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Record W2588980304 · doi:10.5539/jas.v9n3p98

Effect of Bio-Rational Approaches on the Larval Population and Pigeonpea Pod Damage by Exelastis atomosa (Wlsm.)

2017· article· en· W2588980304 on OpenAlexvenueno aff
Paras Nath, R. S. Singh, S. N., Ram Keval

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
FundersBanaras Hindu UniversityUniversity Grants Commission
KeywordsBiologyPopulationLarvaPoint of deliveryCropAgronomyInfestationCajanusIntercroppingDry weightHorticultureBotany

Abstract

fetched live from OpenAlex

Effect of bio-rational approaches such as intercropping and application of bio-pesticide on the larval population, pod damage, grain damage and grain weight loss by plume moth (Exelastis atomosa (Wlsm.)) infesting pigeonpea (Cajanus cajan (L.) Millsp.) was studied. Pigeonpea intercropped with maize, pearl millet, sorghum, rice and black gram had significant effect on the larval population of plume moth when compared with pigeonpea sole crop infestation. The pigeonpea pod damage, grain damage and grain weight loss due to larval infestation in different pigeonpea intercrops and pigeonpea sole crop differed significantly however few exceptions were also recorded. The average larval population, pod damage, grain damage and grain weight loss in different intercrops varied from 0.25 to 0.39 larva/plant, 1.29 to 1.79%, 0.41 to 0.55% and 0.25 to 0.35%, respectively. The pigeonpea sole crop had recorded relatively higher larval population (0.39 larva/plant), pod damage (2.03%), grain damage (0.85%) and grain weight loss (0.59%) than the intercropped pigeon pea. The two sprays of NSKE 5% (first at flowering and pod formation stage and second after 20 days) were found superior in reducing larval population, pod damage, grain damage and grain weight loss. However, the plots devoid of any biopesticidal treatment had maximum larval population (0.68 larva/plant), pod damage (2.75%), grain damage (0.86%) and grain weight loss (0.60%) by E. atomosa.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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