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 chapter proposes a network-based framework to analyze and evaluate participatory and evidence-based policy processes. Four network based performance indicators are derived by incorporating a network model of political belief formation into a political bargaining model of the Baron–Grossmann–Helpman type. The application of our approach to the CAADP reform in Malawi delivers the following results: (i) beyond incentive problems, i.e.
There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.
Relying entirely on survey information and personal exchanges with over 70 scientists from within the CGIAR network, this working paper attempts to achieve a better understanding of the scope of social learning related efforts undertaken in CGIAR and main issues of relevance to more current efforts, such as that planned by the CGIAR program on Climate Change Agriculture and Food Security (CCAFS). A wide range of methods was identified, where groups of people learn in order to jointly arrive at solutions to pressing food security problems.
Local extension agents can benefit from the simple procedures in developing irrigation calendars for other irrigated crops. This study gives important lesson for local and regional decision makers, on their endeavour to increase the productivity of small scale irrigated agriculture. This paper is organized as follows: Section 2 describes the study area, practical irrigation schedule development method, alternative irrigation schedules and data collection and analysis methods. Section 3 presents the results.
Here, it is described a new participatory protocol for assessing the climate-smartness of agricultural interventions in smallholder practices. This identifies farm-level indicators (and indices) for the food security and adaptation pillars of CSA. It also supports the participatory scoring of indicators, enabling baseline and future assessments of climate-smartness to be made. The protocol was tested among 72 farmers implementing a variety of CSA interventions in the climate-smart village of Lushoto, Tanzania.
This practitioner’s guide, a companion volume to The Innovation Paradox picks up where the previous report left off. It aims to help policy makers in developing countries better formulate innovation policies. It does so by providing a rigorous typology of innovation policy instruments, including evidence of impact—and more importantly, the critical conditions in terms of institutional capabilities to successfully implement these policy instruments in developing countries.
ICT-driven digital tools to support smallholder farmers are arguably inevitable for agricultural development, and they are gradually evolving with promising outlook. Yet, the development and delivery of these tools to target users are often fraught with non-trivial, and sometimes unanticipated, contextual realities that can make or mar their adoption and sustainability. This article unfolds the experiential learnings from a digital innovation project focusing on surveillance and control of a major banana disease in East Africa which is being piloted in Rwanda.
Continually increasing food demand from a still–growing human population and the need for environmentally–friendly strategies for sustainable agricultural development require innovation and further enhancement of cropping systems’ factor productivity. The system of rice intensification (SRI) has been proposed as a suitable strategy to improve rice yields with reduced input requirements, most notably water and seed, while enhancing soil and water quality because agrochemical applications can be cut back.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.