Effects of genetic line and feeding system on methane emissions from dairy systems

Estimates of the genetic contribution to methane emission in dairy cows: a meta-analysis

The present study aimed to perform a meta-analysis using the three-level model to integrate published estimates of genetic parameters for methane emission traits [methane yield (METY), methane intensity (METINT), and methane production (METP)] in dairy cows. Overall, 40 heritability estimates and 32 genetic correlations from 17 papers published between 2015 and 2021 were used in this study. The heritability estimates for METY, METINT, and METP were 0.244, 0.180, and 0.211, respectively. The genetic correlation estimates between METY and METINT with corrected milk yield for fat, protein, and or energy (CMY) were negative (- 0.433 and - 0.262, respectively). Also, genetic correlation estimates between METINT with milk fat and protein percentages were 0.254 and 0.334, respectively. Although the genetic correlation estimate of METP with daily milk yield was 0.172, its genetic correlation with CMY was 0.446. All genetic correlation estimates between METP with milk fat and protein yield or percentage ranged from 0.005 (between METP-milk protein yield) to 0.185 (between METP-milk protein percentage). The current meta-analysis confirmed the presence of additive genetic variation for methane emission traits in dairy cows that could be exploited in genetic selection plans.

Estimating the environmental impact of dairy cattle breeding programs through emission intensity

A recently developed methodological approach for determining the greenhouse gas emissions impact of national breeding programs was applied to measure the effects of current and future breeding goals on the emission intensity (EI) of the Canadian dairy industry. Emission intensity is the ratio of greenhouse gas outputted in comparison to the product generated. Traits under investigation affected EI by either decreasing the direct emissions yield (i.e. increasing feed performance), changing herd structure (i.e. prolonging herd life) or through the dilution effect of increased production (i.e. increasing fat yield). The intensity value (IV) of each trait, defined as the change in emissions' intensity per unit change in each trait, was calculated for each of the investigated traits. The IV trend of these traits was compared for the current and prospective selection index, as well as for a system with and without quota (the supply management policy designed to prevent overproduction). The overall EI of the average genetic merit Canadian dairy herd per breeding female was 5.07 kg CO₂eq/kg protein equivalent output. The annual reduction in EI due to the improvement of production traits was -0.027, -0.018 and -0.006 for fat, protein and milk other solids, respectively. The functional traits, herd life and mastitis resistance, had more modest effects (-0.008 and -0.001, respectively). These results are consistent with international studies that identified traits related to production, survival, health and fertility as having the largest impact on the environmental footprint of dairy cattle. Overall, the dairy industry is becoming more efficient by reducing its EI through selection of environmentally favorable traits, with a 1% annual reduction of EI in Canada.

Determining the economic value of daily dry matter intake and associated methane emissions in dairy cattle

Feed represents a substantial proportion of production costs in the dairy industry and is a useful target for improving overall system efficiency and sustainability. The objective of this study was to develop methodology to estimate the economic value for a feed efficiency trait and the associated methane production relevant to Canada. The approach quantifies the level of economic savings achieved by selecting animals that convert consumed feed into product while minimizing the feed energy used for inefficient metabolism, maintenance and digestion. We define a selection criterion trait called Feed Performance (FP) as a 1 kg increase in more efficiently used feed in a first parity lactating cow. The impact of a change in this trait on the total lifetime value of more efficiently used feed via correlated selection responses in other life stages is then quantified. The resulting improved conversion of feed was also applied to determine the resulting reduction in output of emissions (and their relative value based on a national emissions value) under an assumption of constant methane yield, where methane yield is defined as kg methane/kg dry matter intake (DMI). Overall, increasing the FP estimated breeding value by one unit (i.e. 1 kg of more efficiently converted DMI during the cow's first lactation) translates to a total lifetime saving of 3.23 kg in DMI and 0.055 kg in methane with the economic values of CAD $0.82 and CAD $0.07, respectively. Therefore, the estimated total economic value for FP is CAD $0.89/unit. The proposed model is robust and could also be applied to determine the economic value for feed efficiency traits within a selection index in other production systems and countries.

Consequences of genetic selection for environmental impact traits on economically important traits in dairy cows

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.

Is there a relationship between genetic merit and enteric methane emission rate of lactating Holstein-Friesian dairy cows?

