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Record W2800748394 · doi:10.7939/r3ng4h59w

Optimization of semiochemical monitoring for pea leaf weevil, Sitona lineatus (Coleoptera: Curculionidae), in the Prairie Provinces

2017· article· en· W2800748394 on OpenAlexaboutno aff
Amanda J St.Onge

Bibliographic record

VenueUniversity of Alberta Library · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
Fundersnot available
KeywordsCurculionidaeSemiochemicalWeevilBiologyAgronomyBotanyPEST analysis

Abstract

fetched live from OpenAlex

The pea leaf weevil, Sitona lineatus Linnaeus (Coleoptera: Curculionidae) is an invasive pest of increasing concern to pulse producers in the Canadian Prairie Provinces. Pea leaf weevil larvae cause damage to field pea (Pisum sativum) and faba bean (Vicia faba) crops by feeding on root nodules which contain nitrogen-fixing Rhizobium bacteria. Larval feeding reduces the nitrogen balance of the pea and bean crops, causing a reduction in the number and quality of pods, as well as reducing the amount of fixed nitrogen available in the soil for future crops. Larval feeding is difficult to monitor but adult weevils are active aboveground, particularly during spring and fall dispersal to reproductive or overwintering sites, respectively. Both sexes of adults are attracted to semiochemicals, including the male-produced aggregation pheromone (4-methyl-3,5-heptanedione) and host plant volatiles ((Z)-3-hexenol, (Z)-3-hexenyl acetate, and linalool). The purpose of this research is to develop an optimal semiochemical trap, which reliably attracts and retains PLW, is related to PLW activity in fields, is cost effective, and can be used for monitoring pea leaf weevil in field pea crops in the Canadian Prairie Provinces. Different combinations of semiochemicals at various release rates were tested in pitfall traps positioned at the edge of pea crops in southern Alberta. Weevils were attracted to aggregation pheromone lures in both the spring and fall activity periods; the addition of host plant volatiles to the pheromone lure sometimes enhanced weevil captures, especially in the fall. Of the various trap types tested to capture and retain weevils including various cone traps, sticky traps, unitraps, and pitfall traps, the pitfall traps were the most successful. A secondary objective of this research was to investigate seasonal plasticity in pea leaf weevil response to semiochemicals. Male and female pea leaf weevil adults were tested individually in a 4-way olfactometer for their response to four natural odour sources: 1) five male pea leaf weevils; 2) five male pea leaf weevils on pea plants; 3) pea plants; or 4) a blank control. Weevils in three physiological states were tested in the olfactometer: newly eclosed, recently overwintered, and reproductively active. The response of pea leaf weevils in the olfactometer bioassays did not differ with weevil physiological state or sex. Weevils of all physiological states and both sexes responded preferentially to odours released by male pea leaf weevils. The semiochemical traps developed here can be used to determine the presence of pea leaf weevil in its expanded range. These semiochemical traps are also useful to monitor the arrival of pea leaf weevil into a pea crop at the start of the season, to better time the application of foliar insecticides. Further research relating captures of PLW in the fall to weevil damage in the upcoming spring would provide pea producers with a method to predict upcoming damage.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.206

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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