Journal ArticleDOI
Visualising food traceability systems: A novel system architecture for mapping material and information flow
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TLDR
A novel, material and information flow modelling technique, to visualise FTS architecture, which can support common understanding and iterative implementation of effective FTSs that contextualise food supply chains at multiple levels and provides opportunity to identify points at where inefficiencies can occur so that actions can be taken to mitigate them.Abstract:
Background Traceability of food products, ingredients and associated operations are important requirements for improving food safety and consumer confidence. Food traceability systems (FTSs) often suffer from inefficiency in either material or information flow within an enterprise or between supply chain partners. Modelling of system architecture is a visualisation approach that allows multiple parties to collaborate in a system design process, identify its inefficiencies and propose improvements. However, there is little academic research on the ability to use a standard visualisation tool that supports collaborative design and considers both material and information flow for a given food traceability system. Scope & approach The aim of this research is to propose a new visualisation approach that allows supply chain operators to collaborate effectively in the design process of FTSs capable of maintaining streamlined information flow, minimising information loss, and improving supply chain performance. Key findings & conclusion Food traceability systems are complex, encompassing processes, material flow, information flow, techniques, infrastructure, people and control strategies. Screening of literature demonstrates that model-based system engineering (MBSE) offers a sound way for visualisation of such complex systems. However, in the food traceability literature, an MBSE-based standardised traceability system modelling approach is absent. This study makes a strong contribution to existing literature by proposing a novel, material and information flow modelling technique (MIFMT), to visualise FTS architecture. MIFMT can support common understanding and iterative implementation of effective FTSs that contextualise food supply chains at multiple levels and provides opportunity to identify points at where inefficiencies can occur so that actions can be taken to mitigate them.read more
Citations
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Journal ArticleDOI
Trends and challenges on fruit and vegetable processing: Insights into sustainable, traceable, precise, healthy, intelligent, personalized and local innovative food products
Xue Liu,Carine Le Bourvellec,Jiahao Yu,Lei Zhao,Kai Wang,Yang Tao,Catherine M.G.C. Renard,Zhuo Yan Hu +7 more
TL;DR: In this article , a comprehensive exploration of the challenges, future trends and solutions for F&Veg post-harvest and processing to counter F&Veeg losses and waste, and to promote food consumption and sustainable development is presented.
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A Hybrid Traceability Technology Selection Approach for Sustainable Food Supply Chains
TL;DR: A hybrid approach combining the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with integer linear programming to select the optimum traceability technologies for improving sustainable performance in cold food supply chains is presented.
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Systematic assessment of food traceability information loss: A case study of the Bangladesh export shrimp supply chain
TL;DR: In this paper , the authors developed a systematic information loss assessment technique, modifying and integrating Failure mode effect and criticality analysis (FMECA) and a traceability modelling tool, Material and information flow modelling technique (MIFMT).
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Blockchain for Food Tracking
TL;DR: It was concluded that 97.54% of the participants using the established system found the application useful and wanted such an application to become widespread, and a value of 0.038 s for latency is 435 times better than Ethereum, one of the most popular blockchain infrastructures.
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Unsupervised Outlier Detection Mechanism for Tea Traceability Data
TL;DR: Wang et al. as discussed by the authors proposed an unsupervised outlier detection mechanism for tea traceability data, in which the data is preprocessed to aggregate features based on relevance, which makes it easier to identify abnormal features.
References
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Journal ArticleDOI
Traceability of food products: General framework and experimental evidence
TL;DR: The aim of this paper is to provide a general framework for the identification of fundamental mainstays and functionalities in an effective traceability system used by Parmigiano Reggiano (the famous Italian cheese) which was developed using the proposed general framework.
Proceedings ArticleDOI
A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things
TL;DR: A food supply chain traceability system for real-time food tracing based on HACCP, blockchain and Internet of things, which could provide an information platform for all the supply chain members with openness, transparency, neutrality, reliability and security is built and a new concept BigchainDB is introduced to fill the gap in the decentralized systems at scale.
Journal ArticleDOI
Food traceability as an integral part of logistics management in food and agricultural supply chain
Techane Bosona,Girma Gebresenbet +1 more
TL;DR: A comprehensive literature review on food traceability issues is presented in this article, where the authors reviewed about 74 studies, mainly focusing on food tracing issues and published during 2000-2013.
Journal ArticleDOI
Perspectives on traceability in food manufacture
TL;DR: In this article, the authors outline the fundamental theoretical issues of traceability systems and present a more practical discussion of its extent in the food industry, and discuss the benefits of well-thought-out traceability strategies.
Journal ArticleDOI
Blockchain-Based Soybean Traceability in Agricultural Supply Chain
TL;DR: This paper proposes an approach that leverages the Ethereum blockchain and smart contracts efficiently perform business transactions for soybean tracking and traceability across the agricultural supply chain, eliminating the need for a trusted centralized authority, intermediaries and provides transactions records, enhancing efficiency and safety with high integrity, reliability, and security.