Foam stability of leaves from anthocyanidin‐accumulating <i>Lc</i>‐alfalfa and relation to molecular structures detected by fourier‐transformed infrared‐vibration spectroscopy
Bibliographic record
Abstract
Abstract Foam stability related to pasture bloat from alfalfa pastures might be reduced by introducing a gene that stimulates the accumulation of mono‐/polymeric‐anthocyanidin. The objective of this study was to determine the foam formation (at 0 min) and stability (at 150 min) from aqueous leaf extracts of three transgenic Lc‐alfalfa progeny (BeavLc1, RambLc3 and RangLc4), parental non‐transgenic (NT) alfalfa and AC Grazeland (bloat‐reduced cultivar) harvested at 07:00 or 18:00 h. Initial and final foam volumes at 07:00 h were lower for AC Grazeland compared with all other treatments and lower for RangLc4 compared with the other two Lc‐progeny at 0 min and NT‐alfalfa at 150 min. At 18:00 h, initial foam volume was larger for NT‐alfalfa and final foam volume was larger for RambLc3 compared with AC Grazeland, BeavLc1 and RangLc4. Spectroscopic vibration associated with carbohydrates increased initial foam volume and stability. More amide I relative to amide II, fewer α‐helices relative to β‐sheets and leaf extract ethanol‐film and protein content increased initial foam volume but did not stabilize it. Spectroscopic vibration associated with all carbohydrates other than structural carbohydrates was more important than vibration from protein structures for foam formation and stabilization. In conclusion, Lc‐alfalfa accumulated anthocyanidin and had reduced foaming properties compared with parental NT alfalfa but AC Grazeland and RangLc4 had the lowest foaming properties.
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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".