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

Abstract

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, R 2 > 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.

Machine learning‐based modeling in food processing applications: State of the art

“…ML‐based modeling is an exciting option to predict baking kinetics and control the quality of the product without much difficulty. Considering the benefits of ML‐based predictive modeling, recently researchers have attempted to apply ML in many areas of food baking such as the baking of biscuits/cookies (Broyart & Trystram, 2003; Isleroglu & Beyhan, 2020; Olawoye et al., 2020), milk cake (Emerald et al., 2020), bread (Banooni et al., 2009; Sablani et al., 2002), and soft cake (Goyal & Goyal, 2011).…”

Celiac Disease Management through Gluten-Free Diets

“…In research for remedy, food products have been developed from GF-dough made from GF-flour (such as rice, sorghum, buckwheat, amaranth, quinoa, and maize) [19,21], dairy products [22], dietary fibers [3,23], and starches [2][3][4]. Advantages of these alternatives are low glycemic index, antihypertensive, and antihyperlipidemia [2][3][4].…”

“…The rapid changes had also resulted in a large number of people suffering from poor health conditions due to the food they consume. Owing to this, there had been an increase in people's awareness about the role in which foods play in the emergence of these diseases [2][3][4]. One of such diseases resulting from food consumption is celiac disease (CD).…”

“…Gluten-free products' marketability is estimated to increase in value from US$ 4.18 billion in 2017 to US$ 6.47 billion by 2023 in which gluten-free bread and cookie are estimated to be the most consumed cereal-based GF-food globally [9]. During the production of food products made from gluten, gluten present in the food products is responsible for the elasticity, extensivity and texture resistant if the dough [2,12]. However, to improve the quality (texture and specific volume) of gluten-free diet/products, hydrocolloids such as hydroxypropylmethylcellulose, xanthan gum, pectin, carboxymethylcellulose are commonly used to improve the baking quality, imparting texture and appearance as well as stability in the gluten-free dough.…”

Physicochemical and sensory properties of gluten‐free cupcakes added with fig seeds pomace flour

“…Glycemic index is briefly defined as degree of the blood glucose level reached two hours after the consumption of foods. And the diseases such as type2 diabetes, cardiovascular diseases and obesity are correlated with consuming foods have high glycemic index which is larger than 71 (Olawoye et al, 2020). Therefore, there is an increasing demand for exploring new functional ingredients that could help the development of different types of high-quality and low glycemic index gluten-free foods.…”