Post-transplant reactions of mycorrhizal and mycorrhiza-free seedlings of <i>Leucaena leucocephala</i> to pH changes in an Oxisol and Ultisol of Hawaii
Bibliographic record
Abstract
The extent to which pretransplant colonization of seedlings with the arbuscular mycorrhizal fungus (AMF) Glomus aggregatum Schenck and Smith emend. Koske could enhance the post-transplant growth of two cultivars of Leucaena leucocephala (Lam.) de Wit (cv. K-8 and cv. K-636) in Al- and Mn-rich acid soils was evaluated in a greenhouse. Arbuscular mycorrhizal colonization measured at the end of the experiment was significantly stimulated by inoculation in both cultivars at all pH levels tested, although colonization was most stimulated if cv. K-8 was grown in the Al-rich soil at the lowest pH. Symbiotic effectiveness measured as P content of Leucaena pinnules was significantly suppressed in both cultivars if they were grown at the lowest pH. Symbiotic effectiveness measured as pinnule P content and shoot biomass yield was enhanced in both cultivars by liming. The trends in effectiveness were similar in both cultivars, but cultivar effect was significant in the Mn-rich Oxisol (Wahaiawa soil) but not in the Al-rich Ultisol (Leilehua soil). The tolerance of the cultivars to acid soil toxicity in the Wahiawa soil varied with the pretransplant mycorrhizal status of their seedlings. The effect of pretransplant colonization of seedlings was to eliminate the differences in the tolerance of the cultivars to acid soil toxicity. Our data suggest that AMF could offset some of the growth reduction associated with soil acidity and that host genotype could play a role in this regard.
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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".