Avaliação da taxa de mortalidade no transporte industrial de Tilápia, Oreochromis niloticus (LINNAEUS, 1758)

• Ano de defesa: 2014
• Autor(a) principal: SILVA, Thales Serrano
• Orientador(a): PIANA, Pitágoras Augusto
• Banca de defesa: SÉBASTIEN, Nyamien Yahaut , ZACARKIM, Carlos Eduardo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Parana
• Programa de Pós-Graduação: Programa de Pós-Graduação Stricto Sensu em Recursos Pesqueiros e Engenharia de Pesca
• Departamento: Recursos Pesqueiros e Engenharia de Pesca
• País: BR
• Palavras-chave em Português: Variável abiótica; Resíduo nitrogenado; Diferença de gradiente
• Palavras-chave em Inglês: Abiotic variable; Nitrogenous waste; Difference gradient
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCA
• Link de acesso: http://tede.unioeste.br:8080/tede/handle/tede/1937

With the growth of the aquaculture even small mortality rates take big losses, so this study was goal to evaluate possible causes of death in fish at industrial scale in transportation. So eight abiotic variables of water quality were examined: water temperature, dissolved oxygen, ammonia, nitrate, nitrite, pH, conductivity and turbidity, as well transportation time and density and gradient difference of the variables from the catch to the end transport. For this ten samplings between setembro/2013 and fevereiro/2014 were performed in western Paraná. The water sampling were performed at three different times during the transport process, because it was necessary to subdivide them for obtain the difference in gradient of environmental variables and identify which is the most critical step of the process. To characterize the quality of water, the abiotic variables were summarized using Principal Component Analysis (PCA). The combined variation of variables was summarized in an index called variation in environmental gradient (ΔG). Further, to verify which variables were associated with mortality, the Probit model was used in the linear regressions. Both analyzes were evaluated at a significance level of five percent. APC in three main axes, which indicated high concentrations of nitrite for time pond, in loading the variables analyzed were satisfactory and unloading time had water with high levels of nitrate, electrical conductivity and ammonia. In linear regressions nitrite was significant for mortality in pond time, water temperature and electrical conductivity for loading and ammonia and dissolved oxygen for unloading time. Abrupt changes in gradient of the variables did not cause fish mortality and nitrogenous waste found in large concentrations at the end of the transport interfered in fish mortality. With that suggest that fish are subjected to stress before the transport process due to bad quality of water pond.