Synergistic effect of a phosphate-solubilizing fungus and an arbuscular mycorrhizal fungus on leucaena seedlings in an Oxisol fertilized with rock phosphate
Bibliographic record
Abstract
A greenhouse experiment was conducted to determine the effects of a phosphate-solubilizing fungus (Mortierella sp.) and an arbuscular mycorrhizal fungus (Glomus fistulosum (Skou and Jakobsen)) in enhancing plant Pi uptake and growth of Leucaena leucocephala (Lam.) grown in an Oxisol fertilized with graded amounts of rock phosphate (RP). For this purpose, a surface soil sample was fertilized with four levels of the Huila RP (P = 0, 150, 300, and 600 mg·kg −1 ) and inoculated with none, one, or both fungi. In the unfertilized soil, leucaena plants grew poorly and there was no plant response to individual or dual inoculation. When RP was added G. fistulosum significantly increased plant Pi uptake and growth, the effect of inoculation was significantly higher at the P levels of 300–600 mg·kg −1 . Mortierella sp. was highly effective in increasing plant P uptake and growth of mycorrhizal leucaena, but it was ineffective in nonmycorrhizal leucaena across the RP gradient. The synergistic effects of dual inoculation were more evident on plant Pi uptake than on growth. The results indicate that the phosphate-solubilizing fungus effect was limited by soil Pi sorption. This limitation likely was overcome by the mycorrhizal association, which allowed a more efficient capture of the Pi released due to RP dissolution.
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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) | 0.001 | 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 | 0.001 |
| 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".