PREDICTION AND OPTIMIZATION TO MAXIMIZE BREAKING STRENGTH OF MODIFIED CASSAVA-KODO MILLET BASED LOW GLYCEMIC FUNCTIONAL NOODLES USING RESPONSE SURFACE METHODOLOGY APPROACH

Keywords

low glycemic functional pasta, kodo millet, modified cassava starch, breaking strength, optimization, and response surface methodology

Abstract

Functional Food products are achieving importance in the recent world.Pasta is the generic term for any variety of flour based noodles with low glycemic index. Modification in diets is an established means of risk reduction of metabolic disorders. It is very important to select and control the ingredients to enhance the breaking strength of the pasta products. Response surface methodology (RSM) is an effective statistical technique which has been widely used to optimize processes or formulations with minimal experimental trials when many factors and their interactions may be involved. In this investigation, an attempt has been made to predict and optimize to maximize the breaking strength of composite functional pasta. From the results, it was concluded that wheat pre dominates the breaking strength of the developed pasta product followed by kodomillet flour and modified cassava starch.