Antifungal efficacy of thyme essential oil: a multi-model approach to growth inhibition - Hernández-Figueroa, Ricardo H.; Mani-López, Emma; López-Malo, Aurelio; Palou, Enrique; Cid-Pérez, Teresa Soledad; Nevárez-Moorillón, Guadalupe Virginia; Avila-Sosa, Raúl (Frontiers in Sustainable Food Systems, 2025)
This study evaluates the antimicrobial potential of thyme essential oil (EO) against fungal growth in high-risk conditions. It uses an integrative modeling approach, including logistic regression, survival analysis, and kinetic modeling. The goal is to understand the conditions that promote fungal growth and the growth rate over time, including pH, water activity (aw), and thyme EO concentration in solid-model systems. The antimicrobial activity was tested against Aspergillus flavus and Penicillium citrinum, varying pH levels (3, 4, and 5), aw (0.90, 0.95, and 0.99), and EO concentrations (0, 25, 50, 100, and 500 ppm) in potato-dextrose agar. The mold growth responses under the different tested conditions were evaluated using complementary modeling techniques, binary logistic regression, regression with life data, and kinetic model using the Gompertz equation. Results showed that reducing aw or pH alone was insufficient to inhibit mold growth without thyme EO. Each tested model offers unique insights into mold growth. The binary logistic model assesses growth versus no-growth conditions and identifies threshold values. Time-to-growth regression analysis with failure data helps understand the delay in mold growth and evaluate the combined preservation factors’ efficacy. When combining stress factors, the kinetic model provides detailed insights into growth rates, maximum growth, and lag phases. Analyzing the data with the three models allows a comprehensive understanding of how the studied factors influence mold growth, which is crucial for food safety and shelf-life evaluation.