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Record W4407756959 · doi:10.3389/finsc.2025.1468262

Sustainable control of the bird cherry-oat aphid (Rhopalosiphum padi L.) in northwestern Ontario using Beauveria bassiana delivered by bumblebees

2025· article· en· W4407756959 on OpenAlexafffundabout
Jean Pierre Kapongo, Morel Libère Comlan KOTOMALE, Alphonsine Muzinga Bin Lubusu, Romuald Simo Nana, Donald Rostand Fopie Tokam, Grace Suzert Nottin Mboussou

Bibliographic record

VenueFrontiers in Insect Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCollège Boréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBeauveria bassianaAphidRhopalosiphum padiBiologyBiological pest controlAgronomyHorticultureBotanyPEST analysisHomopteraAphididae

Abstract

fetched live from OpenAlex

Rhopalosiphum padi is one of the main vectors of barley yellow dwarf virus (BYDV), which affects the grain yield of oats. Several biological control strategies have been studied to control this pest, one of which is Bee Vectoring Technology (BVT) using bumblebees. We tested the efficacy of Beauveria bassiana , as vectored by bumblebees, and a direct spray application of neem (a natural bio-insecticide derived from the Azadirachta indica tree) on aphids. An assessment of the pest’s impact on the plots surveyed in northwestern Ontario revealed incidence rates of 80%. The use of bumblebees as a dispersal agent of B. bassiana significantly reduced the aphid population (0.542 ± 0.147b) compared to the untreated control (0.125 ± 0.069a). The application of diluted neem also showed a reduction in the aphid population (0.708 ± 0.221a). Although the products used controlled the pests, they had no effect on the aphid’s natural enemy, the ladybug. Therefore, the dissemination of B. bassiana by the bumblebee Bombus impatiens leads to a decrease in the vector Rhopalosiphum padi population and consequently reduces the severity of barley yellow dwarf disease in oat fields.

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)0.001
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 score0.334
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.191
Teacher spread0.177 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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