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.
The main objective of this paper is to describe the AgroFE and Agrof-MM projects. This projects aims to develop an agroforestry training system based on a common framework and core content, and to promote training at European level. The knowledge databank is a component of the project training system. It aims to gather and share a set of documents, resources that partners can use and which will have been accessed by learners and the public users.
In the paper, is presented the opinion of the main stakeholders to the Innovation potential of the Institute of Agricultural Economics and Information (IAEI) as a significant actor in the AKIS. In the paper, is also defined the innovation potential of the IAEI as the ability to create, execute or provide the innovation and crucial information to the Czech AKIS. In order to mapping the current position and the innovation potential of the IAEI, were used desk research and semi-structured interviews
The aim of this research is to explore the different policy frameworks adopted by the Italian regions to support cooperation for innovation projects in RDPs in the period 2007-2013. These were analysed against the conceptual background outlined by the European Commission and the international literature on the interactive approach to innovation processes (EC, 2013). The study is supported by the use of a mixed-methods approach, based on desk and on field research, qualitative and quantitative methods
The aim of the paper is to analyse the linkage between science development, innovative ideas, their dissemination, establishment of extension services and their impact on the innovative development of the agricultural sector. As a result, solutions for expanding the coverage of the extension network, together with the diversification and improvement of its services are provided. The primary data from key stakeholders were collected through a semi-structured interview.
Agricultural innovation in low-income tropical countries contributes to a more effective and sustainable use of natural resources and reduces hunger and poverty through economic development in rural areas. Yet, despite numerous recent public and private initiatives to develop capacities for agricultural innovation, such initiatives are often not well aligned with national efforts to revive existing Agricultural Innovation Systems (AIS).
Grown in Jamaica since the days of slavery, food yams are major staples in local diets and a significant non-traditional export crop. The cultivation system used today is the same as 300 years ago, with alleged unsustainable practices. A new cultivation system called minisett was introduced in 1985 but the adoption rate twenty four years later is extremely low.
The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one.
Indicator-based tools are widely used for the assessment of farm sustainability, but analysts still face methodological and conceptual issues, including data availability, the complexity of the concept of sustainability and the heterogeneity of agricultural systems. This study contributes to this debate through the illustration of a procedure for farm sustainability assessment focussed on the case study of the South Milan Agricultural Park, Italy. The application is based on a set of environmental, social and economic indicators retrieved from the literature review.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.