Abstract

The purpose of this study was to explore the relationships between odd- and branched-chain fatty acids (OBCFA) in milk with calculated enteric CH4 production for lactating dairy cows using multiple linear regression (MLR), partial least squares regression (PLS) and a genetic algorithm approach (GA). A dataset collected from 13 experiments containing 224 paired observations of measured acetate, propionate and butyrate proportions in rumen fluid VFA and 7 measured OBCFA was used. Methane proportion (mmol/mol VFA) was calculated from acetate, propionate and butyrate and expressed relative to the sum of these volatile fatty acids (VFA). Calculated CH4 production was related to milk OBCFA using MLR and PLS, resulting in a linear prediction model. The GA approach resulted in a model which predicted rumen VFA proportions of total VFA from milk OBCFA. Methane proportion was calculated from predicted acetate, propionate and butyrate proportions in total VFA based on rumen stoichiometry and compared with CH4 proportion calculated from measured VFA proportions. The prediction error was low (i.e., root mean square prediction error <5%), and models captured up to 66% of the variance in the data and the concordance correlation coefficient was close to 0.8. The variance of the prediction error was less than 40% of the variance of the calculated CH4 proportion. Seven milk OBCFA were initially considered as predictors, from which the branched-fatty acids iso C14:0, iso C15:0, iso C16:0 were positively related to calculated enteric CH4 production and the odd-fatty acids C15:0 and the sum of C17:0 and C17:1 cis–9 were negatively related to it. Relationships in this large data set identify the most relevant OBCFA in milk as potential predictors of rumen methanogenesis.This paper is part of the special issue entitled: Greenhouse Gases in Animal Agriculture – Finding a Balance between Food and Emissions, Guest Edited by T.A. McAllister, Section Guest Editors; K.A. Beauchemin, X. Hao, S. McGinn and Editor for Animal Feed Science and Technology, P.H. Robinson.

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