A Meta-Analytic Approach to Predict Methane Emissions from Dairy Goats Using Milk Fatty Acid Profile

Abstract

The aim of this work was to develop an equation to predict methane yield (CH4, g/kg dry matter intake) from dairy goats using milk fatty acid (FA) profile. Data from 12 research papers (30 treatments and 223 individual observations) were used in a meta-regression. Since most of the selected studies did not extensively report milk fat composition, palmitic acid (C16:0) was selected as a potential predictor. The obtained equation was: CH4 (g/kg dry matter intake) = 0.525 × C16:0 (% in milk fat). The coefficient of determination (R2 = 0.46), the root mean square error of prediction (RMSPE = 3.16 g/kg dry matter intake), and the concordance correlation coefficient (CCC = 0.65) indicated that the precision, accuracy and reproducibility of the model were moderate. The relationship between CH4 yield and C16:0 content in milk fat would be supported by the fact that diet characteristics that increase the amount of available hydrogen in the rumen for archaea to produce CH4, simultaneously favor the conditions for the synthesis of C16:0 in the mammary gland. The obtained equation might be useful, along with previous published equations based on diet characteristics, to evaluate the environmental impact of dairy goat farming.