A multicriteria decision making approach for wheat starch isolation intensification

Abstract

Starch isolation processes from cereals involve the use of enzymes to improve yield by removing lipids, proteins and undesired polysaccharides. Experimental evidence shows that this strategy is successful, leading to yield increases of 15–30 % compared to traditional techniques using chemicals promoters. Although the use of enzymes can be labeled as green and sustainable, it may entail relatively low isolation yield. An approach is to use ultrasound to further increase isolation yield. Within the framework of process intensification, enzymes and ultrasound can be combined within a sole process to increase isolation yield and reduce the usage of disposable chemical substances. However, process intensification is not obtained without cost as it may entail some deterioration of desirable starch characteristics. Hence, the selection of optimal isolation conditions for starch isolation faces multiple conflicting objectives. This work addressed this problem by developing experiments to establish the effect of enzyme and ultrasound aimed at establishing the best isolation conditions considering not only yield but also color and in vitro digestibility criteria. The decision analysis used the popular TOPSIS approach in combination with Monte Carlo simulations to include experimental uncertainty. The analysis showed that the weighting given to decision criteria groups allows for the analysis of various manufacturing scenarios where nutritional aspects are weighted above other criteria. Experimental data uncertainty plays a significant role, as measurement error can decisively affect the best operating condition choice. Results presented here promote the use of computational multicriteria decision-making tools for process optimization and intensification in food industry.