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Record W6894101575 · doi:10.5281/zenodo.7411573

Potential of Nabis americoferus and Orius insidiosus as biological control agents of Lygus lineolaris in strawberries.

2022· article· en· W6894101575 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHemiptera Insect Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsLygusBiological pest controlPredationTarnished plant bugMiridaePopulationOmnivoreAnthocoridae

Abstract

fetched live from OpenAlex

The tarnished plant bug, <em>Lygus lineolaris,</em> is a major strawberry pest. Only marginally effective control methods exist to manage this pest. Various predators attack <em>L. lineolaris</em>, but their potential is overlooked. In this study, we explore the potential of two omnivorous predators of the tarnished plant bug: the damsel bug, <em>Nabis americoferus,</em> and the minute pirate bug, <em>Orius insidiosus</em>. Firstly, the predation rate of these predators was measured in laboratory tests. Secondly, their potential release rates and release periods were determined in the field. Results show that <em>N. americoferus</em> feeds on all nymphal stages and adults of the tarnished plant bug, while <em>O. insidiosus</em> attacks only smaller nymphs. In the field, all tested densities of <em>N. americoferus</em> (0.25, 0.5, and 0.75 individual/ plant) reduced the population of tarnished plant bugs for several weeks compared to the control treatment, but the effect of <em>O. insidiosus </em>alone was marginal. Additionally, for all release periods tested, <em>Nabis americoferus</em> was efficient in reducing the pest population. These results demonstrate the potential of <em>N. americoferus</em> to control the tarnished plant bug in strawberry fields. We discuss the possible application of these results for the establishment of an effective and economically viable biological control strategy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.647
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.028
GPT teacher head0.227
Teacher spread0.199 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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