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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Non-destructive assessment of instrumental and sensory tenderness of lamb meat using NIR hyperspectral imaging
Food Chemistry, Volume 141, No. 1, Year 2013
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Description
The purpose of this study was to develop and test a hyperspectral imaging system (900-1700 nm) to predict instrumental and sensory tenderness of lamb meat. Warner-Bratzler shear force (WBSF) values and sensory scores by trained panellists were collected as the indicator of instrumental and sensory tenderness, respectively. Partial least squares regression models were developed for predicting instrumental and sensory tenderness with reasonable accuracy (Rcv = 0.84 for WBSF and 0.69 for sensory tenderness). Overall, the results confirmed that the spectral data could become an interesting screening tool to quickly categorise lamb steaks in good (i.e. tender) and bad (i.e. tough) based on WBSF values and sensory scores with overall accuracy of about 94.51% and 91%, respectively. Successive projections algorithm (SPA) was used to select the most important wavelengths for WBSF prediction. Additionally, textural features from Gray Level Co-occurrence Matrix (GLCM) were extracted to determine the correlation between textural features and WBSF values. © 2013 Elsevier Ltd. All rights reserved.
Authors & Co-Authors
Kamruzzaman, M.
Ireland, Dublin
National University of Ireland
ElMasry, Gamal
Ireland, Dublin
National University of Ireland
Sun, Da-Wen
Ireland, Dublin
National University of Ireland
Allen, Paul
Ireland, Carlow
Teagasc - Irish Agriculture and Food Development Authority
Statistics
Citations: 183
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.1016/j.foodchem.2013.02.094
ISSN:
03088146