Spatial-temporal event analysis as a prospective approach for signalling emerging food fraud-related anomalies in supply chains

Ana M. Jiménez-Carvelo; Pengfei Li; Sara W. Erasmus; Hui Wang; Saskia M. van Ruth

doi:10.3390/foods12010061

Spatial-temporal event analysis as a prospective approach for signalling emerging food fraud-related anomalies in supply chains

Ana M. Jiménez-Carvelo, Pengfei Li, Sara W. Erasmus, Hui Wang, Saskia M. van Ruth^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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Abstract

One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.

Original language	English
Article number	61
Journal	Foods
Volume	12
Issue number	1
Early online date	22 Dec 2022
DOIs	https://doi.org/10.3390/foods12010061
Publication status	Published - 01 Jan 2023

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10.3390/foods12010061Licence: CC BY

Spatial-temporal event analysis as a prospective approach for signalling emerging food fraud-related anomalies in supply chains
Copyright 2022 the authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
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abstract = "One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.",

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AU - Jiménez-Carvelo, Ana M.

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AU - Wang, Hui

AU - van Ruth, Saskia M.

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N2 - One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.

AB - One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.

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Spatial-temporal event analysis as a prospective approach for signalling emerging food fraud-related anomalies in supply chains

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