GRAPEVINE VIRUS DISEASES:ECONOMIC IMPACT AND CURRENT ADVANCES IN VIRAL PROSPECTION AND MANAGEMENT
Bibliographic record
Abstract
ABSTRACT Grapevine (Vitis spp.) is a major vegetative propagated fruit crop with high socioeconomic importance worldwide. It is susceptible to several graft-transmitted agents that cause several diseases and substantial crop losses, reducing fruit quality and plant vigor, and shorten the longevity of vines. The vegetative propagation and frequent exchanges of propagative material among countries contribute to spread these pathogens, favoring the emergence of complex diseases. Its perennial life cycle further accelerates the mixing and introduction of several viral agents into a single plant. Currently, approximately 65 viruses belonging to different families have been reported infecting grapevines, but not all cause economically relevant diseases. The grapevine leafroll, rugose wood complex, leaf degeneration and fleck diseases are the four main disorders having worldwide economic importance. In addition, new viral species and strains have been identified and associated with economically important constraints to grape production. In Brazilian vineyards, eighteen viruses, three viroids and two virus-like diseases had already their occurrence reported and were molecularly characterized. Here, we review the current knowledge of these viruses, report advances in their diagnosis and prospection of new species, and give indications about the management of the associated grapevine diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".