Presence of Soybean Vein Necrosis Orthotospovirus (Tospoviridae: Orthotospovirus) in Pakistan, Pakistani Scientists’ and Farmers’ Perception of Disease Dynamics and Management, and Policy Recommendations to Improve Soybean Production
Bibliographic record
Abstract
Soybean vein necrosis orthotospovirus (SVNV: Tospoviridae: Orthotospovirus) is a well-recognized thrips-vectored and seed-borne virus common in the United States (U.S.), Canada, and Egypt. Pakistan started the commercial cultivation of soybeans in the 1970s, when some soybean cultivars were imported from the U.S. to meet the country's domestic requirement of oil, poultry, animal feed, and forage. A survey of farmers and scientists was conducted in the Punjab and Khyber Pakhtunkhwa provinces of Pakistan to understand perceptions of SVNV in the indigenous Pakistani community. Concurrently, soybean fields were sampled for SVNV presence at the National Agricultural Research Institute in Islamabad, Pakistan. Based upon survey and SVNV detection results through ELISA and qRT-PCR, a policy was developed. Overall, we found that SVNV was present in Islamabad, Pakistan in USDA-approved soybean cultivars. Although scientists knew about general thrips biology and insecticides, knowledge about identification of vectors (Thrips species) was not significantly different between the scientists and the farmers. Scientists at the Islamabad location were more aware of crop production technology and pests. This study reports that Pakistan needs to strengthen its research institutes, scientists' and farmers' capacity building, and extension programs to understand the disease complex in soybean crops.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".