Serena Mandolesi

Innovations in low input and organic dairy supply chains—What is acceptable in Europe?

The growth in organic and low-input farming practices is driven by both market demand for high quality, safe food, and European Union policy support, and these types of farming practices are considered in European Union policies for sustainable production, food quality, healthy life, and rural development. However, many constraints to the development of low-input and organic dairy farming supply chains have been identified, including economic, political, and technical constraints. In order for these types of supply chains to develop and provide further benefits to society, innovations are required to improve their sustainability. However, an innovation will only be taken up and result in desirable change if the whole supply chain accepts the innovation. In this paper, Q methodology is used to identify the acceptability of dairy supply chain innovations to low-input and organic supply chain members and consumers in Belgium, Finland, Italy, and the United Kingdom. A strong consensus existed across all respondents on innovations that were deemed as unacceptable. The use of genetically modified and transgenic organisms in the farming system and innovations perceived as conflicting with the naturalness of the production system and products were strongly rejected. Innovations that were strongly liked across all participants in the study were those related to improving animal welfare and improving forage quality to be able to reduce the need for purchased concentrate feeds. Only minor differences existed between countries as to where the priorities lay in terms of innovation acceptability.

Automatic Analysis of Eye-Tracking Data for Augmented Reality Applications: A Prospective Outlook

Eye-tracking technology is becoming easier and cheaper to use, resulting in its increasing application to numerous fields of research. Recent years have seen rapid developments in this area. In light of the foregoing, in the context of Cultural Heritage (CH), the definition of a modern approach to understand how individuals perceive art is challenging. Despite the art perception is highly subjective and variable according to knowledge and experience, more recently, several scientific study and enterprises started to quantify how subjects observe art by the application of the eye-tracking technology. The aim of this study was to understand the visual behaviour of subjects looking at paintings, using eye-tracking technology, in order to define a protocol for optimizing an existing Augmented Reality (AR) application that allows the visualization of digital contents through a display. The stimuli used are three famous paintings preserved at the National Gallery of Marche (Urbino, Marche Region, Italy). We applied eye-tracking to have a deeper understanding of people visual activities in front of these paintings and to analyse how digital contents eventually influence their behaviour. The description of the applied procedure and the preliminary results are presented.

Using Q methodology to facilitate the establishment of the 2030 vision for the EU organic sector

A participatory application of Stephenson’s Q methodology known as InQuiry was used to investigate stakeholder perspectives on a desired future for the organic sector in Europe in order to develop a shared vision. A selected group of experts from different organisations and nationalities were asked to provide their viewpoints on what should be the vision for the organic sector in Europe in 2030, sorting 48 statements containing possible future visions about the organic sector. Results indicated two distinct and common positions about the future of EU organic sector, which helped in drafting the IFOAM EU 2030 vision for the organic sector in Europe.

User-Centered Predictive Model for Improving Cultural Heritage Augmented Reality Applications: An HMM-Based Approach for Eye-Tracking Data

Today, museum visits are perceived as an opportunity for individuals to explore and make up their own minds. The increasing technical capabilities of Augmented Reality (AR) technology have raised audience expectations, advancing the use of mobile AR in cultural heritage (CH) settings. Hence, there is the need to define a criteria, based on users’ preference, able to drive developers and insiders toward a more conscious development of AR-based applications. Starting from previous research (performed to define a protocol for understanding the visual behaviour of subjects looking at paintings), this paper introduces a truly predictive model of the museum visitor’s visual behaviour, measured by an eye tracker. A Hidden Markov Model (HMM) approach is presented, able to predict users’ attention in front of a painting. Furthermore, this research compares users’ behaviour between adults and children, expanding the results to different kind of users, thus providing a reliable approach to eye trajectories. Tests have been conducted defining areas of interest (AOI) and observing the most visited ones, attempting the prediction of subsequent transitions between AOIs. The results demonstrate the effectiveness and suitability of our approach, with performance evaluation values that exceed 90%.