, Vol.33, No.24

244 2012, Vol.33, No.24 1 1, * 2 1 1 (1. 2. 100193) 81 224 130 1799nm (WBSF) 154 91 (PLS-DA) 100%70 39 96% 90% Discrimination of Meat from Young Bulls and Culled Cows by Near Infrared Reflectance (NIR) Spectroscopy LIU Xiao-ye 1 TANG Xiao-yan 1, * SUN Bao-zhong 2 MAO Xue-fei 1 WANG Min 1 (1. Key Laboratory of Agrifood Safety and Quality, Ministry of Agriculture, Institute of Quality Standards and Testing Technology for Agri-Products, Chinese Academy of Agricultural Sciences, Beijing 81, China 2. Institute of Animal Science for Agri-Products, Chinese Academy of Agricultural Science, Beijing 100193, China) Abstract Meat was sampled from different parts of carcasses of young bulls and culled cows of the same breed from Inner Mongolia and Xinjiang autonomous regions, China. A total 224 and 130 beef samples were obtained from cattle carcasses from Inner Mongolia and Xinjiang autonomous regions, respectively. Fresh and frozen-thawed samples were minced and tested using a portable NIR spectrometer in the range of 1799 nm. Meanwhile, the contents of protein, fat and moisture and Warner-Bratzler shear force (WBSF) were measured. A total of 154 and 91 samples from Inner Mongolia and Xinjiang autonomous regions were selected as modeling sets. Two models for discriminating meat from young bulls and culled cows from both regions were established using partial least squares discriminant analysis (PLS-DA). The established models showed 100% accuracy for discriminating calibration set and validation set and 96% and 90% accuracy for the remaining 70 and 39 beef samples from Inner Mongolia and Xinjiang, respectively. Key words beef classification near infrared reflectance spectroscopy discrimination TS251.7 A 1002-6630(2012)24-0244-05 [1-3] [4-13] DNA [8] 2011-09-26 948 (2011-G5)()(200903012) (2012DFA31140) (1986 )E-mail xiaoye.liu86@gmail.com *(1976 )E-mail txycaas@126.com

2012, Vol.33, No.24 245 1 1.1 1.2 SupNIR- Kjeltec TM 2300Soxtec TM 2050 FossGM2000 Retsch Model 235 G-R Manufacturing 1.3 1.3.1 10 648h14( ) 2247 414154 3214 70 20 4648h13 ( ) 130 341391 1213 39 1.3.2 1799nm 10nm 503 1.3.3 GB/T 9695.11 2008 GB/T 9695.7 2008 GB/T 9695.15 2008 NY/T 1180 1.3.4 Unscrambler(version 9.8 CAMO)(partial least-squares discriminant analysis PLS-DA) SAS/PC(8.0) PLS-DA(PLS) PLS1 Y X 1 2(12) (predictive residual error sum of squares PRESS) PLSR (1 2) 2 2.1 1014 140 614 84 1 1 Table 1 Fat, protein and moisture contents and WBSF of meat from young bulls and culled cows /% /% /% /kg 20.86 1.03 a 1.61 0.94 a 76.11 1.72 a 4.26 1.42 a 21.01 1.12 a 3.33 2.13 b 73.77 2.55 b 6.58 2.41 b (P 01) (P 5) 1 (P 5) (P 01) (P 01) (P 01) [14] 2.2 Fig.1 0.7 0.6 0.4 0.3 0.2 0.1 1 Average NIR spectra [Log(1/R)] of beef samples obtained from young bulls and culled cows of the same breed from Inner Mongolia Mongolia

