Soil quality is directly linked to food quality and quantity. However the globalisation and the pressure to increase the agricultural production results to deterioration of the environment, climate change and a serious threat to human and animal health. Soil contamination effected by the environmental pollution is one of the most pressing issues in the political and expertise debate on food safety within the related EU policies as Common agricultural policy, EU agri-environmental, EU food policy and EU health policy. Numerous studies have shown that heavy metals can accumulate in tissues, subsequently affect organ functions, and disrupt the reproductive, nervous or endocrine system. Therefore, the health status in relation to xenobiotics should be monitored and explored. The international scientific conference „Quality Soil as a Pathway to Healthy Food in the EU- Challenges to 2030“ aimed to highlight challenges of the food and feed management on the EU until 2030, including identification of risk factors for food and feed production, food chain, and sustainable agriculture. At the conference experts from 9 EU countires presented their latest research results related to soil and food quality and their visions and proposals how to decrease the negative effects of contamination of soil and food.
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Western-European consumers have become not only more demanding on product availability in retail outlets but also on other food attributes such as quality, integrity, and safety. When (re)designing food supply-chain networks, from a logistics point of view, one has to consider these demands next to traditional efficiency and responsiveness requirements. The concept ‘quality controlled logistics’ (QCL) hypothesizes that if product quality in each step of the supply chain can be predicted in advance, goods flows can be controlled in a pro-active manner and better chain designs can be established resulting in higher product availability, constant quality, and less product losses. The paper discusses opportunities of using real-time product quality information for improvement of the design and management of ‘AgriFood Supply Chain Networks’, and presents a preliminary diagnostic instrument for assessment of ‘critical quality’ and ‘logistics control’ points in the supply chain network. Results of a tomato-chain case illustrate the added value of the QCL concept for identifying improvement opportunities in the supply chain as to increase both product availability and quality. Future research aims for the further development of the diagnostic instrument and the quantification of costs and benefits of QCL scenarios.
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This study theorizes on the sociomateriality of food in authority-building processes of partial organizations by exploring alternative food networks (AFNs). Through the construction of arenas for food provisioning, AFNs represent grassroots collectives that deliberately differentiate their practices from mainstream forms of food provisioning. Based on a sequential mixed-methods analysis of 24 AFNs, where an inductive chronological analysis is followed by a qualitative comparative analysis (QCA), we found that the entanglements between participants’ food provisioning practices and food itself shape how authority emerges in AFNs. Food generates biological, physiological and social struggles for AFN participants who, in turn, respond by embracing or avoiding them. As an outcome, most AFNs tend to bureaucratize over time according to four identified patterns while a few idiosyncratically build a more shared basis of authority. We conclude that the sociomateriality of food plays an important yet indirect role in understanding why and how food provisioning arenas re-organize and forge their forms of authority over time. Pascucci, S., Dentoni, D., Clements, J., Poldner, K., & Gartner, W. B. (2021). Forging Forms of Authority through the Sociomateriality of Food in Partial Organizations. Organization Studies, 42(2), 301-326. https://doi.org/10.1177/0170840620980232
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Flying insects like dragonflies, flies, bumblebees are able to couple hovering ability with the ability for a quick transition to forward flight. Therefore, they inspire us to investigate the application of swarms of flapping-wing mini-drones in horticulture. The production and trading of agricultural/horticultural goods account for the 9% of the Dutch gross domestic product. A significant part of the horticultural products are grown in greenhouses whose extension is becoming larger year by year. Swarms of bio-inspired mini-drones can be used in applications such as monitoring and control: the analysis of the data collected enables the greenhouse growers to achieve the optimal conditions for the plants health and thus a high productivity. Moreover, the bio-inspired mini-drones can detect eventual pest onset at plant level that leads to a strong reduction of chemicals utilization and an improvement of the food quality. The realization of these mini-drones is a multidisciplinary challenge as it requires a cross-domain collaboration between biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. Moreover a co-creation based collaboration will be established with all the stakeholders involved. With this approach we can integrate technical and social-economic aspects and facilitate the adoption of this new technology that will make the Dutch horticulture industry more resilient and sustainable.
The consortium would like to contribute to structural reduction of post-harvest and food losses and food quality improvement in Kenyan avocado and dairy value chains via the application of technical solutions and tools as well as improved chain governance competences in those food chains. The consortium has four types of partners: 1. Universities (2 Kenyan, 4 Dutch), 2. Private sector actors in those chains, 3. Organisations supporting those chains, and 4. Associate partners which support category 1 to 3 partners through co-financing, advice and reflection. The FORQLAB project targets two areas in Kenya for both commodities, a relatively well-developed chain in the central highlands and a less-develop chain in Western-Kenya. The approach is business to business and the selected regions have great potential for uptake of successful chain innovations as outcome of research results. The results are scalable for other fresh and processed product chains via a living lab network approach. The project consists of 5 work packages (WPs): 1. Inventory , status quo and inception, 2. Applied research, 3. Dissemination of research outputs through living lab networks, 4. Translation of project output in curricula and trainings, and 5. Communication among partners and WPs. The applied research will be implemented in cooperation with all partners, whereby students of the consortium universities will conduct most of the field studies and all other partners support and interact depending on the WPs. The expected outcomes are: two knowledge exchange platforms (Living Labs) supported with hands on sustainable food waste reduction implementation plans (agenda strategy); overview and proposals for ready ICT and other tech solutions; communication and teaching materials for universities and TVETs; action perspectives; and knowledge transfer and uptake.
Granular materials (GMs) are simply a collection of individual particles, e.g., rice, coffee, iron-ore. Although straightforward in appearance, GMs are key to several processes in chemical-pharmaceutical, high-tech, agri-food and energy industry. Examples include laser sintering in additive manufacturing, tableting in pharma or just mixing of your favourite crunchy muesli mix in food industry. However, these bulk material handling processes are notorious for their inefficiency and ineffectiveness. Thereby, affecting the overall expenses and product quality. To understand and enhance the quality of a process, GMs industries utilise computer-simulations, much like how cars and aeroplanes have been designed and optimised since the 1990s. Just as how engineers utilise advanced computer-models to develop our fuel-efficient vehicle design, energy-saving granular processes are also developed utilising physics-based simulation-models, using a computer. Although physics-based models can effectively optimise large-scale processes, creating and simulating a fully representative virtual prototype of a GMs process is very iterative, computationally expensive and time intensive. On the contrary, given the available data, this is where machine learning (ML) could be of immense value. Like how ML has transformed the healthcare, energy and other top sectors, recent ML-based developments for GMs show serious promise in faster virtual prototyping and reduced computational cost. Enabling industries to rapidly design and optimise, enhancing real-time data-driven decision making. GranML aims to empower the GMs industries with ML. We will do so by (i) performing an in-depth GMs-ML literature review, (ii) developing open-access ML implementation guidelines; and (iii) an open-source proof-of-concept for an industry-relevant use case. Eventually, our follow-up mission is to build upon this vital knowledge by (i) expanding the consortium; (ii) co-developing a unified methodology for efficient computer-prototyping, unifying physics- and ML-based technologies for GMs; (iii) enhancing the existing computer-modelling infrastructure; and (iv) validating through industry focused demonstrators.
