Rootstock microbiome as a target for manipulation to combat apple replant disease
Bibliographic record
Abstract
Apple replant disease (ARD) describes a phenomenon of reduction of crop productivity in the early years of orchard establishment on sites previously planted with apple. Currently, manipulation of the soil microbiome through (bio)fumigation is the primary approach to alleviate ARD. An alternative approach to combat ARD, could involve adjusting the rootstock microbiome to better cope with biotic stress present in orchard soil. In this study we evaluated differences in microbiome structure and composition between nursery grown rootstock and mature apple trees, cultivated in Nova Scotian orchards. We found that mature apple tree roots associated microbiome dramatically differed in its diversity, structure and composition compared to that associated with saplings. Our research identified several fungal and bacterial taxa as potential candidates for further study in the context of nursery inoculation and their possible role in mitigating ARD in re-planted apple orchards. The results of this study provide a foundation for development of a synthetic community which could be used in nurseries during rootstock propagation to improve saplings adaptation to ARD soils. This approach may offer an ecologically safe and cost-effective alternative to current soil amendments to alleviate ARD consequences.
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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".