In the present study we describe the relationship between laboratory values obtained with routinely used laboratory analytical methods and near infrared (NIR) spectral data of 126 whole blood and 228 blood serum samples. Spectra were measured with a SPECTRALYZER 1025 (PMC) computerised research analyser. The relationship among laboratory data and values of the second derivative of the log (1/R) spectra measured at different wavelengths was determined by multiple linear regression (MLR) using three and four term linear summation equations, principal component regression (PCR) and partial least-squares (PLS) regression methods.Along with examples for qualitative detection of protein and lipid in human sera, as well as distinction of albumin and globulin dissolved in physiological saline solution, we describe mathematical models and evaluate their performance for the determination of protein and beta-lipoprotein (β-LP) content of serum as well as oxygen saturation and carbon dioxide pressure in whole blood. Validation of our results yielded a standard error of performance (SEP) of 2.47 g L -1 for protein content and 0.79 TU for β-LP content in blood serum, whereas SEP values of 5.41% for oxygen saturation and 5.27 mm Hg for carbon dioxide pressure in whole blood were found. Our results presented in this preliminary study indicate that NIR measurements can be related to analytical data of whole blood and serum. NIR spectroscopy is a rapid, accurate, cost effective method for determining quality parameters of whole blood and serum and might be a promising new tool in the field of automated clinical laboratory analysis.

The near infrared spectra are useful information sources relating to quality (e.g. composition) of a material examined. To obtain and interpret useful information requires in most cases the application of sophisticated methods of mathematical statistics. A method different from those mentioned above, implementing a large scale data reduction based on geometrical consideration is the PQS. According to this method, the quality of a material can be characterised by the centre of its spectrum represented in a polar co-ordinate system. In many cases it is enough to know whether the investigated product deviates in a certain degree from a given "standard product" or not. This can be decided by determining special "distances" between the two (investigated and standard) products using their near infrared spectra. Besides the successfully used Euclidean and Mahalanobis distances a new one, the "polar distance" was introduced giving the distance between the two centres (quality points) of the spectra of the two products examined. A method was elaborated to select the optimal wavelength range giving the maximum normalised distance between the two quality points of the investigated products. The so called "wavelength range optimisation" can not be used to work with non spectral data sets. While in case of NIR spectra the sequence of the data are determined by nature, in several cases the order of the data can be freely varied and the goal is the determination of the optimal data sequence. By introducing the "sequence optimisation" PQS could be generalised and used from the field of near infrared spectroscopy to solve any kind of multivariate tasks. The advantage of the PQS optimisation method is its simplicity. Since PQS was developed to extract the needed information from NIR spectra, the basic principles of the technique are introduced with the help of near infrared spectra of some milk powder samples of different fat content. The sequence optimisation is demonstrated with the sensor signal responses of an electronic nose (chemosensor array) instrument measuring different steam distilled volatile oil samples.

A new, rapid qualification method was introduced at the 3rd International Conference on Near Infrared Spectroscopy according to which a "quality point" was defined on a two-dimensional "quality plane". The quality point of the investigated material was given by the center of its spectrum represented in a polar coordinate system. The method was further developed, three interpretations were given for the "center" of the polar spectrum, resulting in three different formulas for determining the x and y coordinates of the quality point. The effect of the change in the amplitude of the absorption peaks, the effect of the noise of the spectrum, the effect of the shifting and tilting the base-line of the spectrum on the location of the quality point were investigated using the three formulas. The results of the investigation and the characteristic features of the three formulas are introduced.

Oregano is used worldwide both as spice and crude drug, which is mainly provided by species of Origanum genus. The quality of the product is usually determined by chemical analysis, whereas in food industrial applications sensory tests are also practised. The aim of the present study was a comparison of parallel quality investigations of oregano samples by a new and effective instrumental sensory evaluation method, the "electronic nose", and by gas-chromatographic and human sensory analysis.The GC analysis of essential oil components revealed mainly differences between plant species (Origanum vulgare subsp. hirtum and Origanum majorana). Main components of the oil of the former taxon are carvacrol and thymol, while those of marjoram are terpinene-4-ol, -terpinene and terpinolene. A wholesale oregano sample showing considerable divergence from the other ones with respect to ratios of carvacrol, -caryophyllene -cubebene and thymol. It was assumed not to belong to ssp. hirtum.The electronic nose analysis, evaluated by PCA, proved to be an appropriate, rapid, nondestructive, reagent-less method for the reliable separation of all of the oregano samples based on their complex aroma features. Assumptions could be made about correlations between separation of samples by the instrumental sensors and proportions of terpenoid compounds of the oil established by GC in some cases only. The varying essential oil content of the samples did not influence the success of instrumental evaluation.The instrumental and human sensory analysis showed similar results: varieties of O. majorana could be well distinguished on the basis of their complex aroma, while their gas-chromatograms did not show characteristic differences.The results call the attention that quality evaluation of drug items of aromatic plants should be oriented in different directions, considering the current utilisation area of the items.

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