacterial spoilage can occur during wine alcoholic fermentation resulting in economic losses and low quality wines. When a deviation is suspected, samples are usually sent to an oenological laboratory for the off-line analysis of specific quality control parameters. The use of ATR-MIR as a fast analytical tool to monitor the fermentation process could be very useful, as getting real-time information of the process allows making readjustments before the process ends. In this study, we aimed at detecting white wine spoilage during alcoholic fermentation due to the action of lactic bacteria using a portable ATR-MIR instrument and MSPC charts. A total of 33 small-scale alcoholic fermentations were conducted (25 in normal operation conditions (NOC) and 8 simulating a bacterial spoilage with the addition of lactic bacteria (MLF)) to evaluate the capability of the MSPC charts to detect deviations from NOC. MSPC control charts were developed based on Q residuals and Hotelling's T2 statistics. Time-wise unfolding was applied to the original three-way data to build different PCA models, obtaining very satisfactory results: MLF samples were detected before the end of alcoholic fermentation in the Q residuals charts after 80 hours and Hotelling T2 chart could also differentiate the samples after 100 hours.
  • Others:

    Project code: AGL2015-70106-R, AEI/FEDER, UE
    Keywords: Wine State Quality control Process analytical technology Process analytical technologies (pat) Nir Mspc Infrared-spectroscopy Attenuated total reflectance Atr-mir Alcoholic fermentation
    Record's date: 2023-12-16
    Papper version: info:eu-repo/semantics/acceptedVersion
    Papper original source: Chemometrics And Intelligent Laboratory Systems. 201 (104011):
    APA: Cavaglia J; Schorn-García D; Giussani B; Ferré J; Busto O; Aceña L; Mestres M; Boqué R (2020). Monitoring wine fermentation deviations using an ATR-MIR spectrometer and MSPC charts. Chemometrics And Intelligent Laboratory Systems, 201(104011), -. DOI: 10.1016/j.chemolab.2020.104011
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Acronym: EnoPAT
    Publication Type: Journal Publications
    Project code 3: 2020 FISDU 00221
    Author, as appears in the article.: Cavaglia J; Schorn-García D; Giussani B; Ferré J; Busto O; Aceña L; Mestres M; Boqué R
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Aceña Muñoz, Laura / Boqué Martí, Ricard / Busto Busto, Olga / Cavaglia Pietro, Julieta / Ferré Baldrich, Joan / Mestres Solé, Maria Montserrat / Schorn García, Daniel
    Abstract: © 2020 Despite the winemaker's efforts, deviations such as bacterial spoilage can occur during wine alcoholic fermentation resulting in economic losses and low quality wines. When a deviation is suspected, samples are usually sent to an oenological laboratory for the off-line analysis of specific quality control parameters. The use of ATR-MIR as a fast analytical tool to monitor the fermentation process could be very useful, as getting real-time information of the process allows making readjustments before the process ends. In this study, we aimed at detecting white wine spoilage during alcoholic fermentation due to the action of lactic bacteria using a portable ATR-MIR instrument and MSPC charts. A total of 33 small-scale alcoholic fermentations were conducted (25 in normal operation conditions (NOC) and 8 simulating a bacterial spoilage with the addition of lactic bacteria (MLF)) to evaluate the capability of the MSPC charts to detect deviations from NOC. MSPC control charts were developed based on Q residuals and Hotelling's T2 statistics. Time-wise unfolding was applied to the original three-way data to build different PCA models, obtaining very satisfactory results: MLF samples were detected before the end of alcoholic fermentation in the Q residuals charts after 80 hours and Hotelling T2 chart could also differentiate the samples after 100 hours.
    Program founding action 2: Ayudas para la contratación de personal investigador novel (FI-2018)
    Thematic Areas: Statistics & probability Spectroscopy Software Robotics & automatic control Química Process chemistry and technology Mathematics, interdisciplinary applications Matemática / probabilidade e estatística Interdisciplinar Instruments & instrumentation Farmacia Engenharias iv Engenharias iii Engenharias ii Computer science, artificial intelligence Computer science applications Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, analytical Biotecnología Automation & control systems Analytical chemistry
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 01697439
    Author's mail: 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
    Author identifier: 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
    Founding program action 3: Ayudas de apoyo a departamentos y unidades de investigación universitarios para la contratación de personal investigador predoctoral en formación (FI SDUR 2020)
    Project code 2: FI_B100154
    Founding program 2: Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR)
    Funding program: 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
    Founding program 3: Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR)
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2020
    Funding program action: Ciencias y tecnologías de los alimentos
  • Keywords:

    Analytical Chemistry,Automation & Control Systems,Chemistry, Analytical,Computer Science Applications,Computer Science, Artificial Intelligence,Instruments & Instrumentation,Mathematics, Interdisciplinary Applications,Process Chemistry and Technology,Robotics & Automatic Control,Software,Spectroscopy,Statistics & Probability
    Wine
    State
    Quality control
    Process analytical technology
    Process analytical technologies (pat)
    Nir
    Mspc
    Infrared-spectroscopy
    Attenuated total reflectance
    Atr-mir
    Alcoholic fermentation
    Statistics & probability
    Spectroscopy
    Software
    Robotics & automatic control
    Química
    Process chemistry and technology
    Mathematics, interdisciplinary applications
    Matemática / probabilidade e estatística
    Interdisciplinar
    Instruments & instrumentation
    Farmacia
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Computer science, artificial intelligence
    Computer science applications
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Chemistry, analytical
    Biotecnología
    Automation & control systems
    Analytical chemistry
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