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

• 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: Milk; methane; fatty acids; infrared spectrophotometry; heritability; cows
• Online Access: http://hdl.handle.net/11006/176
• ISSN: 1370-6233; 1780-4507

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.