Selection of mango rosa genotypes in a breeding population using the multivariate-biplot method

ABSTRACT: Mango ( Mangifera indica L.) trees stand out among the main fruit trees cultivated in Brazil. The mango rosa fruit is a very popular local variety (landrace), especially because of their superior technological characteristics such as high contents of Vitamin C and soluble solids (SS), as w...

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Main Authors: Maria Clideana Cabral Maia, Lúcio Borges de Araújo, Carlos Tadeu dos Santos Dias, Luís Cláudio de Oliveira, Lúcio Flavo Lopes Vasconcelos, José Eduardo Vasconcelos de Carvalho Júnior, Marcelo Simeão, Yuri Gagarin Muniz Bastos
Format: Article
Language:English
Published: Universidade Federal de Santa Maria
Series:Ciência Rural
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Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016001001689&lng=en&tlng=en
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Summary:ABSTRACT: Mango ( Mangifera indica L.) trees stand out among the main fruit trees cultivated in Brazil. The mango rosa fruit is a very popular local variety (landrace), especially because of their superior technological characteristics such as high contents of Vitamin C and soluble solids (SS), as well as attractive taste and color. The objective of this study was to select a breeding population of mango rosa (polyclonal variety; ≥5 individuals) that can simultaneously meet the fresh and processed fruit markets, using the multivariate method of principal components and the biplot graphic. The principal components, biplot graphic, and phenotype correlations were obtained using the R (2012) software. Pulp percentage and the pulp, skin, and seed mass variables can be indirectly selected using the smallest fruit diameter, which allowed an easier measurement. The P23R AREA3, P30R AREA3, and P32R AREA3 genotypes are selection candidates due to the presence of alleles, which are important agro-technological traits for mango breeding. This study showed that the biplot analysis is a valuable tool for decision making and visualization of interrelationships between variables and genotypes, facilitating the mango selection process.
ISSN:1678-4596