Variation for whole plant water use efficiency and leaf-level traits affecting drought tolerance in soybean
Bibliographic record
Abstract
Genotypic variation for water use efficiency and a correlated leaf-level trait, the dark-adapted leaf epidermal conductance (gdark ) has been previously identified among soybean cultivars adapted to Ontario, Canada. In the present work, parents of existing soybean mapping populations were screened for variation in these two traits to identify populations that would be suitable for identifying chromosomal regions controlling the traits. Second, a comparison of greenhouse and field data demonstrated that greenhouse screening experiments could predict cultivar differences for g dark in the field, but only when plants in the greenhouse were grown under a cyclic drought treatment. Third, greenhouse experiments were conducted to examine restrictions to photosynthesis in six soybean cultivars during recovery from drought stress. No treatment by cultivar interactions were found. Compared to control plants, drought-stressed plants showed residual limitations to photosynthesis 24 h after rewatering. The lower photosynthetic rates were primarily caused by reduced mesophyll conductance.
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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".