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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Application of NIR hyperspectral imaging for discrimination of lamb muscles
Journal of Food Engineering, Volume 104, No. 3, Year 2011
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Description
The potential of near-infrared (NIR) hyperspectral imaging system coupled with multivariate analysis was evaluated for discriminating three types of lamb muscles. Samples from semitendinosus (ST), Longissimus dorsi (LD) and Psoas Major (PM) of Charollais breed were imaged by a pushbroom hyperspectral imaging system with a spectral range of 900-1700 nm. Principal component analysis (PCA) was used for dimensionality reduction, wavelength selection and visualizing hyperspectral data. Six optimal wavelengths (934, 974, 1074, 1141, 1211 and 1308 nm) were selected from the eigenvector plot of PCA and then used for discrimination purpose. The results showed that it was possible to discriminate lamb muscles with overall accuracy of 100% using NIR hyperspectral reflectance spectra. An image processing algorithm was also developed for visualizing classification results in a pixel-wise scale with a high overall accuracy. © 2011 Elsevier Ltd. All rights reserved.
Authors & Co-Authors
Kamruzzaman, M.
Ireland, Dublin
University College Dublin
ElMasry, Gamal
Ireland, Dublin
University College Dublin
Sun, Da-Wen
Ireland, Dublin
University College Dublin
Allen, Paul
Ireland, Carlow
Teagasc - Irish Agriculture and Food Development Authority
Statistics
Citations: 224
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.1016/j.jfoodeng.2010.12.024
ISSN:
02608774