How to work with agricultural innovation systems
by Guadalupe Mata
Agricultural innovation systems (AIS) are networks that contribute to creating, disseminating and using scientific and technological knowledge, as well as coordinating and supporting technological processes. However, the way in which farm projects are designed and research processes are organized has hindered the implementation of these systems. In order to establish guidelines for designing these type of initiatives, MAIZE and the Royal Tropical Institute (KIT) of the Netherlands organized a workshop called “Designing projects focusing on agricultural innovation systems” in Wageningen, the Netherlands, on 11-13 December 2015.
Representatives of the CGIAR, Sustainable Intensification of Maize and Legume Systems for Food Security in Eastern and Southern Africa (SIMLESA), Cereal Systems Initiative for South Asia (CSISA), Intensification of Maize-Legume Systems in the Eastern Province of Zambia (SIMLEZA) and CIMMYT’s MasAgro and Buena Milpa projects attended the workshop in order to exchange knowledge on lessons learned from their own experiences implementing AIS.
One of the main activities of the workshop included defining AIS as having a holistic and integrated focus that includes technology, innovation and methodology. Workshop participants indicated that based on the lessons they had learned, each farmer has unique needs and it’s essential to integrate technologies at the farm level.
Another subject discussed at the workshop was the scaling out of knowledge to other locations and at different system levels. Scaling out depends on establishing strong and complementary partnerships, on the interaction of the actors in the system and on organizational and institutional change. In agricultural research, it is important to get out of the lab and into the field to understand the social drivers behind technology uptake, recognize diversities of needs and understand the reasons behind the adoption – or failure to adopt – certain technologies. Participants completed the workshop with an understanding of the complex, multidimensional aspects of AIS.
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