Asparagine and dough quality: Gluten strength factors in hard red spring wheat
Bibliographic record
Abstract
Abstract Background and Objectives Safety aspects regarding free asparagine concentration in wheat arise because of its acrylamide formation potential in baked wheat products. Free asparagine concentration in wheat is affected by environment, genotype, and nitrogen and sulfur fertilization, which also affect wheat protein content and composition. Changing protein content and composition affects gluten strength, altering product quality. This study investigated how gluten strength was affected by environment, genotype, and fertilization treatments grown under commercially relevant conditions. Findings Environment predominated in affecting dough extensibility and genotype primarily affected resistance to extension, with minimal effects from fertilization treatments. Differences in extensigraph parameters at two resting times segregated genotypes according to gluten strength. Conclusions Factors affecting free asparagine accumulation in wheat also affect gluten strength. Genotype and environment require primary attention since they play an important role in both wheat safety and quality. Significance and Novelty The lack of studies investigating the impact of factors affecting free asparagine concentration on the gluten strength of wheat has implications for the global wheat market. From a novel perspective on dough extensibility and resistance to extension, the effects of environment, genotype, and fertilization on the gluten strength of commercially important wheat varieties are considered in a food safety context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".