Statistical protocol for nonlinear model selection using cumulative CO2 production during alcoholic fermentation by Saccharomyces cerevisiae

Understanding the kinetics of alcoholic fermentation is essential for characterizing the metabolic performance of wine yeasts under different environmental conditions. This study aimed to establish a systematic method for selecting nonlinear regression models to describe the cumulative carbon dioxide production by Saccharomyces cerevisiae during alcoholic fermentation at two different temperatures: 18 °C and 28 °C. Fermentations were conducted in synthetic must based on diluted grape must with 250 g L−1 of reducing sugars, inoculated with a commercial yeast strain, and incubated under static conditions. CO2 production was monitored gravimetrically through daily mass loss. Four sigmoidal models were evaluated: the reparameterized Gompertz model, the classical Gompertz model, the Logistic model, and the No Lag Phase model. Ordinary least squares were used to fit the models, and statistical diagnostics were performed to validate the assumptions of normality, homoscedasticity, and independence of residuals. The reparameterized Gompertz model showed superior statistical and biological performance, yielding significant and coherent estimates of lag phase, maximum CO2 production rate, and final cumulative CO2. At 18°C, a distinct adaptation phase was observed, whereas at 28°C, fermentation commenced immediately with higher production rates and total yield. The reparameterized Gompertz model achieved the best fit at both temperatures, with the lowest root mean square error and Bayesian information criterion values, and was the only model to satisfy all residual diagnostic tests. The results demonstrate that temperature exerts a critical influence on yeast kinetics and model adequacy. This study contributes a robust and reproducible protocol for selecting nonlinear models applied to laboratory-scale alcoholic fermentation by S. cerevisiae, supporting improved kinetic characterization under controlled experimental conditions.