Abstract Near infrared (NIR) spectra in the 1300– 1850 nm region were measured for control serum solu- tions containing both albumin and γ-globulin of various concentrations. Partial least squares two (PLS2) regres- sion was applied to the NIR spectra to determine simulta- neously the concentrations of both proteins. For albumin, the correlation coefficient (R) of 0.988, the standard error of calibration (SEC) of 1.61 g/L, the standard error of pre- diction (SEP) of 1.29 g/L, the relative standard deviation (RSD) of 0.026 and the ratio of standard deviation of ref- erence data in prediction to SEP (RPD) of 12.2 were ob- tained. For γ-globulin, the corresponding values were 0.997, 1.36 g/L, 1.35 g/L, 0.0365 and 8.66, respectively. The regression coefficients (RCs) of PLS factors were compared between albumin and γ-globulin, and the ob- served differences in the RCs were discussed based upon the differences in the hydration between albumin and γ-globulin. In order to explore the effects of various metabo- lites such as glucose, and cholesterol on the chemometrics models, the RCs for albumin and γ-globulin in the control serum solutions were also compared with those for albu- min and γ-globulin in phosphate buffer solutions previ- ously studied. The results of our experiments show that NIR spectroscopy with the use of PLS2 regression has considerable promise in nondestructive determination of the concentrations of blood serum proteins. 1 Introduction The quantitative determination of blood proteins is very important in clinical test, diagnosis, and therapy because the concentration of each protein in blood varies with the conditions of health. Nowadays, the concentrations of hu- man serum albumin and γ-globulin are determined by electrophoresis and the Biuret method. The present meth- ods have acceptable accuracy and precision, but they re- quire considerable amounts of blood and various kinds of reagents. Therefore, if we consider the burden to a patient, escalating health care costs, and environmental problems, it is desirable to develop a more rapid, more efficient, less expensive, and reagentless method for the blood test. Near-infrared (NIR) spectroscopy in combination with multivariate analysis holds considerable promise as a new method for determining the concentrations of various metabolites in blood because it has the following advan- tages [1–21]. First, it is a nondestructive analytical tech- nique. Second, no or little reagents are needed for the NIR analysis. Third, multicomponent analysis may be possi- ble. In addition, it requires minimal technical expertise and no or little sample manipulation. We have started investigations for multivariate deter- mination of serum albumin and γ-globulin in blood by NIR spectroscopy with the aim of developing a NIR mul- ticomponent assay of blood substrates [20, 21]. In the first paper, we reported on determination of the concentration of albumin in a phosphate buffer solution and of the con- centration of γ-globulin in a separate buffer solution by use of NIR spectroscopy and multivariate analysis [20]. In the second paper, simultaneous determination by NIR- partial least squares two (PLS2) regression of the concen- trations of the two kinds of serum proteins in a phosphate buffer solution was described [21]. The results obtained in our previous studies were very encouraging from the point of future applications of the NIR-chemometrics analysis to clinical tests. In order to make the blood test by NIR-PLS2 more re- alistic, the determination of the concentrations of blood Koichi Murayama · Keiichi Yamada · Roumiana Tsenkova · Yan Wang · Yukihiro Ozaki Determination of human serum albumin and γ-globulin in a control serum solution by near-infrared spectroscopy and partial least squares regression Fresenius J Anal Chem (1998) 362 : 155–161 © Springer-Verlag 1998 Received: 31 December 1997 / Revised: 9 April 1998 / Accepted: 27 April 1998 ORIGINAL PAPER Dedicated to the memory of Professor Dr. Robert Kellner K. Murayama · K. Yamada Merchandise Development Laboratory, Daiken Medical Co., Ltd., 4–36, Funaocho-Higashi, Hamadera, Sakai 592–8341, Japan R. Tsenkova Department of Environment Information and Bio-production Engineering, Faculty of Agriculture, Kobe University, Rokkodai, Nada-ku, Kobe 657–8501, Japan Y. Wang · Y. Ozaki () Department of Chemistry, School of Science, Kwansei-Gakuin University, Uegahara, Nishinomiya 662–8501, Japan e-mail; ozaki@kwansei.ac.jp