Digitalization and internet use are transforming every aspect of our lives. Digital technologies are profoundly changing how we grow food, pack it, transport it and even shop for food. Digitalization and use of digital data, applications, and platforms are opening new possibilities for developing and restructuring the agrifood system. Digital agriculture is turning to digitalizing agrifood, rural economy, and rural societies. This report introduces the FAO Digital Village Initiative, which aims to facilitate through knowledge and information.
Year 1 activities were mainly on establishment of the project team at the global and country levels. A Partnership Agreement between AGRINATURA-EEIG and FAO was formalized and signed, and practical coordination mechanisms established. A Specific Power of Attorney between AGRINATURA-EEIG members within CDAIS was created, agreed and signed by all members, serving as the consortium agreement among members.
The 2016 Global Agricultural Productivity Report advocates policies and innovations in five key areas to help the agriculture and food sectors manage uncertain seasons of fluctuating business cycles and climate change, while fostering competitiveness today and sustainable growth tomorrow.
IFPRI’s flagship report reviews the major food policy issues, developments, and decisions of 2016, and highlights challenges and opportunities for 2017 at the global and regional levels. This year’s report looks at the impact of rapid urban growth on food security and nutrition, and considers how food systems can be reshaped to benefit both urban and rural populations. Drawing on recent research, IFPRI researchers and other distinguished food policy experts consider a range of timely questions:
■ What do we know about the impacts of urbanization on hunger and nutrition?
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
This study introduces a framework for managing information flow in innovation systems. An organisation's capacity to receive information, to share it with others and to learn from it is assumed to be the key factor that shapes the flow patterns and, hence, the performance of the innovation system concerned. The framework is applied to characterise the information structure underlying the agricultural innovation system of Azerbaijan and to develop an information strategy for the system to accelerate the information flow.
Technological innovations have driven economic development and improvement in living conditions throughout history. However, the majority of smallholder farmers in sub‐Saharan Africa have seldom adopted or used science‐based technological innovations. Consequently, several scholars have been persistently questioning the effectiveness of intervention models in smallholder agriculture.
- 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.
ICARDA scientists along with CGIAR LIVESTOCK developed a cloud-based genetic database platform to boost breed improvement programs in community-based livestock breeding programs in Ethiopia.
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.