Phosphorus acquisition by citrate‐ and phytase‐exuding <scp><i>Nicotiana tabacum</i></scp> plant mixtures depends on soil phosphorus availability and root intermingling
Bibliographic record
Abstract
Citrate and phytase root exudates contribute to improved phosphorus (P) acquisition efficiency in Nicotiana tabacum (tobacco) when both exudates are produced in a P‐deficient soil. To test the importance of root intermingling in the interaction of citrate and phytase exudates, Nicotiana tabacum plant‐lines with constitutive expression of heterologous citrate (Cit) or fungal phytase (Phy) exudation traits were grown under two root treatments (roots separated or intermingled) and in two soils with contrasting soil P availability. Complementarity of plant mixtures varying in citrate efflux rate and mobility of the expressed phytase in soil was determined based on plant biomass and P accumulation. Soil P composition was evaluated using solution 31P NMR spectroscopy. In the soil with limited available P, positive complementarity occurred in Cit + Phy mixtures with roots intermingled. Root separation eliminated positive interactions in mixtures expressing the less mobile phytase (Aspergillus niger PhyA) whereas positive complementarity persisted in mixtures that expressed the more mobile phytase (Peniophora lycii PhyA). Soils from Cit + Phy mixtures contained less inorganic P and more organic P compared to monocultures. Exudate‐specific strategies for the acquisition of soil P were most effective in P‐limited soil and depended on citrate efflux rate and the relative mobility of the expressed phytase in soil. Plant growth and soil P utilization in plant systems with complementary exudation strategies are expected to be greatest where exudates persist in soil and are expressed synchronously in space and time.
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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 | 0.000 |
| 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 | 0.000 | 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".