MétaCan
Menu
Back to cohort
Record W1876070517 · doi:10.21273/hortsci.48.12.1433

Resistance of Vitis Germplasm to Elsinoë ampelina (de Bary) Shear Evaluated by Lesion Number and Diameter

2013· article· en· W1876070517 on OpenAlexaboutno aff
Atsushi Kono, Akihiko Sato, Yusuke Ban, Nobuhito Mitani

Bibliographic record

VenueHortScience · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarVitis viniferaTable grapeGermplasmBiologyHybridHorticultureWineWine grapePlant disease resistanceBotanyGeneticsFood scienceGene

Abstract

fetched live from OpenAlex

We evaluated the resistance of 133 grapevine cultivars or selections, including Vitis vinifera and American hybrids, on the basis of lesion number and length to identify sources of resistance to grapevine anthracnose. All germplasms tested in this study showed anthracnose symptoms to some extent, and the distribution of lesion number and diameter was continuous. Most table grape V. vinifera cultivars were highly susceptible, showing many large lesions. However, V. vinifera wine grapes were more resistant with smaller lesions. Some American hybrid grapes such as ‘Ontario’ showed very few and small lesions. There was a significant positive correlation between lesion number and size in American ( r = 0.63, P = 0.0041) and Japanese hybrids ( r = 0.56, P < 0.001), whereas there was no correlation between these characters in V. vinifera . Japanese tetraploid cultivars were neither highly susceptible nor resistant. High anthracnose susceptibility of most well-known table grape V. vinifera cultivars, including ‘Muscat of Alexandria’, ‘Italia’, ‘Rizamat’, ‘Kattakurgan’, and ‘Thompson Seedless’, indicates that resistance should be introgressed from other cultivars such as American hybrids or wine grapes when these susceptible table grapes or their descendants are used in breeding anthracnose-resistant table grapes.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
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
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.282
Teacher spread0.255 · 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 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

Citations27
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueHortScienceSame topicHorticultural and Viticultural ResearchFrench-language works237,207