MODEL PREDICTION FOR SENSORY ATTRIBUTES OF NONGLUTEN PASTA

Response surface methodology was used to predict sensory attributes of a nongluten pasta and develop response surface plots to help visualize the optimum region. Optimum regions of xanthan gum, modified starch, and locust bean gum were selected by overlapping the contour plots of sensory properties of nongluten pasta as compared with the control pasta. The formula of nongluten pasta that possessed the most desirable properties was xanthan gum at 40 g, modified starch at 35 g, locust bean gum at 40 g, tapioca starch at 113 g, potato starch at 57 g, corn flour at 250 g, and rice flour at 50 g. The quality of nongluten pasta could be improved by using different levels of nongluten starches and flours, and nonstarch polysaccharides.