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Record W3048435093 · doi:10.1139/cjm-2020-0293

Fungal endophyte diversity in table grapes

2020· article· en· W3048435093 on OpenAlexaffvenueabout
Champa Wijekoon, Zoe Quill

Bibliographic record

VenueCanadian Journal of Microbiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEndophyteBiologyPlant use of endophytic fungi in defenseCladosporiumBotanyTable grapeAlternariaMetagenomicsAmplicon sequencingMicrobiomeTable (database)RhizoctoniaBiological pest controlPenicilliumBacteriaCultivarGene

Abstract

fetched live from OpenAlex

Plant fungal endophytes are diverse microbial sources that reside inside plants. Grapes (Vitis vinifera) are rich in polyphenols that have beneficial health effects, and recent research has shown that fungal endophytes in grapes may contribute to the production of these polyphenols and may serve as biocontrol agents. In this study, we determined the fungal microbial endophyte diversity in North American table grapes found at a Winnipeg, Manitoba, market. The amplicon internal transcribed spacer (ITS) metagenomics approach was used to profile the fungal communities of the fruit endophyte microbiome of three table grape types. The data supported endophyte diversity in different table grapes, including possible bioactive, saprophytic, and pathogenic fungi. Culturable endophytes were isolated and identified by morphology and ITS amplicon sequencing. The majority of the isolated culturable strains included Alternaria spp. and Cladosporium spp. The results provided evidence of the existence of diverse fungal endophytes isolated and identified from the fruit of the table grapes. These fungal endophytes may have potential in agricultural, industrial, and pharmaceutical applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.185
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2020
Admission routes3
Has abstractyes

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