**Contents**


#### **Alexandra Sintori, Irene Tzouramani and Angelos Liontakis**


## **About the Special Issue Editors**

**Mizeck Chagunda** is a Professor and Chair of Animal Breeding and Husbandry in the Tropics and Subtropics at the University of Hohenheim, Germany. Mizeck earned his doctorate degree in Animal Breeding and Genetics from the University of Gottingen, ¨ Germany, after obtaining his MSc and BSc from the University of Malawi. He has previously worked at the University of Malawi, Aarhus University in Denmark, and SRUC (Scotland's Rural College) in Scotland. Mizeck's research interests are in improving biological and economic efficiency in livestock production systems. He achieves this through investigating novel phenotypes and difficult-to-measure traits, the environmental impact of livestock, and the use of technologies and data-driven decision-support systems, optimising animal breeding strategies and breeding goals. This includes methods for quantifying greenhouse gases (GHGs), applying life cycle analysis (LCA) and techniques for measuring methane from breath in ruminants. As an example of direct industry-relevant research, Mizeck was part of the BIOSENS team (Aarhus University) that developed and tested models that ended up as embedded software for HerdNavigator-R .

**Peter Løvendahl** is a Senior Scientist working at Aarhus University (AU-Foulum, Denmark), Center for Quantitative Genetics and Genomics. Peter earned his MSc and later PhD at the Royal Veterinary and Agricultural University in Copenhagen, now a part of Copenhagen University. Peter has studied phenotypic and genetic variation in a wide range of traits in dairy cattle and pigs. The range of traits has included milk production, endocrine regulation, behaviour, milking behaviour, maternal behaviour and aggression in sows, fertility traits in dairy cows, feed efficiency, methane emission in cows, and metagenomic aspects of ruminant digestion. Peter has focused on improved phenotyping as a means of improving genetic progress in dairy cattle and pig production, especially focusing on methods for automated recording of new traits of possible use in genetic selection. Peter has been involved in numerous collaborative projects with industry partners, including the development of new managemen<sup>t</sup> tools for dairy farming.

## **Preface to "Quantification and Mitigation Strategies to Reduce Greenhouse Gas Emissions from Livestock Production Systems"**

#### **Mizeck Chagunda 1 and Peter Løvendahl 2**

1 Animal Breeding and Husbandry in the Tropics and Subtropics, University of Hohenheim, 70599 Stuttgart, Germany

2 Department of Molecular Biology and Genetics, Faculty of Science and Technology, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark

In recent years, the evidence of change in the global climate system has been unequivocal, and climate change has become a growing international concern. Further, it is well-established that the release of greenhouse gases (GHGs) predominantly derived from human activities is a major contributing factor to most of the observed climate change.

As the largest land-use system on earth, the livestock sector occupies 30% of the world's ice-free surface (Herrero et al., 2013). On the one hand, livestock supply chains are estimated to account for 14.5% of total human-induced GHG emissions (Gerber et al., 2013). In livestock value chains, GHG emissions arise from processes both on and off the farm, and these emissions include methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2). On the other hand, livestock supply chains contribute to 40% of global agricultural gross domestic product, providing income for more than 1.3 billion people and nourishment for at least 800 million food-insecure people, all the while using vast areas of rangelands, one-third of the freshwater, and one-third of global cropland as feed. Different initiatives are being taken to reduce GHG emissions. For example, the European Union has committed itself to reducing its GHG emissions by 20% by the year 2020, relative to 1990 levels. Different countries and groups of countries have different targets. However, it is important to undertake initiatives that can reduce GHG emissions without compromising livestock productivity. Finding a balance between improving productivity and reducing GHG emissions in livestock systems is crucial for maintaining sustainability in the future. Although primarily focused on ruminant production (Henderson et al., 2017) reported that promising practices for reducing enteric CH4 emissions and for sequestering soil C in grazing lands could abate up to 379 MtCO2-eq yr<sup>−</sup><sup>1</sup> of emissions. This is equivalent to 11% of annual global ruminant GHG emissions. (Henderson et al., 2017). Efficient agricultural practices are key to reducing greenhouse gas emissions. These practices can be achieved through several aspects of livestock production. For example, livestock genetic improvement, changes in feeding strategies, nutritional improvement, disease control and animal health improvement, and improvement in animal welfare and general husbandry. However, care ought to be taken as a focus on reducing emissions in one particular part of a system may result in an inherent increase elsewhere in the system.

