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This study is aimed at optimizing the Saffron essential oil (SEO) nanoparticles using the ionic gelation method. Response surface methodology (RSM) with Box-Behnken design (BBD) was applied to investigate the optimum conditions and the effects of three independent variables: LWCS concentration (0.1-0.3%), Arabic gum concentration (9.6-9.8%), and ratio (core: wall material) (1 : 5, 1 : 7.5, 1 : 10) on the responses of  z -average, polydispersity index (PDI), and zeta potential. The results showed that the quadratic model developed from the RSM was statistically significant ( p value &lt; 0.05). The quadratic model can be used to describe well the relationship between the variables on the response observed. The lack of fit was nonsignificant ( p value &gt; 0.05) relative to pure error for all response variables, indicating that the model fitted well. The model equation obtained for the process through RSM was adequate. The LWCS concentration and Arabic gum concentration had a significant effect on  z -average and PDI. The ratio (oil: Arabic gum/LWCS) has a significant effect on zeta potential. The optimum condition was the LWCS concentration of 0.1% and Arabic gum concentration of 9.6%, and the ratio (oil: Arabic gum/LWCS) 1 : 5 produced the optimum SEO nanoparticles with a  z -average value of 16.24, PDI of 0.495, and zeta potential of 15.76. The verification values were close to the predictive value given by the Design Expert® 12 program with  p value &gt; 0.05 at the 95% confidence level. Therefore, the application of the RSM with Box-Behnken was suitable for optimizing the saffron oil nanoparticles with desirable responses.

Optimization of Saffron Essential Oil Nanoparticles Using Chitosan-Arabic Gum Complex Nanocarrier with Ionic Gelation Method