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Record W1979856445 · doi:10.1094/cchem.2002.79.2.183

Swelling Index of Glutenin Test. I. Method and Comparison with Sedimentation, Gel‐Protein, and Insoluble Glutenin Tests

2002· article· en· W1979856445 on OpenAlexaff
C. Wang, Miklós Kovács

Bibliographic record

VenueCereal Chemistry · 2002
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGluteninSwellingChemistryChromatographyFood scienceBiochemistryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

ABSTRACT Molecular weight distribution of wheat proteins is primarily responsible for the viscoelastic properties of flour dough. Furthermore, the amount of SDS insoluble proteins (mainly high molecular weight glutenin) plays the major role. We have developed a simple test to determine the swelling power of glutenin (swelling index of glutenin or SIG) for predicting dough properties and end‐use quality. Flour samples (40 mg) were hydrated in distilled water and then allowed to swell in nonreducing solvents (SDS, lactic acid, or mixtures of the two) followed by low speed centrifugation. The SIG was calculated as the weight of the residue divided by the original sample weight. The SIG test was compared with the results from other small‐scale tests for 20 flour samples. SIG tests showed highly significant correlations with the gel protein and insoluble glutenin test (r ≥ 0.85, r ≥ 0.93, P < 0.001, respectively) and significant correlations with SDS and Zeleny sedimentation tests (r ≥ 0.74, r ≥ 0.72, P < 0.001, respectively). The swelling capacity of glutenin depended on swelling time and mixing intensity in nonreducing solvents. Swelling curves obtained from SIG values versus different swelling time can be divided into three distinct stages: swelling, swollen, and breakdown. These stages may reflect soluble and insoluble glutenin contents and quality among different cultivars. SIG test values for short swelling time and low mixing intensity were significantly correlated to gel protein content and SDS‐sedimentation values (r = 0.96, r = 0.90, P < 0.001, respectively). SIG test values for long swelling time and high mixing intensity were significantly correlated to insoluble glutenin content (r = 0.96, P < 0.001). The difference of swelling condition (time and mixing intensity) among these small‐scale methods is the reason for their different correlations with insoluble glutenin content. Because large numbers of samples can be analyzed in a short time with excellent reproducibility, the SIG test may be a useful screening test in a breeding program, predicting the quantity and quality of insoluble glutenin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.262
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations63
Published2002
Admission routes1
Has abstractyes

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