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JAIT 2023 Vol.14(5): 1088-1095
doi: 10.12720/jait.14.5.1088-1095

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

Tippaya Thinsungnoen 1,*, Jessada Rattanasuporn 2, Manoch Thinsungnoen 2, Thanakorn Pluangklang 3, Vanida Choomuenwai 3, Chareonsak Lao-ngam 3, Panadda Phansamdaeng 3, Chutima Pluangklang 3, and Maliwan Subsadsana 3
1. Information Technology Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand
2. Computer Science Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand; Email: jessada.r@nrru.ac.th (J.R.), manoch.t@nrru.ac.th (M.T.)
3. Chemistry Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand;
Email: thanakorn.p@nrru.ac.th (T.P.), vanida.c@nrru.ac.th (V.C.), charoensak.l@nrru.ac.th (C.L.), panadda.p@nrru.ac.th (P.P), chutima.p@nrru.ac.th (C.P.), Suebsadsana@gmail.com (M.S.)
*Correspondence: tippayasot@hotmail.com (T.T.)

Manuscript received March 3, 2023; revised May 23, 2023; accepted July 11, 2023; published October 20, 2023.

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%.
 
Keywords—image processing, mobile application, linear equation, k-means clustering, microfluidic paper-based

Cite: Tippaya Thinsungnoen, Jessada Rattanasuporn, Manoch Thinsungnoen, Thanakorn Pluangklang, Vanida Choomuenwai, Chareonsak Lao-ngam, Panadda Phansamdaeng, Chutima Pluangklang, and Maliwan Subsadsana, "Applying an Image Technology to Estimates Values of Nitrite in Processed Meat Products," Journal of Advances in Information Technology, Vol. 14, No. 5, pp. 1088-1095, 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.

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