Consequences of genetic selection for environmental impact traits on economically important traits in dairy cows
Purna Kandel A , Sylvie Vanderick A , Marie-Laure Vanrobays A , Hélène Soyeurt A and Nicolas Gengler A B
+ Author Affiliations
- Author Affiliations
A University of Liege, Gembloux Agro-Bio Tech, TERRA Teaching and Research Center, Passage des Déportés, 2, B-5030 Gembloux, Belgium.
B Corresponding author. Email: nicolas.gengler@ulg.ac.be
Animal Production Science 58(10) 1779-1787 https://doi.org/10.1071/AN16592
Submitted: 2 September 2016 Accepted: 28 April 2017 Published: 20 June 2017
Journal compilation © CSIRO 2018 Open Access CC BY-NC-ND
Abstract
Methane (CH4) emission is an important environmental trait in dairy cows. Breeding aiming to mitigate CH4 emissions require the estimation of genetic correlations with other economically important traits and the prediction of their selection response. In this study, test-day CH4 emissions were predicted from milk mid-infrared spectra of Holstein cows. Predicted CH4 emissions (PME) and log-transformed CH4 intensity (LMI) computed as the natural logarithm of PME divided by milk yield (MY). Genetic correlations of PME and LMI with traits used currently were approximated from correlations between estimated breeding values of sires. Values were for PME with MY 0.06, fat yield (FY) 0.09, protein yield (PY) 0.13, fertility 0.17; body condition score (BCS) –0.02; udder health (UDH) 0.22; and longevity 0.22. As expected by its definition, values were negative for LMI with production traits (MY –0.61; FY –0.15 and PY –0.40) and positive with fertility (0.36); BCS (0.20); UDH (0.08) and longevity (0.06). The genetic correlations of 33 type traits with PME ranged from –0.12 to 0.25 and for LMI ranged from –0.22 to 0.18. Without selecting PME and LMI (status quo) the relative genetic change through correlated responses of other traits were in PME by 2% and in LMI by –15%, but only due to the correlated response to MY. Results showed for PME that direct selection of this environmental trait would reduce milk carbon foot print but would also affect negatively fertility. Therefore, more profound changes in current indexes will be required than simply adding environmental traits as these traits also affect the expected progress of other traits.
Additional keywords: dairy cows, genetic correlation, methane intensity, predicted methane emissions, selection response.
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