Project Description

Measurements of fruit ripening

Detection of chemical agents (ripeness and pesticides) and ripeness levels in fruit using multi-spectral imaging and machine learning. A low cost, high accuracy and non-destructive method usable in mobile field environments, where current methods are expert- and/or lab-intensive.

The global fruit market is very big. The 10 biggest exporting markets had a combined value of more than USD 44 Billion in 2016.

There is a significant gap/potential in the appliance of imaging technology and machine learning in contexts with low cost equipment and non-expert users. Bringing this technology to maturity in these contexts through a research-based adaptation has a huge potential.

Technology verification with fruit industry partner.