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Record W2100694755 · doi:10.5539/sar.v1n1p36

Onion as a Pest Control Intercrop in Organic Cabbage (Brassica oleracea) Production System in Ghana

2012· article· en· W2100694755 on OpenAlexvenueno aff
Philip Kweku Baidoo, M. B. Mochiah, K. Apusiga

Bibliographic record

VenueSustainable Agriculture Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
FundersKwame Nkrumah University of Science and Technology
KeywordsPlutellaBiologyBrassica oleraceaIntercroppingAgronomyPEST analysisCropRandomized block designBrevicoryne brassicaeInfestationBrassicaPopulationPest controlHorticultureBotanyHomopteraLarva

Abstract

fetched live from OpenAlex

The use of chemical insecticides in the control of insect pests has left in its wake resistance of some pests to some of the conventional insecticides. Alternative methods of managing pests such as cultural control have to be employed to reduce pest infestation of crops. Onion was used in an intercrop as a non host crop to manage the pests of cabbage. The experiment was conducted in a Randomized Complete Block Design with four treatments; sole cabbage (T1), 2 rows of cabbage to 1 row of onion (T2), 3 rows of cabbage to 1 row of onion (T3) and 4 rows of cabbage to 1 row of onion (T4), each of which was replicated three times. Data were collected on pests’ numbers, plant height, damaged leaves at harvest, canopy spread, number of damaged heads and fresh weight. Significantly fewer Bemisia tabaci, Hellula undalis and Brevicoryne brassicae infested the intercropped plants than the sole crop. However, intercropping cabbage with onion did not significantly reduce Plutella xylostella population on cabbage. Number of damaged heads, fresh weight and damaged leaves were significantly different (P< 0.05).

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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.285
Teacher spread0.261 · 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

Citations41
Published2012
Admission routes1
Has abstractyes

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