The advancements of smart farming are noteworthy, largely driven by rapid developments in digital technologies such as the Internet of Things, Big Data, and AI. However, the mere availability of these technologies does not guarantee their effective integration into agricultural systems. Aligning the different digital components, such as sensors, platforms, data analytics, and decision-support tools, remains a complex task. This often prevents smart farming systems from reaching their full potential. Limited integration results in isolated data flows, interoperability problems, and inefficiencies across farm operations. This study presents a comprehensive Capability Maturity Model (CMM) for assessing the level of digital integration in smart farming from both technical and organisational perspectives. The model defines five maturity levels ranging from fragmented manual operations to a fully integrated and optimized level (Ad hoc, Managed, Integrated, Predictable, Innovative). It assesses the maturity of capabilities across six key dimensions: business processes, people and culture, strategy, technology, digital governance and data and analytics. A multi-case study of three smart farms in the Netherlands was conducted to validate the model. The findings indicate that the proposed model provides a holistic and practical framework for assessing digital integration maturity across different contexts. It not only supports strategic planning for interoperability but also identifies critical integration challenges and promotes a whole-farm approach to smart agriculture literature. As a decision-support tool, it provides agri-food practitioners with concrete and tailored guidance on which specific capabilities need to be improved to advance the maturity of smart farming.

Traditional farming has evolved from standalone computing systems to smart farming, driven by advancements in digitalization. This has led to the proliferation of diverse information systems (IS), such as IoT and sensor systems, decision support systems, and farm management information systems (FMISs). These systems often operate in isolation, limiting their overall impact. The integration of IS into connected smart systems is widely addressed as a key driver to tackle these issues. However, it is a complex, multi-faceted issue that is not easily achievable. Previous studies have offered valuable insights, but they often focus on specific cases, such as individual IS and certain integration aspects, lacking a comprehensive overview of various integration dimensions. This systematic review of 74 scientific papers on IS integration addresses this gap by providing an overview of the digital technologies involved, integration levels and types, barriers hindering integration, and available approaches to overcoming these challenges. The findings indicate that integration primarily relies on a point-to-point approach, followed by cloud-based integration. Enterprise service bus, hub-and-spoke, and semantic web approaches are mentioned less frequently but are gaining interest. The study identifies and discusses 27 integration challenges into three main areas: organizational, technological, and data governance-related challenges. Technologies such as blockchain, data spaces, AI, edge computing and microservices, and service-oriented architecture methods are addressed as solutions for data governance and interoperability issues. The insights from the study can help enhance interoperability, leading to data-driven smart farming that increases food production, mitigates climate change, and optimizes resource usage.

The production of pharmaceutical cannabis is a complex and dynamic industry that has to meet critical challenges concerning product quality, compliance, traceability, food safety, sustainability and health. Digital twins have the potential to be powerful enablers for producers to meet these challenges. However, digital twins for the pharmaceutical production of cannabis are still under exploration and not yet researched. This paper contributes to overcoming this situation by proposing a reference architecture for the development and implementation of digital twins in this domain. Based on a design-oriented methodology, it defines and applies a coherent set of architecture views for modelling digital twin-based systems. Furthermore, a proof of concept of an immersive digital twin has been developed in order to test the applicability of reference architecture. This digital twin is developed in the open, cross-industry platform Unity and includes an extensive 3D model of a cannabis production facility. It is connected with real-world data through an application programming interface integration displaying real-time sensor data from a live greenhouse. The 3D environment is fully explorable, where the user takes control of an avatar character to walk around the facility and view real-time sensor readings. The expert validation shows that the developed digital twin is a valuable and innovative first step for remote management of pharmaceutical cannabis production. Further developments are needed to leverage its full potential, especially adding more types of sensor data, developing implementation-specific 3D models, extending the digital twin with predictive and prescriptive capabilities and connecting it to actuators.

This paper presents a conceptual framework that reflects the current state of thinking on tokenizing circularity in agri-food systems. The framework is built upon classifications of tokens and the key principles of circular economy and shows how tokenization can support circularity in agri-food systems through the flows of information and flows of value. Based on an integrative review of literature on tokenization, blockchain and the circular economy and multiple case studies in the agri-food domain, we show the relevance of tokenization to the circular economy in three ways: 1) enhancing traceability of physical and digital objects in supply chains; 2) improving transparency and credibility of circularity claims; 3) facilitating collaborative business ecosystems with incentives for more circular production and distribution. Based on the framework, we derive important research questions for future research agenda on tokenizing circularity in agri-food systems.

