Wine vinegar is produced through a two-phase fermentation of grape must: initially, yeast converts grape sugars into ethanol, and subsequently, acetobacteria oxidize ethanol into acetic acid. This process, spanning weeks when conducted by surface fermentation, requires constant monitoring of ethanol and total acidity levels. To enhance the quality and efciency of process monitoring, vinegar production is shifting to faster, environmentally sustainable methods. Near-infrared (NIR) spectroscopy, recognized for its non-invasiveness and speed, is ideal for online implementation in process control. This study tracked dual fermentation in red grape must over an extended period, monitoring two diferent batches simultaneously to assess fermentation kinetics and reproducibility. Ethanol content and total acidity were analyzed in fermenting musts throughout the whole fermentation process using both classical laboratory analyses and FT-NIR spectroscopy. Principal Component Analysis (PCA) was used to explore the spectral dataset, then Partial Least Squares (PLS) was used to develop calibration models for predicting ethanol and acidity. The models calculated considering the entire spectral range were compared with those obtained for two narrower zones, where more cost-efective and easily miniaturizable sensors are available on the market. FT-NIR allowed to efectively determine ethanol content and acidity (R2 Pred>0.98), both over the entire range (12,500–4000 cm−1, corresponding to 800–2500 nm) and in the 10,526–6060 cm−1 (950–1650 nm) region. Although less satisfactory, still acceptable results were obtained in the 12,500–9346 cm−1 (800–1070 nm) region (R2 Pred>0.81), confrming the potential for cost-efective devices in real-time fermentation monitoring.
Comparison of Different Spectral Ranges to Monitor Alcoholic and Acetic Fermentation of Red Grape Must Using FT‑NIR Spectroscopy and PLS Regression / Menozzi, Camilla; Foca, Giorgia; Calvini, Rosalba; Catellani, Lisa; Bezzecchi, Andrea; Ulrici, Alessandro. - In: FOOD ANALYTICAL METHODS. - ISSN 1936-9751. - (2024), pp. 1-2. [10.1007/s12161-024-02636-3]
Comparison of Different Spectral Ranges to Monitor Alcoholic and Acetic Fermentation of Red Grape Must Using FT‑NIR Spectroscopy and PLS Regression
Camilla Menozzi;Giorgia Foca
;Rosalba Calvini;Lisa Catellani;Alessandro Ulrici
2024
Abstract
Wine vinegar is produced through a two-phase fermentation of grape must: initially, yeast converts grape sugars into ethanol, and subsequently, acetobacteria oxidize ethanol into acetic acid. This process, spanning weeks when conducted by surface fermentation, requires constant monitoring of ethanol and total acidity levels. To enhance the quality and efciency of process monitoring, vinegar production is shifting to faster, environmentally sustainable methods. Near-infrared (NIR) spectroscopy, recognized for its non-invasiveness and speed, is ideal for online implementation in process control. This study tracked dual fermentation in red grape must over an extended period, monitoring two diferent batches simultaneously to assess fermentation kinetics and reproducibility. Ethanol content and total acidity were analyzed in fermenting musts throughout the whole fermentation process using both classical laboratory analyses and FT-NIR spectroscopy. Principal Component Analysis (PCA) was used to explore the spectral dataset, then Partial Least Squares (PLS) was used to develop calibration models for predicting ethanol and acidity. The models calculated considering the entire spectral range were compared with those obtained for two narrower zones, where more cost-efective and easily miniaturizable sensors are available on the market. FT-NIR allowed to efectively determine ethanol content and acidity (R2 Pred>0.98), both over the entire range (12,500–4000 cm−1, corresponding to 800–2500 nm) and in the 10,526–6060 cm−1 (950–1650 nm) region. Although less satisfactory, still acceptable results were obtained in the 12,500–9346 cm−1 (800–1070 nm) region (R2 Pred>0.81), confrming the potential for cost-efective devices in real-time fermentation monitoring.File | Dimensione | Formato | |
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