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Combining heterogeneous across-country data for prediction of enteric methane from proxies in dairy cattle
Negussie, E.; Gonzàlez Recto, O.; de Haas, Y. et al.
2018In Proceedings of the World Congress on Genetics Applied to Livestock Production
Peer reviewed
 

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Keywords :
enteric methane; heterogeneous data; prediction accuracy; methane proxies; random forest; dairy cattle
Abstract :
[en] Large-scale measurement of enteric methane (CH4) from individual animals is a prerequisite for estimation of genetic parameters and prediction of breeding values. Direct measurement of individual CH4 emissions is logistically demanding and expensive, and correlated traits (proxies) or models can be used instead as a means to predict emissions. However, most predictive models tend to be specific and are valid mainly within the circumstances under which they were developed. Robust prediction models that work across countries and production environments may be built by combining heterogeneous data from several sources. However, combining heterogeneous individual animal observations on CH4 proxies from several sources is challenging and reports are scant in the literature. The main objective of this study was to combine heterogeneous individual animal observations on CH4 proxies to develop robust enteric CH4 prediction models. Data on dairy cattle CH4 emissions and related proxies from 16 herds were made available by 13 research centers across 9 European countries within the Methagene EU COST Action FA1302 consortium on “Large-scale methane measurements on individual ruminants for genetic evaluations”. After a thorough editing and harmonization, the final dataset comprised 48,804 observations from 2,391 cows. Random Forest (RF) models were used to predict CH4 emissions and to estimate the relative importance of proxies for across-country predictions. Principal component analysis (PCA) was used to detect potential data stratifications. Milk yield, milk fat, DIM, BW, herd and country of origin appeared to be the most relevant proxies in the prediction model. An overall prediction accuracy of 0.81 was estimated from the combined heterogeneous data. This study is a first attempt to develop methods and approaches tocombine heterogeneous individual animal data on proxies for CH4 to build robust models for prediction of CH4 emissions across diverse production systems and environments. The methodology outlined here can be extended to combining heterogeneous data, pedigree information and genome-wide dense marker information for estimation of genetic parameters and prediction of breeding values for traits related to dairy system CH4 emissions.
Disciplines :
Animal production & animal husbandry
Author, co-author :
Negussie, E.;  Biometrical Genetics, Natural Resources Institute (Luke) - Finland
Gonzàlez Recto, O.;  INIA - Spain
de Haas, Y.;  ABGC-WUR, Wageningen, The Netherlands
Gengler, Nicolas  ;  Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Ingénierie des productions animales et nutrition
Soyeurt, Hélène  ;  Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Modélisation et développement
Peiren, N.;  ILVO - Belgium
Pszczola, M.;  Poznan University, Poznan, Poland
Garnsworthy, P.;  University of Nottingham, Nottingham, UK
Battagin, M.;  Roslin Institute, Edinburgh, UK
Bayat, A.;  Biometrical Genetics, Natural Resources Institute (Luke), Finland
Lassen, J.;  Viking Genetics Randers, Denmark
Yan, T.;  AFBI, Hillsborough, UK
Boland, T.;  University College Dublin, Dublin, Ireland
Kuhla, B.;  Leibniz Institute (FBN), Dummerstorf, Germany
Strabel, T.;  Poznan University, Poznan, Poland
Schwarm, A.;  ETH, Zürich, Switzerland
Vanlierde, Amélie ;  CRA-W, Gembloux, Belgium > Doct. sc. agro. & ingé. biol.
Biscarini, F.
More authors (8 more) Less
Language :
English
Title :
Combining heterogeneous across-country data for prediction of enteric methane from proxies in dairy cattle
Publication date :
February 2018
Event name :
World Congress on Genetics Applied to Livestock Production (WCGALP)
Event date :
February 2018
Audience :
International
Main work title :
Proceedings of the World Congress on Genetics Applied to Livestock Production
Peer reviewed :
Peer reviewed
Available on ORBi :
since 13 May 2019

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