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Record W4207016523 · doi:10.1093/jee/toab258

Semi-Quantitative Detection of<i>Drosophila suzukii</i>(Diptera: Drosophilidae) From Bulk Trap Samples Using PCR Technology

2022· article· en· W4207016523 on OpenAlexafffund
Justin M. Renkema, Wendy McFadden-Smith, Shu Chen

Bibliographic record

VenueJournal of Economic Entomology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsUniversity of GuelphMinistry of Agriculture, Food and Rural AffairsVineland Research and Innovation CentreAgriculture and Agri-Food Canada
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsDrosophila suzukiiDrosophila (subgenus)DrosophilidaeBiologyPEST analysisZoologyBotanyDrosophila melanogasterGenetics

Abstract

fetched live from OpenAlex

Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is a ubiquitous global pest of several fruit crops. Trapped adult numbers are used to monitor populations and make control decisions, but differentiating D. suzukii from other trapped Drosophila spp. is laborious. We developed a real-time PCR method for specific detection and semi-quantification of D. suzukii from trap samples. The PCR assay did not amplify DNA from 29 other Drosophilidae species tested. Drosophila suzukii was detected from ≥0.96 pg target DNA and from laboratory samples containing one D. suzukii in 2000 other Drosophila spp. flies. We tested DNA stability of one D. suzukii in 100 Drosophila spp. flies in water or ethanol at 20, 25, or 30°C for 1, 4, or 7 d. Only water at 30°C for 7 d fully impaired D. suzukii DNA detectability. Substituting mouthwash for water resulted in D. suzukii detection in all samples held for 7 d at 30°C or daily fluctuating temperatures of 33/23°C. Traps with mouthwash as a drowning liquid had D. suzukii captures equal to traps with water. A calibration curve was established using samples in mouthwash containing 1/1,000-100/1,000 D. suzukii/total Drosophila spp. flies and incubated at 25°C for 7 d. The curve had a coefficient of determination (R2) of 0.9279 between D. suzukii numbers from the PCR and the true D. suzukii numbers in samples prepared in 70% ethanol. Collecting samples in mouthwash is expected to improve detection accuracy, and the qPCR method can be a useful tool to support D. suzukii monitoring and management.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.038
GPT teacher head0.266
Teacher spread0.228 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

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