This presentation at the GCARD Montpellier, in March 2010, focuses on the Danish model for agricultural advisory services.
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.
As part of the EU funded AgriSpin project (www.agrispin.eu), which aimed at “creating space for innovations” in agriculture across Europe, this contribution addresses the above mentioned knowledge gaps by a. elaborating a generic typology appropriate to capture the variety of ISS, b. structuring selected innovations along the degree of technological change and coordination levels, and c.
This study aims at contributing to a better understanding of the linkage between supply chain performance and possible performance improvement with respect to food quality and safety. Therefore, the paper addresses the question whether the level of collaborative planning and close supply chain relationships could help improve quality and safety of organic supply chains. The study was conducted as a part of the multi-disciplinary EU-wide survey of organic supply chains, carried out in 8 European countries.
This article therefore analyses whether agricultural advisors representing companies that do not sell pesticides (independent advisors) are more likely to recommend reduced pesticide use than agricultural advisors who represent companies with an economic interest in selling pesticides (supplier-affiliated advisors). However, we would not necessarily expect a crude relationship between economic incentive and higher pesticide recommendations. After all, advisors have to justify their recommendations to their customers, the farmers.
The development of future food systems will depend on normative decisions taken at different levels by policymakers and stakeholders. Scenario modeling is an adequate tool for assessing the implications of such decisions, but for an enlightened debate, it is important to make explicit and transparent how such value-based decisions affect modeling results.
There has been an increasing interest in science, technology and innovation policy studies in the topic of policy mixes. While earlier studies conceptualised policy mixes mainly in terms of combinations of instruments to support innovation, more recent literature extends the focus to how policy mixes can foster sustainability transitions.
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).
Invasive species such as Ambrosia (an annual weed) pose a biosecurity risk whose management depends on the knowledge, attitudes and practices of many stakeholders. It can therefore be considered a complex policy and risk governance problem. Complex policy problems are characterised by high uncertainty, multiple dimensions, interactions across different spatial and policy levels, and the involvement of a multitude of actors and organisations. This paper provides a conceptual framework for analysing the multi-level and multi-actor dimensions of Ambrosia management.
Precision Agriculture (PA) has been advocated as a promising technology and management philosophy that provides multidimensional benefits for producers and consumers while being environmentally friendly. In Europe, private stakeholders (farm advisors, farm equipment producers, decision support providers, farmers) and research institutions have been trying to develop, test and demonstrate adoption of precision agriculture solutions with governments financing big projects in these areas. Despite these efforts, adoption is still lagging behind expectations.