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Authordc.contributor.authorBiscarini, Filippo 
Authordc.contributor.authorNazzicari, Nelson 
Authordc.contributor.authorBink, Marco 
Authordc.contributor.authorArús, Pere 
Authordc.contributor.authorAranzana, Maria José 
Authordc.contributor.authorVerde, Ignazio 
Authordc.contributor.authorMicali, Sabrina 
Authordc.contributor.authorPascal, Thierry 
Authordc.contributor.authorQuilot-Turion, Benedicte 
Authordc.contributor.authorLambert, Patrick 
Authordc.contributor.authorDa Silva Linge, Cassia 
Authordc.contributor.authorPacheco, Igor 
Authordc.contributor.authorBassi, Daniele 
Authordc.contributor.authorStella, Alessandra 
Authordc.contributor.authorRossini, Laura 
Admission datedc.date.accessioned2019-03-18T11:59:31Z
Available datedc.date.available2019-03-18T11:59:31Z
Publication datedc.date.issued2017
Cita de ítemdc.identifier.citationBMC Genomics, Volumen 18, Issue 1, 2018,
Identifierdc.identifier.issn14712164
Identifierdc.identifier.other10.1186/s12864-017-3781-8
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/167164
Abstractdc.description.abstract© 2017 The Author(s). Background: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach. Results: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3-5 years. An analysis of imputation accuracy of missing genotypic data wa
Lenguagedc.language.isoen
Publisherdc.publisherBioMed Central Ltd.
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
Sourcedc.sourceBMC Genomics
Keywordsdc.subjectFruit weight
Keywordsdc.subjectGenome-enabled predictions
Keywordsdc.subjectGenotype imputation
Keywordsdc.subjectPeach (Prunus persica)
Keywordsdc.subjectRepeatability model
Keywordsdc.subjectSugar content
Keywordsdc.subjectTitratable acidity
Títulodc.titleGenome-enabled predictions for fruit weight and quality from repeated records in European peach progenies
Document typedc.typeArtículo de revista
dcterms.accessRightsdcterms.accessRightsAcceso Abierto
Catalogueruchile.catalogadorSCOPUS
Indexationuchile.indexArtículo de publicación SCOPUS
uchile.cosechauchile.cosechaSI


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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile