Molecular and Metagenomic Analyses Reveal High Prevalence and Complexity of Viral Infections in French-American Hybrids and North American Grapes
Bibliographic record
Abstract
grapes remains understudied. We report here the results from a large-scale survey to assess the prevalence of 14 viruses among 533 composite samples representing 2665 vines from seven French-American hybrid wine grape cultivars, two North American juice grape cultivars (Concord and Niagara), and the table grape cultivar Sovereign coronation. Based on reverse transcription polymerase chain reaction (RT-PCR) assays, ten viruses were detected. Grapevine rupestris stem pitting-associated virus, grapevine leafroll-associated virus 3, grapevine Pinot gris virus and grapevine red blotch virus were detected with the highest frequency. As expected, mixed infections were common; 62% of the samples contained two or more viruses. Overall, hybrid wine grapes were infected with more viruses and a higher prevalence of individual viruses than juice and table grapes. To validate these findings and to refine the virome of these non-European grapes, high-throughput sequencing (HTS) analyses of five composite samples representing each category of grapevine cultivars was performed. Results from HTS agreed with those from RT-PCR. Importantly, Vidal, a widely grown white-wine grape with international recognition due to its use in the award-winning icewine, is host to 14 viruses, four of which comprise multiple and distinct genetic variants. This comprehensive survey represents the most extensive examination of viruses among French-American hybrids and North American grapes to date.
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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 | 0.000 | 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) | 0.000 | 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 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".