Understanding how different modification processes affect the physiochemical, functional, thermal, morphological structures and digestibility of cardaba banana starch

In this study, starch was isolated from cardaba banana starch and was subjected to modification by heat-moisture treatment, citric acid, octenyl succinic anhydride, and sodium hexametaphosphate. Both the native and modified cardaba banana starches were examined for chemical, functional, pasting, thermal, morphological, structural, and antioxidant properties, as well as in vitro starch digestibility. Modification significantly influenced the properties of the cardaba banana starch. Cross-linking treatment improved the water, oil absorption, alkaline hydration capacity, swelling power, solubility and paste clarity of the starch. The final viscosity of the banana starch paste was increased alongside succinic anhydride modification which in turn enhanced the suitability of the starch in the production of high viscous products. Both FTIR spectra and X-ray diffractograms confirmed the starch had a C-type starch which was not affected by modification. Modification led to a decrease in relative crystallinity of the starch with succinylation having the maximum effect. The starch fractions; both SDS and RS significantly increased due to modification while the hydrolysis and glycemic index of the starch were significantly decreased by chemical modification. In conclusion, both physical and chemical modification of cardaba banana starch produced a starch that can serve as functional food or functional food ingredients.

Gluten-free cookies with low glycemic index and glycemic load: optimization of the process variables via response surface methodology and artificial neural network

This research investigates the effect of baking temperature and time on the resistant starch (RS), glycemic index (GI) and glycemic load (GL) of gluten-free cookies, optimized the processing parameter using a chemometrics approach of response surface methodology (RSM) and artificial neural network (ANN). The in-vitro starch digestibility of the formulated cookies exhibited a monophasic starch digestogram. Increase in resistant starch, and a decrease in the predicted GI of the cookies, was associated with low temperature and high baking time. The use of RSM and ANN modelling techniques accurately predict the RS, pGI and GL (coefficient of determinant, R² > 0.93 and root mean square of error = 0.43–0.62) of the gluten-free cookies. The optimal condition for the production of cookies with high RS, low pGI and GL were baking temperature of 158 °C and baking time of 20 min with predicted RS value of 19.61 g/100g of dry starch, pGI value of 56.98 and GL value 52.64.