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.
A New Index to Detect Process Deviations Using IR Spectroscopy and Chemometrics Process Tools
Giussani B.
2023-01-01
Abstract
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.File | Dimensione | Formato | |
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