Detection of potyviruses infecting Iranian common beans using broad-spectrum antibodies and universal primer pairs
Bibliographic record
Abstract
Six provinces of Iran were surveyed during 2012–2014 to detect potyviruses infecting common bean crops. A total of 277 leaf samples were collected from bean plants and some other legumes as well as weeds and wild legumes showing virus-like symptoms. Enzyme-linked immunosorbent assay (ELISA) using broad-spectrum potyvirus antibodies gave a positive reaction with 63 samples (22.7%). Moreover, a mixed colony of aphids (Aphis craccivora and A. fabae), collected from a locust tree plant (Robinia sp.), transmitted a potyvirus to young healthy bean plants; the infection was confirmed through serological assays. Partial nuclear inclusion b (NIb) and coat protein (CP) regions of the genomes of 19 ELISA-positive samples were amplified by reverse-transcription polymerase chain reaction (RT-PCR) using NIb and NWCIEN (or WCIEN) universal primer sets, respectively. Potyvirus species identification was confirmed by BLASTN and phylogenetic analyses followed by ELISA tests using virus-specific antibodies or biological assays. The results clearly showed the presence of Bean common mosaic virus (BCMV), Bean common mosaic necrosis virus (BCMNV), Bean yellow mosaic virus (BYMV) and Wisteria vein mosaic virus (WVMV) in the samples tested. Non-specific amplification of a Cucumovirus genome by using NIb primers was also recorded. The results showed the natural occurrence of a new potyvirus species (WVMV), and a new host for BYMV (Trifolium repens) in the mid-Eurasian region of Iran. Our findings indicate the capacity of the universal detection systems for fast and accurate detection of legume potyviruses in the country and for use in routine diagnostic assays.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".