- Lack of automated data capture systems affects timely feedback and accuracy of information for breeding decisions.
- CGIAR researchers and national research partners have adopted a digital genetic database, Dtreo, that is enhancing genetic improvement by providing timely and accurate animal ranking information to communities.
- Dtreo is a digital genetic database that is flexible and easy to use, that allows users to capture and save data offline. Data is uploaded to the database once an internet connection has been established.

Digital platform enhances genetic progress in community-based sheep and goat breeding programs in Ethiopia:

- Up-to-date information on estimated breeding values and animal rankings is directly channeled to breeder organizations and used for selection decisions.

- The digital platform motivated use of more complicated evaluation models which improve accuracy of breeding values considerably.

- When upscaled, this will help create a permanent multi-country source of information.

Ethiopia is a home for diverse livestock including small ruminants and has the largest population of livestock in Africa. Livestock is kept for export earnings, food security, economic growth, poverty reduction and employment opportunities. Small ruminants are an important resource for livelihood and food security improvement serving as sources of food, income, risk mitigation, property security, monetary saving, investment, and providing other social and cultural benefits.

IFAD’s technical assistance programme INSURED (Insurance for rural resilience and economic development) has been building knowledge about how to strengthen women producers’ access to climate risk insurance. Working with partners, INSURED supported research, and fieldwork in Ethiopia including group discussions with smallholders about insurance options. A checklist was drawn up for insurance designers and implementers to help them reach out to women every step of the way.

This report describes the findings of the country study carried out for the design of IFAD project on Restoration of Landscapes and Livelihoods (ROLL P) in Lesotho. Following an IFAD designed project to develop an integrated approach for designing climate-smart and nutrition-sensitive investments, support was provided to undertake a thorough situation analysis for climate, nutrition and their interlinkages and to identify potential pathways and interventions to achieve both climate action and nutrition outcomes.

This report describes the findings of the country study carried out for the design of IFAD Smallholder Agriculture Cluster Project (SACP) in Zimbabwe. Following an IFAD designed project to develop an integrated approach for designing climate-smart and nutrition-sensitive investments, support was provided to undertake a thorough situation analysis for climate, nutrition and their interlinkages and to identify potential pathways and interventions to achieve both climate action and nutrition outcomes.

This case study presents an analysis undertaken for the IFAD-funded Agropastoral Value Chains Project in the Governorate of Médenine, Tunisia. High-resolution imagery makes it possible to track the development of roads, buildings, irrigation schemes, and other types of investments. Over 140 km of road constructed or rehabilitated by the project are easily detectable on satellite imagery.

Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.

Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop production and food-availability forecasts. Adapting rainfed agriculture to climate change requires improved harmonization of planting with the onset of rains, and the rising ubiquity of mobile phones in east Africa enables real-time monitoring of this important agricultural decision.