Iranian Research Organization for Science and Technology (IROST) Innovative Food Technologies 2783-350X 12 2 2025 01 20 Comparison of Modeling with Fuzzy Logic Method and Mixture Design in Predicting the Formulation of Ziziphora Essential Oil Nanoemulsion Production Comparison of Modeling with Fuzzy Logic Method and Mixture Design in Predicting the Formulation of Ziziphora Essential Oil Nanoemulsion Production 114 135 1523 10.22104/ift.2025.7221.2188 FA Reza Beigzadeh Department of Chemical Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran Omid Ahmadi Department of Chemical Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran Journal Article 2024 11 14 Kakooti, which possesses significant antioxidant and antibacterial properties, can enhance bioavailability and absorption in the body when utilized in nanoemulsions. The production of this type of emulsion through a subcritical water method offers higher stability and a more uniform distribution due to the small particle size, which can contribute to improving the efficacy of its active compounds. In the present study, kakooti essential oil was extracted using a Cloninger device, yielding 2.2 milliliters of oil. Subsequently, the formulation optimization of kakooti essential oil (0-0.25), Tween 80 emulsifier (0-4.5), and distilled water (20-25 milliliters) was conducted under subcritical water conditions at 120°C for 2 hours. The results indicated that the optimal formulation consisted of 0.44 mL of essential oil, 3.56 mL of emulsifier, and 21 mL of distilled water, which resulted in the smallest average particle size (150 nanometers) and the highest antioxidant property (58%). In this study, fuzzy logic was employed to predict the two responses: average particle size and antioxidant property as a function of the formulation quantities. The analysis of the fuzzy logic model demonstrated its effectiveness as a powerful method for estimating the characteristics of the produced nanoemulsion in the studied system. The average relative errors of the proposed fuzzy method compared to the target data for average particle size and antioxidant property were found to be 1.84% and 5.82%, respectively. The comparison of the fuzzy logic method's errors with those of the mixture design model (84.2% and 72.7% errors for estimating average particle size and antioxidant property) clearly highlights the superiority of the fuzzy modeling technique. Kakooti, which possesses significant antioxidant and antibacterial properties, can enhance bioavailability and absorption in the body when utilized in nanoemulsions. The production of this type of emulsion through a subcritical water method offers higher stability and a more uniform distribution due to the small particle size, which can contribute to improving the efficacy of its active compounds. In the present study, kakooti essential oil was extracted using a Cloninger device, yielding 2.2 milliliters of oil. Subsequently, the formulation optimization of kakooti essential oil (0-0.25), Tween 80 emulsifier (0-4.5), and distilled water (20-25 milliliters) was conducted under subcritical water conditions at 120°C for 2 hours. The results indicated that the optimal formulation consisted of 0.44 mL of essential oil, 3.56 mL of emulsifier, and 21 mL of distilled water, which resulted in the smallest average particle size (150 nanometers) and the highest antioxidant property (58%). In this study, fuzzy logic was employed to predict the two responses: average particle size and antioxidant property as a function of the formulation quantities. The analysis of the fuzzy logic model demonstrated its effectiveness as a powerful method for estimating the characteristics of the produced nanoemulsion in the studied system. The average relative errors of the proposed fuzzy method compared to the target data for average particle size and antioxidant property were found to be 1.84% and 5.82%, respectively. The comparison of the fuzzy logic method's errors with those of the mixture design model (84.2% and 72.7% errors for estimating average particle size and antioxidant property) clearly highlights the superiority of the fuzzy modeling technique. https://jift.irost.ir/article_1523_df12ecd077efc8c23881028604dbb8cc.pdf