High temperature promotes early senescence in primary leaves of sunflower (<i>Helianthus annuus</i> L.) plants
Bibliographic record
Abstract
De la Haba, P., De la Mata, L., Molina, E. and Agüera, E. 2014. High temperature promotes early senescence in primary leaves of sunflower (Helianthus annuus L.) plants. Can. J. Plant Sci. 94: 659–669. High temperature affects numerous biochemical and physiological traits in plants. Primary leaves of sunflower (Helianthus annuus L.) were collected from plants grown under a control temperature (day/night regime of 23/19°C) or a high temperature (day/night regime of 33/29°C) for 16, 22, 28, 32 or 42 d. Leaves of sunflower plants exposed to high temperature exhibited decreased growth, as reflected by lower specific leaf mass and reduced leaf area as compared with controls. A superior decrease in soluble protein content during leaf life span in plants grown at high temperature relative to control plants (70% vs. 45%, respectively) suggests that high temperature promotes soluble protein degradation in leaves. High temperature also reduces net photosynthetic rate (P N ) possibly by decreasing the content in photosynthetic pigments and the stomatal conductance (g s ). The activity of nitrate reductase and glutamine synthetase decreased while deaminating activity in glutamate dehydrogenase increased in leaves exposed to high temperature. Our results suggest that high temperature induced early senescence in sunflower leaves, probably as a result of an accumulation of soluble sugars and the associated decrease in starch levels. Oxidative damage resulting from increased H 2 O 2 accumulation and a decline in antioxidant activity may have also contributed to accelerated senescence of primary leaves at high temperature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".