MétaCan
Menu
Back to cohort
Record W1986397792 · doi:10.5539/sar.v2n3p1

Effects of Sowing Date on Sunflower (Helianthus annuus) Damage by Pachnoda interrupta (Coleoptera: Scarabaeidae) and an Economic Threshold Levels for Its Management at Maiduguri, Sudan Savannah Ecological Zone of Nigeria

2013· article· en· W1986397792 on OpenAlexvenueno aff
G. Abdullahi, B. M. Sastawa, Shehu A

Bibliographic record

VenueSustainable Agriculture Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsSowingSunflowerHelianthus annuusBiologyAnimal scienceYield (engineering)AgronomyField experimentPhysics

Abstract

fetched live from OpenAlex

<em>Pachnoda interrupta</em> is one of the head-infesting insect pests of sunflower in Maiduguri. Two separate field experiment(one each for sowing date effect and threshold level) were conducted to investigate the influence of sowing date on damage and yield loss by <em>P. interrupta</em> on sunflower and the economic threshold level for its control in Maiduguri. The result for influence of sowing date experiment shows that percentage incidence of infestation was highly significant on sunflower sown on the 5<sup>th</sup> July than other planting date except that of 26<sup>th</sup> July. Significantly lower damage was recorded on sunflower sown on 19<sup>th</sup> July than those on the 5<sup>th</sup> and grain yield loss was also significantly higher on 26<sup>th</sup> July sowings than all other dates. The results for economic threshold level experiment indicated that 2.38 and 2.36 beetles/head were the economic threshold level for flowing and milky grain stage respectively and there was a 1:4.9 cost: benefit ratio/ ha. This means that there is a 20% return for every unit of inputs. The result implies that 19<sup>th</sup> of July is the best planting date to reduce infestations, damage and yield loss from <em>P. interrupta</em> in Maiduguri and artificial control measures should be initiated when there are 1.9 to 2.0 beetles/plant.

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 score0.685
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.026
GPT teacher head0.282
Teacher spread0.257 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSustainable Agriculture ResearchSame topicBiological Control of Invasive SpeciesFrench-language works237,207