The World Health Organization has identified the addition of sugar to processed foods and beverages as a health concern. Therefore, reducing added sugar in products would help consumers decrease the calorie intake and manage their health concerns in the long run.
Natural sweeteners as sugar replacers
Natural non-nutritive sweeteners (NNSs) like Stevia and Monk fruit have greater potential as sugar replacers. As no single sugar has a sensory profile close to sucrose, therefore, use of two or more sweeteners could be an option to partially reduce the sugar in products. In order to develop a low sugar product with optimum sensory attributes, a powerful tool i.e. Response Surface Methodology (RSM) could be employed for optimizing the level of sweeteners taking the sensory attributes into consideration.
Response Surface Methodology (RSM) and Consumer panel
n=120 consumers were recruited for the tasting of flavoured milk and were asked to rate liking for different sensory attributes e.g. overall liking, appearance, aroma, sweetness, mouthfeel and aftertaste.
Optimization of the sweeteners was performed based on their responses for different sensory attributes for the maximum liking of the product.
Response surface methodology was used for quadratic modelling of the concentrations of the natural sweeteners.
Using the 3D contour plot, the optimum concentration of the sweeteners were identified for the maximum liking of the product with replaced sugar.
Further, the liking of the products were compared to the commercial reference sample as a benchmark.
It is possible to achieve a 50% of added sugar reduction in chocolate milk using stevia and monk fruit compounds
The use of two sweeteners provide synergistic effects on sensory attributes
The optimum sensory response is comparable to the control sample with full sugar
The combined use of natural non-nutritive sweeteners could be used to partially reduce sugar in food products which will benefit the health of the population significantly.
I Khan, A Yousif, S Johnson, S Gamlath
(2015), Vol. 34, pp. 415-421, Clinical nutrition, Amsterdam, The Netherlands, C1
V Illupapalayam, S Smith, S Gamlath
(2014), Vol. 55, pp. 255-262, LWT – Food Science and Technology, C1
I Khan, A Yousif, S Johnston, S Gamlath
(2014), Vol. 79, pp. 1560-1567, Journal of food science, Hoboken, NJ, C1
I Khan, A Yousif, S Johnson, S Gamlath, (2013), Vol. 54, pp. 578-586, Food research international, Amsterdam, The Netherlands, C1
Visit PublicationI Khan, A Yousif, S Johnson, S Gamlath
(2013), Vol. 54, pp. 578-586, Food research international, Amsterdam, The Netherlands, C1
