First Report of Soybean vein necrosis virus in Soybean Fields of Oklahoma
Bibliographic record
Abstract
Soybean vein necrosis virus (SVNV) causes a new emerging disease of soybean that has been recorded in more than 10 states (1,2,3,4) of the United States, but so far no information is available about its presence in soybean crops of Oklahoma. Surveys of commercial soybean fields were conducted for soybean viruses during summer of 2012. A total of 327 samples were randomly collected from soybean fields in 11 counties. Symptoms typical of SVNV infections including leaf chlorosis and leaf-vein necrosis were observed on some soybean plants in the field (4). All soybean leaf samples were tested against SVNV polyclonal antisera obtained from AC Diagnostics, Inc. (Fayetteville, AR) by dot-immunobinding assay (DIBA) (1). Fifty-three samples reacted positively with SVNV antisera. Total RNA was extracted from three DIBA-positive samples collected from soybean plants in Choctaw County and tested by reverse transcription (RT)-PCR using SVNV-specific primers (forward primer 5'-ATGTTCTCTCTATAATAGCCA and reverse primer 5'-ACCCATAACAATTGATCAAGA-3') that were designed from the available sequence in the GenBank (Accession No. GU722317.1) to amplify a fragment from RNA1. A band of the expected size of 344 bp was observed on a 1% agarose gel in all three samples. The PCR products were purified using QIAquick PCR Purification Kit (QIAGEN, Valencia, CA), cloned (pGEM-T Easy Vector, Promega, Madison, WI) and sequenced in both directions. The consensus sequence of the 344-bp fragment was 99% identical with the corresponding region of RNA 1 of SVNV isolate 'Milan_TN' (Accession No. GU722317.1). These results confirmed the presence of SVNV in soybean fields, which are mostly located in Criage, Choctaw, Hughes, LeFlore, Mayes, Muskogee, McCurtain, Okmulgee, Ottawa, Rogers, and Sequoyah counties of Oklahoma. None of the samples collected from north central or western parts of the state were positive against SVNV. To our knowledge, this is the first report of SVNV in soybean crops in Oklahoma. Soybean is one of the major oil seed crops cultivated on approximately 200,000 hectares annually in Oklahoma and the presence of SVNV could pose a potential threat to the production of soybean in the future. References: (1) J. L. Jacobs and M. I. Chilvers. Plant Dis. 97:1387, 2013. (2) J. Han et al. Plant Dis. 97:693, 2013. (3) D. L. Smith et al. Plant Dis. 97:693, 2013. (4) J. Zhou et al. Virus Genes 43:289, 2011.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".