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Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs

BACKGROUND: Live bivalve molluscs, echinoderms, tunicates and marine gastropod are referred in EU food laws, and require member states to implement official controls in classified production areas, with the monitoring and classification of those areas. If, due to contaminant tests results, a product...

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Autores principales: da Costa, Manuel Beja, Jurczuk, Magdalena, Marques, Bernardo, Silva, João Nuno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761835/
https://www.ncbi.nlm.nih.gov/pubmed/30815683
http://dx.doi.org/10.1093/eurpub/ckz018
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author da Costa, Manuel Beja
Jurczuk, Magdalena
Marques, Bernardo
Silva, João Nuno
author_facet da Costa, Manuel Beja
Jurczuk, Magdalena
Marques, Bernardo
Silva, João Nuno
author_sort da Costa, Manuel Beja
collection PubMed
description BACKGROUND: Live bivalve molluscs, echinoderms, tunicates and marine gastropod are referred in EU food laws, and require member states to implement official controls in classified production areas, with the monitoring and classification of those areas. If, due to contaminant tests results, a production area is closed, any product from there is prohibited to be commercialized. Mobile applications optical character recognition (OCR) functionalities could ease the access to contaminant levels and production area classifications. This study verifies what information is available in live bivalves’ labels, describes an OCR algorithm for those labels and evaluates it. METHODS: 86 labels were selected from four sale points in Lisbon, and photographed using smartphones. Each label was evaluated by a human to determine what data was available (either required or not). An OCR algorithm was developed and applied on the collected labels and validated against the data extracted by the human analysis. RESULTS: The analysis shows that all the labels included the required information, and 63% of the labels included the identifier for the production zone. The label-reading algorithm performs with an accuracy of 79.85% for the individual values. CONCLUSION: High accuracy of the developed label-reading algorithm shows potential for providing instant automatic access to the date and production area, but is affected by the variability on the label structure. Although not required by food laws, the majority of the sampled labels included complementary information (classified production area) that will allow access to more precise information about the existing biotoxin tests and analysis results.
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spelling pubmed-67618352019-10-02 Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs da Costa, Manuel Beja Jurczuk, Magdalena Marques, Bernardo Silva, João Nuno Eur J Public Health Food and Nutrition BACKGROUND: Live bivalve molluscs, echinoderms, tunicates and marine gastropod are referred in EU food laws, and require member states to implement official controls in classified production areas, with the monitoring and classification of those areas. If, due to contaminant tests results, a production area is closed, any product from there is prohibited to be commercialized. Mobile applications optical character recognition (OCR) functionalities could ease the access to contaminant levels and production area classifications. This study verifies what information is available in live bivalves’ labels, describes an OCR algorithm for those labels and evaluates it. METHODS: 86 labels were selected from four sale points in Lisbon, and photographed using smartphones. Each label was evaluated by a human to determine what data was available (either required or not). An OCR algorithm was developed and applied on the collected labels and validated against the data extracted by the human analysis. RESULTS: The analysis shows that all the labels included the required information, and 63% of the labels included the identifier for the production zone. The label-reading algorithm performs with an accuracy of 79.85% for the individual values. CONCLUSION: High accuracy of the developed label-reading algorithm shows potential for providing instant automatic access to the date and production area, but is affected by the variability on the label structure. Although not required by food laws, the majority of the sampled labels included complementary information (classified production area) that will allow access to more precise information about the existing biotoxin tests and analysis results. Oxford University Press 2019-10 2019-02-27 /pmc/articles/PMC6761835/ /pubmed/30815683 http://dx.doi.org/10.1093/eurpub/ckz018 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Food and Nutrition
da Costa, Manuel Beja
Jurczuk, Magdalena
Marques, Bernardo
Silva, João Nuno
Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title_full Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title_fullStr Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title_full_unstemmed Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title_short Evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
title_sort evaluation of new approaches to the access of official monitoring results for live bivalves molluscs
topic Food and Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761835/
https://www.ncbi.nlm.nih.gov/pubmed/30815683
http://dx.doi.org/10.1093/eurpub/ckz018
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