GENETIC DIVERSITY OF STRAWBERRY MOTTLE VIRUS BASED ON CP GENE
Bibliographic record
Abstract
The strawberry mottle virus (SMoV) is a huge threat to the strawberry production, which seriously reduces the productivity of strawberries.The systematic study on the distribution, structural variation and genetic diversity of SMoV is useful for the prevention and control of SMoV.In this study, 159 strawberry leaves were randomly collected from 7 major strawberry growing areas in Shanxi Province for RT-PCR detection.The cp genes of positive samples were sequenced and analyzed through MEGA5, SDTv 1.2, DnaSP v5.10 and RDP v.4.31.RT-PCR detection showed that 65 samples of the 159 strawberry leaves were positive with a detection rate of 38.46%.The 65 positive samples were isolated, sequenced, and cloned to obtain three SMoV isolates.The phylogenetic tree analysis showed the 25 SMoV isolates were divided into three groups with group 1 containing 14 isolates from China, group 2 containing 10 isolates from Canada, Japan, and the United States, and group 3 containing 1 isolate from Japan.The results of selective pressure analysis and neutrality test in group 1 and group 2 showed that there were significant genetic differences between group 1 and group 2. The negative selection pressure maybe the reason for the genetic diversity of SMoV.Sequence similarity analysis displayed that the nucleotide identity range and the consistency range of amino acids was ranged from 94.68% to 99.53%, while from 98.12% to 99.84% for amino acids.This study demonstrated that SMoV was of high genetic variation, and the negative selection pressure may be the cause of SMoV genetic diversity, which provides theoretical guidance for SMoV in Shanxi.
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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 | 0.000 |
| 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) | 0.001 | 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".