Met-myoglobin is a major component related to meat discoloration, and it gradually accumulates over time after the meat is slaughtered. Recently, studies have been conducted to observe the changes in the composition of met-myoglobin in the meat along with its storage time using Diffuse Reflectance Spectroscopy(DRS). DRS is an optical technique that is simple and can estimate the composition of chromophores without damaging the sample. However, since DRS requires high resolution and complicated fitting process, it is difficult to apply DRS to the mobile environment. Therefore, the purpose of our study is to classify the freshness of meat by extracting features from low spectral resolution diffuse reflectance spectrum by using the deep learning model. To improve the generality of the model, a data augmentation was used. To consider the applicability at low-resolution spectrometer, the diffuse reflectance spectrum was down-sampled 5, 10, 30 and 50 times.

Date Published: 9 March 2020
PDF
Proc. SPIE 11243, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVIII, 112431C (9 March 2020); doi: 10.1117/12.2545967

Published in SPIE Proceedings Vol. 11243:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVIII
Daniel L. Farkas; Attila Tarnok, Editor(s)