Common Agricultural Policy (CAP) proposes environmental policies developed around action-based conservation measures supported by agri-environment schemes (AES). High Nature Value (HNV) farming represents a combination of low-intensity and mosaic practices mostly developed in agricultural marginalized rural areas which sustain rich biodiversity. Being threatened by intensification and abandonment, such farming practices were supported in the last CAP periods by targeted AES.
Organic farming is recognized as one source for innovation helping agriculture to develop sustainably. However, the understanding of innovation in agriculture is characterized by technical optimism, relying mainly on new inputs and technologies originating from research. The paper uses the alternative framework of innovation systems describing innovation as the outcome of stakeholder interaction and examples from the SOLID (Sustainable Organic Low-Input Dairying) project to discuss the role of farmers, researchers and knowledge exchange for innovation.
Analysis of the role of Global Value Chains (GVC) in accessing knowledge and enhancing learning and innovation. Global Value Chains, Innovation Systems, Governance, Foreign Direct Investment, Learning, Upgrading, Productivity. Three main conclusions emerge from the analytical framework and evidence presented in this paper.
This paper starts describing the importance of agroforestry systems for the increase of productivity, resilience and efficiency. After the papaer describes the current state of agroforestry in Eastern Europe and its challenges and introduces good examples of agroforestry innovation networks initiatives in the region.
Recently, Agricultural Knowledge and Innovation Systems (AKISs) have gained considerable attention in scientific and political forums in the European Union (EU). AKIS is considered a key concept in identifying, analysing and assessing the various actors in the agricultural sector as well as their communication and interaction for innovation processes. Using qualitative expert interviews and organizational mapping, the features of national AKISs were investigated in selected EU member states (Belgium, France, Ireland, Germany, Portugal and the UK).
This article starts by describing the evolution of innovation in agricultural research and cooperation for development, including an historical overview of agricultural research for development from green revolution to the re-discover of traditional knowledge. Then the authors analyze participation in innovation processes and make a comparison of innovation systems and platforms targeting the agri-food sector in developing countries. A particular focus is reserved to the European regional networks and to the experience of the USAID Middle East Water and Livelihoods Initiative.
The innovation of agricultural systems management is a determinant factor that guarantees adaptation to a new paradigm of global economy, environmental protection, and social requirements. The conventional concepts of innovation, applicable to new products and processes, do not consider many characteristics of the agricultural sector, such as social innovation and innovation resulting from new or renewed processes.
In this paper it is assessed the types of knowledge networks utilised by small-scale farmers in four case studies (located in Bulgaria, Poland, Portugal, and the United Kingdom). We focus on knowledge acquired to inform three new activities being undertaken by study participants: agricultural production, subsidy access and regulatory compliance, and farm diversification (specifically agritourism).
Organic farming can play an important role in rural development and food production, by reinforcing the trend toward sustainable agriculture and its purpose of ecosystem conservation. The agribusiness of organic farming is particularly relevant in family farming, given the labor availability and the short marketing circuits. The innovative techniques of organic farming, namely with soil fertility, weed and pest control, opens a wide range of possibilities in its development and extension.
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.