Productivity, nutritive value, and profitability of high-digestibility alfalfa cultivars harvested at two stages of development in eastern Canada
Bibliographic record
Abstract
Alfalfa ( Medicago sativa L.) cultivars developed for improved digestibility by conventional breeding or genetic modification have not been evaluated in eastern Canada. This study compared yield, nutritive value, and profitability of two reduced-lignin genetically modified (GM) cultivars, three conventionally selected for low lignin or high pectin, and one population with improved stem degradability, with two commercially adapted cultivars as controls. Alfalfa was harvested at the early bud (intensive management) or early flower (extensive management) stage of development during the first post-seeding year at three sites and the second post-seeding year at one site. All cultivars/populations had similar annual dry matter (DM) yields, except for the lower DM yield (−20%) of the improved stem degradability population. Conventionally selected cultivars for improved digestibility did not differ from control cultivars for in vitro DM digestibility (IVTD) and neutral detergent fiber digestibility (NDFd). Reduced-lignin GM cultivars, however, had a greater IVTD and NDFd (+10%) and less lignin (−10%) than control cultivars at the same stage of development. Reduced-lignin GM cultivars under extensive management had similar NDFd and greater annual DM yield (+1 to 2 Mg DM ha−1), but reduced total digestible nutrients (−41 to 44 g kg−1 DM), in comparison to control cultivars under intensive management. Using partial budget analysis, the comparison of more digestible GM cultivars to the control cultivars resulted in an increase in annual farm net profits ranging from CAD$7.40 to $79.60 cow−1 year−1 depending on stage of development at harvest. Further investigations are needed to quantify the performance of dairy cows fed cultivars with improved digestibility.
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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 | 0.001 | 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 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".