(untitled) (Research, Society and Development, 2021)
The current paper aims to perform data mining and artificial intelligence algorithms for genealogical data related to creole horses awarded in the “Expointer” competition, in order to uncover patterns and characteristics of winning animals. The dataset was obtained on a repository from the “Associação Brasileira de Criadores de Cavalos Crioulos”. The techniques and algorithms employed were frequency analysis, means comparison and linear regression. In total, information from 1866 animals was extracted, which were organized in two groups according to the competition events of “Morfologia” and “Freio de Ouro”. The paternal lineage with better performance out of the champions from both events was Aculeo Vastago. In comparison, the more successful maternal branches demonstrated higher variability; Nevertheless, a dominance was observed for the families Torhuela, Che Pitanga 565 and BT Fuzarca in the “Morfologia” event. The mean comparison analyses revealed a statistically signifficant difference (p<0,001) between the mean final punctuation in comparison to final position in the event. Overall, the analysis of this dataset demonstrated high variability and few patterns. Still, we were able to identify the most recurrent lineages amongst the better positioned animals in the “Morfologia” and “Freio de Ouro” events. The findings contained in this study can be used as support for genetic enhancement of creole breeds, allowing for a better performance in competitions.