| Revista: | Acta scientiarum. Agronomy |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000460004 |
| ISSN: | 1679-9275 |
| Autores: | Sant’Anna, Isabela de Castro1 Silva, Gabi Nunes2 Carneiro, Vinícius Quintão3 Pontes, Daiana Salles1 Nascimento, Moysés1 Cruz, Cosme Damião1 |
| Instituciones: | 1Universidade Federal de Vicosa, Departamento de Estatistica, Vicosa, Minas Gerais. Brasil 2Universidade Federal de Rondonia, Departamento de Matematica e Estatistica, Ji-Parana, Rondonia. Brasil 3Universidade Federal de Vicosa, Departamento de Biologia Geral, Vicosa, Minas Gerais. Brasil |
| Año: | 2020 |
| Volumen: | 42 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Descriptivo |
| Resumen en inglés | The objective of this study was to compare different graphical dispersion analysis techniques in two- or three-dimensional planes. In this study, the data from different published works were used in order to determine the best methodology for analyzing the genetic diversity of different species. In this study, efficiency is measured by the amount of original distance absorbed by the projection of distances technique, which in the case of major components is equal to the amount of total variation originally available and retained by the principal components used for dispersion purposes. The projection of dissimilarity measurement technique, principal component analysis (PCA), and principal coordinate analysis (PCoA) were used. Considering the analysis by means of three orthogonal axes, the graphical dispersion efficiency was 82.22 for PCA, 87.22 for PCoA, and 85.25 for the projection of distances technique. For the 2D analysis, considering the two main axes, the mean dispersion efficiency was 69.90 for the PCA, 75.06 for the projection technique, and 78.16 for PCoA. Considering the studies carried out with experimental data of six different species, it is concluded that the principal coordinate analysis is superior |
| Disciplinas: | Biología |
| Palabras clave: | Genética, Adaptación, Diversidad genética, Análisis multivariado, Cultivos |
| Keyword: | Genetics, Adaptation, Multivariate analysis, Crops |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
