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Enregistrement W6964091436 · doi:10.25394/pgs.24749982

<b>Developing Sustainable Carrot Weevil Management Informed by Genetic and Behavioral Studies of Populations in the Great Lakes Region of the United States</b>

2023· dissertation· en· W6964091436 sur OpenAlexaboutno aff

Notice bibliographique

RevuePurdue · 2023
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueInsect-Plant Interactions and Control
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWeevilCultivarIntegrated pest managementPopulationCropPEST analysisAgricultureGenetic diversity

Résumé

récupéré en direct d'OpenAlex

Specialty crop growers in the Great Lakes region of the United States and Canada have been struggling for decades to manage the carrot weevil (<i>Listronotus oregonensis</i>). In carrot, parsley, and celery production, growers may experience 40-100% yield loss, despite the intensive use of insecticides (Boivin, 1999; Jasinski, 2008; Telfer et al., 2019). To improve sustainable management of this native pest in commercial vegetable production, we must address existing knowledge gaps in carrot weevil mate-finding behavior, population genetic diversity and gene flow, and grower adoption and efficacy of integrated pest management (IPM) strategies, like cultivar selection, to combat this pest. To date, these factors have not been evaluated in the carrot weevil system, yet together they have significant implications for developing novel monitoring tools, grower decision making, and the potential evolution of insecticide resistance in this damaging pest.To address knowledge gaps in grower adoption and the efficacy of IPM strategies, such as cultivar selection, I investigated the influence of carrot cultivar on the oviposition preference of carrot weevil in the laboratory and quantified the diversity of insect assemblages on carrots in Ohio and Indiana. In tandem, I delivered an online survey to specialty crop growers in Indiana and Ohio to measure their knowledge and use of insect-resistant cultivars as a part of an IPM strategy. I found that carrot cultivar did not impact carrot weevil oviposition preference, but rather the number of petiole trichomes was positively correlated with the cumulative number of egg scars found on a given carrot cultivar. Similarly, cultivar did not influence the diversity of insect assemblages associated with carrot foliage, but hemipterans were the dominant group found across cultivars. Moreover, insect diversity across all carrot cultivars was high, with Shannon-Weiner diversity indices ranging from 2.14 to 2.45.I analyzed survey responses from vegetable growers regarding their knowledge, current use, and future use of insect-resistant cultivars and found no significant differences between conventional or organic growers, in either Indiana or Ohio, or across experience levels regarding their knowledge and current or future use of insect-resistant cultivars. Although a greater number of organic growers were aware of insect-resistant cultivars, they were not incorporated into their IPM plans. In contrast, half of responding conventional growers indicated implementing insect-resistant cultivars in current IPM plans. Growers indicated that more information about the efficacy, costs, and benefits of insect-resistant vegetable cultivars would be most helpful in informing their decision to incorporate this IPM tactic on their farms.To address knowledge gaps regarding carrot weevil mate-finding behavior, I investigated behavioral response to conspecific frass using Y-tube bioassays and the volatiles of frass samples were analyzed using gas-chromatography mass-spectrometry (GC-MS) as starting points to assess the presence of volatile chemical cues that might function as sex or aggregation pheromones. I found that male and female weevils oriented strongly towards volatiles from male frass. However, conspecifics were not attracted to mixed or female frass, suggesting male frass contains behaviorally relevant chemical cues that are unique or present in greater abundance than in female frass. When I analyzed the chemical abundance and composition of the male frass volatiles, I found 16 common compounds across all samples and no compounds were unique to the male volatile blend. Specifically, (1S)-6,6-dimethyl-2-methylene-Bicyclo[3.1.1]heptane and (1R)-2,6,6-Trimethylbicyclo[3.1.1]hept-2-ene were present in significantly higher abundance in extracts of males frass compared to those of female frass.Finally, to address knowledge gaps in the genetic diversity and gene flow of carrot weevil populations in the Great Lakes Region of the U. S., I used single nucleotide polymorphisms (SNPs) to compare genetic diversity and structure of agricultural populations of carrot weevil in Michigan and Ohio. I found limited genetic differentiation between three carrot weevil populations collected from celery and parsley fields located in Michigan and Ohio. I also found high inbreeding coefficients and heterozygote deficiency in all populations, suggesting that all carrot weevil populations are locally confined. These results suggest significant gene flow between populations, which has implications for management, specifically the mitigation and management of insecticide resistance.Together, the results from my dissertation can be applied to the improvement of carrot weevil IPM across the Great Lakes region of the United States and Canada. Further investigations into the impact of physical characteristics, specifically petiole trichomes, on carrot weevil oviposition behavior can inform the breeding and development of resistant carrot cultivars. Results from my behavioral bioassay studies represent a critical first step towards the identification of an aggregation or sex pheromone, which would greatly improve detection of resident carrot weevil populations when used in conjunction with current monitoring traps. My results also suggest that monitoring and mitigation of insecticide resistance in carrot weevil populations should be considered at the regional scale, at minimum, with significant gene flow between carrot weevil populations within the Great Lakes Region.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,443
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,058
Tête enseignante GPT0,310
Écart entre enseignants0,251 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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