Effect of CO<sub>2</sub> enrichment and increased nitrogen supply on the induction of sunflower (<i>Helianthus annuus</i> L.) primary leaf senescence
Bibliographic record
Abstract
A study was made of the effect of atmospheric CO2 enrichment and increased nitrogen availability on primary leaf senescence in sunflower (Helianthus annuus L.). First, markers normally used for monitoring leaf development (dry weight, leaf surface area, protein content, photosynthetic pigment levels, CO2 fixation rate, changes in the enzymes involved in nitrogen metabolism, and plant-tissue oxidative status) were measured in plants grown for 42 days under ambient (400 µL L−1) or enriched CO2 conditions (800 µL L−1), and with two different levels of nitrate supply (10 mM and 25 mM). Second, two-dimensional electrophoresis (2-DE) was used to compare primary-leaf protein profiles (16 and 42 days) in sunflowers grown under ambient or enriched CO2 conditions with elevated nitrate supply. Plants grown under enriched CO2 conditions and with high nitrogen supply displayed faster growth, a higher CO2 fixation rate, and increased activity by antioxidative and nitrogen-metabolism-related enzymes than those grown under elevated CO2 with low nitrogen supply. These findings indicate that CO2 enrichment and increased nitrate availability slow down the induction of senescence, suggesting that senescence may be directly related to leaf C/N ratio. These results enhance our understanding of the sunflower’s response to increased atmospheric CO2 levels, one of the environmental factors favoring climate change.
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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) | 0.001 | 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".