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Easy Nitrite Analysis of Processed Meat with Colorimetric Polymer Sensors and a Smartphone App
[Image: see text] We have developed an in situ methodology for determining nitrite concentration in processed meats that can also be used by unskilled personnel. It is based on a colorimetric film-shaped sensory polymer that changes its color upon contacting the meat and a mobile app that automatica...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389542/ https://www.ncbi.nlm.nih.gov/pubmed/35920554 http://dx.doi.org/10.1021/acsami.2c09467 |
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author | Guembe-García, Marta González-Ceballos, Lara Arnaiz, Ana Fernández-Muiño, Miguel A. Sancho, M. Teresa Osés, Sandra M. Ibeas, Saturnino Rovira, Jordi Melero, Beatriz Represa, Cesar García, José M. Vallejos, Saúl |
author_facet | Guembe-García, Marta González-Ceballos, Lara Arnaiz, Ana Fernández-Muiño, Miguel A. Sancho, M. Teresa Osés, Sandra M. Ibeas, Saturnino Rovira, Jordi Melero, Beatriz Represa, Cesar García, José M. Vallejos, Saúl |
author_sort | Guembe-García, Marta |
collection | PubMed |
description | [Image: see text] We have developed an in situ methodology for determining nitrite concentration in processed meats that can also be used by unskilled personnel. It is based on a colorimetric film-shaped sensory polymer that changes its color upon contacting the meat and a mobile app that automatically calculates the manufacturing and residual nitrite concentration by only taking digital photographs of sensory films and analyzing digital color parameters. The film-shaped polymer sensor detects nitrite anions by an azo-coupling reaction, since they activate this reaction between two of the four monomers that the copolymer is based on. The sensory polymer is complemented with an app, which analyzes the color in two different digital color spaces (RGB and HSV) and performs a set of 32 data fittings representing the concentration of nitrite versus eight different variables, finally providing the nitrite concentration of the test samples using the best fitting curve. The calculated concentration of nitrite correlates with a validated method (ISO 2918: 1975) usually used to determine nitrite, and no statistically significant difference between these methods and our proposed one has been found in our study (26 meat samples, 8 prepared, and 18 commercial). Our method represents a great advance in terms of analysis time, simplicity, and orientation to use by average citizens. |
format | Online Article Text |
id | pubmed-9389542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-93895422022-08-20 Easy Nitrite Analysis of Processed Meat with Colorimetric Polymer Sensors and a Smartphone App Guembe-García, Marta González-Ceballos, Lara Arnaiz, Ana Fernández-Muiño, Miguel A. Sancho, M. Teresa Osés, Sandra M. Ibeas, Saturnino Rovira, Jordi Melero, Beatriz Represa, Cesar García, José M. Vallejos, Saúl ACS Appl Mater Interfaces [Image: see text] We have developed an in situ methodology for determining nitrite concentration in processed meats that can also be used by unskilled personnel. It is based on a colorimetric film-shaped sensory polymer that changes its color upon contacting the meat and a mobile app that automatically calculates the manufacturing and residual nitrite concentration by only taking digital photographs of sensory films and analyzing digital color parameters. The film-shaped polymer sensor detects nitrite anions by an azo-coupling reaction, since they activate this reaction between two of the four monomers that the copolymer is based on. The sensory polymer is complemented with an app, which analyzes the color in two different digital color spaces (RGB and HSV) and performs a set of 32 data fittings representing the concentration of nitrite versus eight different variables, finally providing the nitrite concentration of the test samples using the best fitting curve. The calculated concentration of nitrite correlates with a validated method (ISO 2918: 1975) usually used to determine nitrite, and no statistically significant difference between these methods and our proposed one has been found in our study (26 meat samples, 8 prepared, and 18 commercial). Our method represents a great advance in terms of analysis time, simplicity, and orientation to use by average citizens. American Chemical Society 2022-08-03 2022-08-17 /pmc/articles/PMC9389542/ /pubmed/35920554 http://dx.doi.org/10.1021/acsami.2c09467 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Guembe-García, Marta González-Ceballos, Lara Arnaiz, Ana Fernández-Muiño, Miguel A. Sancho, M. Teresa Osés, Sandra M. Ibeas, Saturnino Rovira, Jordi Melero, Beatriz Represa, Cesar García, José M. Vallejos, Saúl Easy Nitrite Analysis of Processed Meat with Colorimetric Polymer Sensors and a Smartphone App |
title | Easy Nitrite Analysis
of Processed Meat with Colorimetric
Polymer Sensors and a Smartphone App |
title_full | Easy Nitrite Analysis
of Processed Meat with Colorimetric
Polymer Sensors and a Smartphone App |
title_fullStr | Easy Nitrite Analysis
of Processed Meat with Colorimetric
Polymer Sensors and a Smartphone App |
title_full_unstemmed | Easy Nitrite Analysis
of Processed Meat with Colorimetric
Polymer Sensors and a Smartphone App |
title_short | Easy Nitrite Analysis
of Processed Meat with Colorimetric
Polymer Sensors and a Smartphone App |
title_sort | easy nitrite analysis
of processed meat with colorimetric
polymer sensors and a smartphone app |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389542/ https://www.ncbi.nlm.nih.gov/pubmed/35920554 http://dx.doi.org/10.1021/acsami.2c09467 |
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