Articles producció científicaQuímica Analítica i Química Orgànica

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

  • Dades identificatives

    Identificador:  imarina:9366512
    Autors:  Schorn-Garcia, Daniel; Ezenarro, Jokin; Busto, Olga; Acena, Laura; Boque, Ricard; Mestres, Montserrat; Giussani, Barbara
    Resum:
    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.
  • Altres:

    Enllaç font original: https://link.springer.com/article/10.1007/s11947-023-03266-z
    Referència 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
    Referència a l'article segons font original: Food And Bioprocess Technology. 17 (9): 2782-2792
    DOI de l'article: 10.1007/s11947-023-03266-z
    Any de publicació de la revista: 2024
    Entitat: Universitat Rovira i Virgili
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Data d'alta del registre: 2025-03-22
    Autor/s de la URV: Aceña Muñoz, Laura / Boqué Martí, Ricard / Busto Busto, Olga / EZENARRO GARATE, JOKIN / Mestres Solé, Maria Montserrat / Schorn García, Daniel
    Departament: Química Analítica i Química Orgànica
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipus de publicació: Journal Publications
    Autor segons l'article: Schorn-Garcia, Daniel; Ezenarro, Jokin; Busto, Olga; Acena, Laura; Boque, Ricard; Mestres, Montserrat; Giussani, Barbara
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Àrees temàtiques: 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
    Adreça de correu electrònic de l'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
  • Paraules clau:

    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
    Food Science
    Food Science & Technology
    Industrial and Manufacturing Engineering
    Process Chemistry and Technology
    Safety
    Risk
    Reliability and Quality
    Biodiversidade
    Biotecnología
    Ciência de alimentos
    Ciências agrárias i
    Ciências biológicas i
    Ciências biológicas ii
    Engenharias ii
    Ensino
    Farmacia
    Interdisciplinar
    Materiais
    Medicina i
    Medicina ii
    Medicina veterinaria
    Nutrição
    Química
    Saúde coletiva
    Zootecnia / recursos pesqueiros
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