引用本文:
Yong Nian Ni, Wei Lin. Near-infrared spectra combined with partial least squares for pH determination of toothpaste of different brands[J]. Chinese Chemical Letters,
2011, 22(12): 1473-1476.
doi:
10.1016/j.cclet.2011.07.010
Citation: Yong Nian Ni, Wei Lin. Near-infrared spectra combined with partial least squares for pH determination of toothpaste of different brands[J]. Chinese Chemical Letters, 2011, 22(12): 1473-1476. doi: 10.1016/j.cclet.2011.07.010
Citation: Yong Nian Ni, Wei Lin. Near-infrared spectra combined with partial least squares for pH determination of toothpaste of different brands[J]. Chinese Chemical Letters, 2011, 22(12): 1473-1476. doi: 10.1016/j.cclet.2011.07.010
Near-infrared spectra combined with partial least squares for pH determination of toothpaste of different brands
摘要:
Near-infrared spectroscopy (NIR), which is generally used for online monitoring of the food analysis and production process, was applied to determine the internal quality of toothpaste samples. It is acknowledged that the spectra can be significantly influenced by non-linearities introduced by light scatter, therefore, four data preprocessing methods, including off-set correction, 1st-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC), were employed before the date analysis. The multivariate calibration model of partial least squares (PLS) was established and then was used to predict the pH values of the toothpaste samples of different brand. The results showed that the spectral date processed by MSC was the best one for predicting the pH value of the toothpaste samples.
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关键词:
- Toothpaste
- / NIR spectroscopy
- / Partial least squares
- / Preprocessing
- / pH value
English
Near-infrared spectra combined with partial least squares for pH determination of toothpaste of different brands
Abstract:
Near-infrared spectroscopy (NIR), which is generally used for online monitoring of the food analysis and production process, was applied to determine the internal quality of toothpaste samples. It is acknowledged that the spectra can be significantly influenced by non-linearities introduced by light scatter, therefore, four data preprocessing methods, including off-set correction, 1st-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC), were employed before the date analysis. The multivariate calibration model of partial least squares (PLS) was established and then was used to predict the pH values of the toothpaste samples of different brand. The results showed that the spectral date processed by MSC was the best one for predicting the pH value of the toothpaste samples.
-
Key words:
- Toothpaste
- / NIR spectroscopy
- / Partial least squares
- / Preprocessing
- / pH value
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