Spectrometry, especially spectrophotometry, is getting more and more often the method of choice not only in laboratory analysis of (bio)chemical substances, but also in the off-laboratory identification and testing of physical properties of various products, in particular - of various organic mixtures including food products and ingredients. Specialised spectrophotometers, called spectrophotometric analysers, are designed for such applications. This paper is on the state of the art in the domain of data processing in spectrophotometric analysers of food (including beverages). The following issues are covered: methodological background of food analysis, physical and metrological principles of spectrophotometry, the role of measurement data processing in spectrophotometry. General considerations are illustrated with examples, predominantly related to wine and olive oil analysis.

Science and technology frequently contribute to one another: scientific advances lead to the development of new technologies, and new technologies broaden the experimental potential of science, enabling advancement of research. This is a motivation behind introduction of the concept of technoscience addressing the integration of science and technology – the process progressing from the beginning of the twentieth century, which has been the source of extraordinary achievements of our civilisation, but – at the same time – has engendered global socioeconomic transformations whose negative side effects may endanger humanity. This paper is devoted to an outline of ethical challenges implied by the development of technoscience, with special emphasis of those which are rooted in the development of information technologies. It is suggested that those challenges should be met by people of technoscience in a concerted effort undertaken with philosophers and educators.

Spectrophotometry is an analytical technique of increasing importance for the food industry, applied i.a. in the quantitative assessment of the composition of mixtures. Since the absorbance data acquired by means of a spectrophotometer are highly correlated, the problem of calibration of a spectrophotometric analyzer is, as a rule, numerically ill-conditioned, and advanced data-processing methods must be frequently applied to attain an acceptable level of measurement uncertainty. This paper contains a description of four algorithms for calibration of spectrophotometric analyzers, based on the singular value decomposition (SVD) of matrices, as well as the results of their comparison - in terms of measurement uncertainty and computational complexity - with a reference algorithm based on the estimator of ordinary least squares. The comparison is carried out using an extensive collection of semi-synthetic data representative of trinary mixtures of edible oils. The results of that comparison show the superiority of an algorithm of calibration based on the truncated SVD combined with a signal-to-noise ratio used as a criterion for the selection of regularisation parameters - with respect to other SVD-based algorithms of calibration.