Characterization and Genetic Variation of Sugarcane Streak Mosaic Virus, a Poacevirus Infecting Sugarcane in Thailand
Bibliographic record
Abstract
<p>Sugarcane disease surveys were conducted from 2010 to 2014 at major sugarcane growing areas in 5 provinces (Nakhon Pathom, Kanchanaburi, Udon Thani, Khon Kaen, Nakhon Ratchasima) and germplasm collection fields. Random samples of the virus-like sugarcane leaves obtained from the surveyed areas suggested yellow streak mosaic symptoms. Direct antigen coating ELISA using locally produced SCSMV antiserum, revealed widespread incidence of SCSMV in the major sugarcane growing areas and the germplasm collection fields, ranging from 43.48-90.91% and 54.17-100% respectively. The virus isolate from sugarcane in Kamphaeng Saen, Nakhon Pathom, designated as THA-NP3, was characterized by genomic sequencing. Complete genome of THA-NP3 (JN163911) contained 9,781 nucleotides, excluding 3¢ Poly (A) tail which encoded a polyprotein of 3,130 amino acid residues comprising 10 functional proteins, namely P1, HC-Pro, P3, 6K1, CI, 6K2, NIa-VPg, NIa-Pro, NIb and CP. Sequence comparisons revealed that THA-NP3 showed 97.84% nucleotide identity to JP2 (JF488065) from China and 81.39-97.78% nucleotide identities to other recorded SCSMV sequences. Detection for the presence of CP gene by RT-PCR indicated 1094 bp containing 846 bp of the CP coding region. Analysis of the CP gene revealed genetic variation of 58 Thai SCSMV isolates, 86.17-100% nucleotide identities among them and 85.70-99.29% nucleotide identities to SCSMV isolates from other countries. Recombination events existed in the CP coding regions between two distinct sub-populations, the germplasm isolates and the farmers’ field isolates. These results suggested the incidence of SCSMV variants between the farmers’ fields and the germplasm collection fields. <strong></strong></p>
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".