Selecting optimal mixtures of natural sweeteners for carbonated soft drinks through multi-objective decision modeling and sensory validation

The objective of this study was to develop a methodology to optimize mixtures of natural, noncaloric sweeteners—with the highest sweetness and the lowest bitterness—for carbonated soft drinks. To this end, and with the aid of a trained sensory panel, we first determined the most suitable mixtures of tagatose, sucrose, and stevia in a soft drink matrix, using a three-component simplex lattice mixture design. Then, we developed a multi-objective thermodynamically-based decision model to this purpose. Results indicate that both, sucrose and tagatose, were able to reduce stevia's bitterness. However, an increase of bitterness intensity was found above 0.23 g/L of stevia (sucrose equivalency or SE >5). Both, sensory analysis and multi-objective decision modeling identified similar optimal mixtures, corresponding to 23–39 g/L sucrose, 0.19–0.34 g/L stevia, and 34–42 g/L tagatose, depending on the desired sweetness/bitterness balance. Within this constrained area, a reduction of almost 60% of sucrose can be achieved in both approaches, keeping bitterness intensity low. Practical applications: Current demand of low-calorie beverages has significantly raised as a result of consumer concerns on the negative effects of refined sugars present in carbonated soft drinks. Consequently, natural sweeteners, and their mixtures, are being increasingly used for these product developments. This study provides a methodology to optimize mixtures of natural, noncaloric sweeteners for preparing carbonated soft drinks with the lowest possible caloric content, while maintaining the tastiness—high sweetness and low bitterness—of full caloric ones, containing the bulk sweetener tagatose and the high-intensity sweetener stevia.