Lactic acid is widely used in the food industry. It can be produced via chemical synthesis or biotechnological pathways by using renewable resources as substrates. The main challenge of sustainable production lies in reaching productivities and yields that allow for their industrial production. In this case, the application of process engineering becomes a crucial tool to improve the performance of bioprocesses. In this work, we performed the solid-state fermentation of grape stalk using Rhizopus oryzae NCIM 1299 to obtain lactic acid, employing three different temperatures (22, 35, and 40 °C) and a relative humidity of 50%. The Logistic and First-Order Plus Dead Time models were adjusted for fungal biomass growth, and the Luedeking and Piret with Delay Time model was used for lactic acid production, obtaining higher R² values in all cases. At 40 °C, it was observed that Rhizopus oryzae grew in pellet form, resulting in an increase in lactic acid productivity. In this context, the effect of temperature on the kinetic parameters was evaluated with a polynomial correlation. Finally, using this correlation, a smooth and continuous optimal temperature profile was obtained by a dynamic optimization method, improving the final lactic acid concentration by 53%.

SO2 is traditionally used to limit or nullify the proliferation of spoilage yeasts in must/wine, but its use has become controversial due to its negative effects on human health. An alternative strategy for the control of spoilage yeasts is the use of biocontrol yeasts. Wickerhamomyces anomalus is an outstanding biocontroller yeast that has been examined by our group and that is a good biocontrol agent against Brettanomyces bruxellensis and Zygosaccharomyces rouxii. The challenge regarding the application of the results of microbial biocontrol studies lies in exploring technologically simple and economical ways to make use of microbial biocontrol activity. The introduction of foreign microbiota adds complexity to the fermentation medium and can cause technological difficulties and have oenological consequences inherent to the implementation of mixed cultures. Therefore, the objective of this study was to characterise the concentrated culture supernatant of W. anomalus and evaluate its biocontrol action in liquid medium on two main wine spoilage yeasts. W. anomalus BWa156 supernatant demonstrated inhibitory killer protein characteristics. The production of the inhibitory supernatant by the biocontroller yeast was independent of the presence or absence of the spoilage yeast. Supernatant can be produced faster under aerobic conditions than in traditional fermentation (i.e., with around 24 h), thus increasing its potential for technological development. The treatment with the supernatant of BWa156 was effective against the two spoilage populations Zygosaccharomyces rouxii and Brettanomyces bruxellensis, which are considered problematic for the wine industry. The supernatant of the biocontrol yeast can be considered to be a relevant additional stress factor for the spoilage population, which together with other factors such as ethanol, competition for nutrients, oxygen and pH, contributes to the elimination of the polluting population. This technology would allow a simple future application, through its production in a bioreactor parallel to the fermentation and subsequent inoculation in the must/wine.

Traditional fermentation models often oversimplify kinetics by treating microbial populations as physiologically homogeneous. To address this, we introduce a novel framework that explicitly incorporates cellular fitness by distinguishing the metabolically active subpopulation (“productive cells”) responsible for biosynthesis. This approach integrates established growth models (First Order Plus Dead Time and Logistic) with a modified Luedeking–Piret model (MALP), which introduces a new differential equation to dynamically quantify productive cells. This modeling study relies exclusively on experimental data available in the literature; no new experimental work was conducted. Validated against four diverse fermentation systems from published datasets, the MALP model demonstrated superior predictive accuracy, achieving coefficients of determination (R² > 0.97) for metabolite kinetics. Sensitivity analysis identified time-delay and maintenance-associated parameters as dominant factors governing system behavior. The key contribution of this work is a mechanistic equation that universally captures the real-world dynamics of metabolite production, providing a more realistic and robust framework for modeling heterogeneous bioprocesses.

Solid-state fermentation (SSF) is the bioprocess where microorganisms are cultivated in the absence of free water under controlled conditions. Lactic acid can be produced by Rhizopus oryzae SSF of grape stalks. During the microorganism’s growth, the temperature and water content of the solid bed fluctuate, leading to areas of either dry or excessive moisture in the solid substrate. Therefore, it is crucial to control the water supply to the matrix. In this work, we obtain lactic acid through SSF of grape stalks using Rhizopus oryzae NCIM 1299. The SSF was conducted at a fixed temperature of 35 °C, with five constant relative humidity (RH) levels: 50, 57, 65, 72, and 80%RH. Mathematical models, including the Logistic and First-Order Plus Dead-Time models for fungal biomass growth and the Luedeking and Piret with Delay Time model for lactic acid production, were adjusted to kinetic curves. Growth kinetic parameters (X_max, μ_max, T_p, T₀, Y_p/x, and t_d) were determined for all conditions. These kinetic parameters were then correlated with relative humidity using a second-degree polynomial relationship. We observed a decrease in X_max with an increasing %RH, while the value of Y_p/x increased at a higher %RH. Finally, the optimal variable relative humidity profile was obtained by applying the dynamic optimization technique, resulting in a 16.63% increase in lactic acid production.

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.