INTERAÇÃO GENÓTIPOS POR AMBIENTES EM CLONES DE Pinus taeda L.

• Ano de defesa: 2019
• Autor(a) principal: Braga, Rayssa Chaves
• Orientador(a): Tambarussi, Evandro Vagner
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Centro-Oeste
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciências Florestais (Mestrado)
• Departamento: Unicentro::Departamento de Ciências Florestais
• País: Brasil
• Palavras-chave em Português: Adaptabilidade; Estabilidade; GGE biplot
• Palavras-chave em Inglês: Adaptability; Stability; GGE biplot
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL; RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL::MANEJO FLORESTAL
• Link de acesso: http://tede.unicentro.br:8080/jspui/handle/jspui/1388

The interaction between genotypes and environments (GxE) represents one of the most important outcomes of the final stages of a forest improvement program as these effects directly influence the selection of preoperative genotypes. This study aimed to analyze the GxE interaction, as well as the magnitude of the interaction, in clonal tests of Pinus taeda established across three states in the South and Southeast of Brazil: São Paulo, Paraná and Santa Catarina. The tests were implemented using a complete randomized block design with eight replications and one plant per plot repeated across four environments. Measurements were performed at 11 years of age and the characteristics evaluated were diameter at breast height (DBH), total height and volume (a variable of economic interest). Mixed models were used for the joint analysis, which presented high significance for the interaction effect, with 0.01% error, as well as the variance components for the genetic parameter estimates. The mean heritability (ˆ2 hm) for DBH was 0.37 and for total height was 0.53. The estimated genetic correlation for the growth traits DBH and height with volume were positive and statistically significant, indicating the possibility of indirect selection. Herein, we performed the analysis based on the variable DBH, because it is easy to measure and is less subject to errors. The results showed a complex interaction between genotypes and environments, which makes the selection and recommendation of genotypes difficult. Therefore, analyses of adaptability and genotypic stability are necessary to select superior individuals. Through the GGE biplot analysis it was possible to identify the most stable genotypes and those that are well adapted to the planting conditions of the test sites, thus informing superior genotype selection. The Rio Negro-PR and Sengés-PR environments were highly correlated and formed a macroenvironment, a set of geographic locations that share superior genotypes. Genotypes 3, 4, 5, 6 and 7 are indicated for selection based on the GGE biplot analysis that simultaneously considers productivity, stability and adaptability.