End-of-line quality check - food safety

End-of-line quality check - food safety.

Frozen pizza is a highly competitive high volume consumer food market. This leads to the need to consistently produce symmetrical, standardised and appealing products while still keeping producing large quantities. Due to the high production speed, unwanted ingredients from other pizza variants can end up on a Pizza as well as a number of physical contaminants.

In this example, Chemical Sensing is used to detect physical contaminants on a vegetable pizza. Multiple materials that might occur as physical contaminants have been placed onto the pizza. The left image shows the pizza as it is. The contaminants are marked in the middle image: scraps of paper (red), PVC pieces (blue), pieces of a Latex glove (cyan), wood pieces (purple), and pieces of a zip tie (magenta). The right image shows the Chemical Sensing result.

Chemical Sensing uses hyperspectral imaging technology and spectroscopic analysis and modelling algorithms to portrait chemical/molecular properties as colours in an image (see Wikipedia(1) for a brief introduction to hyperspectral imaging or Elmasry(2) for a more extensive review of hyperspectral imaging in respect to the quality evaluation of food products). The much lower number of of water molecules or complete lack thereof in the non-food products allows for a differentiation between the pizza and the physical contaminants between 1000 nm and 1700 nm. Furthermore some of the contaminants themselves show absorption features in this spectral range. The images were recorded using the measurement system Perception HEAD Model 2 and analysis and modelling were done using Perception STUDIO.

In the Chemical Sensing image the pizza is depicted in grey, scraps of paper are depicted in red, PVC pieces are depicted in green, pieces of a Latex glove are depicted in blue, wood pieces are depicted in yellow and pieces of a zip tie are depicted in cyan. This clearly shows the non-destructive detection of physical contaminants in the production line offered by Chemical Sensing.

(1) https://en.wikipedia.org/wiki/Hyperspectral_imaging

(2) Gamal Elmasry, Mohammed Kamruzzaman, Da-Wen Sun & Paul Allen (2012) Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review, Critical Reviews in Food Science and Nutrition, 52:11, 999-1023, DOI: 10.1080/10408398.2010.543495

Article written by: Christoph Miksits, Senior Application Engineer