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Record W7104000651 · doi:10.1080/07060661.2025.2573936

Survey and first molecular characterization of <i>Banana bunchy top virus</i> infecting <i>Musa</i> spp. cv. Sabri in Bangladesh

2025· article· en· W7104000651 on OpenAlexvenueno aff

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdentification (biology)PopulationPolymerase chain reactionGenomeOutbreak

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.016
GPT teacher head0.220
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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