Accounting for shear scission in the size-exclusion chromatography of debranched starch

The chain-length distribution (CLD) of starch influences many functional properties of starch-containing substances, and also contains information about starch biosynthetic processes. The commonest method for measuring this CLD is to debranch the starch enzymatically, and then to measure the molecular weight distribution of the resulting linear chains using size-exclusion chromatography (SEC). However, SEC suffers from various artifacts, including shear scission of longer chains. Here, a method of correcting for such shear scission is developed: fitting the apparent CLDs (affected by shear scission) with biosynthesis-based models, over a range of flow rates, and extrapolating the resulting model-based parameters to zero flow rate. To apply this, the apparent CLDs of five rice starches were measured using SEC with a range of flow rates, and these apparent CLDs were parameterized using biosynthesis-based models. The model parameters fitted from CLDs at different flow rates were extrapolated to zero flow rate, and were then used to calculate the CLD that would be obtained with zero flow rate, thereby taking partial account of shear scission. The extrapolation suggests that shear scission significantly degrades extra-long (degree of polymerization, DP, >1500) amylose chains to shorter chains (DP ~ 500-1500), which, if uncorrected, would vitiate inferences from SEC results. The partial correction method devised here can be used to develop more reliable relationships between structural and biosynthesis-related parameters of starch and functional properties of starch-containing substances.

Authors

Institutions

Publication Details

Journal
Analytical and Bioanalytical Chemistry
Published
2025-05-24
DOI
https://doi.org/10.1007/s00216-025-05917-w
Primary Topic
Food composition and properties
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accounting for shear scission in the size-exclusion chromatography of debranched starch

Robert G. Gilbert, Jihui Zhu, Ziyi Wang
Analytical and Bioanalytical Chemistry
Food composition and properties
article

Accounting for shear scission in the size-exclusion chromatography of debranched starch

Robert G. Gilbert, Jihui Zhu, Ziyi Wang
article en

Abstract

The chain-length distribution (CLD) of starch influences many functional properties of starch-containing substances, and also contains information about starch biosynthetic processes. The commonest method for measuring this CLD is to debranch the starch enzymatically, and then to measure the molecular weight distribution of the resulting linear chains using size-exclusion chromatography (SEC). However, SEC suffers from various artifacts, including shear scission of longer chains. Here, a method of correcting for such shear scission is developed: fitting the apparent CLDs (affected by shear scission) with biosynthesis-based models, over a range of flow rates, and extrapolating the resulting model-based parameters to zero flow rate. To apply this, the apparent CLDs of five rice starches were measured using SEC with a range of flow rates, and these apparent CLDs were parameterized using biosynthesis-based models. The model parameters fitted from CLDs at different flow rates were extrapolated to zero flow rate, and were then used to calculate the CLD that would be obtained with zero flow rate, thereby taking partial account of shear scission. The extrapolation suggests that shear scission significantly degrades extra-long (degree of polymerization, DP, >1500) amylose chains to shorter chains (DP ~ 500-1500), which, if uncorrected, would vitiate inferences from SEC results. The partial correction method devised here can be used to develop more reliable relationships between structural and biosynthesis-related parameters of starch and functional properties of starch-containing substances.

Analytical and Bioanalytical ChemistryVol. 417(17)
The University of Queensland (AU), Kansas State University (US), Agriculture and Food (AU), ARC Centre of Excellence for Plant Success in Nature and Agriculture (AU), Yangzhou University (CN)
University of Queensland, National Natural Science Foundation of China
Openalex Percentile: Top 87%
Food composition and properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.