Otimização de processo de biodegradação de óleo diesel por Candida lipolytica UCP 0988 em água do mar

• Ano de defesa: 2018
• Autor(a) principal: Henriques, Maria Luísa Oliveira Mergulhão de Freitas
• Orientador(a): Albuquerque, Clarissa Daisy da Costa
• Banca de defesa: Albuquerque, Clarissa Daisy Costa , Silva, Carlos Alberto Alves da , Gusmão, Norma Buarque de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Católica de Pernambuco
• Programa de Pós-Graduação: Mestrado em Desenvolvimento de Processos Ambientais
• Departamento: Departamento de Pós-Graduação
• País: Brasil
• Palavras-chave em Português: Metodologia de superfície de resposta; Biodegradação; Óleo diesel; Biossurfactante; Biorremediação marinha
• Palavras-chave em Inglês: Response surface methodology; Biodegradation; Diesel oil; Marine bioremediation; Biosurfactant
• Área do conhecimento CNPq: CIENCIAS BIOLOGICAS::BIOLOGIA GERAL
• Link de acesso: http://tede2.unicap.br:8080/handle/tede/1054

Response surface methodology was used to model the concentration of biomass in the process of diesel oil biodegradation in sea water by Candida lipolytica CPU 0988. The seawater was collected from beach near Suape's industrial port complex, Pernambuco, Brazil. A 24 full factorial design was carried out to evaluate the effects and interactions of initial pH and concentrations of diesel oil, ammonium sulfate and monobasic potassium phosphate on biomass concentration, surface tension,emulsification activity, salinity and pH at 96h.Twenty 1000 mL Erlenmeyer flasks containing the media for biodegradation were incubated on a rotatory shaker at 28ºC and 200 rpm for four days. The yeast was able to use diesel oil and to produce biosurfactants and bioemulsifiers. The biomass concentrations varied between 7 and 36 g/L and the surface tension reductions between 8 and 37%. A biomass concentration model was developed as a function of pH and concentrations of diesel oil, ammonium sulfateand monobasic potassium. A high coefficient of determination (R2=0.9544) and a low p-value (p <0.05) confirm the statistical significance of the model. The non-significant lack-of-fit value (p>0.05) suggests the adequacy of the biomass model to explain data in the studied conditions.