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Record W2005845327 · doi:10.1139/g08-064

Gene pool variation and phylogenetic relationships of an indigenous northeast Italian grapevine collection revealed by nuclear and chloroplast SSRs

2008· article· en· W2005845327 on OpenAlexvenueno aff
Marzia Salmaso, Renzo Dalla Valle, Margherita Lucchin

Bibliographic record

VenueGenome · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
FundersRegione del Veneto
KeywordsGermplasmBiologyMicrosatelliteNuclear geneHaplotypeAlleleGene poolGenetic variationPhylogenetic treeCultivarGeneticsGeneGenetic diversityBotanyGenomePopulation

Abstract

fetched live from OpenAlex

A germplasm safeguard programme was set up with 19 grapevine varieties considered as indigenous to northeastern Italy. To better estimate how genetic structure can be used to obtain a conservation perspective of local varieties, genetic variability was examined at 30 nuclear and 3 chloroplast polymorphic microsatellite loci in the native varieties plus 7 European cultivars taken as reference. The genetic profiles of all the cultivars were searched for possible parentage relationships and several suspected cases of the same variety having different names were investigated. The alleles shared at the loci suggest a parent-offspring relationship between Merlot and Cabernet Franc, 'Gruaja' and 'Negrara Veronese', and Marzemina Nera and Marzemina Bianca. Alleles at the 30 nuclear loci are consistent with Raboso Veronese being the progeny of Marzemina Bianca and Raboso Piave. Chloroplast-specific haplotypes were singled out for the first time in this indigenous germplasm and should be considered typical of the region. It is hypothesized that there are many specific haplotypes for the local varieties due to a past contribution of wild grapevine to the cultivated gene pool. The majority of investigated cultivars were demonstrated to constitute an independent source of genetic variation, and therefore a possible valuable resource of genetic traits for breeders.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.498

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 studies0.0010.000
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 head0.023
GPT teacher head0.219
Teacher spread0.196 · 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 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

Citations21
Published2008
Admission routes1
Has abstractyes

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