The Quantitative Analysis for Cereal s Components by Artificial Neural Networks

Abstract

Abstract: Cereal' s eight components (the concentration between10^-1～10^-3), that is, protein (Pro), fat(Fat), leucine(Leu), isoleucine(Ile), valine(Val), threonine(Thr), phenylalanine(Phe) and lysine(Lys) were quantitatively analyzed by Artificial Neural Networks.For the eight components the prediction correlation coefficients (R) are 0.969, 0.892, 0.897, 0.884, 0.970, 0,860, 0.854, 0.899, and the coefficients of variability are 2.66%, 5, 39%, 7.62%, 7.06%, 2.97%, 7, 83%, 13.38%, 2.68% respectively.These results are superior to those of SRA, and have no systematical errors with classical chemistry' s methods.

Key words: Artificial neural networks, Quantitative analysis, Cereal

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JI Hai-Yan, YAN Yan-Lu . The Quantitative Analysis for Cereal s Components by Artificial Neural Networks[J]. Chem. J. Chinese Universities, 1993, 14(5): 618.

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The Quantitative Analysis for Cereal s Components by Artificial Neural Networks

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