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Updated: Feb 6, 2026

Analysis and Specification of Starch Granule Size Distributions
Published on: March 4, 2021
Chlorogenic acid alters the physicochemical and functional properties of starch by multiple intermolecular
Zhijie Liu1, Zhicheng Jin1, Zhangchi Peng1
1State Key Laboratory of Rice Biology and Key Lab of the Ministry of Agriculture for Nuclear Agricultural Sciences, Institute of Nuclear Agricultural Sciences, Zhejiang University, Hangzhou, 310029, Zhejiang, PR China.
Abstract:
Chlorogenic acid (CGA) can influence the structural and functional properties of starch by forming complexes with starch, while the underlying interaction mechanisms, particularly their variations across starch types, remain unclear. This study employed molecular dynamics simulations to investigate how CGA interacts with amylose and affects the structural and physicochemical properties of corn starch (CS), potato starch (PoS), and pea starch (PeS). Molecular dynamics simulations revealed that CGA bound to amylose via hydrogen bonding, van der Waals forces, and electrostatic interactions. The presence of CGA disrupted the short-range ordered structure across all three types of starches, resulting in looser network morphologies. CGA universally inhibited starch retrogradation but led to divergent viscosity profiles. Specifically, CS-6CGA and PoS-6CGA blends exhibited peak viscosity of 898 cP and 2182 cP, respectively, significantly lower than their gelatinized counterparts. In contrast, the peak viscosity of PeS increased from 860 cP to 1019 cP upon the 6% addition of CGA. All starch-CGA blends demonstrated reduced thermal stability, yet less weight loss. Notably, CGA significantly enhanced resistant starch (RS) content and reduced starch digestibility across three types of starch. This effect was most pronounced in PeS, which showed a 9.53% increase in RS content and a decreased digestibility from 67.16% to 57.73%. These findings highlight the differential effects of CGA on various starches, providing critical insights for selecting optimal starch sources based on desired functional properties, thereby expanding the potential application of CGA in food processing.
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