Equações de predição de valores energéticos em alimentos para gatos

• Ano de defesa: 2016
• Autor(a) principal: Oca, Mônica Andreina Rodriguez Montes de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Zootecnia; UFLA; brasil; Departamento de Zootecnia
• Palavras-chave em Português: Gato – Alimentação e rações; Alimentos – Teor calórico – Modelos matemáticos; Cats – Feeding and feeds; Food – Caloric content – Mathematical models; Nutrição e Alimentação Animal
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/11930

The knowledge of energy and digestibility values of food is important for the adequate balance of feeds for cats. In addition, the energy content of the food directly interferes in consumption and, consequently, in meeting the nutritional needs of these animals. In this sense, many methods have been proposed to determine the energy content of food, among which is the use of prediction equations based on chemical composition of the food. However, the prediction equations used for calculating energy values need better accuracy. Therefore, with this study, we aimed at elaborating and validating prediction equations for metabolisable energy (ME) and digestible energy (DE) of complete feeds for cats. The chemical and energy composition of 38 complete feeds obtained in different works conducted in the period from 2010 to 2015 were used. The equations were estimated by multiple linear regressions, using the stepwise method. Subsequently, the obtained equations were validated along with equations found in literature. For selecting the best equations, the probability value (t Student) for the null hypothesis, the coefficient of determination (R 2 ), the error values (MAD, MAPE and m.s.e) and bias were considered. Despite most equations proposed presenting a tendency for value overestimation, all can be used to predict the energy values of food. The equations best evaluated were ADE = 47.24PB + 32.52EE – 81.27MM + 2531.76, presented in this study, and ME = 75EE + 2766, presented in literature.