Fraser Macfarlane

Machine Learning Research Scientist
Information and Computational Sciences
Fraser is a Machine Learning Research Scientist with an interest in computer vision. His background is in Hyperspectral Imaging, Machine Learning and Image Processing. Fraser is currently completing a PhD in Electronic and Electrical Engineering at the University of Strathclyde, where his research is on the design of optimal object recognition and compression algorithms. Fraser joined the Institute in 2021, and his work is applied across a range of scientific activities such as high-throughput plant phenotyping within the Advanced Plant Growth Centre (APGC) and International Barley Hub (IBH), as well as for the analysis of remote sensing imagery.

Plant Phenotyping

  • Machine Learning-based phenotyping of blueberries, potatoes, barley, and others.
  • Analysis of in-situ field imagery from robotic and drone-based platforms.
  • Low throughput bespoke hyperspectral imagery of barley seeds and blueberry varieties.
  • Predicting the photosynthetic capacity of potato plants using hyperspectral imagery.

Remote Sensing

  • High Resolution Aerial Image Segmentation of Peatland drainage and erosion for GHG Emission estimates.
  • Peatland condition and land use classification in Scotland.


  • Digitisation of historic Ordnance Survey maps using AI.
  • Non-destructive yield estimation in poultry.


Past research

  • Machine Learning-based mapping of peatland condition in Northern Ireland.
  • Drone-based analysis of agricultural biodiversity.
  • Hyperspectral image analysis for detecting late blight in potato varieties.