RCUK-CIAT Newton Fund Advancing sustainable forage-based livestock production systems using multi-source remote sensing and social science approaches

Agriculture and livestock production have historically been one of the major components of Colombian economic development and it is one of the top countries in the world in terms of greatest agricultural land expansion potential. Approximately 34% of the land area (~40m Ha) is used for livestock activities, with most pastures dedicated to extensive grazing systems. Agriculture is a critical source of employment in rural Colombia and is one of the sectors most affected by climate and climate change and where solutions to key challenges affecting the productivity and sustainability of pastures and the livestock sector are required. This collaborative project between University of Glasgow (UofG) University of Bristol (UofB) and CIAT will bring together cross-disciplinary perspectives and methodologies to develop RS-based approaches for forage monitoring and management at local and regional levels. The specific objectives are to: 1) develop co-designed work-flows for acquiring, processing and analysis of multi-dimensional multispectral and radar data for trial sites at CIAT headquarters; 2) investigate operational functions for extraction of grass growth and quality metrics from combined airborne/spaceborne/in situ datasets and develop a framework for a forage management decision support system; and 3) investigate methodologies for engagement with smallholders and determine attitudes to and potential barriers of incorporation of such technologies and their outputs into practice. The project will deliver new data to establish a baseline understanding of the capabilities of multi-source remote sensing and predictive analysis tools to provide reliable and consistent information on forage quantity and quality and smallholder capability and willingness to adopt such technologies. Outputs from the project will directly inform forage production management activities and will be communicated to stakeholders via a project website, an end-of-project workshop, and through promotion at further dissemination events run by CIAT.

Overall, outputs from this project will lead to improved information, processes, and in time, decision support services capable of generating efficiencies in spending private money and creating potential employment in areas of forage-production management and remote sensing (RS)-driven data analytics. Broader impacts include reducing poverty and sustaining farmer livelihoods in rural communities most affected by crop damage and land degradation through the incorporation of environmental and RS-driven data analytics in an effective decision support system. It will also facilitate the decision making for important national endeavours related with mitigation of greenhouse gases (GHG) committed at the COP in the Nationally Determined Contribution (NDC). One vehicle to achieve the GHG emission reductions is the National Appropriate Mitigation Action (NAMA) of the cattle sector and its Monitoring Reporting and Verification (MRV) system where the big gaps are still to be solved in terms of capturing information in a rapid manner in remote areas. CIAT researchers are working in these areas together with national partners and see multi-source remote sensing as an excellent technology to reach Colombian goals in this matter. Combining UofG expertise in radar and multispectral remote sensing and UofB expertise in social sciences with CIAT`s knowledge of local forage production systems in Colombia will lead to new innovations in combined aerial and satellite-based smart agriculture applications and progress ease of access to the best possible and timely information for targeted decision making. The collaboration will enhance the independent knowledge, scientific and technical expertise of not only UofG, UofB and CIAT colleagues, but the wider scientific, political and rural communities through smallholder engagement and an end-of-project workshop in March 2019. The project will directly contribute to advancing on-going research of the CIAT phenotyping team and the enhancement of the Phenomics Platform, facilitating the evaluation and diagnosis processes of forages with the overall objective of contributing to eco-efficient agriculture.