This study aims to assess if AKIS are effectively disseminating integrated soil fertility management (ISFM) knowledge by comparing results from two sites in Kenya and Ghana, which differ in the uptake of ISFM. Social network measures and statistical methods were employed using data from key formal actors and farmers. Their results suggest that the presence of weak knowledge ties is important for the awareness of ISFM at both research sites.
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.
Development education, it combines various methodologies of education to promoting knowledge, so that agriculture sector needs development education to revive productivity through agriculture. ICT (Information communication technology) help to provide knowledge to the door step of farmers.
This report aims to o estimate the current use of machinery in rice and bananas value chains; To establish determinants of mechanization in rice and bananas along the entire value chains; and estimate the effects of the determinants on mechanization levels. This study therefore seeks to identify factors that influence
mechanization levels for rice and bananas value chains. The findings from this study will help provide technical and policy recommendations for the improvement of not only the rice and banana value chains but the entire agriculture sector
This report assesses trends in investments, human resource capacity, and outputs in agricultural research in SSA, excluding the private (for-profit) sector. The analysis uses information collected by Agricultural Science and Technology Indicators (ASTI)—led by the International Food Policy Research Institute (IFPRI) within the portfolio of the CGIAR Research Program on Policies, Institutions, and Markets (PIM).
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.
Innovation platforms are equitable, dynamic spaces designed to bring heterogeneous actors together to exchange knowledge and take action to solve a common problem. Although innovation platforms are being set up to attain collectively defined development objectives, there are limited methods and tools available using quantitative data to evaluate whether they are effective.
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.
This decision guide is intended to help extension professionals and their organizations make informed decisions about which extension method and approach to use for providing information, technologies and services to rural producers and to facilitate interactions and knowledge flow. Expected users include field-based rural advisors, extension managers and programme planners.
- 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.