2026-04-17T12:06:03Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/70832022-10-06T00:05:21Zcom_10259_5377com_10259_5086com_10259_2604com_10259_4292com_10259_5363com_10259.4_2519com_10259.4_2512com_10259.4_106com_10259_3592com_10259_3591com_10259_4313col_10259_5378col_10259_4293col_10259_5364col_10259_6199col_10259_3930col_10259_4314

Guembe García, Marta González Ceballos, Lara Arnáiz Alonso, Ana Fernández Muiño, Miguel Ángel Sancho Ortiz, María Teresa Osés Gómez, Sandra María Ibeas Cortes, Saturnino Rovira Carballido, Jordi Melero Gil, Beatriz Represa Pérez, César García Pérez, José Miguel Vallejos Calzada, Saúl 2022-10-05T10:32:16Z 2022-10-05T10:32:16Z 2022-08 1944-8244 http://hdl.handle.net/10259/7083 10.1021/acsami.2c09467 1944-8252 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. The authors gratefully acknowledge the financial support provided by all funders. S.V. received funding from “La Caixa” Foundation (Grant LCF/PR/PR18/51130007). J.M.G. received funding from “Spanish Agencia Estatal de Investigación” (Grant PID2020-113264RB-I00/AEI/10.13039/501100011033). The authors also appreciate the support and collaboration of the company Inforapps for the development of the smartphone application “Colorimetric Titration”. application/pdf eng American Chemical Society ACS Applied Materials & Interfaces. 2022, V. 14, n. 32, p. 37051–37058 https://doi.org/10.1021/acsami.2c09467 info:eu-repo/grantAgreement/Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona//LCF%2FPR%2FPR18%2F51130007 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113264RB-I00/ES/DISEÑO, SINTESIS Y CARACTERIZACION DE POLIMEROS INTELIGENTES. APLICACION DE SENSORES QUIMICOS POLIMERICOS EN CONTROL Y SEGURIDAD ALIMENTARIA Y EN EL AMBITO SANITARIO Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Polymer chemosensory films Sensors Nitrite in meat Colorimetry RGB HSV Color space Química orgánica Alimentos Informática Chemistry, Organic Food Computer science Easy Nitrite Analysis of Processed Meat with Colorimetric Polymer Sensors and a Smartphone App info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion ACS Applied Materials & Interfaces 14 32 37051 37058