Molecular characterization of strawberry vein banding virus from China and the development of loop‑mediated isothermal amplification assays for their detection
Bibliographic record
Abstract
Strawberry vein banding virus (SVBV) is one of the serious viral pathogens infecting strawberry worldwide. To understand the molecular characterization of SVBV from China, complete genome sequences of sixteen SVBV isolates were cloned and sequenced. Sequence comparison showed they shared high nucleotide sequence identity (93.6-99.5%) with isolates from China and Japan (96.6-98.4%), while relatively low identity with the isolates from Canada (91.9-93.7%) and USA (85.5-85.9%). Phylogenetic analyses based on the complete genome sequence or coat protein (CP) gene showed the SVBV isolates clustered into three clades correlated with geographic distribution. Recombination analyses identified 13 recombinants and 21 recombinant events, indicating frequent and multiple recombinations in SVBV evolution. Furthermore, a sensitive loop-mediated isothermal amplification (LAMP) method was developed for rapid detection of SVBV isolates, which could be especially suitable for seedling propagation, virus-free culture and routine diagnostics in field investigation. This study offers new understanding of the molecular evolution and may help to improve the management of SVBV.
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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 | 0.000 | 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".