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Record W2953109021 · doi:10.7202/1059304ar

Pathogenicity of Pratylenchus penetrans to dwarfing apple rootstocks

2019· article· en· W2953109021 on OpenAlexaffvenue
Guy Bélair, Nathalie Dauphinais, Yvon Fournier

Bibliographic record

VenuePhytoprotection · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsCégep Saint-Jean-sur-RichelieuAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRootstockDwarfingPratylenchus penetransBiologyShootInoculationHorticultureDry weightAgronomyMalusNematodeEcology

Abstract

fetched live from OpenAlex

The objective of this research was to measure the effect of P. penetrans densities on the vegetative growth of three apple dwarfing rootstocks Bud 9, M.9 and M.26 under field microplot conditions. Under 500 nematodes kg -1 soil density, the shoot dry weights of Bud 9, M.9 and M.26 rootstocks were significantly reduced by 30%, 23% and 14% respectively. Under the 1 500 nematodes kg -1 soil density, the dry shoot weight of Bud 9 and M.9 were not significantly different from the 500 nematodes kg -1 soil density except M.26 which exhibited a 29% decrease. The root dry weights of rootstocks were not significantly reduced when exposed to these P. penetrans densities except M.26 which was reduced 26% relative to non-inoculated trees under the 1 500 nematodes kg -1 soil density. These results confirm the pathogenic effect of P. penetrans on dwarfing apple rootstocks. Although preliminary, these results suggest some tolerance of M.26 to P. penetrans under lower density when compared to M.9 and Bud 9. Under higher nematode densities, both Bud 9 and M.9 exhibited a tolerance of their root system in comparison to M.26. Our results also emphasize the need to further assess the susceptibility/tolerance of dwarfing apple rootstocks to various densities of P. penetrans .

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.303

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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