Agri-Food Innovation
Rapid Screening of Heavy Metals in Food/Feed Powders
The presence of heavy metals in food/feed is a timely issue, involving contamination of the food chain and harm to public health. This technology employs spectroscopic and machine learning methods for the quick detection of heavy metals in food/feed samples.
Technology overview
The presence of heavy metals in food/feed is a timely issue that involves contamination of the food chain and poses risks to public health. One potential solution is to conduct more frequent testing of food/feed samples. However, existing testing methods are often time-consuming and require highly skilled laboratory personnel. This technology combines spectroscopic methods with machine learning to enable the rapid detection of heavy metals in food/feed samples.
Technology features
The developed machine learning model can:
Perform a multi-class differentiation of different types of heavy metals based on spectroscopic measurements.
Predict the concentration of heavy metals in food/feed powders using spectroscopic measurements.
Require minimal sample preparation, allowing for the swift screening of food/feed powder samples.
Applications
Applicable to insect powders, animal feeds, milk powders, protein supplement powders, and plant-based nutritional supplements
Benefits
Quick detection of heavy metal species with minimal sample preparation.
Capacity to screen large quantities of samples in a short amount of time.
Comparable model performance and predicted results to industry-accepted methods for measuring heavy metal content.
Commercialisation
This technology is available for licensing and technology transfer.
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