Digital Twin in the Agri-Food Supply Chain: A Literature Review

Tebaldi, Letizia; Vignali, Giuseppe; Bottani, Eleonora

doi:10.1007/978-3-030-85910-7_29

Cited by 14 publications

(7 citation statements)

References 27 publications

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“…Additionally, we added publications to our list, which we did not find directly were referred by other publications and possibly relevant for this research (backward search). In the literature search process, we also identified reviews, e.g., [ 29 , 39 , 40 , 41 ]. However, as we wanted to avoid the misinterpretation or incorrect reproduction of information, we rather included the original publications or sources of such reviews.…”

Section: Methodsmentioning

confidence: 99%

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Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Henrichs

Noack

Piedrahita

et al. 2021

Sensors

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The food industry faces many challenges, including the need to feed a growing population, food loss and waste, and inefficient production systems. To cope with those challenges, digital twins that create a digital representation of physical entities by integrating real-time and real-world data seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. Therefore, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are classified according to a taxonomy and key elements to implement digital twins are identified. Further, the challenges and potentials of digital twin applications in the food industry are discussed. The survey revealed that the application of digital twins mainly targets the production (agriculture) or the food processing stage. Nearly all applications are used for monitoring and many for prediction. However, only a small amount focuses on the integration in systems for autonomous control or providing recommendations to humans. The main challenges of implementing digital twins are combining multidisciplinary knowledge and providing enough data. Nevertheless, digital twins provide huge potentials, e.g., in determining food quality, traceability, or designing personalized foods.

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Section: Methodsmentioning

confidence: 99%

“…A more all-encompassing view on the agri-food SC is presented in the work of Tebaldi et al [ 40 ], including the SC stages supply, processing, and distribution (according to our taxonomy in Section 2.1 ). For the sake of completeness, we included the applications mentioned there in our work.…”

Section: Related Workmentioning

confidence: 99%

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Henrichs

Noack

Piedrahita

et al. 2021

Sensors

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“…has demonstrated substantial limitations compared to hands-on practical and empirical knowledge from immersive experiences. There is great potential and there are challenges in generating VR technologies as an alternative means of education for the students of the future world for various domains of human activity [6]. Recent studies propose various models and future recommendations for integrating VR technologies into meta concepts for virtual education, thus enhancing active learning and practical information accumulation as it pertains to the stakeholders involved.…”

Section: Limitations and Future Workmentioning

confidence: 99%

“…There is a tangible increasing demand for Digital-Twin-driven technologies implemented in various industries, with the market volume previously estimated at USD 3.1 billion for 2020 and forecasted to reach USD 48.2 billion by 2026 [5]. Within agriculture, this notable increase has specifically found footing for precision farming purposes [4,6].…”

Section: Introductionmentioning

confidence: 99%

Virtual Reality-Based Digital Twins: A Case Study on Pharmaceutical Cannabis

Spyrou,

Hurst,

Verdouw

2023

BDCC

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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.

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“…Digital twins are well known in engineering (Glaessgen and Stargel, 2012) and help improving and understanding complex systems and phenomena. Also in natural sciences, realworld phenomena are often described by experts using physical models 1 that encode at least particular aspects of the world, for instance how different organisms contribute to food webs, how ocean currents behave, or how CO2 is exchanged between ocean and atmosphere (Tebaldi et al, 2021, Møttus et al, 2021. It is well-known that modelling only particular aspects is a coarse approximation of the world, but models that focus on individual components of larger systems proved to be valuable for understanding and predicting certain aspects, such as effects of fertilizers in sewage waters or flooding of tropical islands due to sea level rise (Delgado et al, 2019, Storlazzi et al, 2018.…”

Section: Introductionmentioning

confidence: 99%

Digital Twinning in the Ocean – Challenges in Multimodal Sensing and Multiscale Fusion Based on Faithful Visual Models

Grossmann

Nakath

Urlaub

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In engineering, machines are typically built after a careful conception and design process: All components of a system, their roles and the interaction between them is well understood, and often even digital models of the system exist before the actual hardware is built. This enables simulations and even feedback loops between the real-world system and a digital model, leading to a digital twin that allows better testing, prediction and understanding of complex effects. On the contrary, in Earth sciences, and particularly in ocean sciences, models exist only for certain aspects of the real world, of certain processes and of some interactions and dependencies between different “components” of the ocean. These individual models cover large temporal (seconds to millions of years) and spatial (millimetres to thousands of kilometres) scales, a variety of field data underpin them, and their results are represented in many different ways. A key to enabling digital twins in the oceans is fusion at different levels, in particular, fusion of data sources and modalities, fusion over different scales and fusion of differing representations. We outline these challenges and exemplify different envisioned digital twins employed in the oceans involving remote sensing, underwater photogrammetry and computer vision, focusing on optical aspects of the digital twinning process. In particular, we look at the holistic sensing scenarios of optical properties in coastal waters as well as seafloor dynamics at volcanic slopes and discuss road blockers for digital twins as well as potential solutions to increase and widen the use of digital twins.

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Digital Twin in the Agri-Food Supply Chain: A Literature Review

Cited by 14 publications

References 27 publications

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

Virtual Reality-Based Digital Twins: A Case Study on Pharmaceutical Cannabis

Digital Twinning in the Ocean – Challenges in Multimodal Sensing and Multiscale Fusion Based on Faithful Visual Models

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