Survey for major viruses in commercial Vitis vinifera wine grapes in Ontario
Bibliographic record
Abstract
BACKGROUND: In recent years, the Ontario grape and wine industry has experienced outbreaks of viral diseases across the province. Little is known about the prevalence of viruses and viral diseases in Ontario. Since 2015, we have conducted large-scale surveys for major viruses in commercial wine grapes in order to obtain a comprehensive understanding of the prevalence and severity of viral diseases in Ontario. METHODS: A total of 657 composite leaf samples representing 3285 vines collected from 137 vine blocks of 33 vineyards from three appellations: Niagara Peninsula, Lake Erie North Shore and Prince Edward County. These samples covered six major red cultivars and five major white grape cultivars. Using a multiplex RT-PCR format, we tested these samples for 17 viruses including those involved in all major viral diseases of the grapevine, such as five grapevine leafroll-associated viruses (GLRaV-1, 2, 3, 4, 7), grapevine red blotch virus (GRBV), grapevine Pinot gris virus (GPGV), grapevine rupestris stem sitting-associated virus (GRSPaV), grapevine virus A (GVA), grapevine virus B (GVB), grapevine fleck virus (GFkV), arabis mosaic virus (ArMV), tomato ringspot virus (ToRSV), trapevine fanleaf virus (GFLV), among others. RESULTS: Fourteen of the 17 viruses were detected from these samples and the predominant viruses are GRSPaV, GLRaV-3, GFkV, GPGV and GRBaV with an incidence of 84.0, 47.9, 21.8, 21.6 and 18.3%, respectively. As expected, mixed infections with multiple viruses are common. 95.6% of the samples included in the survey were infected with at least one virus; 67% of the samples with 2-4 viruses and 4.7% of the samples with 5-6 viruses. The major grape cultivars all tested positive for these major viruses. The results also suggested that the use of infected planting material may have been one of the chief factors responsible for the recent outbreaks of viral diseases across the province. CONCLUSIONS: This is the first such comprehensive survey for grapevine viruses in Ontario and one of the most extensive surveys ever conducted in Canada. The recent outbreaks of viral diseases in Ontario vineyards were likely caused by GLRaV-3, GRBV and GPGV. Findings from this survey provides a baseline for the grape and wine industry in developing strategies for managing grapevine viral diseases in Ontario vineyards.
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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 | 0.002 | 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".