Applying an Image Technology to Estimates Values of Nitrite in Processed Meat Products

Abstract

—Potassium nitrite or saltpeter is used as a food additive and preservative. It confers a fresh and appetizing appearance to food when used in moderation. However, when used in excess, it may lead to cancer. In the present study, an image-processing mobile application was developed for quality control and ensure the hygiene of food products. The developed application is a user-friendly innovation that would raise the quality standards of processed foods, allowing for a competitive edge in the market. The main objectives of the present study were to identify the representatives of each class of suitable color tones and then develop a model-based application for estimating the content of nitrite in processed meat products. The study was conducted in six steps: (1) image layer separation of RGB to three layers comprising the R-G-B layers; (2) identification of the representatives of each class of suitable color tones using the k-means clustering technique; (3) deciphering the linear equations representing the linear relationship between the color tone and the content of nitrite; (4) designing of a mobile application for estimating the amount of nitrite based on an image; (5) development of the model-based mobile application for estimating the nitrite content; (6) evaluation of the developed mobile application using the testing dataset. The results revealed that the mean and median of the green color’s layer were appropriate representatives of the image dataset and could also be associated with the concentration of the nitrite standard solution. In addition, the efficiency of estimating the concentration of nitrite in meat products using the paper analytical apparatus was 88.25%.