Detalhes bibliográficos
| Ano de defesa: |
2015 |
| Autor(a) principal: |
Schafascheck, Lilian
 |
| Orientador(a): |
Matiello, Rodrigo Rodrigues
|
| Banca de defesa: |
Faria, Marcos Ventura
,
Gardingo, José Raulindo
|
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
UNIVERSIDADE ESTADUAL DE PONTA GROSSA
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Agronomia
|
| Departamento: |
Agricultura
|
| País: |
BR
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede2.uepg.br/jspui/handle/prefix/2277
|
Resumo: |
The wheat breeding starts with the selection of the parent to make the crossing blocks, aiming at segregating populations with high yield potential and divergent, to evaluate the adaptability and phenotypic stability in different wheat regions. Therefore, the objectives of this study were to estimate the genetic dissimilarity among wheat genotypes through agronomic characterization, molecular genotyping and coefficient parentage, cluster analyses of genotypes by means of multivariate statistical methods, and to evaluate the adaptability and phenotypic stability by GGE biplot methodology. It was evaluated 43 new wheat lines developed by the breeding program of UEPG and cultivar commercial Safira®. The genetic dissimilarity among the genotypes was obtained from the Generalized Mahalanobis Square Distance (D2) through seven agronomic traits, coefficient parentage (COP) and Jaccard index for SSR and AFLP markers. The genotypes were grouped according to the genetic dissimilarity through the UPGMA and principal component analysis (PCA) methods. The principal component analysis (PCA) enabled the reduction the set of seven variables on three principal components, explaining 67% of the total phenotypic variance. The coefficients of the eigenvectors indicated that the CP1 was more related to grain quality (thousand kernels weight and weight hectoliter) and the vegetative cycle. CP2 in most was influenced by the grain yield (48.4%) and CP3 negatively associated with the plant height (72.08%). CP analysis allowed the identification of groups of different wheat genotypes through agronomic characteristics. The dendrograms obtained through molecular genotyping (SSR and AFLP) and agronomic characterization demonstrated the formation of eight groups, while the coefficient parentage only five groups of genotypes. The cophenetic correlations between the matrices of genetic dissimilarity were low. Nevertheless, the analysis methods were efficient in estimating the genetic dissimilarity among the genotypes and enabled highlight wheat lines which showed higher agronomic performance. To estimate the adaptability and stability of wheat genotypes were evaluated in crops 2010, 2011 and 2012 in Ponta Grossa, for characteristics plant height, reproductive cycle and grain yield. From the results of the graphical analysis, it could identify the ideals genotypes characterized by high agronomic adaptation combined with phenotypic stability. The lines of the UEPG program L8, L15, L17, L31, L34, L38 and L40 showed high adaptation agronomic and phenotypic stability for grain yield. This group of wheat lines showed higher potential productive than that commercial cultivar Safira®, making them strong candidates in the future as new commercial cultivars recommended for the municipality of Ponta Grossa. |
