Applying Numerical Optimization Technique in the Development of Value added Powdered Custard

Abstract

Custard powder is a relatively shelf-stable, fine textured, dry-formulated, carbohydrate-rich breakfast food product primarily made from corn starch with the addition of salt, flavoring, and coloring agents and with or without the inclusion of egg yolk solids, vitamins, and minerals. The aim of this study was to formulate, characterize, and optimize value-added custard from millet, soybean, and tigernut. A three-component constrained optimal (custom) mixture experimental design, with 69 randomized experimental runs, was employed. The formulation design constraints were: millet (10% - 70%), soybean (10% - 70%), and tigernut (10% - 70%). Other constant components of the formulation were sweet potato extract (3%), date (2%), clove (1%), cinnamon (1%), turmeric (1%), and ginger (2%). The formulated samples were analyzed and evaluated for quality and sensory characteristics using standard procedures. The result of the optimization gave optimized custard with an overall desirability index of 0.535, based on the set optimization goals and individual quality desirability indices. The optimal formulated value-added custard was obtained from 10.0 % millet flour, 49.3 % soybean meal, and 30.7 % tigernut. The quality properties of this optimal custard are 3.78 % ash content, 28.5 % crude protein, 10.1 % moisture content, 20.1 % fat content, 4.43 % crude fibre, 33.9 % carbohydrate, and 5.79 overall acceptability. The result of the study showed that the formulated value-added custard was found to be of higher quality than the traditional custard which is produced from mono cereals. Improving the nutritional quality of food and tackling nutrient deficiencies, particularly protein energy malnutrition in populations, is possible through the application of numerical optimization technique in development new, dietary-based food products.