Digital Twins In Farm Management: Illustrations From The Fiware Accelerators Smartagrifood And Fractals

Verdouw, C.N.; Kruize, J.W.

doi:10.5281/zenodo.893661

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…Verdouw et al developed a DT suitable to track real-time movement of agronomic machines for energy monitoring, economic efficiency, and optimal productivity. 18 DTs can not only control machines but also allow for M2M programming of the robots to interact without human intervention. 64,65 4.3.…”

Section: Digital Twins For Agricultural Machinerymentioning

confidence: 99%

“…However, Verdouw and Kruize presented several applications of DTs in different stages of agriculture processing such as crop storage and agriculture machinery. 18 They focused on livestock monitoring for health detection, identification of pests and diseases in plants, productivity optimization by managing storage availability, and cost-effectiveness evaluation of machinery-mediated treatments. More sophisticated, Monteiro et al described a DT for vertical farming, collecting data related to temperature, humidity, luminosity, and the relative CO 2 concentration, properly stored in the cloud and processed using intelligent data analysis resulting in vertical farm optimal production planification.…”

Section: Opportunities Challenges and Perspectivesmentioning

confidence: 99%

“…Autonomous machines and robots precisely and reproducibly carry out labors 24/7, ensuring high standards in quality of products, Figure . Verdouw et al developed a DT suitable to track real-time movement of agronomic machines for energy monitoring, economic efficiency, and optimal productivity . DTs can not only control machines but also allow for M2M programming of the robots to interact without human intervention. , …”

Section: Digital Twins In Agricultural Production: Application Demons...mentioning

confidence: 99%

“…While in other industries pieces can be monitored given the homogeneity of the production, DT technology in agriculture is still under development given the high variability of each individual crop as a biomass. However, Verdouw and Kruize presented several applications of DTs in different stages of agriculture processing such as crop storage and agriculture machinery . They focused on livestock monitoring for health detection, identification of pests and diseases in plants, productivity optimization by managing storage availability, and cost-effectiveness evaluation of machinery-mediated treatments.…”

Section: Opportunities Challenges and Perspectivesmentioning

confidence: 99%

“…The combination of these algorithms in neural networks constitutes an essential tool for AI, to prevent events based on previous data processing, facilitating decision-making, and anticipating actions. DTs are consequently a collection of models built on real-data-bases to assess and predict the behavior of physical processes, designed in a format compatible with automated systems to carry out the corresponding actions . As technology continues to advance, the integration of DTs with other emerging technologies such as blockchain, AI, and advanced analytics will likely further enhance their capabilities in transforming agriculture.…”

Section: Digital Twins: Architecture and Componentsmentioning

confidence: 99%

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Digital Twins in Agriculture: Orchestration and Applications

Escribà-Gelonch,

Liang,

van Schalkwyk

et al. 2024

J. Agric. Food Chem.

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Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

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Section: Digital Twins For Agricultural Machinerymentioning

confidence: 99%

Section: Opportunities Challenges and Perspectivesmentioning

confidence: 99%

Section: Digital Twins In Agricultural Production: Application Demons...mentioning

confidence: 99%

Section: Opportunities Challenges and Perspectivesmentioning

confidence: 99%

Section: Digital Twins: Architecture and Componentsmentioning

confidence: 99%

See 3 more Smart Citations

Digital Twins in Agriculture: Orchestration and Applications

Escribà-Gelonch,

Liang,

van Schalkwyk

et al. 2024

J. Agric. Food Chem.

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Digital twins for land-based aquaculture: A case study for rainbow trout (Oncorhynchus mykiss)

Lima¹,

Royer²,

Bolzonella³

et al. 2022

Open Res Europe

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The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout (Oncorhynchus mykiss) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments.

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