Development of High-Resolution DNA Melting Analysis for Simultaneous Detection of Potato Mop-Top Virus and Its Vector, <i>Spongospora subterranea</i>, in Soil
Bibliographic record
Abstract
(Sss), was developed. The infestation of soil by PMTV was detected with a tobacco-based baiting system. Total RNA extracted from the soil led to successful RT-PCR gel electrophoresis detection of both PMTV and Sss. To facilitate more efficient detection, newly designed primer pairs for PMTV RNA species (i.e., RNA-Rep, RNA-CP, and RNA-TGB) were analyzed together with the existing Sss primers via real-time RT-PCR. The resulting amplicons exhibited melting profiles that could be readily differentiated. Under duplex RT-PCR format, all PMTV and Sss primer combinations led to successful detection of respective PMTV RNA species and Sss in the samples by HRM analyses. When the duplex HRM assay was applied to soil samples collected from six fields at four different sites in New Brunswick, Canada, positive detection of PMTV or Sss was found in 63 to 100% samples collected from fields in which PMTV-infected tubers had been observed. In contrast, the samples from fields where neither PMTV- nor Sss-infected tubers had been observed resulted in negative detection by the assay. Bait tobacco bioassay for PMTV and Sss produced similar results. Of the soil samples collected from PMTV-infested fields, 63 to 83% and 100% led to PMTV and Sss infections in the bait tobacco plants, respectively, whereas no PMTV- or Sss-infected plants were obtained from soil samples collected from PMTV- and Sss-free fields.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".