Estudo da classificação e coincidência de seleção de rainhas Apis mellifera L. (Hymenoptera: Apidae)
The existence of errors in the information of kinship or absence of data, can lead to erroneous interpretations, resulting in the decrease of the response to selection. In bees, because the queen has the habit of multiple mating under natural fertilization, the male's information is lost. Conse...
| Autor principal: | Silva Neto, João Barbosa da |
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| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2020
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/11333 |
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| Resumo: |
The existence of errors in the information of kinship or absence of data, can lead to erroneous interpretations, resulting in the decrease of the response to selection. In bees, because the queen has the habit of multiple mating under natural fertilization, the male's information is lost. Consequently genetic evaluation in bees was little studied. Therefore the objective of this study was to study the classification and coincidence of selection in a population of Africanized queens selected for emergency weight, in the different ways of considering the information of the male in the genetic evaluation. Bayesian Inference was used to estimate genetic parameters. For the study were used groups of parents known, unknown, ghost parents with three groups and ghost parents with six groups. The highest coincidence values (81.43%, 94.29% and 72.85%) and correlations (0.70, 0.94, 0.83) were verified when compared to known parents having complete information from the six generations with parents without the latest generation of phenotypic information; known parents with unknown parents and unknown parents having complete information from the six generations with unknown parents without the last generation phenotypic information, respectively. The lowest coincidence values (17.14% to 22.86%) and correlations (-0.02 to 0.08) were obtained using phantom parents with three and six groups. It can be concluded that for both groups of ghost parents, the selection is less efficient compared to the other methods of genetic evaluation. Thus, the best way to consider the information of drones is through the use of unknown parents, since the same without the last generation phenotypic information was the most efficient to reach near the real value and presented higher values of correlations and coincidence, when compared to the known paternity, indicating that the use of this methodology would not cause a significant difference in queens' classification. |
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