The present study was undertaken to examine the effect of cow genetic merit on enteric methane (CH4) emission rate. The study used a data set from 32 respiration calorimeter studies undertaken at this Institute between 1992 and 2010, with all studies involving lactating Holstein-Friesian dairy cows. Cow genetic merit was defined as either profit index (PIN) or profitable lifetime index (PLI), with these two United Kingdom genetic indexes expressing the expected improvement in profit associated with an individual cow, compared with the population average. While PIN is based solely on milk production, PLI includes milk production and a number of other functional traits including health, fertility and longevity. The data set had a large range in PIN (n=736 records, -£30 to +£63) and PLI (n=548 records, -£131 to +£184), days in milk (18 to 354), energy corrected milk yield (16.0 to 45.6 kg/day) and CH(4) emission (138 to 598 g/day). The effect of cow genetic merit (PIN or PLI) was evaluated using ANOVA and linear mixed modelling techniques after removing the effects of a number of animal and diet factors. The ANOVA was undertaken by dividing each data set of PIN and PLI into three sub-groups (PIN:£15, PLI:£67) with these being categorised as low, medium and high genetic merit. Within the PIN and PLI data sets there was no significant differences among the three sub-groups in terms of CH(4) emission per kg feed intake or per kg energy corrected milk yield, or CH(4) energy (CH(4)-E) output as a proportion of energy intake. Linear regression using the whole PIN and PLI data sets also demonstrated that there was no significant relationship between either PIN or PLI, and CH(4) emission per kg of feed intake or CH(4)-E output as a proportion of energy intake. These results indicate that cow genetic merit (PIN or PLI) has little effect on enteric CH(4) emissions as a proportion of feed intake. Instead enteric CH(4) production may mainly relate to total feed intake and dietary nutrient composition.

Invited review: Enteric methane in dairy cattle production: quantifying the opportunities and impact of reducing emissions

Many opportunities exist to reduce enteric methane (CH4) and other greenhouse gas (GHG) emissions per unit of product from ruminant livestock. Research over the past century in genetics, animal health, microbiology, nutrition, and physiology has led to improvements in dairy production where intensively managed farms have GHG emissions as low as 1 kg of CO2 equivalents (CO2e)/kg of energy-corrected milk (ECM), compared with >7 kg of CO2 e/kg of ECM in extensive systems. The objectives of this review are to evaluate options that have been demonstrated to mitigate enteric CH4 emissions per unit of ECM (CH4/ECM) from dairy cattle on a quantitative basis and in a sustained manner and to integrate approaches in genetics, feeding and nutrition, physiology, and health to emphasize why herd productivity, not individual animal productivity, is important to environmental sustainability. A nutrition model based on carbohydrate digestion was used to evaluate the effect of feeding and nutrition strategies on CH4/ECM, and a meta-analysis was conducted to quantify the effects of lipid supplementation on CH4/ECM. A second model combining herd structure dynamics and production level was used to estimate the effect of genetic and management strategies that increase milk yield and reduce culling on CH4/ECM. Some of these approaches discussed require further research, but many could be implemented now. Past efforts in CH4 mitigation have largely focused on identifying and evaluating CH4 mitigation approaches based on nutrition, feeding, and modifications of rumen function. Nutrition and feeding approaches may be able to reduce CH4/ECM by 2.5 to 15%, whereas rumen modifiers have had very little success in terms of sustained CH4 reductions without compromising milk production. More significant reductions of 15 to 30% CH4/ECM can be achieved by combinations of genetic and management approaches, including improvements in heat abatement, disease and fertility management, performance-enhancing technologies, and facility design to increase feed efficiency and life-time productivity of individual animals and herds. Many of the approaches discussed are only partially additive, and all approaches to reducing enteric CH4 emissions should consider the economic impacts on farm profitability and the relationships between enteric CH4 and other GHG.

The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems

This study compared the environmental impact of a range of dairy production systems in terms of their global warming potential (GWP, expressed as carbon dioxide equivalents, CO(2)-eq.) and associated land use, and explored the efficacy of reducing said impact. Models were developed using the unique data generated from a long-term genetic line × feeding system experiment. Holstein-Friesian cows were selected to represent the UK average for milk fat plus protein production (control line) or were selected for increased milk fat plus protein production (select line). In addition, cows received a low forage diet (50% forage) with no grazing or were on a high forage (75% forage) diet with summer grazing. A Markov chain approach was used to describe the herd structure and help estimate the GWP per year and land required per cow for the 4 alternative systems and the herd average using a partial life cycle assessment. The CO(2)-eq. emissions were expressed per kilogram of energy-corrected milk (ECM) and per hectare of land use, as well as land required per kilogram of ECM. The effects of a phenotypic and genetic standard deviation unit improvement on herd feed utilization efficiency, ECM yield, calving interval length, and incidence of involuntary culling were assessed. The low forage (nongrazing) feeding system with select cows produced the lowest CO(2)-eq. emissions of 1.1 kg/kg of ECM and land use of 0.65 m(2)/kg of ECM but the highest CO(2)-eq. emissions of 16.1t/ha of the production systems studied. Within the herd, an improvement of 1 standard deviation in feed utilization efficiency was the only trait of those studied that would significantly reduce the reliance of the farming system on bought-in synthetic fertilizer and concentrate feed, as well as reduce the average CO(2)-eq. emissions and land use of the herd (both by about 6.5%, of which about 4% would be achievable through selective breeding). Within production systems, reductions in CO(2)-eq. emissions per kilogram of ECM and CO(2)-eq. emissions per hectare were also achievable by an improvement in feed utilization. This study allowed development of models that harness the biological trait variation in the animal to improve the environmental impact of the farming system. Genetic selection for efficient feed use for milk production according to feeding system can bring about reductions in system nutrient requirements, CO(2)-eq. emissions, and land use per unit product.