Modelling of perceived sweetness in biscuits based on sensory analysis as a new tool to evaluate reformulation performance in sugar reduction studies

Sugar reduction in foods is of global interest in food science and industry to limit excessive calorie intake for healthier nutrition. Therefore, a modified Weibull model-based approach is presented here to relate sweetness perception with sugar concentration for the first time. The model was tested by using sweetness perception data obtained from sensory analysis of biscuits (wholewheat flour, whey or hydrolysed pea protein, different sucrose forms, ethylvanillin, furaneol, phenylacetaldehyde) using a line scale and untrained panellists. Sweetness scores increased 56%, 59%, 41% by the addition of wholewheat flour, proteins, or aroma compounds at 17% sucrose containing biscuits, respectively. Wholewheat flour and proteins boosted Maillard reaction products imparting baked/caramel-like flavour. The Weibull model well fitted to the sweetness perception data with a sigmoidal curve and high predicting power. This approach allows to explain how much sugar reduction can be achieved to reach a targeted sweetness perception without performing further sensory analysis.

Automated summary

Sugar reduction is a global concern in the field of food science and industry, and a modified Weibull model-based approach is proposed to link sweetness perception with sugar concentration for the first time. The approach was tested using sensory analysis data from biscuits containing various ingredients. It was found that wholewheat flour and proteins added to the biscuits significantly increased sweetness scores, while the Weibull model accurately predicted sweetness perception based on sugar reduction without the need for further sensory analysis.