Agriculture faces an enormous global challenge of feeding nine billion people by 2050. This means a comprehensive intensification of agriculture is required. Ecological intensification is gaining momentum as a clearly defined vision for increasing agriculture productivity and sustainability. How ecological intensification could be tailored to benefit smallholder farming systems in sub-Saharan Africa (SSA) remains the major question. In this study, we develop pathways relying on ecological intensification technologies and suiting different farm types of smallholder agriculture.
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.
Processes of designing for systemic innovation for sustainable development (SD) through the lens of three long-term case studies are reported. All case studies, which originated from the SLIM (Social Learning for the Integrated Management and Sustainable Use of Water at Catchment Scale) Project, funded within the EU Fifth Framework Program (2001–2004), constitute inquiry pathways that are explored using a critical incident approach.
The current study examined the extent of knowledge concerning agricultural innovation systems amongst researchers, extension agents, farmers, input dealers, and marketers, while determining their attitude towards collaborating with agricultural innovation systems. Through using a simple random sampling technique; researchers, extension agents, farmers, input dealers, and marketers were selected as the study population.