CLEANED training kicked off in Kigali Rwanda

CLEANED training kicked off in Kigali Rwanda

Written by Jessica Mukiri

A team from the Tropical Forages Program at CIAT has been working on CLEANED*, an Excel-based ex-ante tool that assesses the environmental impacts of livestock, over the past four years. The tool’s first version was published at the beginning of 2018 and can be found here. It looks at greenhouse gas emissions, biodiversity loss, soil health and economic impacts. The CLEANED tool was developed for use in ongoing innovation processes in value chains. It helps decision-makers understand the environmental impacts of intensification and develop sustainable livestock intensification plans that mitigate negative impacts and enhance positive ones.

Did you know?

CLEANED stands for Comprehensive Livestock Environmental Assessment for Improved Nutrition, a Secured Environment and Sustainable Development.

The team has already used the tool to conduct the study Feeding a productive dairy cow in western Kenya: environmental and socio-economic impacts in Western Kenya in collaboration with Send a Cow Kenya, Kenya Agriculture and Livestock Research Organization together with ETH Zurich. Other case studies include Nicaragua and Tanzania.

The goal for this training is to strengthen technical capacity for agriculture stakeholders and for them to use this tool for improved decision making in the agriculture development sector with a focus on livestock systems.

The first training session was Nov. 14-16 in Kigali, Rwanda. Participants included researchers, livestock development officers and university lecturers from Tanzania Livestock Research Institute (TALIRI), Send a Cow Rwanda, Uganda and Burundi, University of Rwanda, Rwanda Agricultural Board (RAB), National Livestock Resources Research Institute (NaLIRRI) from Uganda and CIAT Tanzania.

The training aimed at getting participants to understand the tool and how it can be used. During the training, they modelled a livestock enterprise related to work in their fields. They also generated different scenarios to mimic technologies of interest to improve productivity and environmental efficiencies in their systems. The participants expressed the importance of understanding the environmental impacts of livestock enterprises and the challenges that can be faced trying to calculate these different impacts on the ground. The tool works with minimal data that can be easily collected using expert opinion, secondary data and household surveys.

“The application of the tool in my routine research work was really exciting”

Kayondo Siraj Ism

Researcher, NALIRRI

After the three-day training, the participants presented the livestock enterprises they had developed, such as an intensive dairy system in Arumeru Tanzania, smallholder crop-livestock systems in Rwamagana district in Rwanda and a smallholder system in Njombe in Tanzania. The groups modelled several scenarios from improving the dairy cow genetics and feed basket items to improving productivity and natural resource efficiencies. The participants were excited to see how fast the tool generates results and the potential the tool had in policymaking, proposal development and extension service to farmers.

One of the Groups Presentations

I will be using it for teaching the course of Livestock and Environment Interactions as tools that can be on the Environmental Assessment of Livestock intensification/interventions on Environment.

Gilbert Mutoni

Lecturer, University of Rwanda

The training ended with the participants giving feedback on ways the tool could be improved such as including the option of a bio-digester as a means of manure management, which is present throughout the region, to incorporate monastic species such as pigs to the tool as well as a tool to take into account children’s calorie intake when it comes to milk consumption.

The participants also discussed potential ways we could collaborate with them in future projects with the CIAT team offering support through technical backstopping of any potential research.