The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.
This paper is a case study of a network that combined participatory approaches to propose best suited knowledge management (KM) interventions for its member countries. A five-step exercise used existing elements of the alliance’s strategy, a KM survey and a face-to-face participatory validation of the analysis, to identify gaps in current KM approaches and to collectively point to immediate opportunities for improvement. The KM survey, also referred to as a scan, provided a neutral space for reflection.
The CDAIS Communication strategy for 2015-2018 aims to contribute to CDAIS project's core objective of making agricultural innovation systems more efficient and sustainable in meeting the demands of farmers, agribusiness and consumers. For more information on CDAIS, see: https://www.fao.org/in-action/tropical-agriculture-platform/cdais-project...
This concept note has been developed within the context of the EU-funded CDAIS project, which is jointly implemented by AGRINATURA-EEIG and the Food and Agriculture Organization of the United Nations (FAO) to support the TAP Action Plan in eight pilot countries in Africa (Angola, Burkina Faso, Ethiopia, Rwanda), Asia (Bangladesh, Laos) and Central America (Guatemala, Honduras) .
This training manual was prepared under the EU-funded project Capacity Development for Agricultural Innovation Systems (CDAIS), a global partnership (Agrinatura, FAO and 8 pilot countries) that aims to strengthen the capacity of countries and key stakeholders to innovate in complex agricultural systems, thereby achieving improved rural livelihoods.
CDAIS is a global partnership that aims to strengthen the capacity of countries and key stakeholders to innovate in the context of complex agricultural systems, to improve rural livelihoods. The goal of the Capacity Development for Agricultural Innovation Systems (CDAIS) project is to promote innovation that meets the needs of small farmers, small and medium-sized agribusiness, and consumers.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
This tool enables participants to become cognisant of the functional capacities discovered through the capacity scoring questionnaire, and test the limits of these capacities through simulations or role-playing (e.g. problem-solving, collaboration, information sharing, and engagement). The simulation game leads to an intuitive understanding of innovation capacities and of the importance of the enabling environment, helping participants to learn about the significance of these capacities.
This tool is a simple tool to map out the current status of the AIS, and to discover where the actors want to go. The rich picture tool can be used both to describe the current situation and to illustrate future plans. A rich picture opens up discussions and helps participants reach a broad and collective understanding of the situation.
The Action Planning is a tool that formalizes commitments and plots the route to their implementation. An action plan is intended for the use of the core actors, who will have been identified beforehand in the visioning phase. It determines who does what and when, and is therefore essential to ensuring that things get done and that the goals and visions set out in the capacity development strategy are achieved.