Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain

Melesse, Tsega Y.; Franciosi, Chiara; Pasquale, Valentina Di; Riemma, Stefano

doi:10.3390/logistics7020033

Cited by 6 publications

(4 citation statements)

References 90 publications

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“…A digital twin is a virtual representation of a physical system that includes the environment and operational procedures and is updated by information exchanged between the physical and virtual systems. It is a gadget that constantly connects its virtual and physical equivalents (the twin) (Van der Burg et al, 2021;Neethirajan and Kemp, 2021;Melesse et al, 2023). The aim of digital twin is to characterize the behaviour of physical entities by leveraging on their virtual replica in real time (Liu et al, 2022).…”

Section: Digital Twinmentioning

confidence: 99%

Reduction of Losses and Wastage in Seafoods: The Role of Smart Tools and Biosensors Based on Artificial Intelligence

AYISI LARBI,

OSEİ

2024

Journal of AI

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This paper reviews current knowledge on the role of smart tools and biosensors based on artificial intelligence in reducing seafood loss and wastage. This study shows that a variety of biosensors, categorised according to how they function, can be used to measure the quality of seafood. These include optical biosensors, enzyme-based biosensors, immunosensors, microbial biosensors, DNA-based biosensors, electrochemical biosensors, optical biosensors, tissue-based biosensors, and piezoelectric biosensors. Among these biosensors, optical biosensors, electrochemical biosensors, and mechanical biosensors are the most significant. Again, this study report that, for seafood traceability and management, a variety of smart solutions including blockchain technology, quick response (QR) codes, data analytics, digital twins, and radio frequency identification (RFID) tags can be utilised. Catch data, vessel tracking data, and data from the processing plant are some of the different data sources that can be utilised to trace seafood products. Artificial intelligence tools like neural networks, deep learning, machine learning, and others can be used to forecast and improve seafood quality. It is crucial to study the development of biosensors that can properly identify the earliest signs of seafood contamination or rotting.

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Section: Digital Twinmentioning

confidence: 99%

Reduction of Losses and Wastage in Seafoods: The Role of Smart Tools and Biosensors Based on Artificial Intelligence

AYISI LARBI,

OSEİ

2024

Journal of AI

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“…Although digital twinning technology has not been specifically used in the traceability of NMs and NPs in foods, it has the potential to enhance food safety and quality control by enabling real-time monitoring and data transmission (Melesse et al, 2023). Digital twinning technology can be utilized to simulate and optimize NM production and waste management processes.…”

Section: Digital Twinning Technologymentioning

confidence: 99%

Definition, detection, and tracking of nanowaste in foods: Challenges and perspectives

Çiçek,

Yilmaz,

Hadnađev

et al. 2024

Comp Rev Food Sci Food Safe

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Commercial applications of nanotechnology in the food industry are rapidly increasing. Accordingly, there is a simultaneous increase in the amount and diversity of nanowaste, which arise as byproducts in the production, use, disposal, or recycling processes of nanomaterials utilized in the food industry. The potential risks of this nanowaste to human health and the environment are alarming. It is of crucial significance to establish analytical methods and monitoring systems for nanowaste to ensure food safety. This review provides comprehensive information on nanowaste in foods as well as comparative material on existing and new analytical methods for the detection of nanowaste. The article is specifically focused on nanowaste in food systems. Moreover, the current techniques, challenges as well as potential use of new and progressive methods are underlined, further highlighting advances in technology, collaborative efforts, as well as future perspectives for effective nanowaste detection and tracking. Such detection and tracking of nanowaste are required in order to effectively manage this type ofwasted in foods. Although there are devices that utilize spectroscopy, spectrometry, microscopy/imaging, chromatography, separation/fractionation, light scattering, diffraction, optical, adsorption, diffusion, and centrifugation methods for this purpose, there are challenges to be overcome in relation to nanowaste as well as food matrix and method characteristics. New technologies such as radio‐frequency identification, Internet of things, blockchain, data analytics, and machine learning are promising. However, the cooperation of international organizations, food sector, research, and political organizations is needed for effectively managing nanowaste. Future research efforts should be focused on addressing knowledge gaps and potential strategies for optimizing nanowaste detection and tracking processes.

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“…The logistics industry is broad, with studies focusing on the need to apply technological applications in different aspects of operations such as RFID adoption [21], technology forecasting framework [22], inventory management [23], humanitarian logistics [24], digital marketing [25], digitisation [26], automation of warehousing [27,28], supply chain management [29], and [30] explored the implications of adopting industry 5.0 for smart logistics, etc.…”

Section: Effects Of Technological Applications In the Aviation Logist...mentioning

confidence: 99%

Adopting Technological Innovations in the Air Cargo Logistics Industry in South Africa

Adenigbo,

Mageto,

Luke

2023

Logistics

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Background: The air cargo logistics industry has been deemed reluctant to adopt new technologies for their business operations. So, this study aims to examine the adoption of technological innovations in the air cargo logistics industry in South Africa. The specific objective is to emphasise the effects of technologies on air cargo logistics operations to address the reluctance to adopt technological innovations in the industry. Methods: A questionnaire survey was conducted randomly on three hundred and seventy-three (373) cargo agents at the OR Tambo International Airport. The data were subjected to a nonparametric test with Kruskal–Wallis, exploratory factor analysis and regression analysis to explore the effects of technologies for prompt adoption and implementation of emerging innovations that enhance quality service delivery. Results: The study found that promptly adopting emerging technological innovations in the air cargo logistics industry promotes efficient operations, improves warehousing, and enhances cargo delivery services for customer satisfaction. Also, the study established that technologically driven operations and warehousing are significant determinants of quality service delivery in the air cargo logistics industry. Conclusions: This study encourages the prompt adoption and implementation of technological innovations for improved quality service delivery, customer satisfaction, and loyalty in the air cargo logistics industry.

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Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain

Cited by 6 publications

References 90 publications

Reduction of Losses and Wastage in Seafoods: The Role of Smart Tools and Biosensors Based on Artificial Intelligence

Reduction of Losses and Wastage in Seafoods: The Role of Smart Tools and Biosensors Based on Artificial Intelligence

Definition, detection, and tracking of nanowaste in foods: Challenges and perspectives

Adopting Technological Innovations in the Air Cargo Logistics Industry in South Africa

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