Category: Funded projects

2nd Call for Funding: Dr. Michael Pound – Computer Vision Laboratory, School of Computer Science, University of Nottingham

Project Title Predicting plant root growth from time-series data using deep learning Total Fund Requested – £24,677.34 This pilot project will study the potential of deep networks to predict the growth of plants by generating segmentation masks of root systems into the future. We will adapt an existing predictive network, PGGAN, into this new domain.…

Continue reading


2nd Call for Funding: Eric Ober – NIAB

Project Title In-field 3D imaging for high resolution morphometric phenotyping in wheat Total Fund Requested –£24,772 Project Summary The are a number of phenotyping tools currently available that are capable of producing high resolution 3D images of plant features such as the ears of a wheat plant and the individual spikelets within those structures. Quantitative…

Continue reading


2nd Call for Funding: Dr Matt Jones – Institute of Molecular, Cell, and Systems Biology University of Glasgow

Project Title: Measuring the consequences of abiotic stress in vivo using fluorescent and bioluminescent probes Total Fund Requested – £23 687 Project Summary If we are to understand how plants respond to drought and increased temperatures we need to measure both the immediate changes in metabolism inflicted by stress and the consequences of these changes.…

Continue reading


2nd Call for Funding: John Ferguson – University of Nottingham.

Project Title Leveraging optical topography for rapid reconstructions of 3D leaf surfaces to address key questions in plant biology. Total Fund Requested – £25,000.00 Project Summary Introduction and Overview The surfaces of leaves are critical for regulating plant-ecosystem interactions. Micro-morphological structures, such as ridges, veins, stomata, and trichomes define overall leaf surface texture. This texture…

Continue reading


1st Call for Funding: Dr Wenhao Zhang – Centre for Machine Vision, Bristol Robotics Laboratory, UWE, Bristol.

An intelligent, low-cost adaptive 3D multi-scale imaging system for advanced plant phenotyping (PS-Plant+) Total Fund Requested – £24,881 Project Summary Overview: We will develop a multi-scale 3D imaging and modelling system to identify and characterise key growth developmental stages in the model plant Arabidopsis and the important crop oilseed rape. The system will combine two…

Continue reading


1st Call for Funding: Dr Ji Zhou – NIAB

Developing 2D-3D fusion to enable high-throughput phenotypic analysis of key yield-related traits of bread wheat using cost-effective UAV imagery. Total Fund Requested: £24,940 Project Description 2.1 Project aim and objectives In the proposed project, we aim to develop a standardised imaging protocol to acquire high-quality and high-frequency aerial images of wheat crops using low-cost UAVs,…

Continue reading


1st Call for Funding: Prof Bruce Grieve – Electronic Engineering, University of Manchester

Implementation of Active 3D Multispectral Imaging and Photometric Stereo systems as Early Stage Phenotyping Tool for Morphological Features and Biotic Stress Quantification within Complementary Demonstrator Phenotyping Centres (IBERS & P3) Total Fund Requested: £18,480 Project Summary The project will enable a new generation of, cost-effective, integrated Multispectral Imaging (MSI) and Photometric Stereo (PS) sensor system…

Continue reading


1st Call for Funding: Dr Bo Li – NIAB

Investigation of microwave imaging for internal fruit quality and below-ground phenotyping Total Fund Requested – £24,783 Project Summary Food demand is expected to increase anywhere between 59% and 98% by 2050, and consumers are becoming increasingly health conscious about their lifestyles and diets. This will shape agricultural markets in ways we have not seen before.…

Continue reading