Hyperspectral ZT and food safety determination (phase 2)

10 October 2018

Focus area: Product & process integrity

Program stream: Food safety

Project number: 2017-1053

The objectives of this project were to analyse the spectral characteristics of contaminated meats using a hyperspectral camera, to develop a classification algorithm to discriminate between clean and contaminated meat and finally to design, construct, and trial a contaminant detection system in a red meat processing plant’s harvest room.

As part of the project, lamb and contaminant samples were collected from a variety of sources. Preliminary samples were cut to contain equal amounts of fat and meat, and contaminants were applied in incremental amounts between scans to collect a diverse set of data.
Controlled tests showed that contaminants can be detected with an accuracy of more than 90 per cent.

Hyperspectral ZT and food safety determination (phase 2)

Supporting documents

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