Understanding the impact of the levels of alpha-amylase on wheat flour functionality and breadmaking
Bibliographic record
Abstract
Wheat is crucial for the global food supply, but climate change and unpredictable weather conditions, like heavy rainfalls, strain the wheat supply chain due to germination. Wheat germination affects flour’s bread-making quality, yet understanding its impact is limited. This research aims to assess the physicochemical changes that occur in wheat during germination by evaluating the flour breadmaking functionality and the resulting bread characteristics. Wheat kernels belonging to class Canada Western Red Spring (CWRS) were germinated at 21°C for up to 36 hours (0 h, 6 h, 12 h, 18 h, 24 h, and 36 h, which were coded as G0, G6, G12, G18, G24 and G36, respectively) to trigger different levels enzyme activities. Morpho-geometric features showed a progressive increase along germination time, particularly after 18 hours of germination. The falling number (FN) value decreased from 385 seconds in the sound wheat to 63 seconds in G36, while alpha-amylase activity in those samples was 0.11 CU/g and 6.96 CU/g, respectively. Pasting parameters showed a significant decrease after 12 hours of germination. The apparent peak viscosity of sound wheat (1192 mPa.s) was negligible in G36 (85 mPa.s). The apparent viscosity was recovered by adding silver nitrate 1 mM, although silver nitrate 10 mM was needed to inhibit the alpha-amylase activity in G24 and G36. The thermal properties of the control flour showed higher enthalpy values (4.86 J/g). Germination affected gluten functionality as indicated by the gluten performance index (GPI) decrease at G24 (0.40) and G36 (0.39) and the mixing properties like mixing tolerance index (133, 134, respectively), reflecting decreased gluten strength. A modified method for assessing gluten index suggested that despite gluten degradation after 24 h and 36 h of germination, proteins were able to aggregate after 120 min resting. Further, mini-breads displayed increased 2D area in G24 and G36 and lower crumb hardness in G24 and G36. Despite gluten degradation, proteins aggregate sufficiently for bread leavening results an enhanced mini-breads area. Mini breads made from germinated flour show promise for human consumption. Overall, this approach could help produce green-label products and reduce losses from sprouting, promoting sustainability in the food industry.
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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 | 0.001 |
| 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".