Formulation and Optimization of a high protein bar using Response Surface Methodology

Abstract

The growing health consciousness among consumers, especially school-age children, athletes, and gym-goers has led to an increasing demand for nutrient-dense and portable food options. A combination of nuts (walnuts, almonds, cashews, and pistachios), seeds (sunflower, pumpkin, cucumber, muskmelon, and watermelon), legumes (moong), and natural sweeteners like dates, protein sources like whey protein concentrate (WPC) and defatted soy granules (DFGs) were used in this study to prepare a protein-enriched bar. Response Surface Methodology (RSM) was employed to optimize the formulation, ensuring a balance between nutritional quality and consumer acceptability. Moong bean, WPC, and DFGs were chosen as independent factors, and the optimization was carried out involving 9-point hedonic scale. Color and sweetness scores were strongly impacted by the quadratic impact of soy and moong, according to the regression analysis. The optimized formulation, consisting of 11.39% soy granules, 18.78% WPC, and 5.57% moong bean produced predicted sensory scores that closely matched the observed values, with non- significant difference. This indicates full compliance with the model and validates its accuracy (p < 0.05). The model achieved high sensory scores with a composite desirability of 0.859. The findings highlighted the effectiveness of combining natural ingredients and statistical tools for food product innovation tailored to health-conscious and younger consumers.