Survey and first molecular characterization of <i>Banana bunchy top virus</i> infecting <i>Musa</i> spp. cv. Sabri in Bangladesh
Bibliographic record
Abstract
Banana bunchy top virus (BBTV) is a major viral pathogen in bananas, capable of causing up to 100% yield loss. This study investigated the prevalence and molecular characterization of BBTV in three major banana-growing districts – Rajshahi, Natore and Pabna – in Bangladesh. Field surveys revealed that BBTV was the most widespread viral disease, with a 62.7% infection rate in Musa sp. cv. Sabri. All six genomic components (DNA-R, -U3, -S, -M, -C, and -N) of BBTV were successfully amplified using gene-specific primers from isolates in all three districts. DNA sequencing of the Rajshahi isolates revealed 99.96–100% nucleotide identity with the corresponding genomic components of isolates from Natore and Pabna. BLASTn analysis revealed 92–98% nucleotide identity with known BBTV sequences, indicating a close relationship with Indian isolates. Phylogenetic analysis suggests that the Rajshahi isolates belong to the South Pacific group. The six primer sets used in this study proved effective for BBTV detection and are suitable for indexing virus-free tissue culture banana seedlings. This is the first molecular confirmation of BBTV infection in the Sabri cultivar in Bangladesh, underscoring a significant threat to regional banana production and the need for urgent management strategies.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
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".