Nighttime transpiration represents a negligible part of water loss and does not increase the risk of water stress in grapevine
Bibliographic record
Abstract
Abstract Nighttime transpiration has been previously reported as a significant source of water loss in many species; however, there is a need to determine if this trait plays a key role in the response to drought. This study aimed to determine the magnitude, regulation and relative contribution to whole plant water‐use, of nighttime stomatal conductance (gnight) and transpiration (Enight) in grapevine (Vitis vinifera L.). Our results showed that nighttime water loss was relatively low compared to daytime transpiration, and that decreases in soil and plant water potentials were mainly explained by daytime stomatal conductance (gday) and transpiration (Eday). Contrary to Eday, Enight did not respond to VPD and possible effects of an innate circadian regulation were observed. Plants with higher gnight also exhibited higher daytime transpiration and carbon assimilation at midday, and total leaf area, suggesting that increased gnight may be linked with daytime behaviors that promote productivity. Modeling simulations indicated that gnight was not a significant factor in reaching critical hydraulic thresholds under scenarios of either extreme drought, or time to 20% of soil relative water content. Overall, this study suggests that gnight is not significant in exacerbating the risk of water stress and hydraulic failure in grapevine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".