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Record W2900136526 · doi:10.15368/theses.2018.123

Assessment of Granulovirus, Spinosad, and Mating Disruption for Controlling Cydia pomonella L. [Lepidoptera: Tortricidae] in Organic Coastal California Apple Orchards

2018· dissertation· en· W2900136526 on OpenAlexaboutno aff
Raven Lukehart

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pheromone Research and Control
Canadian institutionsnot available
Fundersnot available
KeywordsCodling mothTortricidaeMating disruptionSpinosadOrchardBiologyLepidoptera genitaliaHorticulturePomeMalusPEST analysisToxicologyBotanyAgronomyPesticide

Abstract

fetched live from OpenAlex

Codling moth, Cydia pomonella[Lepidoptera: Tortricidae], is a major entomological pest of apples, pears, and walnuts cross the world (Pajac et al. 2016). Female codling moths lay eggs on the apple exocarp and larvae burrow within the fruit causing economic losses to fruit growers.Organic apple orchards in San Luis Obispo, CA currently have three codling moth, Cydia pomonella,control options commercially available including granulovirus (CpVG), spinosad, and mating disruption. In field tests on apple (Malus), we compare percent fruit injury between treatments of granulovirus (2.43 oz/ha Cyd-X® organically approved, Certis USA, Columbia MD), spinosad (4.05 oz/ha Entrust® Naturalyte® organically approved WP formation, Dow AgroSciences, Indianapolis IN), and a control. We also compared mating disruption in form of codling moth Codlemone® sex pheromone (257 ties/ha (506 mg)/acre Isomate®-OFM TT organically approved Pacific Biocontrol Corporation Vancouver, WA) against a control. Delta taps and 1 mg pheromone lures were used to trap males and track the degree day (DD) model for the two orchard’s codling moth populations to determine application timing for each treatment. A preliminary DD model was used based on the University of California at Davis Agricultural Extension codling moth DD model. During 2016 trialsno detectible control was provided by spray treatments with an average fruit injury of 26% control, 23% granulovirus, 28% spinosad. During 2016 trialsno detectible control was provided by mating disruption with an average fruit injury of 16% control and 16% pheromone. During 2017 trials there was detectible control provided by the treatments to the crop by both spray treatmentsand pheromone ties. 2017 average fruit injury for spray treatments was 51% control, 20% granulovirus, and 14% spinosad. 2017 average fruit injury for mating disruption was 29% control and 6% pheromone. Data suggest underlying relationship between location specific climate factors, cultivars, codling moth populations, and treatment efficacy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.990

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 science0.0000.000
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 head0.012
GPT teacher head0.278
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
Published2018
Admission routes1
Has abstractyes

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