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WasteSense – Freshness Assessment: High precision perception calibrated sensor technologies for shelf life prediction and reduction of food waste

Project: Research

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Every year, many people worldwide become ill related to ingestion of foods where the source is most often spoiled animal products (meat, poultry, fish) this has resulted in understandably cautious constraints on shelf life designation for sell and use by dates. As a result, it is estimated that countless tons worldwide, and approx. 92,500 tonnes / year in Denmark alone, of edible foods are consigned to waste. This of course leads to enormous economic and resource losses in food production and slows down sustainable development vastly in an increasingly competitive industry.
The question then arises, what if one was able to designate and predict shelf life and spoilage with much more precision, allowing for the potential to place more accurate sell and use by dates on foods, enabling less waste?. The condition of food for shelf life designation at present is largely assessed on the basis of bacterial counting (time consuming), and/or using the human senses (accurate but expensive).
There are however, alternative methods to assess spoilage in e.g. meat/poultry/fish by measuring increasing concentrations of bacteria generated biogenic amines. Cadaverine levels in meats for example have been demonstrated as highly predictive of product freshness. However, current sensing methods require chromatography (bulky and expensive) to measure levels.
In this project, biogenic amine measurement will be carried out via highly specific integrated nano-sensors using different sensing methods (cantilever or plasmonic), with the sensors benchmarked in terms of sensitivity, via correlation with microbiological tests and objective sensory evaluation, as well as testing for specificity, miniaturization potential and cost. The ultimate aim of course to enable highly accurate self life prediction and designation on line/at line with a resultant reduction in waste potential.

Funding: Danish Food Innovation, Regional Funds Project: Automations booster, Sino Danish Centre Food and Health Research Program

Collaborator: University of Copenhagen, University of Southern Denmark, Technological Institute, Danish Crown, AmiNIC Aps  
Short titleWasteSense
Effective start/end date01/01/201931/12/2020

ID: 149029800