Hyperspectral ZT and food safety determination (phase 2)

10 October 2018
Focus area: Food safety
Program stream: Product & process integrity
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.
 

Supporting documents

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