Alfalfa resistance to post-harvest <i>Aspergillus</i> species: Response to selection
Bibliographic record
Abstract
Alfalfa (Medicago sativa L.) cultivar development programs routinely incorporate resistance to fungal diseases that limit forage yield, quality and stand longevity. "Hay molding", caused by saprophytic fungi, reduces forage quality during the post-harvest period, but genetic resistance has not been reported. The objective was to determine the response to selection for post-harvest fungal resistance in alfalfa. Initially, 1144 genotypes from 22 alfalfa cultivars were screened for post-harvest fungal resistance with a combination of Aspergillus species. Forty resistant and 40 susceptible genotypes were selected by measuring percentage of leaf area with fungal coverage. The selected genotypes and their maternally derived half-sib families were screened for resistance to Aspergillus repens. Mean leaf area with fungal coverage was significantly (P < 0.05) lower for resistant than susceptible parental genotypes and maternal half-sib families. Percent leaf area with fungal coverage ranged from 13.2 to 70.5% (mean, 41.7 ± 1.7) among resistant and 28.2 – 83.4% (mean, 50.2 ± 1.7) among susceptible parental genotypes. Among the maternal half-sib families, resistant families ranged from 14.0 to 51.3% (mean, 32.1 ± 1.8) and susceptible families from 18.8 to 60.1% (mean, 40.3 ± 1.9). These results show a positive response to selection for post-harvest fungal resistance in alfalfa. Key words: Alfalfa, Medicago sativa, post-harvest fungi, Aspergillus species, breeding, divergent selection
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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".