Biotechnological mechanism for improving plant remobilization of phosphorus during leaf senescence
Bibliographic record
Abstract
Phosphorus enrichment of aquatic ecosystems through diffuse source pollution is an ongoing issue worldwide. A potential solution lies in the use of fast-growing, multipurpose feedstocks, such as trees, to limit the flow of phosphorus into riparian areas through luxury consumption. However, the perennial nature of trees and their use of leaves as storage organs for excess phosphorus may reduce the effectiveness of contaminant removal during periods of leaf abscission. In an attempt to improve phosphorus remobilization during autumnal senescence, transgenic hybrid poplar P39 (Populus alba × Populus grandidentata) and Arabidopsis thaliana harbouring a constitutively expressed low-affinity potato phosphate transporter (35S::StPht1-1) were generated using Agrobacterium-mediated transformation. For both species, the highest expressing 35S::StPht1-1 lines were grown alongside wild-type plants and subjected to increasing phosphate applications. StPht1-1 expression in A. thaliana led to a reduction in biomass when grown under high-phosphate conditions and had no effect on phosphate remobilization during senescence. In contrast, StPht1-1 constitutive expression in P39 resulted in increased leaf phosphate content in the highest expressing transgenic line and minimal to no effect on P resorption efficiency. Surprisingly, sulphate resorption showed the greatest improvement in all three transgenic poplar lines, displaying a 31%-37% increase in resorption efficiency. These results highlight the complexity of nutrient resorption mechanisms in plants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".