| 光谱学与光谱分析 |
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| Research on Prediction Chemical Composition of Beef by Near Infrared Reflectance Spectroscopy |
| SUN Xiao-ming1, 2, LU Ling2, ZHANG Jia-cheng1, ZHANG Song-shan2, SUN Bao-zhong2* |
1.Institute of Animal Husbandry and Veterinary, Chinese Academy of Agricultural Sciences，Beijing 100193, China
2.Food Science Department of Qingdao Agricultural University, Qingdao 266109, China |
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Abstract This study established a near infrared reflectance spectroscopy models for exactly predicting the fat, protein and moisture of the ground and mince beef on line. Using our country’ SupNIR-1000 near infrared spectrometer, the models were set up by artificial neural network (ANN). Related coefficient of calibration (rC) of fat model of mince was 0.971 and related coefficient of prediction (rP) was 0.972.The protein’ rC and RP were 0.952 and 0.949, respectively. The moisture’ rC and rP were 0.938 and 0.927, respectively.Using ground beef established models, the fat’ rC and rP were 0.935 and 0.810; the protein’ rC and rP were 0.954 and 0.868; the moisture’ rC and rP were 0.930 and 0.913, respectively. So near infrared reflectance spectroscopy can better detect the fat, protein and moisture of mince than ground beef. But basically the ground beef model also can be used to quickly predict the chemical composition on line.
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Received: 2010-04-23
Accepted: 2010-08-02
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Corresponding Authors:
SUN Bao-zhong
E-mail: sunbaozhong@yahoo.com.cn
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