A Genotypic Comparison Reveals That the Improvement in Nitrogen Remobilization Efficiency in Oilseed Rape Leaves Is Related to Specific Patterns of Senescence-Associated Protease Activities and Phytohormones
Bibliographic record
Abstract
Oilseed rape (Brassica napus L.) is an oleoproteaginous crop characterized by low N use efficiency (NUE) that is mainly related to a weak Nitrogen Remobilization Efficiency (NRE) during the sequential leaf senescence of the vegetative stages. Based on the hypothesis that proteolysis efficiency is crucial for the improvement of leafNRE, our objective was to characterize key senescence-associated proteolytic mechanisms of two genotypes (Ténor and Samouraï) previously identified with contrasting NREs. To reach this goal, biochemical changes, protease activities and phytohormone patterns were studied in mature leaves undergoing senescence in two genotypes with contrasting NRE cultivated in a greenhouse under limiting or ample nitrate supply. The genotype with the higher NRE (Ténor) possessed enhanced senescence processes in response to nitrate limitation, and this led to greater degradation of soluble proteins compared to the other genotype (Samouraï). This efficient proteolysis is associated with (i) an increase in serine and cysteine protease activities and (ii) the appearance of new cysteine protease activities (RD21-like, SAG12-like, RD19-like, cathepsin-B, XBCP3-like and aleurain-like proteases) during senescence induced by N limitation. Compared to Samouraï, Ténor has a higher hormonal ratio ([salicylic acid] + [abscisic acid]) / ([cytokinins]) that promotes senescence, particularly under low N conditions, and this is correlated with the stronger protein degradation and serine/cysteine protease activities observed during senescence.
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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".