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Record W4410417076 · doi:10.1101/2025.05.09.653057

Sterile insect technique reduces cabbage maggot (Diptera: Anthomyiidae) infestation in root crucifers in Canada

2025· preprint· en· W4410417076 on OpenAlexafffundabout
Anne‐Marie Fortier, Allen Bush‐Beaupré

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsBishop's UniversityPhytodata
FundersAgriculture and Agri-Food CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsAnthomyiidaeMaggotInfestationInsectBiologyLarvaInsect pestHorticultureAgronomyBotany

Abstract

fetched live from OpenAlex

The cabbage maggot ( Delia radicum Linnaeus) is a major pest of brassica vegetables in Canada that has traditionally been managed with soil-applied insecticides. However, recent regulatory restrictions on key products such as chlorpyrifos have created a pressing need for alternative solutions. This study evaluates the sterile insect technique (SIT) as a control method for the cabbage maggot in root crucifers. Large-scale field trials conducted from 2019 to 2022 in Quebec (Canada) demonstrated significant reductions in D. radicum infestations in radish and daikon crops. Quality control measures confirmed the effectiveness of sterilization, with minimal impact on male performance. The results suggest that the SIT is a promising, environmentally friendly alternative to chemical control for cabbage maggot management. The study further highlights the importance of optimizing release strategies and improving predictive models to guide deployment. Overall, the SIT offers growers a viable option to reduce reliance on insecticides while maintaining crop health and yield.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2025
Admission routes3
Has abstractyes

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