246 2012, Vol.33, No.24 1799nm 12 Fig.2 0.8 0.7 0.6 0.4 0.3 0.2 2 Average NIR spectra [Log(1/R)] of beef samples obtained from young bulls and culled cows of the same breed from Xinjiang (Savitzky-Golay 11 ) (Savitzky-Golay 9 ) SNVD ( 3 4) 3 4 1150 1210 1395nm Fig.3 3 1D 6 5 4 3 2 1 0 1 2 Average first-order derivative spectra of beef samples obtained from young bulls and culled cows of the same breed from Inner Mongolia Fig.4 4 1D 5 4 3 2 1 0 1 2 Average first-order derivative spectra of beef samples obtained from young bulls and culled cows of the same breed from Xinjiang 2.4 (principal component analysis PCA) PRESS 7 103 ( 5 6)5 6 PC1 PC1 PC3PC3 06 04 02 00 02 04 06 PC2 04 00 PC3 04 PC1 08 03 02 01 01 02 03 04 00 5 X Y Z 123 Fig.5 3D scatter plot of scores corresponding to principal component 1, principal component 2 and principal component 3 for beef samples obtained from young bulls and culled cows of the same breed from Inner Mongolia X Y 0025 0020 0015 0010 PC2 0005 0000 0005 0010 PC1 0015 0020 PC3 006 004 002 000 002 004 006 008 0020 6 Z 0020 0005 0010 0015 0000 0005 0010 0015 123 Fig.6 3D scatter plot of scores corresponding to principal component 1, principal component 2 and principal component 3 for beef samples obtained from young bulls and culled cows of the same breed from Xinjiang 2.5 (PLS-DA) [15] (Savitzky-Golay 5911 ) (multiplication scatter correction MSC) (SNV De-trending)PLS-DA (Savitzky-Golay 11) ( 2)100% 96%(64/70)( 7) R 2 RMSECV RMSEP0.90 0.24 0.26

2012, Vol.33, No.24 247 (Savitzky-Golay 9) SNVD) ( 2) 100%90%(35/39)( 8) R 2 RMSECV RMSEP0.96 0.20 0.21 Tab 2 2 Effect of different pretreatments on modeling /% S-G(5) 1D 7 100 98.7 91.4 S-G(9) 1D 7 100 98.1 94.3 S-G(11) 1D 7 100 100 95.7 S-G(5) 2D 2 100 91.6 70 S-G(9) 2D 4 100 93.5 78.6 S-G(11) 2D 4 100 90.9 80 S-G(11) 1D MSC 8 100 96.1 90 S-G(11) 1D SNVD 7 100 96.1 91.4 S-G(5) 1D 11 100 100 82.5 S-G(9) 1D 10 100 100 84.6 S-G(11) 1D 10 100 100 82.5 S-G(5) 2D 4 10 100 76.9 S-G(9) 2D 6 100 100 76.9 S-G(11) 2D 6 100 100 76.9 S-G(9) 1D MSC 8 100 100 87.2 S-G(9) 1D SNVD 10 100 100 89.7 1D. 2D. MSC. SNVD. SNV De-trending S-G(5). 5 7 Fig.7 2.5 2.0 1.5 1.0 1 2 Distribution of true and predicted values for the prediction clusters from beef samples obtained from young bulls and culled cows of 8 Fig.8 3.0 2.5 2.0 1.5 1.0 the same breed from Inner Mongolia 1 2 Distribution of true and predicted values for the prediction clusters from beef samples obtained from young bulls and culled cows of the same breed from Xinjiang 3 (P 01) Aberle [16] (P 01) Warris [17] ( 1150 1210nm 1395nm) [18] Prieto [8] McDevitt [9] (PLS-DA) R 2 0.90 0.96 RMSECV 0.24 0.20 96% 90% RMSEP 0.26 0.21 Cozzolino [4] 85%Mamani-Linares [5] 95% Alomar [6] 79% 98% Andres [7] Sun Shumin [10] 100% Chen Quansheng [11] 96% [1] PREVOLNIK M, CANDEK-POTOKAR M, SKORJANC D, et al. Predicting intramuscular fat content in pork and beef by near infrared spectroscopy[j]. Journal of Near Infrared Spectroscopy, 2005, 13(2): 77-85.

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