Technical solutions to reduce GHG emissions have been and continue to be extensively researched. Globally, different research groups are investigating different components in this regard on an ongoing basis. Although some of this information has been previously reported elsewhere, new knowledge is being generated and more effective strategies are being developed. Accompanying these efforts to reduce GHG emissions should be efforts to develop methods and procedures for quantifying GHG emissions in different livestock systems. Although metabolic calorimetric chambers have been considered the gold standard for quantifying GHG in ruminants for some time, they are expensive, require highly skilled technicians, and are not normally compatible for use in practical animal production environments where the majority of animals are found. This Special Issue aimed to put together contributions in these two broad but related areas: 1) measurement techniques and protocols, use of proxies, and methodological opportunities and challenges including uncertainty in quantification of GHG emissions from livestock systems; and 2) methods, techniques, and strategies for reducing GHG emissions from livestock production systems. These contributions were sought as both reviews and original research. After manuscripts went through the normal peer review process, where some were accepted and others rejected, a total of 10 papers ended up in the Special Issue. Two papers were on quantification while eight were on mitigation strategies for GHGs. In terms of species (and subspecies), papers covered dairy cattle and dairy goats, beef cattle, goats, and sheep.

Papers on the quantification of GHG focused on novel high-throughput non-invasive methods that have the potential for not only generating the much-needed data upon which evidence-based interventions can be developed, but also methods that can be deployed in more extensive production systems. By comparing these novel techniques to traditional techniques, both papers argue that there is sufficient correlation in the data from the different methods tested. These include methods such as the portable and innovative Laser Methane DetectorTM (Chagunda et al., 2009), and the automatic breath sampler (Lassen et al., 2010). Data from these different measuring methods can be combined for either international genetic improvement studies or for providing the much-needed framework for combining data that would inform some mitigation strategies (Garnsworthy et al., 2019 and Jagoba et al., 2019). However, they warn that the joint use of different GHG measuring methods should be considered only if sources of disagreement—which result from different between-subject and within-subject variabilities—are identified and corrected for (Jagoba et al., 2019).

The first paper, on methane emissions mitigation, lays the foundation by initially considering the effect of and environmental stresses that are common factors which negatively influence rumen function and enteric methane (CH4) emission (Pragna et al., 2018). This is demonstrated using the goat. Further, Pragna et al. (2018) highlight the three mechanisms by which enteric CH4 can be reduced: targeting the endproduct of digestion to propionate, providing an alternate hydrogen sink, and selectively inactivating rumen methanogens. The strategies that can be implemented to mitigate enteric CH4 include nutritional interventions, managemen<sup>t</sup> strategies, and application of advanced biotechnological tools (Pragna et al., 2018). The next four papers on mitigation strategies demonstrate some results from experiments on how some specific nutritional interventions may reduce methane emissions from ruminates. First, is the use of dietary supplements of Moringa oleifera in lactating dairy cows. The second paper investigates the effects of tea saponin in crossbred dorper ewes while the third is on the use of desmanthus in beef cattle (Dong et al., 2019; Liu et al., 2019; Suybeng et al., 2019). The fourth discusses the effect of encapsulated nitrate and microencapsulated blend of essential oils in beef steers (Alemu et al., 2019).

The next group of two papers deals with GHG emissions reduction through managemen<sup>t</sup> interventions. The first paper in this group deals with the effect of dietary forage proportion in Holstein heifers at various growth stages (Dong et al., 2019) while the other deals with the effect of changes in grazed farmlets for dairy cattle (Van der Weerden et al., 2018). These two papers highlight the fact that improved livestock managemen<sup>t</sup> systems are a key driver not only to reducing methane emissions but also reducing nitrogen leaching which in itself also contributes to GHG emissions. The data generated from these managemen<sup>t</sup> systems can be used to develop regional and national emission inventories and mitigation approaches (Dong et al., 2019; Van der Weerden et al., 2018).

Last, but by far not the least, this Special Issue closes with a paper discussing the abatement potential and cost of different GHG mitigation strategies in dairy goat farming systems (Sintori et al., 2019). 
