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|Research center of Embrapa/Collection:||Embrapa Agroindústria Tropical - Artigo em periódico indexado (ALICE)|
|Type of Material:||Artigo em periódico indexado (ALICE)|
|Authors:||MAIA, M. C. C.|
ARAUJO, L. B. de
DIAS, C. T. dos S.
OLIVEIRA, L. C. de
VASCONCELOS, L. F. L.
LIMA, P. S. da C.
|Additional Information:||MARIA CLIDEANA CABRAL MAIA, CNPAT; Lúcio Borges de Araújo, Matemático/Estatístico, Doutor, Universidade Federal de Uberlândia/UFU, Departamento de Ciências Exatas; Carlos Tadeu dos Santos Dias, Eng. Agrônomo, Doutor, Universidade Federal do Ceará /UFC Departamento de Ciências do Solo; LUIS CLAUDIO DE OLIVEIRA, CPAF-AC; LUCIO FLAVO LOPES VASCONCELOS, CPAMN; PAULO SARMANHO DA COSTA LIMA, CPAMN.|
|Title:||Early selection in a population of the mangaba (Hancornia speciosa Gomes).|
|Publisher:||Revista Agro@mbiente On-line, v. 14, 2020.|
|Description:||The mangaba is a fruit tree with great potential for the northeast of Brazil. Due to the scarcity of improved cultivars, and as it is a species that is still in the process of domestication, exploitation has been based on rational and sustainable extractivism by farmer-gatherers. The aim of this study was to analyse the correlations between technological variables of the mangaba, and to carry out an early selection of the genotypes that make up the base population of the mangaba improvement program of Embrapa Meio-Norte. The variables fruit weight, pulp weight and percentage pulp show significant correlation with fruit length and fruit diameter, allowing indirect selection for the first set of variables by means of the latter, which are easily measured. Genotypes 4, 13, 16, 21, 25, 32, 35 and 49 show a positive association with fruit weight, fruit length, fruit diameter, pulp weight and percentage weight, and are therefore candidates for selection. Principal component 1 is associated with fruit weight, fruit length, fruit diameter, skin weight, number of seeds per fruit, seed weight, TTA and pulp weight. These variables can be selected with greater mathematical certainty, since this component concentrates more information regarding variability and is therefore more important.|
|NAL Thesaurus:||Phenotypic correlation|
Principal component analysis
|Appears in Collections:||Artigo em periódico indexado (CNPAT)|