Novel non-destructive detection of internal defects in potatoes
I have carried a fascination for nature and agriculture with me from an early age. As a natural problem solver, I gained a degree in engineering, studying ‘Electronic Engineering with Music Technology Systems’ at the University of York, developing a toolset for finding new and tangible solutions to real-world problems and being awarded a first for my project using machine learning for assessment of Parkinson’s disease. Many of the most poignant problems we face, both as a species and as a planet, are environmental and agricultural in nature.
I taught myself how to develop video games aged 11 and have been programming ever since; more recently I taught myself to paint. I find that each new artform offers a unique perspective with which to tackle problems in a lateral and innovative way. Fuelled by a passion for sustainability, I was twice elected as campaigns and fundraising officer for my university’s vegan society and volunteered at the university’s low-waste ethical foods shop. I also served on the parkour society committee, building a flourishing and active community.
Studying for a PhD is the perfect opportunity to discover new knowledge and develop practical skills to tackle the world’s most pressing issues. I hope to contribute to the drive toward sustainability and the advancement of human ingenuity.
In my project I am exploring how non-destructive methods can be used to detect internal defects in the potato. Venturing into avenues of spectroscopy, ultrasound and machine learning, I aspire to discover and innovate new and efficient methods of defect detection and identification.
Based at: Lancaster University
Industry Partner: Produce World