A multiscale kinetics model for the analysis of starch amylolysis

Bello‐Pérez, Luis A.; Agama‐Acevedo, Edith; Garcia‐Valle, Daniel E.; Alvarez-Ramı́rez, José

doi:10.1016/j.ijbiomac.2018.10.161

Cited by 39 publications

(25 citation statements)

References 11 publications

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“…This could be attributed to the first minutes of intestinal digestion, in which the amylose and amylopectin were leaching from the gel and probably the amount of alginate dissolved was not enough to slow the hydrolysis. But the values obtained were higher than those reported by Bello‐Perez et al () for Hylon VII starch samples. In this sense, we could suppose that the presence of calcium ions could be the responsible of higher values of k FDS .…”

Section: Resultscontrasting

confidence: 82%

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

Ramírez

Millon

Núñez

et al. 2019

J Food Process Engineering

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The aim of this study was to investigate through the use of Weibull and Multiscale kinetics models the effect of different particle size distributions on starch hydrolysis during in vitro digestion of calcium alginate filled with gelatinized potato starch as model foods. Three-different model foods (calcium alginate and gelatinized starch with a without alginate beads) were used. Three particle size distributions by applying the amount of 5, 10, and 15 compression cycles were generated and characterized by Rosin-Rammler model. The different particle distributions were in vitro digested and starch hydrolysis was quantified. The results showed significant differences (p > .05) between the three particle size distributions. In general, the particle size affected the starch hydrolysis, but structured model food produced a lower hydrolysis (~73%) compared to nonstructured food (>90%). These results also showed that incorporation of beads played an important role in modulating starch hydrolysis. The Weibull-model (R 2 > 0.95) and Multiscale kinetics-model (R 2 > 0.98) were fitted to starch hydrolysis curves. The parameters of both models were able to explain the hydrolysis behavior for the different kind of structures and particle size distributions studied. This study showed that particle size distribution or incorporation of small beads can determine the starch hydrolysis during in vitro digestion. Practical applicationThe chewing process has as main objective to reduce the food to small particles.These particles have a size distribution which will be dependent on the number of chewing cycles that are applied. This distribution can be determinant in the following step of digestion, especially at the intestinal level where carbohydrate hydrolysis mainly occurs. The results showed how food structuring can affect the particle size distributions with the consequent of modulating starch hydrolysis during in vitro digestion of gelatinized potato starch. Certainly, this study, beyond presenting a way to simulate the chewing process, showed the importance to consider a method to produce a particle size distribution which can impact on nutrient release. Finally, for food industry could be useful to have information about how the particle size affect the amount of nutrients that can be obtained from the food, mainly to be informed to consumers into the nutrition facts.

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Section: Resultscontrasting

confidence: 82%

“…The second model used was proposed by Bello‐Perez, Agama‐Acevedo, Garcia‐Valle, and Álvarez‐Ramírez (). They considered the digestible starch fraction ( Y DS ) as two fractions: a fast digestion of digestible starches fraction ( Y FDS ) followed by a slow digestible starches ( Y SDS ).…”

Section: Methodsmentioning

confidence: 99%

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

Ramírez

Millon

Núñez

et al. 2019

J Food Process Engineering

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“…In vitro starch digestibility was assessed in pasta as eaten, i.e. boiled for the optimum cooking time, using a previously reported method by Bello‐Pérez et al 22 . In brief, artificial saliva containing porcine α‐amylase (250 U mL −1 carbonate buffer, pH 7), followed by pepsin (1 mg mL −1 in 0.02 mol L −1 HCl, pH 2) were used.…”

Section: Methodsmentioning

confidence: 99%

Addition of chickpea markedly increases the indigestible carbohydrate content in semolina pasta as eaten

2020

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BACKGROUND There is a growing interest in increasing dietary fiber (DF) consumption because of the health benefits associated with this nutrient. Pulses are considered a good source of non‐digestible carbohydrates. The aim of this study was to investigate the possibility of substituting semolina with chickpea flour to increase indigestible carbohydrate content without altering the texture of the pasta. RESULTS Pasta was prepared by extruding semolina–chickpea blends. The protein and DF content in the cooked pasta increased with the chickpea level, with an important contribution of resistant starch (RS) to the DF values. The optimum cooking time decreased as the chickpea content increased, which was related to the degree of starch gelatinization of the raw pasta. The in vitro digestible starch content decreased with the chickpea substitution level, concomitant with the increase in RS content. In general, the texture of the chickpea‐containing pasta was similar to that of semolina pasta. CONCLUSIONS Pending acceptability studies on these pastas may grant their promotion as good fiber sources, probably helpful in the fight against obesity and diet‐related non‐communicable diseases. © 2020 Society of Chemical Industry

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“…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:

D_{normalt} = D_{0} + D_{\infty ‐ 0} (1 ‐ \exp [‐ K t])

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. Although independently proposed, if p = number of phases and D ∞ = ( D 0 + D 1 + … + D i ), the models are mathematically equivalent and can be generalised as:

D_{normalt} = D_{0} + \sum_{i = 1}^{p} D_{i} (1 ‐ normalexp (][, {‐ K}_{i}, t))

{Or . D}_{normalt} = D_{0} + \sum_{i = 1}^{p} D_{i} ‐ \sum_{i = 1}^{p} D_{i} \exp {(‐ K}_{i} t false)

…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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

Sopade¹

2020

Int J of Food Sci Tech

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A multiscale kinetics model for the analysis of starch amylolysis

Cited by 39 publications

References 11 publications

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

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

Addition of chickpea markedly increases the indigestible carbohydrate content in semolina pasta as eaten

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

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A multiscale kinetics model for the analysis of starch amylolysis

Cited by 39 publications

References 11 publications

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

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

Addition of chickpea markedly increases the indigestible carbohydrate content in semolina pasta as eaten

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

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