Modeling Starch Digestograms: Computational Characteristics of Kinetic Models for in vitro Starch Digestion in Food Research

Abstract

Starch digestion is mostly investigated with in vitro techniques, and time-course measurements are common. These yield digestograms that are modeled by theoretical, semitheoretical, and empirical kinetic equations, many of which are reviewed here. The Duggleby model has Michaelis-Menten functions, and its dependent variable is on both sides of the equation with no apparent parameter for maximum digestible starch (D Ý ). The Gaouar and Peleg models are equivalent. They predict both the initial digestible starch (D 0 ) and D Ý , and an average digestion rate, but they can reveal "biratial" digestions. The first-order kinetic model exhibits diverse predictabilities and, when linearized, D Ý is sometimes equated to 100 g/100 g dry starch (100%), it yields an average rate of digestion and can predict negative D 0 . The log of slope (LOS) model is unique in revealing the rapid-to-slow digestion rate phenomenon, but without guidelines to identify such. The LOS model does not sometimes use all the digestogram data, can predict D Ý greater than 100%, and returns zero digestion rate for some digestograms. However, some starchy materials exhibit a slow-to-rapid digestion rate phenomenon, as demonstrated with an example. The modified first-order kinetic model uses all the digestogram data with practical constraints (D 0 ࣙ 0 g/100 g dry starch; D Ý ࣘ 100 g/100 g dry starch), describes all digestograms, and yields an average digestion rate, but it can also be used for "biratial" digestions. In addition, the logistic and Weibull models are discussed. Using some published data, the computational characteristics of these commonly used models are presented with objective parameters to guide choices.

Effects of Hydrothermal Processing Duration on the Texture, Starch and Protein In Vitro Digestibility of Cowpeas, Chickpeas and Kidney Beans

“…Another explanation for the increase in the rate of starch digestion is likely through hydrothermally induced cell wall permeabilisation [ 21 ], which can increase the random diffusion of α-amylase onto the surface of starch granules [ 46 ], thus increasing starch hydrolysis. An increase in the cell wall permeability was qualitatively illustrated by Pallares Pallares, Alvarez Miranda, Truong, Kyomugasho, Chigwedere, Hendrickx and Grauwet [ 21 ], showing an increased diffusion of fluorescently labelled pancreatic α-amylase into the interior of isolated common bean cells ( Phaseolus vulgaris ) as a function of t c .…”

Modelling multiphasic starch digestograms: an objective procedure for slope discontinuities†

“…Starch digestograms are mainly described with a first‐order kinetic model and its variants, and eqn (1), the modified first‐order kinetics model (Nguyen & Sopade, 2018; Olawoye & Gbadamosi, 2020), is universal for monophasic and segments of multiphasic starch digestograms:where starch digested at time t is D t , at time t = 0 is D 0 , and as time t → ∞ is D ∞ , maximum digestible starch (= ( D 0 + D ∞−0 ) ≤ 100%), while K = rate of in vitro starch digestion. Recently, the first‐order kinetic model was expanded (Bello‐Perez et al ., 2019; Li et al ., 2019) for parallel biphasic starch digestograms.…”

“…This is because, as shown below, neither the second‐ nor the third‐order polynomial equation, relative to the first‐order polynomial equation, majorly described the slope discontinuities in the studied digestograms. However, there are existing starch digestion models with 3–5 parameters (Nguyen & Sopade, 2018; Bello‐Perez et al ., 2019; Li et al ., 2019; Meraz et al ., 2019). Moreover, from published studies (Liu & Sopade, 2011; Nguyen & Sopade, 2018; Olawoye & Gbadamosi, 2020), a second‐order polynomial equation was adjudged suitable only because of the displayed quadratic trend supported by acceptable statistics.…”

“…The health and nutritional importance of starch, which exists in diverse food materials, propels its studies into the forefront of food research, amongst which is understanding its digestion mechanisms. Starch digestion is mostly investigated with in vitro techniques, and the more popular time‐course measurements yield starch digestograms that are modelled to obtain digestion parameters (Nguyen & Sopade, 2018; Olawoye & Gbadamosi, 2020). In vitro starch digestion was modelled as a monophasic (one rate of digestion) process until the studies of Liu & Sopade (2011) first reported and quantitated changes in rates of starch digestion, slope discontinuities or slope changes in the first derivative of time‐course starch digestion data; biphasic starch digestion.…”

Effect of particle size distribution on the in vitro digestion of calcium alginate‐starchy model foods

“…where S H 0 is the initial percentage of hydrolyzed starch measured at time 30 min, S H max corresponds to the maximal percentage of hydrolyzed starch attained at the end of digestion, k defines the time scale of the process (min −1 ) associated with the rate of starch hydrolysis and β is a shape parameter that characterizes the shape of the release curves (Guo, Bellissimo, & Rousseau, ; Nguyen & Sopade, ). Both parameter k and β were obtained by nonlinear regression of the data by minimizing the sum of square error (SSE) using Solver Tool (Excel, Microsoft).…”