Identification of<i>Potato mop-top virus</i>(PMTV) in potatoes in China
Bibliographic record
Abstract
Potato tubers exhibiting necrotic rings/arcs were found in a winter potato crop ‘Favorita’ in the subtropical area Huidong county, Guangdong province, China, in 2012. When the symptomatic tubers were cut crosswise, light to dark brown necrotic arcs were observed in the tuber flesh. A mini-survey of the crop found 8% symptomatic tubers in an area of 10 meters2. To reveal the causal agent of the disease, reverse transcription–polymerase chain reactions (RT-PCR) targeting 9 common potato viruses including those viruses (e.g, Potato mop-top virus (PMTV), Tobacco rattle virus, Tomato spotted wilt virus, and Potato virus Y tuber necrosis strain) known to be capable of induction of tuber necrosis, were carried out. Except for PMTV, no other viruses were detected. Sequencing of the 460 bp amplicon revealed that the fragment exhibited a 99-100% sequence identify with most PMTV coat protein sequences deposited in GenBank, which was confirmed by a further phylogenetic analysis. Enzyme linked immunosorbent assay with PMTV antibody on the symptomatic tubers was also carried out, and a positive reading was observed. Together, these results demonstrate that PMTV was the causal agent for the spraing disease in potatoes in the winter crop in Guangdong. To our knowledge, this is the first report of PMTV in Guangdong province, China, and the first scientific confirmation of PMTV in China.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".