Digital Twins are digital equivalents of real-life objects. They allow producers to act immediately in case of (expected) deviations and to simulate effects of interventions based on real-life data. Digital Twin and eXtended Reality technologies (including Augmented Reality, Mixed Reality and Virtual Reality technologies), when coupled, are promising solutions to address the challenges of highly regulated crop production, namely the complexity of modern production environments for pharmaceutical cannabis, which are growing constantly as a result of legislative changes. Cannabis farms not only have to meet very high quality standards and regulatory requirements but also have to deal with high production and market uncertainties, including energy considerations. Thus, the main contributions of the research include an architecture design for eXtended-Reality-based Digital Twins for pharmaceutical cannabis production and a proof of concept, which was demonstrated at the Wageningen University Digital Twins conference. A convenience sampling method was used to recruit 30 participants who provided feedback on the application. The findings indicate that, despite 70% being unfamiliar with the concept, 80% of the participants were positive regarding the innovation and creativity.

CONTEXT: Digital technologies nowadays play a major role in innovation within the agri-food domain. The evolution of IT systems has currently arrived at a level that involves complex systems integration and business ecosystems in which many stakeholders in different roles are involved. A new paradigm for digital innovation is needed that copes with this increased complexity.OBJECTIVE: This paper presents an empirically informed framework for analysing and designing viable, sus-tainable digital innovation ecosystems in the agri-food domain.METHODS: The research is based on a series of European large-scale public-private innovation projects from 2011 to 2021 with a total budget of 73 M euro . They involved hundreds of stakeholders that were developing a large number of digital solutions through which a digital innovation ecosystem for agri-food was formed. In a lon-gitudinal study, a conceptual framework was used to analyse these projects and describe how the digital innovation ecosystem has developed. Lessons learnt are translated into a number of design principles and an organizational approach to foster digital innovation ecosystems in agri-food.RESULTS AND CONCLUSIONS: The conceptual framework consists of 6 key concepts: (i) innovation strategy, (ii) innovation organization, (iii) innovation network that contains (iv) the innovation process and (v) the innovation object and finally (vi) an innovation infrastructure. Along these 6 concepts, lessons learnt and in total 21 design principles are derived from analysing the projects forming a basis for the organizational framework. At the core of this framework is a lean multi-actor approach to trials and use case development interacting with a set of multidisciplinary activities: (i) developing a common technical collaboration infrastructure, (ii) identifying value streams with user engagement, (iii) engaging the right partners and stakeholders at the right time supported by strategic project planning and dynamic management. The most important conclusion is that effective, successful and quick use of appropriate IT in agri-food requires that actors should not be analysed in isolation from both their technological and business environment. Another consequence is that a 'minimal viable ecosystem' only emerges after considerable time, resources and ingenuity is invested and may require outside (government) intervention.SIGNIFICANCE: Results from this paper can be used both by public and private stakeholders to diagnose and improve digital innovation projects and develop viable, sustainable digital innovation ecosystems in agri-food.

The three major meat supply chains in emerging markets are the traditional wet markets, the integrated supply chains, and the more recent collaborative supply chains. Customers in these markets are increasingly demanding safe and high-quality meat, which requires more transparency in the supply chain. This paper presents a framework for modelling and designing transparency systems. The framework consists of the domain, product flow, business control, business process and transparency data models. The framework is demonstrated in the three pork supply chain types that are also widely present in Vietnam and are representative of the pork supply chains of emerging markets in general. The applicability of the framework is described in detail in a case study of a collaborative supply chain of independent members, which is one of the three pork supply chain types. The case study is selected for detailed analysis because the members work closely together to provide safe and traceable pork meat to consumers.

The three major meat supply chains in emerging markets are traditional wet markets, integrated supply chains, and the more recent collaborative supply chains. Customers in these markets are increasingly demanding safe and high-quality meat, which requires more transparency in the supply chain. This paper presents a generic framework for modelling and designing transparency systems in meat supply chains, with special attention to the needs of emerging markets like Vietnam where all the three supply chain types co-exist. The framework consists of domain, product flow, business control, business process and transparency data models. The main novelty of the proposed framework is its complementarity to cross-industry reference architectures and generic traceability standards, and its stakeholder-centric approach. The framework is demonstrated in the three pork supply chain types that are also widely present in Vietnam and are representative of the pork supply chains of emerging markets in general. The applicability of the framework is described in detail in a case study of a collaborative supply chain of independent members, which is one of the three pork supply chain types. The case study is selected for detailed analysis because the members work closely together to provide safe and traceable pork meat to consumers.

