Novel enzymes for fragrance and flavour

Ingredients from plants used in the flavour and fragrance industry are increasingly produced by microbial production platforms. Good examples include terpenes, such as valencene for citrus flavour or steviosides for low-calorie sweetening. The advantage of microbial production is that availability of these ingredients no longer depends on harvest or quality of the plant material. As a result of predictable production time, availability and costs, the ingredients can be included in a much wider range of products. As in all production chains, the efficiency of a microbial production platform depends on its most inefficient component, which is the terpene synthase. In this proposal we want to harness two ways to improve the microbial flavour production systems: machine learning (methods for big data analysis well-known from e.g. Google) and gas screening methods (inspired by air quality monitoring).