Progresso genético da soja no Brasil em um programa de melhoramento comercial
The increase in soybean productivity over the years is the result of improved environment, pest and disease management, soil fertility, among others, and genetics, development of cultivars with greater productive potential. Advances in genetics, measured by genetic gain, within a historical series,...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Institución: | Universidade Tecnológica Federal do Paraná (UTFPR) |
| Repositorio: | Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT)) |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.utfpr.edu.br:1/28143 |
| Acceso en línea: | http://repositorio.utfpr.edu.br/jspui/handle/1/28143 |
| Access Level: | acceso abierto |
| Palabra clave: | Soja Soja - Melhoramento genético Grãos - Rendimento Plantas - Melhoramento genético Soybean Soybean - Breeding Grain - Yields Plant breeding CNPQ::CIENCIAS AGRARIAS::AGRONOMIA Agronomia |
| Sumario: | The increase in soybean productivity over the years is the result of improved environment, pest and disease management, soil fertility, among others, and genetics, development of cultivars with greater productive potential. Advances in genetics, measured by genetic gain, within a historical series, help breeders to understand the advances obtained, and allow them to outline strategies and adopt new methods in order to increase the efficiency of the program. The objectives of the present study were to quantify the genetic gain of the GDM soybean breeding program; to measure the genetic gain of the conventional platforms, Intacta, Enlist Conkesta E3TM and Intacta 2 Xtend, in the different Brazilian macroregions; and establish strategies for the increment and continuity of obtaining future gains in the improvement program. For this, data from crop value tests (VCU) were used, conducted in the 2011/12 to 2020/21 harvests. Data were analyzed via mixed models, with the aid of the lme4 package, to obtain the best unbiased linear predictor for each genotype tested. From these values, the gain was quantified using regression analysis. All analyzes were performed in the Software R Core Team (2020). The soybean improvement program has shown positive progress in all soybean macroregions and platforms. At the Brazilian level, the program showed a progress rate of 118,69 kg ha-1 year-1 (3.69% a year-1). The breeding techniques used have been efficient in the selection of productive lines. |
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