Avaliação do uso de acelerômetro na observação do comportamento ingestivo de bovinos em pastejo

• Ano de defesa: 2020
• Autor(a) principal: Casanova, Pedro Trindade
• Orientador(a): Quadros, Fernando Luiz Ferreira de
• Banca de defesa: Bremm, Carolina , Trindade, José Pedro Pereira da , Oliveira, Leandro Bitencourt de, Pötter, Luciana
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Centro de Ciências Rurais
• Programa de Pós-Graduação: Programa de Pós-Graduação em Zootecnia
• Departamento: Zootecnia
• País: Brasil
• Palavras-chave em Português: Inteligência artificial; Monitoramento; Pecuária; Tecnologia
• Palavras-chave em Inglês: Artificial intelligence; Monitoring; Livestock; Technology
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::ZOOTECNIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/21084

The aim of this work was to evaluate the potential for substitution of traditional methodology for assessing the ingestive behavior of cattle grazing, visual observation, by the use of an electronic recorder provided with an accelerometer. For this purpose, filming, visual monitoring and use of recorder were carried out to identify acceleration patterns for cattle grazing and rumination activities, which made it possible to compare images with graphics generated by the equipment, resulting in the identification of potential for graphic interpretation surpassing the ability for visual observation. Then, an algorithm was evaluated to automate the readings of graphs, qualifying and quantifying time of grazing, rumination and other activities. To conclude the study, comparisons of methodologies (visual observation, graphs interpretation and algorithm versions) were carried out through simple linear regression analysis, seeking the level of correlation between methodologies and the potential for substitution. It was observed that correlations between methodologies were more than 90%, and accuracy of data collected by recorder able to monitor ingestive behavior of cattle grazing using equipment provided with an accelerometer. New tests to develop the algorithm can make this tool even more accurate and able to compute finer data on ingestive behavior such as number of meals, bit rate, rumination rate, among others.