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Pork meat quality assessment based on multispectral imaging technique

6 pagesPublished: July 19, 2023

Abstract

Production of pork is a daily objective for both producers and consumers. Pork quality and its economic advantages can be enhanced by using quick, non-destructive, and inexpensive monitoring techniques. This study investigates the potential of using international photos to monitor pork quality. Image processing is done using the ROI- based processing, and then using a specific algorithm for food quality assessment. This allowed structural characteristics to be retrieved from the several photos of flesh tissue. A monochrome camera and four sets of optical filters covering the red (625 nm), green (525 nm), blue (465 nm), and near-IR (940 nm) spectra were employed in this work. In this research, the use of multispectral imaging and chemometrics combined modeling is validated as a non-destructive, quick, low-cost quality control tool that can effectively monitor pork quality. This offers a scientific foundation for the next study and creation of broadly applicable devices for both assessing pork quality and multispectral imaging techniques.

Keyphrases: image processing, multispectral camera, multispectral imaging, non destructive quality assessment, pork

In: Trung Nghia Tran, Quoc Khai Le, Tich Thien Truong, Thanh Nha Nguyen and Hoang Nhut Huynh (editors). Proceedings of International Symposium on Applied Science 2022, vol 5, pages 114-119.

BibTeX entry
@inproceedings{ISAS2022:Pork_meat_quality_assessment,
  author    = {My Ngoc Nguyen Thi and Minh Chau Ta Ngoc and Anh Xuan Nguyen and Huu Tai Duong and Hong Duyen Trinh Tran and Quy Tan Ha},
  title     = {Pork meat quality assessment based on multispectral imaging technique},
  booktitle = {Proceedings of International Symposium on Applied Science 2022},
  editor    = {Trung Nghia Tran and Quoc Khai Le and Tich Thien Truong and Thanh Nha Nguyen and Hoang Nhut Huynh},
  series    = {EPiC Series in Engineering},
  volume    = {5},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/v2Cc},
  doi       = {10.29007/clnh},
  pages     = {114-119},
  year      = {2023}}
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