Development of mathematical models to predict enteric methane emission by cattle in Latin America

Abstract

Methane (CH4) is recognized as the second most important greenhouse gas (GHG) emitted by anthropogenic sources and is a major driver of climate change along with other GHG. Enteric fermentation CH4 emissions from ruminants contribute to approximately 17% of total global anthropogenic CH4 emissions. Several mathematical models to estimate enteric methane emissions have been published, but the majority are limited to cattle in developed countries. Therefore, our objective was to develop a set of empirical models to predict enteric CH4 emissions by cattle in Latin America (LA). A database was compiled from 67 publications that measured enteric CH4 emissions from cattle in LA using respiration chambers or the sulfur hexafluoride tracer technique. In total, there were 230 treatment means of enteric CH4 emissions measured from Nellore (n = 82), crossbreed (n = 79), Holstein (n = 45), and other breeds (n = 24). New prediction models were developed using a mixed-effects modeling approach with a random effect of study. Daily enteric CH4 emissions from all production systems ranged from 48.5 to 656 g/head with an average of 187 g/head. This large variation was largely explained by dry matter intake (DMI; RSR = 0.68, RMSPE = 29.1%). The prediction of CH4 emissions was further improved by a combination of DMI, digestibility and variables related to diet chemical composition such as dietary non-fibrous carbohydrates or dietary NDF. The best performance was obtained from the model based on DMI, dietary forage and organic matter digestibility (RSR = 0.59, RMSPE = 24.2% of observed mean). The newly developed models based on LA data give a better estimation of CH4 emissions from cattle than extant models, while the updated CH4 emission factors from IPCC 2019 performed better than emission factors of IPCC 2006. The new models developed using data specific to the region are recommended for use in preparing national methane inventories for LA cattle.