Digital Twins can be considered as a new phase in smart and data-driven greenhouse horticulture. A Digital Twin is a digital equivalent to a real-life object of which it mirrors its behaviour and states over its lifetime in a virtual space. Research indicates that they can substantially enhance productivity and sustainability, and are able to deal with the increasing scarcity of green labour in greenhouse horticulture. This paper presents the results of a systematic literature review on Digital Twin applications in greenhouse horticulture. The review identifies 8 articles that explicitly address Digital Twins in greenhouse horticulture and 115 studies that implicitly apply the Digital Twin concept in smart IoT-based systems. Findings indicate that the concept of the Digital Twin is in a seminal phase in greenhouse horticulture, but there are existing applications that are not yet framed as Digital Twins. In the reviewed papers, there is a dominant focus on the cultivation process at the greenhouse level, among others for climate control, energy management and lighting. About 9% of the articles are virtualizing plants themselves, which indicates that the granularity level addressed is still rather limited. Only 7 % of the articles look beyond plants or single greenhouses. None of the reviewed articles consider the company level. Furthermore, most applications address monitoring and control of the state and behaviour of real-life objects. More advanced applications, including predictive and prescriptive capabilities across the complete lifecycle, are still in an early stage of development, although predictive Digital Twins are gaining prominence.

Supply chains are increasingly being virtualized in response to globalization and emerging market challenges. Virtualization requires technical innovation using IoT technologies such as smart sensors, and it allows to transmit quality information across the chain. Associated organizational innovation is complex, especially in SME-dominated supply chains, and relies upon intensive knowledge exchange, discussions and negotiation. However, the development of solutions to address socio-institutional barriers to virtual supply chains has been under-researched up to now. This study analyses barriers to virtualization faced in SME-dominated supply chains, that is, the Dutch floriculture. The second step is developing a solution to core barriers in the form of a dedicated simulation game, the 'Virtual Flower Chain'. Design and experiences are shown. The barriers that the game addresses are a sector-wide lack of cooperation, consumer focus, and sense of urgency, as well as a limited understanding of virtualization. The validation through game sessions shows that 87% of the participants gained more insights about the benefits of virtualization technologies and the willingness to collaborate, rather than blaming others, increased to 89% after the game. Game participants achieved more awareness of their position in a larger system, rather than as an isolated business.

222The IoT European Large-Scale Pilots Programme includes the innovation consortia that are collaborating to foster the deployment of IoT solutions in Europe through the integration of advanced IoT technologies across the value chain, demonstration of multiple IoT applications at scale and in a usage context, and as close as possible to operational conditions. The programme projects are targeted, goal-driven initiatives that propose IoT approaches to specific real-life industrial/societal challenges. They are autonomous entities that involve stakeholders from the supply side to the demand side, and contain all the technological and innovation elements, the tasks related to the use, application and deployment as well as the development, testing and integration activities. This chapter describes the IoT Large Scale Pilot Programme initiative together with all involved actors. These actors include the coordination and support actions CREATE-IoT and U4IoT, being them drivers of the programme, and all five IoT Large-Scale Pilot projects, namely ACTIVAGE, IoF2020, MONICA, SynchroniCity and AUTOPILOT.

Agriculture is of vital importance to feed Europe in a healthy way, while Europe has also an important role in feeding the world. It is a large sector with a big social and economic impact, e.g.: • 43% of the EU’s land area is being farmed [2]; • The food and drink industry is the largest manufacturing sector in the EU, representing 15% of EU manufacturing sector turnover [3]; • Agri-food logistics has 27% share in the EU road transport [4]; • Agri-food exports contribute to more than 7% to total EU exports in goods [5]; • Europe is the largest exporter of agri-food products in the world, EU28 exports reached €122 billion in 2014 [5].

Digital Twins are very promising to bring smart farming to new levels of farming productivity and sustainability. A Digital Twin is a digital equivalent of a real-life object of which it mirrors its behaviour and states over its lifetime in a virtual space. Using Digital Twins as a central means for farm management enables the decoupling of physical flows from its planning and control. As a consequence, farmers can manage operations remotely based on (near) real-time digital information instead of having to rely on direct observation and manual tasks on-site. This allows them to act immediately in case of (expected) deviations and to simulate effects of interventions based on real-life data. This paper analyses how Digital Twins can advance smart farming. It defines the concept, develops a typology of different types of Digital Twins, and proposes a conceptual framework for designing and implementing Digital Twins. The framework comprises a control model based on a general systems approach and an implementation model for Digital Twin systems based on the Internet of Things?Architecture (IoT-A), a reference architecture for IoT systems. The framework is applied to and validated in five smart farming use cases of the European IoF2020 project, focussing on arable farming, dairy farming, greenhouse horticulture, organic vegetable farming and livestock farming.