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Record W4285306603 · doi:10.7202/1088485ar

Plant-parasitic nematodes in Nova Scotia vineyards

2022· article· en· W4285306603 on OpenAlexaffvenueabout
T. Forge, Paige Munro, A. Harrison Wright, Debra L. Moreau

Bibliographic record

VenuePhytoprotection · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyNova scotiaNematodeXiphinemaDaggerPopulationVineyardNematologyBotanyHorticultureEcologyGeographyArchaeology

Abstract

fetched live from OpenAlex

Plant-parasitic nematode populations were analyzed from composite soil samples collected from 62 vineyard blocks throughout Nova Scotia in 2018 and 2019. Nematode groups of potential concern that were found included ring nematodes (family Criconematidae), dagger nematodes (Xiphinema spp.), and root-knot nematodes (Meloidogyne spp.). Ring nematodes were overall the most widespread and abundant group of plant-parasitic nematodes, recovered from 79% of blocks with an overall average population density of 114 nematodes per 100 cm3 soil. Ring nematodes tended to be more abundant in older blocks. DNA sequence analyses of a subset of the ring nematode populations confirmed the presence of Mesocriconema xenoplax, which is the species known to be damaging to and most widely associated with grapevine globally. The analyses indicated that Criconema permistum was also present, notably in samples with the greatest ring nematode population densities. The results indicate that ring nematodes could be affecting the health of Nova Scotia vineyards, particularly in the future as populations continue to develop in relatively young vineyards and as older blocks are replanted. Additional research is needed to delineate the distribution of M. xenoplax vis-à-vis other species and to experimentally assess the host-parasite relationship between C. permistum and grapevine.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score1.000

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)0.0010.000

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 head0.025
GPT teacher head0.225
Teacher spread0.200 · 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

Citations1
Published2022
Admission routes3
Has abstractyes

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