Evaluation of a non-genetically modified reduced-lignin alfalfa cultivar in mixtures with grasses
Bibliographic record
Abstract
Several reduced-lignin alfalfa (Medicago sativa L.) cultivars [GM (genetically-modified) and non-GM] are now available locally and are thought to be a tool that could be used in the dairy industry to increase forage digestibility and intake. Non-GM reduced-lignin cultivars may have more potential locally due to the limited acceptability of GM cultivars in eastern Canada and as they can be grown in mixtures with cool-season grasses [i.e., timothy (Phleum pratense L.) or tall fescue (Schedonorus arundinaceus (Schreb.) Dumort.)]. We evaluated the performance of a non-GM reduced-lignin alfalfa cultivar compared to a standard (non-GM) alfalfa cultivar when mixed with perennial grass species (timothy and tall-fescue) to determine if a reduced-lignin alfalfa cultivar can provide advantages in terms of forage quality and yield in eastern Canada. Dry matter yield, nutritive attributes, and the yield contribution of each species were determined. Irrespective of the alfalfa cultivar, alfalfa-timothy mixtures produced lower grass yields due to drought conditions experienced during the study, but forage quality was higher when compared to alfalfa-tall fescue mixtures. The value of lower quality alfalfa-tall fescue mixtures was compensated by their greater yields. The contribution to yield of grasses was low, alfalfa in all treatments contributing the most (70-80%) to forage yields. Significantly higher yields and lower forage quality were observed when plants were harvested at the early flower stage of alfalfa when compared to the early bud stage. Irrespective of the alfalfa stage at harvest or the grass it was associated with, the reduced-lignin non-GM alfalfa cultivar failed to significantly improve the nutritive value of alfalfa-grass mixtures compared to the standard alfalfa cultivar, an average 4% reduction (or 23 g kg-1 of NDF) in neutral detergent fiber concentration being observed across both production years, with no differences in acid detergent fiber, lignin concentrations, or yields. Therefore, the reduced-lignin non-GM alfalfa cultivar evaluated thus appears to have limited potential locally when used in mixtures with grasses
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".