Response surface methodology: an optimization approach for the synthesis of guar gum nanoparticles

Abstract Guar gum, a biopolymer derived from Cyamopsis tetragonoloba , widely used for encapsulating drugs, microorganisms, and bioactive compounds in various field. This study aims to optimize the synthesis of guar gum nanoparticles using response surface methodology. The nanoparticles were synthesized by nanoprecipitation method, utilizing polymers, cross-linkers, and surfactants. The optimization process employs a central composite design to show the relationship between independent variables and dependent variables. The input variables including guar gum, cross-linker, and surfactant concentration were systematically evaluated and optimized. The quadratic model ( R 2 value – 0.9) showed higher relationship between the independent and dependent variables. The numerical optimization was conducted to validate the model’s reliability, demonstrating that all independent variables had a significant effect on the dependent variables ( p < 0.05). The optimization methodology shows higher desirability of 0.823. The characterization techniques like X-ray diffraction confirms the amorphous nature of the synthesized material. Transmission electron microscopy and energy dispersive X-ray analysis indicates the particle size ranging from 20 to 50 nm and elemental composition. The optimized conditions led to nanoparticles with enhanced stability, uniform size, and improved functional properties. This approach offers a reliable strategy for the large-scale production of guar gum nanoparticles, with promising applications in various fields.