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Record W3167748204 · doi:10.5539/jas.v13n7p47

Production of Natural Insecticide on Management of Plutella xylostella (Linnaeus, 1758) (Lepidoptera: Plutellidae) in Family Farming

2021· article· en· W3167748204 on OpenAlexvenueno aff
Cristiane G. L. Ruiz, Marilza Silva Costa, Santino Seabra Júnior, Mônica J. B. Pereira

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPlutellidaePlutellaDiamondback mothLepidoptera genitaliaBiologyToxicologyHorticulturePesticideAgronomyBotany

Abstract

fetched live from OpenAlex

Collard greens are commonly grown in family farming systems; however, damage caused by the diamondback moth Plutella xylostella (Lepidoptera: Plutellidae) reduces yields, leading to successive applications of insecticides and consequently, environmental and toxicological problems. Therefore, it is essential to search for alternatives that reduce the use of pesticides and are economically viable and accessible to small farmers. This study was aimed at evaluating the insecticidal activity of aqueous extracts of neem and tobacco on P. xylostella. First instar caterpillars were offered collard leaf discs treated with different concentrations (30 caterpillars per treatment) and after the third day, mortality was evaluated. To evaluate ovicidal properties, collard leaves with 30 eggs were immersed in extracts and after 48 h, viability was measured. Oviposition deterrent activity was assessed with 23 couples of P. xylostella released in cages (repetitions) containing treated collard plants and after 48 h, the number of eggs per plant was recorded. Neem and tobacco extracts exhibited larvicidal, ovicidal, and oviposition deterrent properties against P. xylostella, indicating that the use of these extracts may be promising alternatives in family farming systems.

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 score0.681
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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