GENOTYPIC IDENTIFICATION OF SWEET ORANGE TREE ACTIONS THROUGH RANDOMLY AMPLIFIED MICROSATELLITES (RAMs) (Atena Editora)

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MetadadosDescriçãoIdioma
Autor(es): dc.contributor.authorLeón, Isidro Humberto Almeyda-
Data de aceite: dc.date.accessioned2024-10-18T23:38:59Z-
Data de disponibilização: dc.date.available2024-10-18T23:38:59Z-
Data de envio: dc.date.issued2024-10-10-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/870713-
Resumo: dc.description.abstractCitrus fruits are produced in subtropical and tropical zones, and their fruits are consumed by millions of people around the world. In Mexico, sweet orange is the most important citrus species cultivated, mainly because of the area planted (340 thousand ha-1 ) and production (average yields of 13.95 ton ha-1 ), with a value of more than 10.18 billion pesos. The objective of this work was to identify genetically by Random Amplified Microsatellites (RAMs), the accessions of sweet orange (Citrus sinensis L.) stored in the INIFAP Citrus Germplasm Bank at the General Terán Experimental Field. Twenty-eight accessions were collected (two replicates per accession established under greenhouse conditions). Genetic identification was carried out with the Random Amplified Microsatellites (RAMs) technique, using the CA primer, which was selected because it can generate up to 26 polymorphic fragments. The identity of the two replicates was confirmed in 25 accessions; however, differences were found between the two replicates of the Moro, Campbell O.L. and Rio Grande Navel Nuc varieties. These results allow inferring the possibility that the differences recorded between the replicates of these three accessions may be due to the mutation phenomenon, a characteristic that can be used in breeding programs to generate new varieties of commercial interest.pt_BR
Idioma: dc.language.isoenpt_BR
Palavras-chave: dc.subjectGermplasm bankpt_BR
Título: dc.titleGENOTYPIC IDENTIFICATION OF SWEET ORANGE TREE ACTIONS THROUGH RANDOMLY AMPLIFIED MICROSATELLITES (RAMs) (Atena Editora)pt_BR
Tipo de arquivo: dc.typelivro digitalpt_BR
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