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Record W3035349472 · doi:10.3390/insects11060359

Insecticidal Activity of Plant Powders against the Parasitoid, Pteromalus venustus, and Its Host, the Alfalfa Leafcutting Bee

2020· article· en· W3035349472 on OpenAlexaff
Mikhaela Ong, Nora Chomistek, Hanna Dayment, Wayne Goerzen, Danica Baines

Bibliographic record

VenueInsects · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyParasitoidToxicologyHost (biology)BiopesticideBotanyHorticulturePesticideBiological pest controlAgronomyEcology

Abstract

fetched live from OpenAlex

Developing a bee-friendly alternative to traditional insecticides used within commercial environments can contribute to reductions in pesticide exposure experienced by managed bees. We performed acute contact toxicity studies using fifteen plant powders from seven plant families against a parasitoid pest, Pteromalus venustus, and its host, the Alfalfa leafcutting bee (ALB). Ajwain, cinnamon, clove, cumin, fennel, ginger, nutmeg, oregano and turmeric applied at low contact concentrations had sufficient fumigant properties to cause equivalent or higher parasitoid mortality as that obtained with the traditional insecticide. Nutmeg adversely affected adult ALBs at both low and high contact concentrations, thus eliminating it as a candidate. Increasing the contact concentrations did not consistently increase parasitoid control but did increase adverse effects on the ALBs. In addition, the efficacious plant powders significantly reduced the sexual function and fertility of the female parasitoids, a feature not associated with the traditional insecticide. The dual nature of the mechanisms underlying the effects of the plant powders may translate into effective control of the parasitoid populations in the commercial environment. The results reported here support further evaluations of Ajwain, cinnamon, clove, cumin, fennel, ginger, oregano and turmeric as potential botanical insecticides for control of P. venustus.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.325

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 head0.050
GPT teacher head0.247
Teacher spread0.197 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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