Premium
Quantitative Detection of Nitrite in Food Samples Based on Digital Image Colourimetry by Smartphone
Author(s) -
Wang Huihui,
Jing Xu,
Bi Xinyuan,
Bai Bing,
Wang Xiaowen
Publication year - 2020
Publication title -
chemistryselect
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 34
ISSN - 2365-6549
DOI - 10.1002/slct.202002406
Subject(s) - nitrite , detection limit , digital image , relative standard deviation , rgb color model , chemistry , linear range , chromatography , image (mathematics) , image processing , computer science , artificial intelligence , nitrate , organic chemistry
A novel colourimetric method for the detection of nitrite in food samples using digital image colourimetry (DIC) by smartphone is developed. Nitrite directly oxidise 3,3′,5,5′‐tetramethylbenzidine (TMB) to form a yellow TMB diimine (oxTMB). A smartphone was used to capture the image of an inherent colour variation and analyse the image with the RGB (red, green, and blue) model, achieving the quantitative detection of nitrite. Linear response for the detection of nitrite was obtained from 10 μmol L −1 to 440 μmol L −1 and the limit of quantification was 2.34 μmol L −1 . The applicability of the method was confirmed by the detection of nitrite in cabbage, pickle, and ham. The recovery was varied in the range from 96.2 % to 108.2 % with a relative standard deviation of less than 5.0 %. The simple, sensitive, and inexpensive method was an alternative for the detection of nitrite in food samples.