Using the net analyte signal, hybrid linear analysis was proposed to predict chemical concentration. In this paper, we select a sample from training set and apply orthogonal signal correction to obtain an improved pseudo unit spectrum for hybrid least analysis. using the mean spectrum of a calibration training set, we first show the calibration by hybrid least analysis is effective to the prediction of not only chemical concentrations but also physical property variables. Then, a pseudo unit spectrum from a training set is also tested with and without orthogonal signal correction. We use two data sets, one including five chemical concentrations and the other including ten physical property variables, to compare the performance of partial least squares and modified hybrid least analysis calibration methods. The results show that the hybrid least analysis with a selected training spectrum instead of well-measured pure spectrum still gives good performances, which is a little better than partial least squares.

Recently, near-infrared (NIR) spectroscopy and Raman spectroscopy have received keen interest as powerful techniques for nondestructive analysis of biological materials. The purpose of this review paper is to compare the advantages of NIR and Raman spectroscopy in the nondestructive analysis. Both methods are quite unique and often complementary. For example. NIR spectroscopy is very useful in monitoring in situ the content of components inside biological materials while Raman spectroscopy is very suitable for identifying micro-components on the surface of biological materials. In this article specific characters of the two spectroscopic methods are discussed first and then several examples of applications of NIR and Raman spectroscopy to the biological nondestructive analysis are introduced.

Temperature-dependent changes in near-infrared (NIR) spectra have been measured for oleic acid, and nonanoic acid in the pure liquid state. Particular attention has been paid to the 5400-4800 cm$\^$-1/ region where a number of combination bands appear. The NIR spectra of oleic acid show that a band at 5303 cm$\^$-1/ increases with temperature while that at 5270 cm/sup-1/ decreases. It ha been found from their second derivative spectra that these spectral changes take place stepwisely with two break points at 30 and 53$\^{C}$, which correspond to the phase transition temperatures oleic acid reported previously. Principle component analysis (PCA) has been carried out for the NIR spectra of oleic acid in the 5400-4800 cm$\^$-1/ region measured over a temperature range of 15-80$\^{C}$. core plots of the first and second principal components (PCs) show that the NIR spectra are classified into three groups; the spectra measured in the temperature range of 15-30$\^{C}$, those in the range of 31-53$\^{C}$, and those in the range of 54-80$\^{C}$. These temperature ranges correspond to those for quasi-smectic liquid crystal, disordered liquid crystal, and isotropic liquid of oleic acid in the pure liquid state. In other words, PCA provides unambiguous evidence for the phase transitions. similar studies have been carried out for petroselinic acid and nonanoic acid in the pure liquid states, but they do not show any evidence for phase transitions.

The identification step of raw drug materials is an indispensible procedure in the GMP manufacturing process within the pharmaceutical industry. However, wet chemistry methods for identification of drug materials, used by the various Pharmacopeia are time-consuming and expensive steps. In this paper, near-infrared spectroscopy (NIRS) has been developed for identifying eleven drug substances including calcium pantothenate, cefaclor, cefoperazone, cephradine, dextromethorphan, ehtambutol, nicotinamide, pyrozinamide, tramadol, vitamin C, and vitamin E. Also the aim of ths work is to consturct a new algorithm for calibration model using soft independence modeling of class analogy (SIMCA) with Malinowskis Indicator Function (IND), which is used for finding the number of principal components of each class of the SIMACA model. The use of NIR technique with pattern recognition to qualify raw materials can make it possible to monitor process in real time as well as to control all procedures in the pharmaceutical industry. As the result, the samples identified of 183 different batches from 11 different compounds were separated clearly by SIMCA with 2nd derivative spectra in the NIR region of 1100∼2400 nm.

The purpose of this research was to find out suitable soil sample preparation and sample holding tools for NIR reflection radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1,100 to 2,500nm with an InfraAlyzer 500(Bran+Luebbe Co.). Coarse(2.0mm) and fine(0.5mm) soil sample and various sample holding tools were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter and total nitrogen of the soils. Multiple linear regression was used to obtain the best correlation of NIR spectroscopy method. Correlation of NIR spectroscopy method. Correlation of NIR spectra for finely and coarsely sized soil did not show much difference. The standard errors of prediction(SE) using different types of sample holding tools for organic matter, total nitrogen and soil moisture were better than 0.765, 0.041 and 0.63% respectively. From the results it can be concluded that NIR spectroscopy with flow type cell could be used as a fast routine testing method in quantitative determination of organic matter, total nitrogen and soil moisture.

The objectives of this study are to discriminate the geographical origin and cultivation years of ginseng based on the near-infrared(NIR) reflectance spectroscopic analysis. Korea and China ginseng samples were prepared for discrimination of geographical origin. 4, 5 and 6 years-old ginseng samples from Korea were prepared for discrimination of cultivation years. Used spectrometer were InfraAlyzer 500, InfraAlyzer 400 and Fiber optic. Sample type of ginseng was 3, whole ginseng radix, slide section and powder type. The accuracy was affected by sample types and instruments. The accuracy for discrimination geographical origin was 97% in calibration model using IA 500 and ginseng powder. For discrimination of cultivation years, the model with slide selection using IA500 were relative accurate. The accuracy was 96.7% for 4-year, 91.3% for 5-year and 89.3% for 6-year old ginseng. The study shows that NIR spectroscopic analysis can be used to discriminate the geographical origin and cultivation years of ginseng with acceptable accuracy.

The effective component Ginsenoside in Ginseng has been widely used to cure some hypochondriasis and be as supplementary medicines. There are many chemical analysis methods to measure the contents of Ginsenoside in Ginseng; however, all these methods have some shortcomings such as long time, environmental pollution and damaging the samples. In this paper, it is possible to use near infrared spectroscopy to measure the content of Ginsenoside in Ginseng without destruction. As the results, Rg1, Rb1, Re and T-Saponin of Ginsenoside can be measured with the accuracy of R(0.81) SEP (1.704 mg/g), R(0.74) SEP (1.211 mg/g), R (0.78) SEP (1.049 mg/g) and R(0.84), SEP(4.537 mg/g).