Exploring soil microbial and plant parasitic nematode communities involved in the apple replant disease complex in Nova Scotia
Bibliographic record
Abstract
Abstract Apple replant disease (ARD) is incited by a complex of causal agents including various fungi, oomycetes, and plant parasitic nematodes. These causal agents can differ significantly in abundance between orchard sites within a geographic region. Knowledge of the specific etiology of ARD is required in order to develop commercially viable soil management strategies to combat specific/individual components of the pathogen complex. In this study, we analyzed soil from six ARD affected orchard sites to assess the presence and composition of fungal, bacterial and oomycetes communities, as well as the prevalence of plant parasitic nematodes. Five fungal, and 17 bacterial classes were differentially represented in the soil microbiomes across the different locations. Mortierellomycetes was the most abundant fungal taxa represented followed by Sordariomycetes. Mortierella exigua , a fungal endophyte, was the most abundant fungal amplicon sequence variant (ASV) in the core microbiome. Among bacteria, Proteobacteria was the most prevalent phylum identified in these orchard soils. Several potential phytopathogenic fungi associated with ARD, as well as endophytes including Fusarium oxysporum , F. solani , Nectria ramulariae , Ilyonectria robusta and Nectriaceae , were identified in ARD soils. Among oomycetes, Pythium attrantheridium ( Globisporangium attrantheridium ), and P. irregulare ( Globisporangium irregulare ) were the most abundant taxa. Additionally, six different groups of plant-parasitic nematodes were found across the ARD orchard soils. Root-lesion nematodes, Pratylenchus spp., which are commonly associated with ARD, were identified in all orchard soils at population densities range from 12 to 33/100 cm 3 soil. This research enhances our understanding of the ARD pathogen complex and provide important insights for developing alternative disease management strategies in the apple industry.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".