2023
doi: 10.12720/jait.14.5.1088-1095
Applying an Image Technology to Estimates Values of Nitrite in Processed Meat Products
Tippaya Thinsungnoen1,*
,
Jessada Rattanasuporn2 ,
Manoch Thinsungnoen2 ,
Thanakorn Pluangklang3 ,
Vanida Choomuenwai3 ,
Chareonsak Lao-ngam3 ,
Panadda Phansamdaeng3 ,
Chutima Pluangklang3 ,
Maliwan Subsadsana3
- 1Information Technology Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand
- 2Computer Science Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand
- 3Chemistry Program, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Thailand
- Manuscript receivedMarch 3, 2023
- revisedMay 23, 2023
- acceptedJuly 11, 2023
- publishedOctober 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
How to 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. https://doi.org/10.12720/jait.14.5.1088-1095
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
