Modeling the Combined Effect of pH, Protein Content, and Mexican Oregano Essential Oil Against Food Spoilage Molds - Levario-Gómez, Anahí; Ávila-Sosa, Raúl; Gutiérrez-Méndez, Néstor; López-Malo, Aurelio; Nevárez-Moorillón, Guadalupe Virginia (Frontiers in Sustainable Food Systems, 2020)
Hurdle technologies are among the novel food processing techniques for food preservation, where there is a combination of mild antimicrobial factors, which can interact on the inhibition of microbial spoilage. Spices essential oils are widely known as antimicrobial compounds that can have a preservation effect on food, but their effect can be affected by food components. In order to evaluate the effect of pH (4.5-7.0) and protein content (2-8%) on the antifungal effect of Mexican oregano essential oil (150-600 mg/L), a Box-Benkhen design was used to test the effect of the treatments on the radial growth of two food-related fungi, Penicillium expansum (NRRL 2304) and Aspergillus ochraceus (ATCC 22947). Three essential oils were used, these with a different chemical composition. The first chemotype of Lippia berlandieri Schauer, presented a higher proportion of carvacrol (58.23%). The second Lippia berlandieri Schauer essential oil presented a higher concentration of thymol (60.15%). Essential oil from Poliomintha longiflora Gray contained a 43.02% of thymol. Kinetic growth parameters were obtained using the modified Gompertz equation. The maximum mold growth (A) of the molds was affected in a lineal concentration-dependent effect by the three Mexican oregano essential oils and protein concentration. This phenomenon is independent of the chemistry variability in the composition of the three OEO. The higher concentration of protein (8%) was also related to an increase in lag time (λ). These two growth parameters were mainly statistically significant of all treatments evaluated, when considering as intrinsic parameters in food such as pH and protein content. The action of OEO was higher against A. ochraceus, positioning itself as the most sensitive microorganism. The use of predictive modelling can provide valuable information on the interaction of food components to enhance or decrease the antifungal capacity of essential oils.