Greater efficiency of water use in poplar clones having a delayed response of mesophyll conductance to drought
Bibliographic record
Abstract
Improvement of water use efficiency is a key objective to improve the sustainability of cultivated plants, especially fast growing species with high water consumption like poplar. It is well known that water use efficiency (WUE) varies considerably among poplar genotypes, and it was recently suggested that the use of the mesophyll-to-stomatal conductance ratio (gm/gs) would be an appropriate trait to improve WUE. The responses of 7-week-old cuttings of four hybrid poplar clones and one native Balsam poplar (Populus balsamifera L.) to a water stress-recovery cycle were examined to evaluate the relation between the gm/gs ratio and transpiration efficiency (TE), a leaf-level component of WUE. A contrasting gs response to water stress was observed among the five clones, from stomatal closure early on during soil drying up to limited closure in Balsam poplar. However in the hybrids, the decline in gm was consistently delayed by a few days compared with gs. Moreover, in the most water use-efficient hybrids, the recovery following rehydration occurred faster for gm than for gs. Thus, the delay in the response of gm to drought and its faster recovery upon rewatering increased the gm/gs of the hybrids and this ratio scaled positively with TE. Our results support the use of the gm/gs ratio to select genotypes with improved WUE, and the notion that breeding strategies focusing mainly on stomatal responses to soil drying should also look for a strong curvilinearity between net carbon assimilation rate and gs, the indication of a significant increase in gm/gs in the earlier stages of stomatal closure.
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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 | 0.001 | 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 | 0.001 |
| 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".