Background

Various plant-based substitutes are now widely available on the market. There is a wide range of alternatives to conventional cow's milk, especially when it comes to milk substitutes. One nutrient-rich source of protein from which a substitute milk can be obtained is the yellow split pea. It is characterised by a high protein content and environmentally friendly cultivation. Although pea milk is now established on the market, there are still some off-flavours that make this product less attractive to the market. The flavour is often described as beany and bitter. In order to further improve the flavour of these products, it is necessary to identify the substance classes responsible for these off-flavours by mass spectrometry and break them down enzymatically.

Tasks

The aim of this project is to analyse pea milk samples using headspace /ITEX-GC-MS. The focus is on volatile components of the substance groups aldehydes and alcohols, which are to be identified and quantified. The concentrations obtained will also be used to classify how relevant these components are for the flavour (OAV). Subsequently, the use of various enzymes will be used to investigate the conversion of the alcohols and thus also the effects on the flavour. The data collected in this project will also be stored in a suitable format for possible storage in databases from the point of view of ‘AI-ready’ for possible processing with machine learning algorithms.

Practical aspects of the work are:

-Development of a suitable headspace/ITEX method for the analysis of pea milk (solvent, temperature gradient, etc.)
-Identification and quantification of substances with negative flavour association
-Determination of Odour Activity Values (OAV)
-Enzymatic processing of raw pea milk and subsequent analysis
-Clear documentation of the results in electronic form and presentation in a seminar lecture