Cured and processed meats, such as salami or bacon, are often treated with nitrite or nitrate salts to keep them fresh. Nitrate can be converted to the more reactive nitrite in the body. Nitrite can then form nitrosamines, which have been linked to the development of various cancers. Existing methods for determining nitrite levels in foods are often not consumer-friendly and can require expensive instruments and labor-intensive techniques.
José M. García, Saúl Vallejos, Universidad de Burgos, Spain, and colleagues have developed an easy-to-use nitrite quantification system. The researchers created a colorimetric polymer film they call “POLYSEN”, short for “polymeric sensor”. The film was prepared via a bulk radical polymerization of four different monomers, i.e., N-vinylpyrrolidone (VP), methylmethacrylate (MMA), 4-aminostyrene (SNH2), and N-(3-hydroxyphenyl)methacrylamide (HPMA) in a molar ratio of 45:45:5:5, followed by an acid treatment with HCl.
Small disks made from the material were placed on meat samples for 15 min, allowing the components of the film to react with nitrite in an azo coupling reaction. The disks were then removed and dipped in a sodium hydroxide solution to develop the color. When nitrite is present, the film’s yellowish hue darkens. To translate the color change into a nitrite concentration, the researchers used a smartphone app they created. The app self-calibrates using a chart of reference disks photographed in the same image as the sample disk.
The team tested the film on meats they prepared and treated with nitrite, as well as store-bought meats. They found that the developed method produced results similar to a reference nitrite detection method. According to the researchers, the approach could provide a user-friendly and inexpensive way for consumers to determine nitrite levels in foods.
- Easy Nitrite Analysis of Processed Meat with Colorimetric Polymer Sensors and a Smartphone App,
Marta Guembe-García, Lara González-Ceballos, Ana Arnaiz, Miguel A. Fernández-Muiño, M. Teresa Sancho, Sandra M. Osés, Saturnino Ibeas, Jordi Rovira, Beatriz Melero, Cesar Represa, José M. García, Saúl Vallejos,
ACS Appl. Mater. Interfaces 2022.