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Effect of Bee-Borne Entomopathogenic Fungi and Essential Oils in Controlling Cyclamen Mite on Strawberries

2024· preprint· en· W4401587000 on OpenAlexafffundabout
Morel Libère Comlan KOTOMALE, Jean Pierre Kapongo, Alphonsine Muzinga Bin Lubusu, Romuald Simo Nana, Donald Rostand Fopie Tokam, Grace Suzert Nottin Mboussou

Bibliographic record

VenuePreprints.org · 2024
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsCollège Boréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEntomopathogenic fungiMiteBiologyBotanyHorticultureBiological pest control

Abstract

fetched live from OpenAlex

The cyclamen mite, Phytonemus pallidus, is one of the important pests in strawberry cultivation in Canada. This insect pest hides on young strawberry leaves that have not yet opened, which limits their control. In addition, the fight against the latter involves the use of synthetic chemicals that are not without effect on the environment, human health and beneficial organisms. We hypothesized that vectorization by bees could reduce the number of applications, product runoff and provide targeted control of these pathogens. To do this, field trials were conducted to evaluate the effectiveness of bumblebees Bombus terrestris in propagating Beauveria bassiana to control this pest. Our results showed that bumblebees were able to disseminate the inoculum on strawberry plants. Also, all the products used (B. bassiana and neem oil) were effective on P. pallidus. It should be noted that high mortality has been noted on this pest thanks to the application of this entomopathogen by spraying. In addition, neither of the two products tested had a significant effect on lady beetles C. septempunctata. These results therefore suggest the use of bee vectoring and neem essential oils in the sustainable management of strawberry mites.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.296
Teacher spread0.265 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes3
Has abstractyes

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