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Development of near infrared reflectance spectroscopy to predict chemical composition with a wide range of variability in beef.

Authors :
Huawei Su
Kun Sha
Li Zhang
Qian Zhang
Yuling Xu
Rong Zhang
Haipeng Li
Baozhong Sun
Source :
Meat Science. Oct2014, Vol. 98 Issue 2, p110-114. 5p.
Publication Year :
2014

Abstract

A total of 182 beef samples were minced and divided into calibration set (n=140) and independent validation set (n=42). Calibration models of NIRS (1000-1800 nm) were built using partial least squares regression (PLSR) on the calibration set of samples. Both the coefficient of determination in calibration (R2C) and the coefficient of determination in prediction (R2P) were over 0.98 for all chemical compositions. The ratio performance deviation (RPD) was 17.37, 5.12 and 10.43 for fat, protein and moisture, respectively. The results of the present study indicate the outstanding ability of NIRS to predict chemical composition in beef. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03091740
Volume :
98
Issue :
2
Database :
Academic Search Index
Journal :
Meat Science
Publication Type :
Academic Journal
Accession number :
97217686
Full Text :
https://doi.org/10.1016/j.meatsci.2013.12.019