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Record W7045257533

Alternative integrated pest management methods for controlling Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae).

2023· dissertation· en· W7045257533 on OpenAlexaboutno aff

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsTyrophagus putrescentiaeIntegrated pest managementPopulationFumigationPest controlPEST analysisChemical control
DOInot available

Abstract

fetched live from OpenAlex

Tyrophagus putrescentiae (Schrank) (Acaridae), commonly known as the mold mite, cheese mite and ham mite, is one of the most important pests of dry-cured hams. Methyl bromide is the most effective fumigant that has been used to control ham mites. Methyl bromide is now banned for most food uses and is being phased out of use in many countries in accord with the Montreal Protocol on substances that deplete the ozone layer of the earth’s atmosphere. This work is part of a long-term effort to find alternatives to methyl bromide for use in controlling ham mites. In an integrated pest management program, different tools play a role in the successful control of insect pests. Hence, effective, feasible and economically friendly integrated pest management (IPM) tools are needed to help in the control of these ham mites in the dry-cured ham industry. Work for this dissertation is divided into four independent sections by chapter, as described below. Plant essential oils and food-safe compounds were evaluated as repellents for their effectiveness at controlling mites. Experiments to assess the repellency to orientation, oviposition, and population growth of mites on 5 mm³ and 25 mm³ pieces of aged country hams were conducted. Test compounds at different concentrations were dissolved in required solvents and compared to the solvent control. Results indicated that nootkatone and a blend of C8, C9 and C10 straight-chain hydrocarbons had repellency indices of (RI) of 85.6% and 82.3%. Geraniol had the highest RI of 96.3% at 0.04 mg/cm². Ham pieces dipped in C8910 and nootkatone at 150 ppm each had RIs of 89.3% and 82.8%, respectively. In general, as the concentrations of test compounds increased, the numbers of eggs that were laid on these treated ham cubes decreased after the 48h exposure time. In the second study, about fifteen commercially available acaricides were screened as surface applications, and four chemicals were effective against mites. The persistence of these four chemicals over time was further assessed over eight-week periods by applying the recommended rate to three different surfaces: metal, concrete and wood. Results indicated that acequinocyl and amitraz were very persistent and effective at killing mites throughout the experiment period even after the sixth to eighth week aging of the sprayed surfaces, hence suggesting good efficacy for commercial use. Traditionally, the use of residual pesticides and fumigants have been the primary way to control stored product pests, including ham mites. Since the use of these products are being minimized to embrace more environmentally friendly and humanly safe alternatives, the objective of this third experiment was to evaluate different physical barriers to exclude ham mites in a simulated ham-aging facility. The physical treatments included both liquid and sticky barriers. The liquid treatments were water, soapy water, vegetable oil and mineral oil whereas the dry sticky treatment were petroleum jelly and a sticky coating used in insect traps. These experiments indicated that physical barrier treatments can significantly reduce the number of ham mites that may walk up from the floor to infest dry cured hams while they were hanging on racks above the floor. However, barrier methods used for exclusion alone cannot eradicate ham mites in an aging room. Hence, it can certainly be used in conjunction with other pest management tools for successful protection of dry-cured hams.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.066
GPT teacher head0.349
Teacher spread0.282 · 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.

Study designOther design
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueK-State Research Exchange (Kansas State University)Same topicInsect Pest Control StrategiesFrench-language works237,207