Potential impacts of the ring nematode, <i>Mesocriconema xenoplax</i> , on grapevines in British Columbia: a microplot study
Bibliographic record
Abstract
Abstract The Okanagan Valley of British Columbia hosts a wine grape industry that has grown substantially in the past three decades in terms of both acreage and economic benefit to the region. The ring nematode, Mesocriconema xenoplax , has recently been found to be widespread in vineyard soils in the region. This study used field microplots to assess the potential impacts of a local population of M. xenoplax on the first four years growth of either self-rooted ‘Merlot’ or ‘Merlot’ vines grafted onto three commonly used rootstocks: 3309C, 44-53M, and Riparia Gloire. The population of M. xenoplax multiplied to comparable levels on self-rooted vines and all rootstocks, indicating that none of the vine genotypes were resistant to M. xenoplax . Inoculation with M. xenoplax reduced cumulative pruning weights of self-rooted vines by 58%. Inoculation with M. xenoplax reduced trunk cross-sectional areas of 3309C by 45% and that of self-rooted vines by 38%, whereas it did not affect trunk cross-sectional areas of 44-53 or Riparia Gloire, indicating differing levels of rootstock tolerance to M. xenoplax . Our data suggest that M. xenoplax is likely impacting vineyard health and productivity in the region, and the selection of rootstocks and management practices to minimize impacts of this nematode should be considered in future vineyard replant management programs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".