Chemometrics Calculations with Microsoft Excel (5)

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  • YOSHIMURA Norio
    United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology,3-5-8 Saiwaicho Fuchu, Tokyo 183-8509 Japan United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology,3-5-8 Saiwaicho Fuchu, Tokyo 183-8509 Japan
  • TAKAYANAGI Masao
    United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology,3-5-8 Saiwaicho Fuchu, Tokyo 183-8509 Japan United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology,3-5-8 Saiwaicho Fuchu, Tokyo 183-8509 Japan

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  • Microsoft Excelを用いたケモメトリクス計算(5)
  • Microsoft Excelを用いたケモメトリクス計算(5)平滑化と数値微分
  • Microsoft Excel オ モチイタ ケモメトリクス ケイサン(5)ヘイカツカ ト スウチ ビブン

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Although chemometrics has become widely used recently for analyzing experimental chemical data, there exist only a few instructions for the proper usage of chemometrics other than those in some introductory books. As the fifth step of chemometrics calculations with Microsoft Excel (Excel), the smoothing and the numerical differentiation of data, which are used for pretreatment of signal and spectra, are performed on worksheets. One of the most famous methods of smoothing and numerical differentiation is the Savitzky Golay method (SG method), which is based on the least-squares method. We developed a smoothing and numerical differentiation method on Excel worksheet. Two worksheets were constructed in this method. One worksheet was for obtaining the smoothing and the numerical differentiation coefficients, which correspond to the convolution coefficients of the SG method. Another worksheet was for the smoothing and the numerical differentiation. In this worksheet, the Gauss function is used as an example. The smoothed and the numerical differentiated data obtained from our method almost agreed with the Gauss function and its derivatives. It was confirmed that the smoothing and the differentiation coefficients obtained from our method are the same as the convolution coefficients of the SG method. Additionally, we found an error in the table of the convolution coefficients of the SG method. These results revealed that our method is practical for the smoothing and the numerical differentiation.

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