Analytical Sciences

Baseline Noise and Measurement Uncertainty in Liquid Chromatography

Akihito KITAJIMA,*^1,*⁵ Takeshi KASHIRAJIMA,*² Takao MINAMIZAWA,*¹ Hiroyasu SATO,*³ Kazuo IWAKI,*³ Taisuke UEDA,*⁴ Yoshio KIMURA,*⁴ Toshimasa TOYO'OKA,*⁵ Tamio MAITANI,*⁶ Rieko MATSUDA,*⁶ and Yuzuru HAYASHI*⁶

*1 Daiichi Radioisotope Laboratories, 453-1 Shimookura, Matsuo-machi, Sanmu, Chiba 289-1592, Japan
*2 The University of the Air, 2-11 Wakaba, Mihama, Chiba 261-8586, Japan
*3 School of Pharmaceutical Sciences, Ohu University, 31-1 Misumido, Tomita-machi, Koriyama, Fukushima 963-8611, Japan
*4 Hayashi Pure Chemical Ind., Ltd., 3-2-12 Uchihiranomachi, Chuo, Osaka 540-0037, Japan
*5 School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga, Shizuoka 422-8526, Japan
*6 National Institute of Health Sciences, 1-18-1 Kami-Yoga, Setagaya, Tokyo 158-8501, Japan

The stochastic properties of baseline noise in HPLC systems with a UV photo-diode array, photo-multiplier and γ-ray detector were examined by dividing the noise into auto-correlated random process (Markov process) and an independent process (white noise). The present work focused on the effect of the stochastic noise properties on a theoretical estimation of the standard deviation (SD) of area measurements in instrumental analyses. An estimation theory, called FUMI theory (Function of Mutual Information), was taken as an example. A computer simulation of noise was also used. It was shown that the reliability (confidence intervals) of theoretical SD estimates mainly depends on the following factors: the ratio of the white noise and Markov process occurring in the baselines; the number of data points used for the estimation; the width of a target peak for which the SD is estimated.

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