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Record W2048162173 · doi:10.1094/pdis-92-12-1683

Genetic Composition of <i>Pepino mosaic virus</i> Population in North American Greenhouse Tomatoes

2008· article· en· W2048162173 on OpenAlexaboutno aff
Kai‐Shu Ling, William M. Wintermantel, Michael Bledsoe

Bibliographic record

VenuePlant Disease · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenotypePopulationGreenhouseHorticultureGeneticsDemographyGene

Abstract

fetched live from OpenAlex

In just a few short years, pepino mosaic disease has quickly become endemic in greenhouse tomatoes around the world. Although three genotypes of Pepino mosaic virus (PepMV) were identified in the United States, genetic composition of PepMV in greenhouse tomato crops in North America has not been determined. In this study, genetic variability and population structure of PepMV were evaluated through nucleotide sequence comparison and phylogenetic analysis of two genomic regions (helicase domain and TGB2-3) derived from 91 cDNA clones that were derived from 31 field-collected samples. These samples were collected from several major greenhouse tomato facilities in five states in the United States and two provinces in Canada. All four major genotypes of PepMV (EU, US1, US2, and CH2) were found in North America. Three distinct genotypes (EU, US1, and US2) were found in mixed infection in samples collected from Arizona and Colorado, two genotypes (EU and CH2) in Texas, and a single genotype (EU) in Alabama and California and the provinces of British Columbia and Ontario in Canada. The complexity of population genetics of PepMV in the United States poses an additional challenge to the greenhouse tomato industry because a tomato cultivar with durable resistance to multiple genotypes of PepMV may be harder to develop.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

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)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.229
Teacher spread0.205 · 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 teacher head, 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

Citations45
Published2008
Admission routes1
Has abstractyes

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