Nutrient composition and degradation profiles of anthocyanidin-accumulating <i>L</i>c-alfalfa populations
Bibliographic record
Abstract
Alfalfa (Medicago sativa L.) is one of the most used forages in the world but suffers the disadvantage of having poor protein utilization by the animal. The poor protein utilization is the result of excessive ruminal protein degradation, which might be reduced by the protein precipitating capacity of anthocyanidin (AC) and condensed tannins (CT). The objective of this study was to determine the effects of the Lc-transgene on survival, anthocyanidin, condensed tannin and chemical profiles in crossed populations of western Canadian-adapted Lc-alfalfa. These were compared with their non-transgenic (NT) parental varieties, Rangelander, Rambler, and Beaver. Lc-alfalfa forage accumulated enhanced amounts of anthocyanidin, with an average concentration of 197.4 µg g -1 DM, while condensed tannins were not detected. Both of these metabolites were absent in the NT parental varieties. Lc-alfalfa had a lower (24.8 vs. 27.3% DM; P < 0.02) crude protein (CP) and higher (58.3 vs. 55.5% DM; P < 0.01) carbohydrate (CHO) concentration, which resulted in their decreased (P < 0.01) N:CHO ratio (68.1 vs. 79.2 g kg -1 ) compared with NT alfalfa. Slowly degradable N:CHO ratio was decreased by 5.9 g kg -1 (P < 0.03) and total rumen-degradable N:CHO ratio was decreased by 12.9 g kg -1 (P < 0.03) in Lc-alfalfa compared with NT alfalfa. In conclusion, Lc-gene transformation resulted in the accumulation of anthocyanidin, decreased total protein content, increased total carbohydrate content and improved the balance between nitrogen and carbohydrates in the crossed transgenic populations of western Canadian-adapted alfalfa compared to their NT western Canadian parental alfalfa varieties. Key words: Alfalfa, anthocyanidin, Lc-transgene, protein and carbohydrate sub-fractions, nitrogen-to-carbohydrate degradation ratios
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".