Data-driven Decision Support Tools for Reducing GHG Emissions from Livestock Production Systems: Overview and Challenges

Abstract

Livestock sector is known for its contribution to environmental pollution. A large portion of anthropogenic emissions is from livestock-related activities, such as animal feeding and manure management. According to the Food and Agriculture Organization of the United Nations, by 2050, 73% increase in livestock product consumption is anticipated. This poses an alarming threat to the environmental sustainability as a proportionate increase in greenhouse gases (GHG) emission is also expected. On the bright side, with the support of appropriate technologies and mitigation strategies, the livestock production sector is capable of achieving a substantial reduction in the level of emissions. A consistent quantitative analysis of emissions and related activities can help in identifying the sensitive areas to intervene. There are several data-driven decision support tools and practices available in literature that aim to help farmers contribute to sustainability. In this work, we provide an overview of the popular data-driven modelling techniques and decision support tools used to estimate GHG emissions from the various livestock farming-related sources. We also discuss the role of decision support tools in various management activities, such as analysing and designing farm systems trials and integrating environmental, technological and economic aspects. Finally, we discuss the challenges and opportunities in using data for decision support in reducing GHG emissions in livestock farming.