Related Experiment Video
Updated: May 14, 2026

Preparation of Matcha Fresh Noodles with Stable Color using Embedding Method and Microwave Treatment
Published on: July 26, 2024
Enriched Fresh Noodles Incorporating Chestnut Starch-Resveratrol Complexes: Quality, Structural Properties and
Lu Li1,2, Yawei Xu1,2, Yunfei Huang1,2
1College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
Abstract:
Starch-polyphenol complexes have attracted increasing attention as functional ingredients for improving the structural stability and reducing the glycemic potential of starch-based foods, yet their application in extruded fresh noodles remains insufficiently understood. In this study, chestnut starch-resveratrol complexes prepared by heat-moisture synergistic recrystallization treatment (CS-HMRT-Res) were incorporated into extruded fresh noodles, and their quality, structural characteristics, digestibility, and glycemic response were systematically evaluated. Compared with commercial wheat-based Regan noodles, CS-HMRT-Res noodles exhibited enhanced cooking stability (lower swelling and leaching) and improved texture (hardness, chewiness, tensile strength), with a markedly lower total color difference after cooking (ΔE = 1.8 vs. 6.5). SEM, FTIR and XRD indicated a more compact and ordered network; the relative crystallinity of cooked noodles increased to approximately 30.8%. In in vitro digestion, CS-HMRT-Res showed the lowest starch hydrolysis extent at 180 min (45.92%) and yielded a low predicted glycemic index of 53.35, compared with 70.65 for Regan noodles. Consistently, gavage studies in mice confirmed that HMRT-Res-chestnut starch produced the lowest postprandial blood glucose increment response (4.31 mmol/L). Molecular dynamics simulations further suggested that resveratrol could competitively occupy the α-amylase binding cavity and reduce starch accessibility to the enzyme. Overall, CS-HMRT-Res improved processing quality, structural integrity, and reduced glycemic potential, offering a structure-function framework for designing low-GI products.
