Crop Breeding and Applied Biotechnology
URI permanente para esta coleçãohttps://thoth.dti.ufv.br/handle/123456789/12091
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Item Discriminant analysis for the classification and clustering of robusta coffee genotypes(Crop Breeding and Applied Biotechnology, 2004-07-07) Fonseca, Aymbiré Francisco Almeida da; Sediyama, Tocio; Cruz, Cosme Damião; Sakiyama, Ney Sussumu; Ferrão, Romário Gava; Ferrão, Maria Amélia Gava; Bragança, Scheilla MarinaThis study evaluated the adequacy of the composition of three clonal Coffea canephora varieties recommended for the State of Espírito Santo by a multivariate method designated discriminant analysis. This method consists in the establishment of functions that enable the classification of a given individual into one, among various distinct populations, reducing the probability of a misclassification. It simultaneously considers measures of several traits, in order to give the new variety homogeneity. The original classification of genotypes in the three studied varieties, based on agronomical criteria, maintained expressive concordance with the results of the discriminant analysis, with an apparent deviation rate of only 6.25%. Corrected discriminant functions were also proposed, capable of classifying a new genotype into one of the three clonal varieties to be used in improvement programs, eliminating the subjectivity of the clustering process.Item Repeatability and number of harvests required for selection in robusta coffee(Crop Breeding and Applied Biotechnology, 2004) Fonseca, Aymbiré Francisco Almeida da; Sediyama, Tocio; Cruz, Cosme Damião; Sakiyama, Ney Sussumu; Ferrão, Romário Gava; Ferrão, Maria Amélia Gava; Bragança, Scheilla MarinaThis study aimed to estimate the repeatability coefficient of the grain yield in Coffea canephora by three methods: to quantify the precision of the measurements; to predict the real value of an individual based on n evaluations; and to determine the number of phenotypic measures required in each plant to obtain an adequate precision level for an efficient discrimination of the genotypes. The coefficients of repeatability and determination were estimated based on four harvests of 80 genotypes. Highest estimates of the repeatability coefficient were obtained by the method of the principal components derived from the matrix of covariances, which expresses the correlation between each measurement pair. The prediction precision of the real individual value ranged from 65.32 to 81.59%, and remained practically unchanged from the sixth harvest on.