Machine learning approach to map Physi-Trace signatures using trace element profiling of fresh and processed pork

This project aims to use a machine learning approach to map PhysiTrace signatures.

This enables a better understanding of the trace element profiles gathered from both processed and fresh Australian pork. This includes assessing the data sets to identify any influences on the prediction, and recommendations that may improve the model.

Value for producers:

• Machine learning enables PhysiTrace data to be analysed quickly, and easily
• Physitrace data can be used to ensure products are Australian, and where the pork is sourced from
• Physitrace data can be utilised more efficiently in the event pork products need to be traced