SHORT COMMUNICATION
Use of discriminant analysis on NIRS to detect meat-and-bone meal content in ruminant concentrates
Z. Yang 1,2
,
 
L. Han 1,2
,
 
Q. Li 1,2
,
 
X. Fan 3
 
 
 
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1
College of Engineering, China Agricultural University, Beijing 100083, P.R. China
2
Key Laboratory of Modern Precision Agriculture System Integration, Ministry of Education, Beijing 100083, P.R. China
3
Institute of Quality and Standards for Agri-Product, Chinese Academy, of Agricultural Sciences, Beijing 100081, P.R. China
CORRESPONDING AUTHOR
L. Han   

College of Engineering, China Agricultural University, Beijing 100083, P.R. China
Publication date: 2007-09-17
 
J. Anim. Feed Sci. 2007;16(Suppl. 2):442–447
 
KEYWORDS
ABSTRACT
A purpose of this study was to demonstrate the feasibility of using near infrared reflectance spectroscopy (NIRS) to identify MBM (meat-and-bone meal) in the ruminant concentrates. A partial least squares discriminant analysis equation was developed with 235 samples and validated with 59 samples. A calibration model was developed based on spectra region from 1100 to 2498 nm with mathematic pretreatment 2,4,4,1 and with scatter correction SNVDT (the standard normal variate-detrending). For external validation, there was the accurately discriminant rate of 100%. The results indicated that NIRS could provide a rapidly method for detecting the adulteration of ruminant concentrates with MBM.
 
CITATIONS (5):
1.
A Markov random field based approach to the identification of meat and bone meal in feed by near-infrared spectroscopic imaging
Xunpeng Jiang, Zengling Yang, Lujia Han
Analytical and Bioanalytical Chemistry
 
2.
The Potential of near Infrared Microscopy to Detect, Identify and Quantify Processed Animal by-Products
Zengling Yang, Lujia Han, Juan Antonio Fernández Pierna, Pierre Dardenne, Vincent Baeten
Journal of Near Infrared Spectroscopy
 
3.
Computer and Computing Technologies in Agriculture X
Lianping Jia, Peng Jiao, Junning Zhang, Zhen Zeng, Xunpeng Jiang
 
4.
Validation of a near infrared microscopy method for the detection of animal products in feedingstuffs: results of a collaborative study
A. Boix, J.A. Pierna, Holst von, V. Baeten
Food Additives & Contaminants: Part A
 
5.
A Review on the Use of Near-Infrared Spectroscopy for Analyzing Feed Protein Materials
Longjian Chen, Zengling Yang, Lujia Han
Applied Spectroscopy Reviews
 
ISSN:1230-1388