引用本文:
Yan Qing Chen, Yong Nian Ni. Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks[J]. Chinese Chemical Letters,
2009, 20(5): 615-619.
doi:
10.1016/j.cclet.2009.01.006
Citation: Yan Qing Chen, Yong Nian Ni. Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks[J]. Chinese Chemical Letters, 2009, 20(5): 615-619. doi: 10.1016/j.cclet.2009.01.006
Citation: Yan Qing Chen, Yong Nian Ni. Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks[J]. Chinese Chemical Letters, 2009, 20(5): 615-619. doi: 10.1016/j.cclet.2009.01.006
Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks
摘要:
Benzoic acid (BA), methylparaben (MP), propylparaben (PP) and sorbic acid (SA) are food preservatives, and they have well defined UV spectra. However, their spectra overlap seriously, and it is difficult to determine them individually from their mixtures without preseparation. In this paper, seven different chemometric approaches were applied to resolve the overlapping spectra and to determine these compounds simultaneously. With respect to the criteria of% relative prediction error (RPE) and% recovery,principal component regression (PCR) and radial basis function-artificial neural network (RBF-ANN) were the preferred methods.These two methods were successfully applied to the analysis of some commercial samples.
English
Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks
Abstract:
Benzoic acid (BA), methylparaben (MP), propylparaben (PP) and sorbic acid (SA) are food preservatives, and they have well defined UV spectra. However, their spectra overlap seriously, and it is difficult to determine them individually from their mixtures without preseparation. In this paper, seven different chemometric approaches were applied to resolve the overlapping spectra and to determine these compounds simultaneously. With respect to the criteria of% relative prediction error (RPE) and% recovery,principal component regression (PCR) and radial basis function-artificial neural network (RBF-ANN) were the preferred methods.These two methods were successfully applied to the analysis of some commercial samples.
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Key words:
- Spectrophotometry
- / Preservatives
- / Multivariate calibration
- / Artificial neural networks
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