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Record W4303579257 · doi:10.3390/agronomy12102422

Cover Crops as Reservoirs for Young Vine Decline Pathogens

2022· article· en· W4303579257 on OpenAlexafffund
Daniel José Rosa, Mehdi Sharifi, Miranda M. Hart

Bibliographic record

VenueAgronomy · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsCover cropVineBiologyAgronomyCropColonizationHorticultureEcology

Abstract

fetched live from OpenAlex

Young vine decline (YVD) is a grapevine trunk disease (GTD) which results in stunted and delayed growth, reduced yield, root necrosis and eventually death of young vines. Given losses associated with root trunk disease, and increasing limits on chemical fungicides, there is a need for sustainable approaches to combat disease; (1) Cover cropping is a commonly used practice in agricultural systems and has potential to reduce disease in vineyards but there is a risk that cover crop species may act as a host for grapevine pathogens, increasing the risk of infection; (2) We tested 25 plant species commonly used in cover crops to assess their potential to act as a host for a Ilyonectria liriodendri, which is a causal agent of young vine decline. We inoculated greenhouse pots with a pathogeninc strain of Ilyonectria and assayed the roots for the presence of the pathogen; (3) Of the 25 cover crops tested, many of the species showed increased root abundance of Ilyonectria, compared to background levels. In particular phacelia (Phacelia tanacetifolia) and buckwheat (Fagopyrum esculentum) showed very high levels of root colonization. (4) This is the first study to our knowledge that highlights the potential of cover crops to soil borne fungal pathogens.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.492

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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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 designNot applicable
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

Citations3
Published2022
Admission routes2
Has abstractyes

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