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Which one is important to achieve maximum degree of hydrolysis, starch pre-treatment or activated α-amylase: kinetics and mathematical modeling for liquefaction

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A Correction to this article was published on 07 July 2023

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Abstract

To determine whether starch pretreatment or enzyme modification is more effective in achieving maximum hydrolysis, corn starch (CS) as a A-type starch and potato starch (PS) as a B-type starch were pre-treated using freezing–thawing (FTF), ultrasonication (US), high-pressure (HP). On the other side, α-amylase was activated with concomitantly applying dual frequency ultrasound (25 + 40 kHz) and Ca2+ ions. The effect of starch pre-treatment and enzyme modification on the starch digestion behavior were investigated. Freeze-thawed, ultrasonicated, and high-pressurized starches are highly more susceptible to amylolysis than native ones due to higher amount of disordered structure in the disrupted granules (based on crystallinity structure (determined by X-ray) and formation of hole and crack on the surface of pre-treated starches (determined by SEM analysis). Starch hydrolysis kinetics were evaluated using the first-order equation. Comparing the maximum hydrolyzed concentrations (C) and reaction rate constants (k) of pre-treated potato starches indicated that PFTP starch was most affected by a specific enzyme whereas for the pre-treated corn starches, these values were higher in pressurized corn starch. An inverse linear correlation has been shown between ordered structure and the rate of enzyme binding. Concerning to Pareto chart, the starch type depicts a greater influence on the degree of hydrolysis (%) than the other factors. Moreover, activated enzyme and starch pre-treatment represented the same standardized effects on achieving maximum hydrolysis degree.

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Correspondence to Elahe Abedi or Kiana Pourmohammadi.

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Abedi, E., Maleki, S., Pourmohammadi, K. et al. Which one is important to achieve maximum degree of hydrolysis, starch pre-treatment or activated α-amylase: kinetics and mathematical modeling for liquefaction. Food Measure 17, 4938–4953 (2023). https://doi.org/10.1007/s11694-023-01995-5

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