Persistent negative temperature response of mesophyll conductance in red raspberry (<scp><i>Rubus idaeus</i></scp> L.) leaves under both high and low vapour pressure deficits: a role for abscisic acid?
Bibliographic record
Abstract
Abstract The temperature dependence of mesophyll conductance (gm) was measured in well‐watered red raspberry (Rubus idaeus L.) plants acclimated to leaf‐to‐air vapour pressure deficit (VPDL) daytime differentials of contrasting amplitude, keeping a fixed diurnal leaf temperature (Tleaf) rise from 20 to 35 °C. Contrary to the great majority of gm temperature responses published to date, we found a pronounced reduction of gm with increasing Tleaf irrespective of leaf chamber O2 level and diurnal VPDL regime. Leaf hydraulic conductance was greatly enhanced during the warmer afternoon periods under both low (0.75 to 1.5 kPa) and high (0.75 to 3.5 kPa) diurnal VPDL regimes, unlike stomatal conductance (gs), which decreased in the afternoon. Consequently, the leaf water status remained largely isohydric throughout the day, and therefore cannot be evoked to explain the diurnal decrease of gm. However, the concerted diurnal reductions of gm and gs were well correlated with increases in leaf abscisic acid (ABA) content, thus suggesting that ABA can induce a significant depression of gm under favourable leaf water status. Our results challenge the view that the temperature dependence of gm can be explained solely from dynamic leaf anatomical adjustments and/or from the known thermodynamic properties of aqueous solutions and lipid membranes.
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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".