Quality of barley and malt is important in food industry, namely in malting and brewering. It is characterised by chemical analysis – determining various compounds, but mostly in malt. By analysis, non-acceptable quality might be found quite late and all production is wasted. Therefore, there is aim to estimate products quality via analysis of primary raw material, i.e. of barley. However, the relation between barley chemical analysis and malt (consequently of beer produced) quality is up to now not well known. The aim of the project is (i) to find markers responsible for barley quality, especially in connection with compounds formed when barley caryopses are attacked by fungi (ii) to modify present or eventually to develop new analytical methods for the determination of fungi metabolites (iii) applying chemometrics techniques to find the most important compounds responsible for quality and modelling with genetic or artificial neural networks algorithms to formulate „soft“ models for the relation between results of barley analysis and quality of its products (malt, beer, namely gushing) (iv) to verify quality prediction on sufficient data sets. The project enable eliminate low quality barley before its elaboration to malt or in other parts of food industry (cereals, milk industry, etc.), what would have high economic impact for improving malt and consecutive products quality and will have positive impact to healthy harmless food.

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