Call for partners | MouldGuard: Predictive modelling to prevent mould spoilage in food and feed
Fungal growth causes severe losses of food and feed at different stages in the production chain or may cause safety issues when mycotoxins are formed. MouldGuard aims to develop predictive models for germination and outgrowth of spoilage moulds relevant in this category (e.g. species of Aspergillus and Penicillium) that support decision making in quality and safety management.
Partner up for impact
We are looking for:
For this project, we would like to connect and shape the project further with industrial partners that will benefit from predictive models for mould growth to support decision making in quality and safety management. Industrial partners in scope are food and feed producing companies and suppliers of ingredients to prevent mould growth.
About the project
Fungal spores are widely present in the (food processing) environment. After contamination with fungal spores from the environment, outgrowth to visible mycelia on the food or feed products causes product loss and consumer complaints. The mouldy appearance on food or feed products results from two different biological processes, namely (1) the time it takes for spores to germinate, and (2) the growth rate for mycelium formation. Both processes are dependent on product intrinsic properties (pH, water activity, organic acids and other preserving ingredients) and extrinsic factors such as storage temperature and gas atmosphere (CO2, O2).
MouldGuard project is a collaboration between Wageningen Food & Biobased Research and the Food Microbiology group of Wageningen University. The project focuses on both germination and outgrowth of fungal spores of a selection of species/strains relevant to spoilage of semi-moisture products (e.g bakery products, semi-moisture (pet) food, feed, side streams). The involvement of suppliers of state-of-the art equipment ensures high-throughput, automated data generation to build prediction models for mould spoilage. The oCelloScope (BioScience Solutions) allows for automated, live imaging of early events in spore germination, whereas mycelium growth will be automatically measured and quantified using a high-throughput imaging device (RESHAPE).
These automated technologies allow to include more model parameters and species/strains in comparison to classical methods based on manual methods.
The project will deliver:
- Germination and outgrowth prediction models for selected spoilage moulds validated in relevant matrices
- Innovative high-through put methods to determine cardinal and MIC values for mould growth
- Dataset with cardinal and MIC values of selected spoilage moulds and ingredients including the impact of strain diversity
Let's connect
For more information about the project or to collaborate, please contact our programme manager.
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