Vegetable oils belong to a large group of substances consumed on a daily basis. World vegetable oil production is soaring, reducing the popularity of animal fats. Heavy metals pose a threat to human health. It is estimated that about 80% of the daily dose of heavy metals enters the human body through the consumption of food. Hence, it is necessary to monitor their concentrations in food products. Besides, the presence of heavy metals is thought to have possible negative influence on the quality of oils, especially on their taste and smell. Heavy metals may also accelerate the process of the rancidifiction of oils. Rapeseeds, soybean seeds and linseeds were selected for the analysis because they are one of the most popular oilseeds and at the same time they differ in terms of growing conditions. The analyses of different fractions and the ready-made product were also performed. The aim of the study was to determine the variation in concentrations of heavy metals, iron and manganese in different fractions during production. The significant concentrations of iron, manganese and zinc were observed in oilseeds. It was also shown that during different stages of oil refining the concentrations of metals decrease. The concentrations of metals are compared with those reported in literature.

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.