Genotypic differences in red clover (Trifolium pratense L.) response under severe water deficit
Bibliographic record
Abstract
In Ontario, Canada, acreage of red clover ( Trifolium pratense L.) intercropped with winter wheat ( Triticum aestivum L. em. Thell) has declined, despite well-documented soil and yield benefits. The decline has resulted from increasing prevalence of stand non-uniformity, which has been attributed in part to soil moisture deficits. We examined whether there are genotypic differences in drought response between red clover varieties. A double-cut (Belle) and a single-cut variety (Altaswede) were grown under four different durations of drought (4, 8, 12 and 16 days below 15% relative soil water content, RSWC). Shoot dry weight, shoot relative water content (RWC), leaf area and crown water content were measured in control, drought and drought + recovery treatments. Belle used significantly more water during soil moisture deficit and had greater leaf area, shoot dry weight and RWC compared to Altaswede. In contrast, Altaswede had significantly higher survival rates than Belle, attributed to maintenance of meristematic tissue viability in the crown where re-growth, after shoot tissue desiccation, can occur. By demonstrating genotypic variation in survival strategies of red clover, traits can be identified for the development of improved varieties. Varieties with higher survival rates during drought will result in more uniform stands and increased utilization of red clover for environmental and yield benefits.
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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) | 0.000 | 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".