Assessing variability of literature based methane indicator traits in a large dairy cow population

Description of the subject. Dairy production is identified as a major source of methane (CH4) emissions. Selective breeding represents one method for mitigating CH4 emissions but practical and cheap ways to measure this trait are not currently available. In the present study, four CH4 indicator trai...

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Main Authors: Kandel, PB., Gengler, N., Soyeurt, H.
Format: Article
Language:English
Published: Presses Agronomiques de Gembloux 2015-01-01
Series:Biotechnologie, Agronomie, Société et Environnement
Subjects:
Online Access:http://hdl.handle.net/11006/176
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spelling doaj-7c47853e87574891b65c6ebc70be7f4e2020-11-24T23:55:32ZengPresses Agronomiques de GemblouxBiotechnologie, Agronomie, Société et Environnement1370-62331780-45072015-01-011911119Assessing variability of literature based methane indicator traits in a large dairy cow populationKandel, PB.Gengler, N.Soyeurt, H.Description of the subject. Dairy production is identified as a major source of methane (CH4) emissions. Selective breeding represents one method for mitigating CH4 emissions but practical and cheap ways to measure this trait are not currently available. In the present study, four CH4 indicator traits based on milk fatty acid (FA) contents were referenced from the literature. Objectives. The aim of the study was to use these literature CH4 indicators for assessing the variability of methane emissions emitted by dairy cows. Method. Literature CH4 indicator traits were originally defined based on the measurements of FA content by gas chromatography. However, these measurements were not available for all the available cows in our studied population. A sample of 602 gas chromatographic analyses was therefore used to develop a calibration equation for predicting the literature CH4 indicators based on milk mid-infrared (MIR) spectra. This spectral information was available for all the studied cows. Then, in a second step, in order to predict the literature CH4 indicator traits, the developed MIR prediction equations were applied to the 604,028 recorded spectral data collected between 2007 and 2011 for 70,872 cows in their first three lactations. Genetic parameters for these traits were then estimated using single trait test-day random regression animal models. Results. The predicted MIR literature CH4 estimates were in the expected range from 350 ± 40 to 449 ± 65 g per day. The averaged predicted MIR CH4 emission (g per day) increased from the beginning of lactation, reached the highest level at the peak of lactation and then decreased towards the end of lactation. The average daily heritability values were 0.29-.35, 0.26-.40, and 0.22-.37 for the different studied CH4 indicators for the first three lactations, respectively. The largest differences between the estimated breeding values of sires that had daughters in production eructing the highest and the lowest CH4 content was 24.18, 29.33 and 27.77 kg per lactation for the first three parities. Low negative correlations were observed between CH4 indicator traits and milk yield. Positive genetic correlations were estimated between CH4 indicator traits and milk fat and protein content. Conclusions. This study showed the feasibility of using MIR spectrometry results to predict fatty acid derived CH4 indicator traits developed in the literature. Moreover, the estimated genetic parameters of these traits suggested a potential phenotypic and genetic variability of the daily quantity of CH4 eructed by Holstein dairy cows.http://hdl.handle.net/11006/176Milkmethanefatty acidsinfrared spectrophotometryheritabilitycows
collection DOAJ
language English
format Article
sources DOAJ
author Kandel, PB.
Gengler, N.
Soyeurt, H.
spellingShingle Kandel, PB.
Gengler, N.
Soyeurt, H.
Assessing variability of literature based methane indicator traits in a large dairy cow population
Biotechnologie, Agronomie, Société et Environnement
Milk
methane
fatty acids
infrared spectrophotometry
heritability
cows
author_facet Kandel, PB.
Gengler, N.
Soyeurt, H.
author_sort Kandel, PB.
title Assessing variability of literature based methane indicator traits in a large dairy cow population
title_short Assessing variability of literature based methane indicator traits in a large dairy cow population
title_full Assessing variability of literature based methane indicator traits in a large dairy cow population
title_fullStr Assessing variability of literature based methane indicator traits in a large dairy cow population
title_full_unstemmed Assessing variability of literature based methane indicator traits in a large dairy cow population
title_sort assessing variability of literature based methane indicator traits in a large dairy cow population
publisher Presses Agronomiques de Gembloux
series Biotechnologie, Agronomie, Société et Environnement
issn 1370-6233
1780-4507
publishDate 2015-01-01
description Description of the subject. Dairy production is identified as a major source of methane (CH4) emissions. Selective breeding represents one method for mitigating CH4 emissions but practical and cheap ways to measure this trait are not currently available. In the present study, four CH4 indicator traits based on milk fatty acid (FA) contents were referenced from the literature. Objectives. The aim of the study was to use these literature CH4 indicators for assessing the variability of methane emissions emitted by dairy cows. Method. Literature CH4 indicator traits were originally defined based on the measurements of FA content by gas chromatography. However, these measurements were not available for all the available cows in our studied population. A sample of 602 gas chromatographic analyses was therefore used to develop a calibration equation for predicting the literature CH4 indicators based on milk mid-infrared (MIR) spectra. This spectral information was available for all the studied cows. Then, in a second step, in order to predict the literature CH4 indicator traits, the developed MIR prediction equations were applied to the 604,028 recorded spectral data collected between 2007 and 2011 for 70,872 cows in their first three lactations. Genetic parameters for these traits were then estimated using single trait test-day random regression animal models. Results. The predicted MIR literature CH4 estimates were in the expected range from 350 ± 40 to 449 ± 65 g per day. The averaged predicted MIR CH4 emission (g per day) increased from the beginning of lactation, reached the highest level at the peak of lactation and then decreased towards the end of lactation. The average daily heritability values were 0.29-.35, 0.26-.40, and 0.22-.37 for the different studied CH4 indicators for the first three lactations, respectively. The largest differences between the estimated breeding values of sires that had daughters in production eructing the highest and the lowest CH4 content was 24.18, 29.33 and 27.77 kg per lactation for the first three parities. Low negative correlations were observed between CH4 indicator traits and milk yield. Positive genetic correlations were estimated between CH4 indicator traits and milk fat and protein content. Conclusions. This study showed the feasibility of using MIR spectrometry results to predict fatty acid derived CH4 indicator traits developed in the literature. Moreover, the estimated genetic parameters of these traits suggested a potential phenotypic and genetic variability of the daily quantity of CH4 eructed by Holstein dairy cows.
topic Milk
methane
fatty acids
infrared spectrophotometry
heritability
cows
url http://hdl.handle.net/11006/176
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