Effect of atmospheric carbon dioxide levels and nitrate fertilization on glucosinolate biosynthesis in mechanically damaged Arabidopsis plants
Bibliographic record
Abstract
BACKGROUND: Increased atmospheric carbon dioxide (CO2) levels predicted to occur before the end of the century will impact plant metabolism. In addition, nitrate availability will affect metabolism and levels of nitrogen-containing defense compounds, such as glucosinolates (GSLs). We compared Arabidopsis foliar metabolic profile in plants grown under two CO2 regimes (440 vs 880 ppm), nitrate fertilization (1 mM vs 10 mM) and in response to mechanical damage of rosette leaves. RESULTS: Constitutive foliar metabolites in nitrate-limited plants show distinct global patterns depending on atmospheric CO2 levels; in contrast, plants grown under higher nitrate fertilization under elevated atmospheric CO2 conditions have a unique metabolite signature. Nitrate fertilization dampens the jasmonate burst in response to wounding in plants grown at elevated CO2 levels. Leaf GSL profile mirrors the jasmonate burst; in particular, indole GSLs increase in response to damage in plants grown at ambient CO2 but only in nitrate-limited plants grown under elevated CO2 conditions. CONCLUSIONS: This may reflect a reduced capacity of C3 plants grown under enriched CO2 and nitrate levels to signal changes in oxidative stress and has implications for future agricultural management practices.
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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 | 0.001 |
| 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".