| 光谱学与光谱分析 |
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| Determination of Four Contents of Feedstuff Powder Using Near Infrared Spectroscopy by PLS-BP Model |
| LIU Bo-ping1,2,QIN Hua-jun3,LUO Xiang2,4,CAO Shu-wen3 ,WANG Jun-de1* |
1. College of Chemical Engineering, Nanjing University of Science and Technology, Nanjing 210094，China
2. Analytical and Testing Center of Jiangxi Province, Nanchang 330029, China
3. Key Laboratory of Food Science of MOE, Nanchang University, Nanchang 330047, China
4. Department of Chemistry, Nanchang University, Nanchang 330047, China |
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Abstract Partial least squares (PLS) and artificial neural networks (ANN) prediction model for four components of feedstuff has been established with good veracity and recurrence. The spectra put into the model should be processed by second derivative and standard normal variate (SNV). Ten principal components compressed from original data by PLS and two peak values were taken as the inputs of Back-Propagation Network (BP)，while four predictive targets as outputs, according to Kolmogorov theorem and experiment, and twenty three nerve cells were taken as hidden nodes. Its training iteration times was supposed to be 10 000. Prediction deciding coefficient of four components by the model are 0.9950, 0.9980, 0.9990 and 0.9670, while the standard deviation of an unknown sample scanned parallelly are 0.027 74, 0.048 53, 0.032 92 and 0.022 04.
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Received: 2006-07-18
Accepted: 2006-10-26
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Corresponding Authors:
WANG Jun-de
E-mail: jdwang@mail.njust.edu.cn
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| Cite this article: |
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LIU Bo-ping,QIN Hua-jun,LUO Xiang, et al. Determination of Four Contents of Feedstuff Powder Using Near Infrared Spectroscopy by PLS-BP Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(10): 2005-2009.
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| URL: |
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https://www.gpxygpfx.com/EN/Y2007/V27/I10/2005 |
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