Optimization of ingredients composition of non wheat pasta based on cooking quality using response surface methodology (RSM)

Abstract

The purpose of this study was to develop non wheat millet pasta. Box Benhken Design (BBD) under Response Surface Methodology (RSM) was used to find the better composition by considering cooking quality parameter such as cooking time, solid gruel loss, volume expansion and bulk density. Pasta was prepared using tapioca flour, foxtail millet flour and barnyard millet flour, corn flour, water and salt. The corn flour and the salt quantities were kept constant and the remaining flours varied. The dough prepared manually and extruded using cold extruder followed by it was steamed at 80ºC for 10 min and dried at hot air oven at 60ºC. Ingredients were optimized based on derringer’s desirability function. The optimized composition was found to be tapioca flour (50%), foxtail millet flour (24.6%) and barnyard millet flour (65.78 %), at this composition cooking time was 7.17 min, solid gruel loss was 6.198%, volume expansion was 6.99%, bulk density was 321.95kg/m3, carbohydrate was 71.5%, protein was 4.6% and fat was 1.1% with the desirability of 0.829.

Optimization of Prickly Pear Juice Clarification for Better Retention of Betalain and Color Properties

“…Response surface methodology has found be very useful and reliable method for optimizing the process parameters in many of the research experiments (Kaur et al, 2018;Prema et al, 2018;Balasubramanian et al, 2020). It was used for designing of the experiment (Khuri and Cornell 1987).…”