AVALIAÇÃO DE QUALIDADE DE SÊMEN CONGELADO E USO DE ÁRVORE DE DECISÃO PARA PREDIÇÃO DE FERTILIDADE EM IATF DE VACAS ZEBUÍNAS

• Ano de defesa: 2022
• Autor(a) principal: Francisco Eduardo Machado Vaz
• Orientador(a): Ériklis Nogueira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Inseminação Artificial, Fertilidade, Predição.
• Link de acesso: https://repositorio.ufms.br/handle/123456789/5452

The study was conducted with the objective of looking for correlations of laboratory analyzes and pregnancy rate for fertility prediction in FTAI of zebu cows. Laboratory tests were carried out with semen samples from 71 Nelore and Angus bulls, used in the FTAI of 13,174 Nelore cows, in the state of Mato Grosso do Sul. To determine sperm quality, post-thawing motility and vigor, sperm concentration, morphological analysis and rapid thermo-resistance test (TTR) were evaluated. Computerized analysis to evaluate sperm kinetics was determined by the Computer Assisted Semen Analyze (CASA), Ivos-Ultimate model, and analysis of parameters: total motility (%; MT), progressive motility (%; MP), mean velocity (μm /s; VAP), rectilinear velocity (μm/s; VSL), curvilinear velocity (μm/s; VCL), lateral head amplitude (μm; ALC), linearity (%; LIN), rectilinearity (%, STR). Flow cytometry procedures were performed using the CytoFLEX™ equipment evaluating plasma membrane integrity and mitochondrial potential assessment. The most significant parameters for pregnancy were submitted to the SAS Logistic Proc, and the generated equation was P/IA = -0.11 + (ECC x 0.0589) - (integral x 0.004) + (polarized x 0.0070) + (motcasa x 0.0109) + (vigor x 0.15) – (total defects x 0.0069) – (progcasa x 0.024) – (vsl x 0.0052). Relevant data which are more effective for pregnancy (P/AI), when taken together, were obtained by the Weka 3.8 software, through the J48 classifier, producing a decision tree, with the most important parameters for pregnancy prediction in FTAI identified: Progressive Motility, Total Motility and Rectilinear Velocity (VSL) in CASA, Plasma Membrane Integrity, Sperm Vigor and Total Defects. The average of the observed pregnancy rate was equal to that calculated by the generated equation, thus, we concluded that the model is multifactorial with compensation situations that must be considered in the analyses.