The control of spoilage yeasts in wines is crucial to avoid organoleptic deviations in wine production. Traditionally, sulfur dioxide (SO₂) was used to control them; nevertheless, SO₂ influence on human health and its use is criticized. Biocontrol emerges as an alternative in wine pre-fermentation, but there is limited development in its applicability. Managing kinetics is relevant in the microbial interaction process. pH was identified as a factor affecting the interaction kinetics of Wickerhamomyces anomalus killer biocontrol on Zygosaccharomyces rouxii. Mathematical modeling allows insight into offline parameters and the influence of physicochemical factors in the environment. Incorporating submodels that explain manipulable factors (pH), the process can be optimized to achieve the best-desired outcomes. The aim of this study was to model and optimize, using a constant and a variable pH profile, the interaction of killer biocontrol W. anomalus vs. Z. rouxii to reduce the spoilage population in pre-fermentation. The evaluated biocontrol was W. anomalus against the spoilage yeast Z. rouxii in wines. The kinetic interactions of yeasts were studied at different pH levels maintained constant over time. The improved Ramón-Portugal model was adopted using the AMIGO2 toolbox for Matlab. A static optimization of a constant pH profile was performed using the Monte Carlo method, and a dynamic optimization was carried out using a method based on Fourier series and orthogonal polynomials. The model fit with an adjusted R² of 0.76. Parametric analyses were consistent with the model behavior. Variable vs. constant optimization achieved a lower initial spoilage population peak (99% less) and reached a lower final population (99% less) in a reduced time (100 vs. 140 h). These findings reveal that control with a variable profile would allow an early sequential inoculation of S. cerevisiae. The models explained parameters that are difficult to quantify, such as general inhibitor concentration and toxin concentration. Also, the models indicate higher biocontrol efficiency parameters, such as toxin emission or sensitivity to it, and lower fitness of the contaminant, at pH levels above 3.7 during biocontrol. From a technological standpoint, the study highlights the importance of handling variable profiles in the controller associated with the pH management actuators in the process without incurring additional costs.

Microalgae possess the remarkable ability to autotrophically grow, utilizing atmospheric carbon dioxide (CO₂) for photosynthesis, thereby converting solar energy into chemical energy and releasing oxygen. This capacity makes them an effective tool for mitigating industrial CO₂ emissions. Mathematical models are crucial for predicting microalgal growth kinetics and thus assessing their potential as industrial CO₂ sequestration agents under controlled conditions. This study innovatively evaluated the effect of continuously supplying CO₂ from winemaking processes on microalgal cultivation and biomass production, demonstrating a novel approach to both carbon capture and the valorization of a valuable by-product. To analyze microalgal growth kinetics, three mathematical models were employed: Logistic, First Order Plus Dead Time, and Second Order Plus Dead Time. Optimal parameter values for each model were identified using a hybrid search algorithm developed by our research group. First, an integrated microvinification system was established, utilizing two microalgae species, Chlorella spp. (FAUBA-17) and Desmodesmus spinosus (FAUBA-4), in conjunction with yeast fermenters. This system facilitated a comparison of the biomass kinetics of these two microalgae species, selecting Chlorella spp. (FAUBA-17) as the most suitable candidate for subsequent cultivation. A pilot-scale vertical column photobioreactor was then constructed and installed at the Casimiro Wines boutique winery in Angaco, San Juan, Argentina. After 15 days of operation within the photobioreactor, a biomass growth of 1.04 ± 0.05 g/L and 1.07 ± 0.1 g/L was obtained in Photobioreactors 1 and 2, respectively. This novel integrated approach to CO₂ capture in the winemaking process is unprecedented. These findings highlight the potential for producing high-value microalgal biomass, promoting the establishment of a local biorefinery and fostering a circular economy and sustainable social development.

Microbial interactions play a decisive role in fermentation dynamics and final wine quality. The sequential co-inoculation of non-conventional yeasts with Saccharomyces cerevisiae has been proposed as a strategy to enhance organoleptic properties, reduce ethanol content and/or exert biocontrol over spoilage yeasts, thereby decreasing the use of sulphur dioxide (SO2). Among these species, Wickerhamomyces anomalus has shown effectiveness; however, its interaction with S. cerevisiae under sequential inoculation schemes has not been explored from an ecological modelling perspective. In this study, the population dynamics of both species were analysed using an Ordinary Differential Equation (ODE)-based model, evaluating the influence of co-inoculation timing, temperature, and SO2 concentration to maximise the viability of the biocontrol yeast without affecting the fermentative kinetics of S. cerevisiae. Fifteen fermentations were carried out following a Box–Behnken experimental design, varying temperature (15–20 °C), molecular SO2 (0–0.2 ppm), and co-inoculation time (0–48 h). A Gilpin–Ayala competition model was applied, incorporating secondary temperature models (Arrhenius and Ratkowsky) and constant parameters for the effects of SO2 and co-inoculation time. The model was refined through parameter estimation and the Akaike Information Criterion (AIC), and was experimentally validated under different inoculum proportions. The iterative fitting process led to a simplified Lotka–Volterra model modified solely to include the effect of co-inoculation time. Inoculating S. cerevisiae 48 h after W. anomalus significantly increased the viability of the latter (by 75 % compared to simultaneous inoculation) without affecting fermentative kinetics. Simulations confirmed the final dominance of S. cerevisiae and the convergence of both populations toward the same sink point. Delaying S. cerevisiae inoculation favoured the early establishment of W. anomalus, enhancing biocontrol efficacy without compromising alcoholic fermentation. This simplified ecological model provides a framework to optimise microbial management in winemaking, reduce SO2 usage, and promote more sustainable fermentation processes.