Improving the resistant starch in succinate anhydride‐modified cardaba banana starch: A chemometrics approach

Abstract

Resistant starch of succinate anhydride‐modified cardaba banana starch was model using response surface methodology (RSM) and artificial neural network (ANN). This was investigated by varying the octenyl succinic anhydride (OSA) concentration (3%–5%), time (30–60 min), and pH (8–10) using a Box–Behnken design. According to the result, both the RSM and ANN modeling techniques predict the modification process with high accuracy (coefficient of determinant, R2 > .97 and root mean square of error =.44–.47). The optimization of the process parameters to maximize the resistant starch was performed using RSM and ANN coupled with genetic algorithm (GA). The ANN‐GA gave the highest resistant starch content (39.87%) under the optimal process condition of OSA concentration 4.38%, reaction time 59.79 min, and 8.01 pH. This study revealed that the ANN‐GA proved to be superior to RSM in the optimization of cardaba starch modification process. Practical applications In this study, the optimum starch modification conditions (succinate anhydride concentration, time, and pH) for maximizing the resistant starch in cardaba banana were investigated using response surface methodology and artificial neural network. The result obtained will enable the development of appropriate processes for starch modification from cardaba banana. It would then be possible to predict efficiently the conditions of succinate anhydride concentration, time, and pH, which will facilitate the maximization of resistant starch in the banana and increase its potential for use as a functional food ingredient in the food product development.

Lignocellulose, dietary fibre, inulin and their potential application in food

“…After all, when starch is broken down, it is reduced to glucose, which is in the form of sugar, supplying sugar to the blood. Therefore, eating a high quantity of starch results in a high level of glucose in the human blood, however, in the case of consuming resistant starch which is immune to digestion, there is a reduction in the glucose in the blood because the starch is not broken dow thereby reducing the risks of some blood diseases that might arise due to excess glucose in the blood ( Olawoye et al., 2020b ).…”

“…In healthy humans, resistant starch is starch as well as degrading products of starch, which are not digestible in their small intestine by enzymes ( Olawoye et al., 2020a ; Olawoye et al., 2020b ). Several foods containing carbohydrates in different proportions have resistant starch.…”

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

“… Akintunde et al. (2015) and Olawoye et al. (2020) also reported the superiority of ANN over RSM when optimizing the extraction of oil from Bauhinia monandra seed and cardaba starch respectively.…”

“…This result was also supported by the parity plot between the predicted and experimental values. Akintunde et al (2015) and Olawoye et al (2020) also reported the superiority of ANN over RSM when optimizing the extraction of oil from Bauhinia monandra seed and cardaba starch respectively.…”

Modelling and prediction of hydrolysis index of gluten-free cookies from cardaba banana starch vis-?-vis response surface methodology and support vector machine.

“…The application of the cooking banana is limited due to its high perishability when ripe and unlike dessert banana, it found no usage after ripening. Due to this, it had found application in the production of complementary food (Ayo-Omogie & Ogunsakin, 2013) as well as functional starch (Olawoye et al, 2020a;Olawoye et al, 2020c). However, because the cooking banana contains no gluten, it serves as good raw material in the production of gluten-free products.…”