Co-inoculation with an arbuscular mycorrhizal fungus and a phosphate-solubilizing fungus promotes the plant growth and phosphate uptake of avocado plantlets in a nursery
Bibliographic record
Abstract
An experiment was conducted to evaluate the individual and combined effects of treatment with the phosphate solubilizing fungus Mortierella sp. and the arbuscular mycorrhizal fungus Rhizoglomus fasciculatum on the plant growth and phosphate uptake on plantlets of avocado (Persea americana Mill. cv. ‘Hass’) grown in a nursery. A completely randomized test design was used. Treatments consisted of individual and combined inoculations with R. fasciculatum and Mortierella sp. at two concentrations (106 and 108 CFU·mL−1), and the results were compared with an uninoculated control. The plant height, shoot dry mass, and shoot phosphate uptake were significantly higher in plants inoculated with both of the fungi than with either fungus individually, or in the uninoculated control plants. The colonization of fine roots with both fungi decreased when they were co-inoculated by comparison with when they were individually inoculated, which suggests that these fungi compete for root space. Despite this competition, the dual inoculation showed that the fungi had additive effects on plant performance. Thus, shoot phosphate levels in plantlets inoculated with mycorrhizae was significantly higher when Mortierella sp. was co-inoculated at both concentrations, compared with the single inoculations and the uninoculated control plants (mycorrhiza free).
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".