Hyperspectral imaging improves vision and discrimination power by using spectral signature information of surface materials, and it is one of the most promising techniques currently investigated for quality evaluation purposes. The main advantage of the hyperspectral imaging system is its ability to incorporate both spectroscopy and imaging information, not only to make direct assessment of different components simultaneously, but also to locate the spatial distribution of such components in the tested products. As the hyperspectral, imaging technique is a non-destructive tool it is being used more and more in food applications and in sectors such as pharmaceutical, medical device and photonics. Hyperspectral imaging can be used for remote sensing, machine vision, optical sorting, medical imaging, life science applications, spectroscopy instrumentation, automotive and transport, trace detection, biotechnology, precision agriculture, industrial monitoring, wood processing, and sorting and security.

Hyperspectral imaging in the food and beverage sector can offer food authentication and analysis across the sector but specifically in the areas of meat, fruit and vegetables, dairy products, grains, powders and seaweed. Such examples include analysing the percentage of fat or water content in food products, identifying defects, characterising product quality and locating contaminants.

The Hyperspectral imaging system at CAPPA incorporates a spectral camera (HySpex SWIR – 384) with several lenses on a translation stage, combined with a focused broadband illumination source. The camera has a state of the art MCT sensor with cooling down to 150K which yields low background noise, high dynamic range and exceptional signal noise (SNR) levels, making it ideal for a wide range of applications.  

Since CAPPA first expanded its hyperspectral imaging capabilities, they have worked on a variety of different projects within the food and beverage industry. CAPPA has investigated the classification of fat levels in a variety of foods using hyperspectral imaging. One such project involved the hyperspectral imaging of duck meat. In the below picture you can see the visible image of duck meat and the classification of poor fat levels that can be seen when using the hyperspectral imaging system.

Another project in the food and beverage industry that CAPPA carried out was on the hyperspectral imaging of a bottle cap. The below image on the left shows the first component of the principal component analysis performed on hyperspectral SWIR images of the bottle sample. The image on the right shows pseudo images of the modelled response of the bottle. In both sets the top left image is the capped bottle without the stopper, the top middle is an example of the capped bottle with the stopper and the bottom middle is the bottle without cap or stopped. The third image shows the results of testing of the classification model. In each instance, the correct category was chosen.

You can see some of the previous work CAPPA has conducted in the food and beverage industry here and if you would like to learn more about the hyperspectral imaging capabilities available you can contact CAPPA directly here.