Visualization of amino acid composition differences between processed protein from different animal species by self-organizing feature maps |
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| Authors: | Xingfan ZHOU Zengling YANG Longjian CHEN Lujia HAN |
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| Institution: | 1. College of Engineering, China Agricultural University, Beijing 100083, China2. Beijing Key Laboratory of Occupational Health and Safety, Beijing Municipal Institute of Labor Protection, Beijing 100054, China |
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| Abstract: | Amino acids are the dominant organic components of processed animal proteins, however there has been limited investigation of differences in their composition between various protein sources. Information on these differences will not only be helpful for their further utilization but also provide fundamental information for developing species-specific identification methods. In this study, self-organizing feature maps (SOFM) were used to visualize amino acid composition of fish meal, and meat and bone meal (MBM) produced from poultry, ruminants and swine. SOFM display the similarities and differences in amino acid composition between protein sources and effectively improve data transparency. Amino acid composition was shown to be useful for distinguishing fish meal from MBM due to their large concentration differences between glycine, lysine and proline. However, the amino acid composition of the three MBMs was quite similar. The SOFM results were consistent with those obtained by analysis of variance and principal component analysis but more straightforward. SOFM was shown to have a robust sample linkage capacity and to be able to act as a powerful means to link different sample for further data mining. |
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| Keywords: | self-organizing feature maps visualization processed animal proteins (PAPs) amino acid |
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