The study proposes a knowledge-intensive and qualitative research methodology based on researcher-farmer participatory approach, with the aim to improve the state of knowledge on organic rice, explore the yield potential and variability, and identify the successful agronomic practices. A wide range of cropping systems placed in North Italy were monitored and analysed during three years by a multi-actor network.

The economic globalisation has opened new pathways for commerce and triggered a logistical revolution, which in turn has produced enormous technological innovations. In this context, the role of startups is becoming increasingly crucial since they are positioning themselves as innovation enablers among large and small companies. Between these innovations, IoT, Big Data Analytics and Blockchain can be used in various domains, among which the logistics of the whole wine supply chain.

Proven that the adoption rate of a new product is influenced by the network characteristics of the early adopters, the aim of this paper is to find the network features of the early adopters associated with high adoption rates of a specific new practice: the use of biodegradable mulching films containing soluble bio-based substances derived from municipal solid wastes. The study simulated the diffusion process by means of an agent-based model calibrated on real-world data.

In this paper is studied the case of Trentino, an Italian Alpine region where alternative food chains are quickly developing, by comparing the development of alternative markets in this context with other Italian peri-urban areas. The mountain environment makes it very difficult for farms to standardize their products according to the requirement of the large retailers. Through alternative food chains, the typicality of products and the savoir faire of the farmers – representing the two main factors of products’ added value – are endorsed and more easily communicated to the market.

The impact of the COVID-19 pandemic will vary for different groups of rural population, with the highest impact expected to be on farmers and other vulnerable groups, especially women and youth. Targeted support is feasible only by activating a network of actors or organizations within agricultural innovation systems (AIS) and promoting customized technologies and practices suitable for location specific contexts.

Social farming (SF) has emerged as a social innovation practice shaping heterogeneous approaches and results. This study discusses the complexity of SF policy and practices, and it is led by the main hypothesis that the relationship between agricultural and social dimensions might be very heterogeneous, not only in different national contexts but also within the same national and local level. SF policy and practices are investigated testing the hypothesis of three main different modalities of interaction according to how the social and the agricultural perspectives interact.

The paper analyses the determinants of farmers’ adoption of innovations and studies the effect of the source of information and the connection with agricultural research on the contribution of innovation to farm performance. The paper uses primary data collected ad hoc in the Province of Bologna (Emilia-Romagna, Italy) and analyses it through an econometric analysis. The results indicate that structural factors and farm specialisation still play a relevant role in innovation adoption.

Industrial agriculture and its requirement for standardized approaches is driving the world towards a global food system, shrinking the role of farmers and shifting decision-making power. On the contrary, a holistic perspective towards a new food-system design could meet the needs of a larger share of stakeholders. Long-term experiments are crucial in this transition, being the hub of knowledge and the workshop of ‘participation in’ and ‘appropriation of’ the research in agriculture over a long term.

Innovation is considered as one of the key drivers for a competitive and sustainable agriculture and the European Commission highlights the importance of tailoring innovation support to farmers’ needs, especially in European Rural Development Policy (reg EU 1305/2013). The scientific literature offers a wide panorama of tools and methods for the analysis of innovation in agriculture but the lack of data on the state of innovation in the farms hampers such studies. A possibility to partially overcome this limit is the use of data collected by the Farm Accountancy Data Network (FADN).