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Record W2083712555 · doi:10.7202/706080ar

Effects of aldicarb and fungicides on Pratylenchus penetrans populations, root rot and net blotch severity on barley

2005· article· en· W2083712555 on OpenAlexafffundvenue
J. Kimpinski, H. W. Johnston

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsUniversité de Montréal
FundersAgriculture and Agri-Food Canada
KeywordsAldicarbBiologyPratylenchus penetransRoot rotAgronomyFungicidePratylenchusPopulationHordeum vulgareRoot systemOxamylHorticultureNematodePesticidePoaceae

Abstract

fetched live from OpenAlex

Population levels of the root lesion nematode, Pratylenchus penetrans , which produces necrotic lesions in the root cortex, were recorded in barley ( Hordeum vulgare ) in experimental plots during 1988, 1989, and 1990. Root lesion nematodes were the onlyendoparasitic nematodes recovered from barley roots and were the dominant nematode group found in the soil. Based on 3-yr averages, root rot ratings, caused primarily by Cochliobolussativusand Fusarium spp ., increased from 27% at Zadoks Growth Stage (ZGS) 30-32 in July to 73 % at ZGS 70-72 in late August and early September. Net blotch (incited by Pyrenophora teres ) was suppressed by a fungicide treatment consisting of a seed application of carbathiin and thiram, and a foliar application of propiconazole. Aldicarb suppressed the populations of root lesion nematodes in the soil, in the total root System, and in crown and seminal roots of barley. Yields were increased by ca 30% where aldicarb and fungicides were applied as a combined treatment. Population densities of root lesion nematodes were much greater in seminal roots than in crown roots at ZGS 30-32 and 55-60. Correlation coefficients between nematodes and yield data were often negative and significant (P≤0.05). There were no consistent trends in the numerical relationships between numbers of root lesion nematodes in roots or soil, and incidences of net blotch or root rot of barley.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.173

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.212
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2005
Admission routes3
Has abstractyes

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