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Greenhouse gases emission from bovine excreta of C3 forage and C4 grasses in tropical pastures

Grant number: 17/20279-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2017
Effective date (End): June 30, 2019
Field of knowledge:Agronomical Sciences - Animal Husbandry - Pastures and Forage Crops
Principal Investigator:Ana Cláudia Ruggieri
Grantee:Rodolfo Nussio Lumasini
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The environmental impact caused by of greenhouse gases (GHG)emission of agricultural sector, it is a subject very much discussed today, since the sector contributes for the emission of 33% of the total in the country. The challenge faced by the ruminant production system is to develop management, as well as the quality of the food ingested by these animals, aiming to increase productive efficiency and reduce the impacts of global warming. The present study aims to quantify greenhouse gases emission in pastures of palisade grass (C4) intercropped with Arachis pintoi (C3) or fertilized with nitrogen fertilizer. The experimental design will be in blocks completely randomized (BCR). The treatments will be: 1) 1.0 L of urine of the animals in pastures without nitrogen source; 2) 1.0 L of urine of the animals in pastures with nitrogen source(150 kg N ha-¹ year-1); 3) 1.0 L of urine of the animals in pastures intercropped with Arachis pintoi; 4) 1.6 kg of fresh feces of the animals in pastures without nitrogen source; 5) 1.6 kg of fresh feces of the animals in pastures with nitrogen source (150 kg N ha-¹ year-1); 6) 1.6 kg of fresh feces of the animals in pastures intercropped with Arachis pintoi; 7) nitrogen fertilizer of the soil (150 kg N ha-1 year-1); and 8) control (without addition of excretas or fertilizers). The variables analyzed will be emission of N2O, CO2 and CH4, and the explanatory variables mineral N (NO3- e NH4+) humidity and soil temperature. The accumulated data will be analyzed in BCR, the treatments will be considered as main effects. The PROC GLM procedure of the SAS statistical program will be used, and when differences have been found, will be applied the Tukey ru Scott-knnot for test comparison. It will be tested the effect of soil and climate variables on gas flows through correlation analysis. (AU)