Genetic selection for nonstructural carbohydrates and its impact on other nutritive attributes of alfalfa (<i>Medicago sativa</i>) forage
Bibliographic record
Abstract
Abstract High concentration of nonstructural carbohydrates (NSC) in forages improves ruminant N utilization and performance. The present study evaluated the direct and indirect effects of one cycle of divergent phenotypic selection for NSC in alfalfa along with the diurnal and seasonal stability of the trait. For this purpose, divergent NSC populations were developed (NSC+ and NSC−) and two field trials were established in Quebec, Canada. Forage samples were collected twice a day (morning and afternoon) and three times a year (spring, summer and autumn) and analysed for NSC, crude protein (CP), fibre concentration, digestibility and yield. The NSC+ population maintained greater NSC concentrations than the NSC− population over 2 establishment years (+18%, 129 vs. 109 g/kg) and three production years (+8%, 126 vs. 116 g/kg). Time of cutting and period of harvest had significant effects on alfalfa NSC concentration and other nutritive attributes, but they did not affect the response to selection for NSC concentration. Phenotypic selection for NSC concentration can therefore be used in a recurrent phenotypic selection approach to improve alfalfa nutritive value.
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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".