Project

Call for Partners | SPECTRA - Spectral imaging for non-invasive detection and prediction of microbiological quality

Microbial activity is a major cause of food loss as microorganisms cause spoilage or even pose a health threat when human pathogens are present. For food producers it is challenging to balance between maximizing shelf life and assuring product quality and safety during shelf life.

Current detection and enumeration of microorganisms in food is dependent on elaborate and invasive methodologies. Wageningen Food & Biobased Research is starting a consortium project aiming at adapting and optimizing spectral imaging as a fast, non-invasive method to determine levels of microbial contaminants.

Being able to detect and enumerate microorganisms in a fast and non-invasive manner would be greatly beneficial for food manufacturers for fast monitoring of product quality at different stages in the food supply chain. This can range from quality control to fast and accurate assessment of (remaining) shelf-life, and when combined with predictive models, the results can even be used for predicting growth or inactivation of microorganisms.

Spectral imaging (SI) in visible and near-infrared light range is a technology that offers potential to overcome the limitations of classical methods of food microbiology. SI captures physicochemical properties of material as a function of infrared light. The varying level and type of microbial activity in the products can result in specific changes in physicochemical properties of products, hence, SI has the potential to detect changes in microbial levels in real-time.

Within SPECTRA, the aim is to develop and finetune SI for fast and non-invasive detection and enumeration of microorganisms in different perishable food matrices such as meat, fish or plant-based products. The potential use of SI includes (but not is not limited to):

  • Application in the food production chain as real-time read-out for the presence and quantity of microorganisms and their effect on product quality.
  • Fast, non-invasive microbial read-out, especially in packaged food products.
  • The outcome of SI analyses can be used as input in predictive models that can be used for more accurate prediction of microbial spoilage of food products, balancing production capacity with availability and quality of raw materials and help to reduce food waste by optimization of the supply chain needs.

Partners

We invite companies active in the field of perishable foods (meat, fish, plant-based products) and interested in innovating their supply chain management by exploiting SI for microbiological and product quality, to join this initiative. Furthermore, companies active in packaging solutions, ingredient solutions or processing technologies are invited to join this consortium. In return for in-cash and in-kind contributions to the project, partners can provide direction to the research activities, will also get early access to this highly innovative technology, or can assess quickly the effect of solutions in final products.