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.

The influence of bean seed surface lipids on infestation of seeds by Acanthoscelides obtectus Say was investigated. The experiments were performed in dual-choice bioassays on three bean varieties: Blanka, Bor and Longina. The collected data for natural and solvent washed seeds concerned the number of ovipositions, embryo mortality, lack of seed-boring activity, dead larvae inside seeds and developed insects. The results clearly indicated that bean seed surface lipids are involved in all infestation stages, and could be used to distinguish resistant and non-resistant varieties of been. Chemical analyses revealed the following groups of surface lipids: wax esters, long chain primary alcohols, n-alkanes, sterols, fatty acids, squalene, aldehydes, monoacylglycerols, ketones and fatty acid esters. Quantitative composition of surface lipids was analysed using selected chemometric procedures to determine correlation with bioactivity. Cluster analysis of surface lipid composition enabled to distinguish resistant and non-resistant varieties. Fatty acids and monoacylglycerols were found to deter bean weevil infestation, while alkan-1-ols acted as attractants.

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.