Mycorrhizal Fungi Collected from the Rhizospheres around Different Olive Cultivars Vary in Their Ability to Improve Growth and Polyphenol Levels in Leeks
Bibliographic record
Abstract
Mycorrhizal fungus spores and propagules were collected from the soils in the vicinity of roots of five different olive cultivars. These mycorrhizal fungus communities were amplified in trap cultures and then their effect on the growth and polyphenol levels of leek plants was determined. All mycorrhizal fungus communities increased plant growth in leeks when compared to controls. In addition, communities from the roots of Frantoio and Manzanillo significantly increased plant growth, in terms of plant height and dry weights, as compared to plants that were given mycorrhizal fungus collected from cultivar Mission. Plants inoculated with mycorrhizal fungus from Frantoio also had an increase in 14 polyphenols compared to uninoculated plants. A majority of polyphenol peaks were also higher in leek plants inoculated with mycorrhizal fungi from Frantoio roots when compared to plants inoculated with mycorrhizal fungi from other olive cultivars. The affected polyphenols were identified by mass spectrometry and were mostly found to be derivatives (e.g., pentose, hexose, malonyl, feruyl, and coumaroyl) of quercetin, kaempferol, and apigenin; four remained unidentified. Molecular fingerprinting of mycorrhizal fungus communities from different olive cultivars indicated that fungi of the family Gigasporaceae were a major component of inocula obtained from Frantoio and Manzanillo roots, which were better performers in terms of plant growth and polyphenol content. Mycorrhizal fungi from cv Mission roots were relatively poor performers and were dominated by the mycorrhizae of the family Glomeraceae, specicifally the genus Rhizophagus.
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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 | 0.000 |
| 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".