Articles producció científica> Química Analítica i Química Orgànica

A New Index to Detect Process Deviations Using IR Spectroscopy and Chemometrics Process Tools

  • Datos identificativos

    Identificador: imarina:9366512
    Autores:
    Schorn-Garcia, DanielEzenarro, JokinBusto, OlgaAcena, LauraBoque, RicardMestres, MontserratGiussani, Barbara
    Resumen:
    Process analytical technologies (PATs) have transformed the beverage production management by providing real-time monitoring and control of critical process parameters through non-destructive measurements, such as those obtained with infrared (IR) spectroscopy and enabling process readjustment if necessary. New requirements in the analysis of beverages call for new methods, so in this article, we propose a method based on the construction of multivariate statistical process control (MSPC) charts from a new dissimilarity index (the evolving window dissimilarity index, EWDI) to monitor fermentation processes. The EWDI was applied to monitor wine alcoholic fermentation, the biochemical transformation of sugars into ethanol. Small-scale fermentations were carried out and analyzed using a portable mid-infrared spectrometer. In some of them, process deviations due to nitrogen deficiency or temperature changes were intentionally promoted to evaluate the performance of the EWDI. The MSPC charts build by using the fermentations carried out under normal operating conditions allowed identifying deviations of the fermentation in its early stages. Furthermore, the shape of the EWDI curve over time provides insights about the specific type of deviation occurring. These results show the potential of this new approach to improve the monitoring and control of key process stages in biochemical processes in the food industry, which allows maximizing quality and minimizing losses.
  • Otros:

    Autor según el artículo: Schorn-Garcia, Daniel; Ezenarro, Jokin; Busto, Olga; Acena, Laura; Boque, Ricard; Mestres, Montserrat; Giussani, Barbara
    Departamento: Química Analítica i Química Orgànica
    Autor/es de la URV: Aceña Muñoz, Laura / Boqué Martí, Ricard / Busto Busto, Olga / EZENARRO GARATE, JOKIN / Mestres Solé, Maria Montserrat / Schorn García, Daniel
    Palabras clave: Confidence limits Control chart Evolving window principal component analysis (pca) Evolving window principal component analysis (pca) Least-squares Mid-infrared spectroscopy Ph Real-time monitoring Saccharomyces-cerevisiae State Temperature Vibrational spectroscopy Wine Wine fermentation
    Resumen: Process analytical technologies (PATs) have transformed the beverage production management by providing real-time monitoring and control of critical process parameters through non-destructive measurements, such as those obtained with infrared (IR) spectroscopy and enabling process readjustment if necessary. New requirements in the analysis of beverages call for new methods, so in this article, we propose a method based on the construction of multivariate statistical process control (MSPC) charts from a new dissimilarity index (the evolving window dissimilarity index, EWDI) to monitor fermentation processes. The EWDI was applied to monitor wine alcoholic fermentation, the biochemical transformation of sugars into ethanol. Small-scale fermentations were carried out and analyzed using a portable mid-infrared spectrometer. In some of them, process deviations due to nitrogen deficiency or temperature changes were intentionally promoted to evaluate the performance of the EWDI. The MSPC charts build by using the fermentations carried out under normal operating conditions allowed identifying deviations of the fermentation in its early stages. Furthermore, the shape of the EWDI curve over time provides insights about the specific type of deviation occurring. These results show the potential of this new approach to improve the monitoring and control of key process stages in biochemical processes in the food industry, which allows maximizing quality and minimizing losses.
    Áreas temáticas: Biodiversidade Biotecnología Ciência de alimentos Ciências agrárias i Ciências biológicas i Ciências biológicas ii Engenharias ii Ensino Farmacia Food science Food science & technology Industrial and manufacturing engineering Interdisciplinar Materiais Medicina i Medicina ii Medicina veterinaria Nutrição Process chemistry and technology Química Safety, risk, reliability and quality Saúde coletiva Zootecnia / recursos pesqueiros
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: laura.acena@urv.cat olga.busto@urv.cat ricard.boque@urv.cat montserrat.mestres@urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat jokin.ezenarro@urv.cat jokin.ezenarro@urv.cat
    Identificador del autor: 0000-0001-5942-9424 https://orcid.org/0000-0001-5942-9424 0000-0002-2318-6800 0000-0001-7311-4824 0000-0001-9805-3482 0000-0003-0997-2191 0000-0003-0997-2191 0000-0003-0997-2191 0000-0001-9234-7877 0000-0001-9234-7877
    Fecha de alta del registro: 2025-03-22
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Referencia al articulo segun fuente origial: Food And Bioprocess Technology. 17 (9): 2782-2792
    Referencia de l'ítem segons les normes APA: Schorn-Garcia, Daniel; Ezenarro, Jokin; Busto, Olga; Acena, Laura; Boque, Ricard; Mestres, Montserrat; Giussani, Barbara (2024). A New Index to Detect Process Deviations Using IR Spectroscopy and Chemometrics Process Tools. Food And Bioprocess Technology, 17(9), 2782-2792. DOI: 10.1007/s11947-023-03266-z
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2024
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Food Science,Food Science & Technology,Industrial and Manufacturing Engineering,Process Chemistry and Technology,Safety, Risk, Reliability and Quality
    Confidence limits
    Control chart
    Evolving window principal component analysis (pca)
    Evolving window principal component analysis (pca)
    Least-squares
    Mid-infrared spectroscopy
    Ph
    Real-time monitoring
    Saccharomyces-cerevisiae
    State
    Temperature
    Vibrational spectroscopy
    Wine
    Wine fermentation
    Biodiversidade
    Biotecnología
    Ciência de alimentos
    Ciências agrárias i
    Ciências biológicas i
    Ciências biológicas ii
    Engenharias ii
    Ensino
    Farmacia
    Food science
    Food science & technology
    Industrial and manufacturing engineering
    Interdisciplinar
    Materiais
    Medicina i
    Medicina ii
    Medicina veterinaria
    Nutrição
    Process chemistry and technology
    Química
    Safety, risk, reliability and quality
    Saúde coletiva
    Zootecnia / recursos pesqueiros
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