Given the search for new solutions to better prepare cities for the future, in recent years, urban agriculture (UA) has gained in relevance. Within the context of UA, innovative organizational and technical approaches are generated and tested. They can be understood as novelties that begin a potential innovation process. This empirical study is based on 17 qualitative interviews in the U.S. (NYC; Philadelphia, PA, USA; Chicago, IL, USA).

In this paper the authors present the development of an analytical framework to study agricultural innovation systems. They divide the agricultural sector into four levels and expand the innovation system approach to study innovation processes.

The European Innovation Partnership for agricultural productivity and sustainability (EIP-AGRI), which can be perceived as a platform based on interaction among farmers, researchers, and advisors/extensionists, represents a useful tool for a better understanding of applied innovation processes.

Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected.

This report is part of the AFRHINET project under the ACP-EU Cooperation Programme in Science and Technology (S&T II). The overall aims of the project are to enhance options for sustainable integration of rainwater harvesting for irrigation through understanding adoption constraints and developing networks for capacity building and technology transfer. The African partners are Addis Ababa University and WaterAid-Ethiopia in Ethiopia, University of Nairobi and ICRAF-Searnet in Kenya, Eduardo Mondlane University in Mozambique, and University of Zimbabwe and ICRISAT-Zimbabwe in Zimbabwe.

This assessment has been conducted over December 2015 to May 2016 under the Powering Agriculture Support Task Order (PASTO). PASTO is funded by USAID and implemented by Tetra Tech ES, Inc. PASTO provides support services to the Powering Agriculture: An Energy Grand Challenge for Development (PAEGC) and its Founding Partners to enable their effective management, monitoring and evaluation of the program.

Crop surface models (CSMs) representing plant height above ground level are a useful tool for monitoring in-field crop growth variability and enabling precision agriculture applications. A semiautomated system for generating CSMs was implemented. It combines an Android application running on a set of smart cameras for image acquisition and transmission and a set of Python scripts automating the structure-from-motion (SfM) software package Agisoft Photoscan and ArcGIS. Only ground-control-point (GCP) marking was performed manually.

The European Innovation Partnership for agricultural productivity and sustainability (EIP-AGRI), which can be perceived as a platform based on interaction among farmers, researchers, and advisors/extensionists, represents a useful tool for a better understanding of applied innovation processes.