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Record W4388977352 · doi:10.3390/v15122305

Co-Infection of Tomato Brown Rugose Fruit Virus and Pepino Mosaic Virus in Grocery Tomatoes in South Florida: Prevalence and Genomic Diversity

2023· article· en· W4388977352 on OpenAlexaboutno aff
Salih Yılmaz, Özgur Batuman

Bibliographic record

VenueViruses · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPhylogenetic treeOutbreakVirusVirologyHorticultureVeterinary medicineMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Tomato brown rugose fruit virus (ToBRFV) is an economically important seed and mechanically transmitted pathogen of significant importance to tomato production around the globe. Synergistic interaction with pepino mosaic virus (PepMV), another seed and mechanically transmitted virus, and long-distance dissemination of these two viruses via contaminated tomato fruits through global marketing were previously suggested. In 2019, we detected both viruses in several grocery store-purchased tomatoes in South Florida, USA. In this study, to identify potential sources of inoculum, co-infection status, prevalence, and genomic diversity of these viruses, we surveyed symptomatic and asymptomatic imported tomatoes sold in ten different groceries in four cities in South Florida. According to the product labels, all collected tomatoes originated from Canada, Mexico, or repacking houses in the United States. With high prevalence levels, 86.5% of the collected samples were infected with ToBRFV, 90% with PepMV alone, and 73% were mixed-infected. The phylogenetic study showed no significant correlations between ToBRFV genomic diversity and the tomato label origin. Phylogenetic analysis of PepMV isolates revealed the prevalence of the PepMV strains, Chilean (CH2) and recombinant (US2). The results of this study highlight the continual presence of PepMV and ToBRFV in imported tomatoes in Florida grocery stores.

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 score0.366
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.271
Teacher spread0.216 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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