Sunflower bran in diets for swine with high weight of slaughter

• Grant number: 10/06893-9
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2010
• End date: July 31, 2012
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Animal Nutrition and Feeding
• Principal Investigator: Maria Cristina Thomaz
• Grantee: Maria Cristina Thomaz
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

Two experiments will be conducted to evaluate the inclusion of sunflower meal in feed restriction program quality for swine slaughtered at 130 kg. In the first experiment, 16 castrated male swine and hybrid with an average of 80 kg will be divided into two groups: one will receive a reference diet consisting primarily of corn and soybean meal, and the other the test diet, comprising 70% of reference diet and 30% sunflower meal. It will use the partial fecal collection method for obtaining digestibility coefficients, levels of nutrients and digestible energy of sunflower meal. The results will be used in formulating rations for the second experiment to evaluate the effects of sunflower meal inclusion (0, 7, 14, 21 and 28%) on performance, diet digestibility, carcass traits, meat quality, serum parameters, weights of organs of the digestive system, production and characteristics of manure and economic evaluation. The second experiment will use 54 castrated male swine and hybrid with an average of 80 kg. Forty-five animals will be distributed in a randomized block design, consisting of five treatments and nine replications of one animal. Nine animals will receive control diet (free of sunflower meal) and will be slaughtered at approximately 100 kg for ratings in the carcass, which will serve for comparison with those of swine slaughtered at 130 kg. The data will be submitted to an ANOVA using the GLM procedure of SAS statistical software (1998), and the observed data in experiment 2 will be evaluated according to multiple linear regressions to the third degree. (AU)