Evaluation of mid-infrared spectra associated with chemometrics for the determination of physicochemical properties during fermentation of a new strawberry-based beverage with water kefir grains

• Published in: Journal of food composition and analysis 2023-10, Vol.123, p.105490, Article 105490
• Main Authors: da Silva Araújo, Cintia, Macedo, Leandro Levate, Teixeira, Luciano José Quintão
• Format: Article
• Language: English
• Subjects: Chemometrics; fermentation; Fermented beverage; fermented beverages; food composition; fruit juices; kefir; MID-infrared; PLS models; prediction; Pretreatments; statistical analysis; titratable acidity; Water kefir
• ISSN: 0889-1575
• DOI: 10.1016/j.jfca.2023.105490

This study aimed to explore the mid-infrared technique for the characterization of a non-dairy fermented beverage. Fruit juice was used as a substrate for fermentation made by microorganisms from water kefir. The fermented beverage was evaluated by standardized methods regarding pH, total titratable acidity, soluble solids, and total reducing sugars. Then, infrared spectra were obtained and calibration models were built to predict these parameters in the fermented beverage. All obtained models showed high coefficients of determination values (R2) in the calibration and prediction stages, in addition to high residual predictive deviation (RPD) values. For the prediction data, the values of R² were equal to 0.91, 0.93, 0.95, and 0.91 for pH, total titratable acidity, soluble solids, and total reducing sugars, respectively. It was evidenced that the soluble solids content was the most suitable physicochemical property for estimation by the elaborated calibration models (higher R2 and RPD values). The results showed that such parameters could be estimated in kefir quickly through the mid-infrared analysis. •The combination of MID-infrared with chemometrics was used to evaluate a beverage fermented by water kefir.•A simultaneous quantitative method for the physicochemical properties of kefir has been established.•PLS models were developed to predict beverage quality•High R2 values were obtained for all response variables.