Microbial Diversity in the Phyllosphere and Rhizosphere of an Apple Orchard Managed under Prolonged “Natural Farming” Practices
Bibliographic record
Abstract
Microbial diversity in an apple orchard cultivated with natural farming practices for over 30 years was compared with conventionally farmed orchards to analyze differences in disease suppression. In this long-term naturally farmed orchard, major apple diseases were more severe than in conventional orchards but milder than in a short-term natural farming orchard. Among major fungal species in the phyllosphere, we found that Aureobasidium pullulans and Cryptococcus victoriae were significantly less abundant in long-term natural farming, while Cladosporium tenuissimum predominated. However, diversity of fungal species in the phyllosphere was not necessarily the main determinant in the disease suppression observed in natural farming; instead, the maintenance of a balanced, constant selection of fungal species under a suitable predominant species such as C. tenuissimum seemed to be the important factors. Analysis of bacteria in the phyllosphere revealed Pseudomonas graminis, a potential inducer of plant defenses, predominated in long-term natural farming in August. Rhizosphere metagenome analysis showed that Cordyceps and Arthrobotrys, fungal genera are known to include insect- or nematode-infecting species, were found only in long-term natural farming. Among soil bacteria, the genus Nitrospira was most abundant, and its level in long-term natural farming was more than double that in the conventionally farmed orchard.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".