This research explored the potential of plant antimicrobial compounds as natural alternatives to synthetic antimicrobials in the food and pharmaceutical industries, emphasizing the urgent need to combat antimicrobial resistance. It detailed various mechanisms by which these plant-derived compounds inhibit microbial growth, including disrupting cell membrane integrity, impeding cell wall and protein synthesis, and preventing biofilm formation, ultimately leading to bacterial cell death. This study highlighted the specific effects of plant antimicrobials on bacterial cells, such as inhibiting biofilm formation, cellular respiration, and cell motility, while also modulating oxygen consumption and reactive oxygen species generation, which are vital in addressing biofilm-mediated infections. Additionally, these compounds can regulate the expression of virulence factors and efflux pumps, enhancing antibiotic efficacy. A bibliometric analysis revealed a growing trend in research output and international collaboration, particularly from China and the United States, with key journals including “Frontiers in Microbiology” and “Antimicrobial Agents and Chemotherapy.” The analysis identified six clusters related to plant antimicrobial research, underscoring the need for further investigation into the mechanisms and applications of these bioactive compounds. In conclusion, understanding the action of plant antimicrobials is important for their effective application in combating antimicrobial resistance.

La industria de la confitería busca satisfacer la demanda de productos palatables manteniendo opciones saludables, debido a los efectos negativos del consumo excesivo de azúcar en la salud. Esta investigación se centró en el uso de polioles como alternativa al azúcar en la industria de la confitería. Se abordó la clasificación de los productos de confitería y la evaluación nutricional de los polioles, metabolismo, impacto en la salud, percepción del consumidor y aplicaciones para brindar una visión general beneficiosa para los interesados. Los resultados indicaron que los polioles son eficaces como sustitutos del azúcar debido a su capacidad como agentes de carga, su bajo índice glucémico y su menor contenido calórico. Además, no afectan los niveles de insulina y presentan efectos beneficiosos para la salud bucal. Sin embargo, su uso presenta desafíos en términos de sabor y costos de producción, y el consumo excesivo puede causar efectos secundarios gastrointestinales. En conclusión, la investigación respaldó el uso de los polioles como alternativas viables al azúcar en la confitería, contribuyendo a ofrecer productos más saludables, aunque se deben considerar las preferencias del consumidor y los posibles efectos secundarios en el desarrollo de estos productos. Due to the adverse effects of excessive sugar consumption on health, the confectionery industry aims to meet the demand for palatable products while maintaining healthy options. This research focused on using polyols as an alternative to sugar in the confectionery industry. It addressed the classification of confectionery products and the nutritional evaluation of polyols, including their metabolism, impact on health, consumer perception, and applications, to provide a beneficial overview for stakeholders. The results indicated that polyols are adequate substitutes for sugar due to their capacity as bulking agents, low glycemic index, and lower calorie content. Additionally, they do not affect insulin levels and benefit oral health. However, their use presents challenges regarding taste and production costs, and excessive consumption can cause gastrointestinal side effects. In conclusion, the research supported using polyols as viable alternatives to sugar in confectionery, contributing to the offering of healthier products. However, consumer preferences and potential side effects should be considered when developing these products.

Acidulants enhance the tartness and flavor of gummy candies. This study employed Python, a free, open-source tool, to perform a simplex–lattice mixture design, optimizing the sourness, flavor, and overall acceptance of lemon-flavored gummies. Citric, malic, and fumaric acids were evaluated, and a combined model measured their sensory attributes. The results showed high R² values and significant effects for individual and interaction terms. The optimal mixture (5.85 g citric, 4.8 g malic, 4.35 g fumaric acids) achieved a combined sensory score of 100.11. This study highlights Python’s utility in product development, providing an accessible resource for researchers and food developers.

Acidulants are crucial for enhancing and balancing the flavor profiles of confectionery products, such as gummy candies, ensuring an optimal sensory experience. This study aimed to develop an R script using the simplex-lattice mixture design to optimize the sourness and flavor levels and the combined response of these attributes for orangeflavored gummy candies, demonstrating its application in improving the sensory qualities of confectionery products. The gummy candies were prepared according to previous research, incorporating citric, malic, and fumaric acids based on the experimental design. The R scripts were provided and uploaded to the GitLab platform for download and analysis (https://gitlab.com/FoodChem-DataSci-Lab/orange-flavored-gummy-candies). The effects of these acids on sourness and flavor were assessed using a 5-point hedonic scale by 30 trained judges. The data were analyzed with R, resulting in mathematical models for the acids’ individual effects, interactions, and combined responses. Effect (Piepel direction) and contour plots were generated as well. The optimal mixture was determined to be 4.95 g of citric acid, 4.65 g of malic acid, and 5.40 g of fumaric acid, achieving an optimal combined response value of 107.14. In conclusion, balancing these three acids is critical to optimizing sourness and flavor levels in orange-flavored gummy candies. This study provided a valuable methodology for formulating confectionery products with enhanced sensory profiles. It demonstrated the capability of R to address complex problems in both the confectionery industry and academia, emphasizing its importance as an analytical tool for developing products with improved sensory characteristics.

This research aimed to automate the fitting of kinetic models using genetic algorithms (GAs) to optimize the estimation of kinetic parameters—the reaction rate constant (k) and the initial value of total titratable acidity (TTA, C₀)—and enhance predictive accuracy. Experimental data were collected from bananas (Musa paradisiaca L.) at ripening stage 2 on Von Loesecke scale, measuring TTA at specific intervals, and three kinetic models—zero-order, first-order, and second-order—were fitted. For optimization, Python-based GA was used to minimize the mean squared error (MSE) and evaluate performance based on R2, AIC, and BIC. Results indicated that while the zero-order model provided the best statistical fit (R2 = 0.918, lowest AIC and BIC), validation on unseen data favored the second-order model, which exhibited superior predictive accuracy (test R2 = 0.9349, lowest test MSE). The integration of GAs enhanced the robustness of kinetic fitting by effectively navigating parameter space and avoiding local minima, outperforming traditional optimization methods, demonstrating their ability to refine parameter estimation and improve model generalization. Future research should explore hybrid models that combine mechanistic kinetic equations with machine learning techniques (e.g., neural networks, or support vector regression), to better capture the biochemical processes underlying acidity changes in bananas. DOI: https://doi.org/10.54167/tch.v19iEspecial.1847