Sensor Development for Quantification and Prediction of Provenance Attributes of Agricultural Products

This project aims to increase the trust of the agricultural supply chain by developing rapid, robust methods linking the physical product to the original source.

The Problem

Food provenance has become a global priority for consumers, producers, and government authorities due to increasing food safety, environmental and authenticity concerns. This in turn is driving demand for independent and objective assurance and verification of food sources.

Our Response

Combining knowledge of hyperspectral sensing methods, agricultural science and mineral exploration this project will develop new field deployable sensors to define and verify the geographic production origin of agricultural products. The project will explore hyperspectral sensing to identify geographically specific and relevant markers occurring in soils, plants, and farm inputs which are retained within products.

Collaborators

This project is lead by Nina Welti (A&F) in collaboration with Brianna Ganly (MR), Hayley Norman (A&F), Roger Lawes (A&F), Carsten Laukamp (MR) and the WP3 Trusted AgriFoods Exports Mission, and is supported by Postdoctoral Fellow Mihiri Gedaralage.