2026-10-15T18:05:15Z https://data.mendeley.com/oai

oai:data.mendeley.com/t32mzg7bn6.2 2026-06-16T23:49:33Z

De La Rosa-Millan, Julian Electrosynthesis-driven fractionation and structural remodeling of corn starch: Implications for molecular architecture, thermal behavior, and digestibility Mendeley Data This dataset contains the experimental data associated with the manuscript entitled “Electrosynthesis-driven fractionation and structural remodeling of corn starch: Implications for molecular architecture, thermal behavior, and digestibility.” The data support the evaluation of electrosynthesis-assisted electro-fractionation as a non-thermal strategy to modify and separate corn starch assemblies after gelatinization, enzymatic hydrolysis, and physical fractionation. The dataset includes compositional, thermal, molecular, colloidal, electrokinetic, and in vitro digestibility parameters for native corn starch, non-electrosynthesized light and heavy fractions, α-amylase-treated fractions, isoamylase-treated fractions, and electrosynthesis-treated counterparts. Specifically, the dataset contains values for yield, moisture, protein, fat, ash, total starch, amylose and amylopectin proportions, DSC thermal transition parameters, molecular weight, radius of gyration, amylopectin chain-length distribution, zeta potential, hydrodynamic diameter, polydispersity index, turbidity, stability index, rapidly digestible starch, slowly digestible starch, resistant starch, and predicted glycemic index. The data were generated from three independent processing batches. Each batch included gelatinization, enzymatic hydrolysis when applicable, electrosynthesis-assisted or non-electrosynthesis fractionation, phase separation, washing, and freeze-drying. Analytical measurements were performed on the independently prepared samples, and results are reported as mean ± standard deviation where applicable. This dataset can be used to reproduce the statistical comparisons, graphical summaries, principal component analysis, and partial least squares regression presented in the manuscript. It may also be useful for researchers interested in starch fractionation, electrically assisted processing, starch molecular architecture, in vitro digestibility, colloidal stability, and structure-function relationships in food hydrocolloid systems. Starch Digestibility Multi-Scale Food Structure Dataset doi:10.17632/t32mzg7bn6.2 oai:data.mendeley.com/t32mzg7bn6.2 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/t32mzg7bn6 2026-06-16T23:49:33Z