Modelos biométricos aplicados na seleção de gerações avançadas de trigo

• Autor(a) principal: Meier, Carine
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/00130000179s1
• Texto Completo: http://repositorio.ufsm.br/handle/1/19632
• topic: Modelos biométricos; Divergência genética; Parâmetros genéticos; Triticum aestivum L; Biometric models; Genetic divergence; Genetic parameters; Triticum aestivum L; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA

Wheat is a cereal that has great economic importance in Brazil, the country produces 5,1 million tons, this situation makes the country one of the largest importers of this cereal. Thus, genetic improvement is of great importance in an attempt to increase yield, productivity and quality of the wheat produced. In addition, increasing the efficiency of breeding programs is essential to reducing the costs and time required to launch new cultivars. The objective of this study was to evaluate advanced wheat generations using multivariate and biometric models in order to obtain information for selecting superior genotypes. The research was conducted in the experimental area of the Laboratory of Genetic Improvement and Plant Production, Federal University of Santa Maria, Frederico Westphalen Campus / RS. For this purpose, 420 wheat genotypes were initially used in the F5 generation, conducted in the experimental design of families with interim controls in the 2017 agricultural year. The F6 generation was conducted with fifteen wheat genotypes, arranged in three replicates in 2018. The following characters were evaluated: a) days from emergence to flowering; b) plant height; c) spike length; d) number of fertile tillers; e) spike weight; f) kernel weight; g) number of spikelets; h) number of kernels per plant; (i) total plant kernel weight. Subsequently, the F7 generation was conducted in the field in a randomized complete block design. The following characters were evaluated: a) plant height; b) spikelets insertion height; c) number of fertile tillers; d) kernel width; e) hectolitic weight; f) number of spikelets and g) kernel weight per plant. From the information obtained, the genotypes were submitted to selection gain analysis and selection indices, variance components and genetic parameters, genetic diversity, phenotypic, genetic and environmental correlations, as well as predicted genotypic values. The selection of plants with higher tiller numbers increased in more productive genotypes. The formation of distinct groups indicated the presence of genetic variability among the evaluated populations. The cycle is the variable that presented the largest contribution to genetic divergence among the studied genotypes. The use of selection indices is advantageous in advanced wheat generations, since they provide selection gains, distributed among all evaluated characters, a situation that is better suited to breeding programs. The FAI-BLUP index revealed the possibility of reduction for plant height and increase in gains for tiller number and total grain mass per plant. The UFSM FW1 02 genotype provides to be superior to the control used in the assays, being able to be evaluated in cultivation and use value assays, since it gathers characteristics closer to the ideal, presenting high productive potential.