Fusarium head blight: Effect on white salted and yellow alkaline noodle properties
Bibliographic record
Abstract
Composite samples of Canada Western Red Winter wheat (CWRW) with varying levels of Fusarium head blight damage (0.5–9.6%) were prepared from the 1998 Western Canadian harvest survey and milled to yield both patent (60% extraction) and straight grade (~76%) flours. The mycotoxin deoxynivalenol (DON) levels in the flours ranged from 0.21 to 2.6 ppm with no significant influence due to flour extraction. No differences were attributable to Fusarium damage (FD) in the amount of work required to sheet either yellow alkaline (YA) or white salted (WS) noodles. The color of the raw (YA) noodles was adversely affected by FD as a significant loss in noodle brightness (L*) and an increase in redness (a*) were observed for noodles prepared from both patent and straight grade flour. Straight grade YA noodles, prepared from wheat with FD levels above acceptable limits for milling grades, displayed a significant loss in yellowness (b*) after aging for 24 h. Differences in noodle brightness of raw WS noodles were observed between the control and 9.6% FD samples for both patent and straight grade noodles at 24 h. Analysis of YA and WS noodles indicated a significant linear relationship between the number of specks and the quantity of FD in the wheat. YA and WS noodles displayed significant loss in cooked noodle texture with increasing FD levels. Maximum cutting stress and recovery declined with increasing FD for both noodle types whether made from patent or straight grade flour. Maximum wheat FD tolerances below 2% are required in order to ensure optimum noodle quality. Key words: Fusarium damage, noodles, color, texture and image analysis
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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 | 0.000 | 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".