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Contrasting Impacts of Pre-harvest Field Sprouting on the Functionality of Bread Wheat and Durum Wheat

2025· article· en· W4409905374 on OpenAlexfundaboutno aff
Kun Wang, Carly Isaak, Bin Xiao Fu

Bibliographic record

VenueACS Food Science & Technology · 2025
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersAgriculture and Agri-Food Canada
KeywordsSproutingAgronomyWinter wheatBiologyField (mathematics)Whole wheatAgricultural engineeringEngineeringMathematicsHorticultureFood science

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide This study was conducted to examine the impacts of pre-harvest field sprouting (PHS) on wheat end-use functionality of bread wheat Canada Western Red Spring (CWRS) and durum wheat Canada Western Amber Durum (CWAD). PHS affected CWRS and CWAD differently in milling performance, dough rheological properties, and final product quality. With decreasing Falling Number (FN), key quality attributes of CWAD remained mostly unchanged but CWRS quality progressively decreased, especially when FN dropped below 200 s. Both CWRS and CWAD showed signs of in situ starch hydrolysis in field-sprouted kernels with more damage apparent in CWRS as greater maltose levels were found in flour than in semolina. Analysis of gluten fractions in flour or semolina indicated that protein composition was not affected by PHS. Unlike pasta-making, which involves low water-absorption, short mixing time, and high-temperature drying, the combination of high water absorption, lower temperature, and long fermentation times magnify the detrimental effects of excessive α-amylase on the bread-making performance of CWRS.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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