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Accuracy, precision and robustness of methane emission estimates of beef cattle in tropical condition

Grant number: 15/19508-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): March 01, 2016
Effective date (End): August 31, 2017
Field of knowledge:Agronomical Sciences - Animal Husbandry - Animal Nutrition and Feeding
Principal Investigator:Elias San Vito
Grantee:Thais Fernanda Ribeiro
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The global emission of methane, a major greenhouse gas, has become the focus of major scientific debates. Farming is responsible for much of greenhouse gases emissions, especially methane emissions. Making studies related enteric methane emissions of utmost importance to Brazil, which has the world's second largest cattle population, estimated at around 205 million head. To enable the development of strategies to reduce methane emissions by cattle, it is necessary to quantify the issue. Because of the various existing techniques that measure the production of enteric methane being costly and difficult to apply in practical conditions of creation, the mathematical models are a viable alternative, and proved efficient. The aim of this study is to use mathematical equations to predict the enteric methane production of beef cattle fed different sources of non-protein nitrogen in diets based on tropical forages. Equations used to predict methane emissions are described by Ellis et al. 2007 take into account the dry matter intake (DMI), NDF intake and percentage of forage in the diet for the calculations. Calculation results are will be compared with actual emissions of methane estimated by the SF6 technique. The data resulting from this study will demonstrate if mathematical equations are applicable or not, giving support to possible adjustments. For this reason it is necessary to be tested and evaluated according to the characteristics of tropical regions. (AU)