Utilization and validation of the polynomial models to predict insecticidal synergy in the essential oils of Thymus vulgaris L. and Thymus zygis L. against Musca domestica L.

This study investigated the applicability of mixture experimental design-based modeling approach to analyze insecticidal activity of thyme essential oils, particularly focusing on the synergistic interaction of their major constituents against Musca domestica. Chemical compositions of twelve commercially available thyme oils were analyzed using GC-MS, revealing their major constituents to be α-pinene, p-cymene, γ-terpinene, linalool, thymol, and undecanoic acid methyl ester. Cox’s component effect analysis pinpointed p-cymene, γ-terpinene, and thymol, as the active ingredients in the oils. Using these compounds, the response surface of mortality in terms of the composition was constructed at a given dosage. The quadratic model better fitted the data than the linear one, indicating synergistic interactions among all binary mixtures of p-cymene, γ-terpinene, and thymol. Subsequent optimization using quadratic programming algorithms facilitated the determination of optimal ratios for maximizing thyme oil's insecticidal activity at a predetermined dosage. The algorithm identified the optimal ratio of p-cymene:γ-terpinene:thymol to 32:23:45, resulting in the highest mortality of 87.5 %. Mixing the three least toxic oils (mortality of 36.7, 40.0, and 3.3 %) using the algorithm also presented viable solutions, suggesting its utility in quality control. This study demonstrates the potential of model-based strategies for utilizing botanical insecticides, offering efficient and accurate ways to identify the active ingredients and their synergistic interactions. This unexplored approach could provide an opportunity for boosting the commercialization of botanical insecticides by maximizing and ensuring their efficacy.