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Record W3139450348 · doi:10.1002/cche.10430

Effectiveness and biochemical basis of wholemeal GlutoPeak test in predicting water absorption and gluten strength of Canadian hard red spring wheat

2021· article· en· W3139450348 on OpenAlexaffabout
Kun Wang, Jatinder S. Sangha, Richard D. Cuthbert, Bin Xiao Fu

Bibliographic record

VenueCereal Chemistry · 2021
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food CanadaCanadian International Grains Institute
Fundersnot available
KeywordsFarinographGlutenChemistryAbsorption of waterFood scienceTriticaleAgronomyBotanyBiology

Abstract

fetched live from OpenAlex

Abstract Background and objectives To further improve the efficiency of GlutoPeak test for selecting water absorption and gluten strength in wheat breeding programs, this study was conducted to investigate the suitability and effectiveness of wholemeal as testing material by eliminating flour milling process which is often the bottleneck of quality evaluation throughput. Findings By analyzing forty‐four advanced wheat lines, strong correlations were found for wholemeal GlutoPeak parameters with conventional flour‐based farinograph absorption ( r = .82, p < .001) and stability ( r > .76, p < .001), and extensigraph R max ( r > .90, p < .001). The secondary structures of gluten proteins, collected at different mixing stages of GlutoPeak test, were examined using Fourier transform infrared (FTIR) spectroscopy. The β‐turn structure increased significantly from partially developed to fully developed gluten, indicating its critical role in contributing to gluten viscoelasticity. Conclusions Without the preparation of refined flour, wholemeal GlutoPeak test can be a powerful tool for rapid and effective selection of key wheat quality traits. Significance and novelty This study demonstrated the effectiveness of wholemeal GlutoPeak test in screening key wheat quality parameters. The changes in gluten protein secondary structure during GlutoPeak test (refined flour or wholemeal) were demonstrated for the first time.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.032
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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 teacher head, 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

Citations8
Published2021
Admission routes2
Has abstractyes

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