With the maturation of high-throughput and low-cost genotyping platforms, the current bottleneck in plant breeding and crop research lies in phenotyping. The Zhou group focuses on developing multi-scale crop phenotyping technologies to enable the acquisition of high-quality sensor- and image-based plant data in the field as well as in greenhouses. Based on large crop and climate datasets, we concentrate on utilising state-of-the-art computer vision, image analysis, machine learning, and GxE modelling techniques to extract meaningful biological knowledge to enable today’s crop improvement research.
We work on projects ranging from the sky to the field, including:
1) AirSurf, an automated aerial analytic software platform that is capable of conducting large-scale phenotypic analyses of crops such as wheat, brassica and lettuce (in collaboration with JIC, G's Growers and Limagrain).
2) CropQuant, a cost-effective, distributed phenotyping platform to study dynamic crop growth and development during the growing season (in collaboration with JIC, ADAS and Bayer Crop Science).
3) SeedGerm, a machine learning-based, automated seed germination screening platform (in partnership with Syngenta Seeds and ChinaSeeds).
4) Leaf-GP, an open-source software application for automating the quantification of growth phenotypes for Arabidopsis and bread wheat images taken using portable devices such as smartphones (in collaboration with JIC and UEA).
5) 3D phenotypic analysis software solutions based on 3D laser scanning platforms, PlantEye and Phenospex (in collaboration with JIC and Phenospex).
Through our innovative work, we are currently partnering with leading industrial and academic organisations throughout the UK, Europe, and China. In 2017, we jointly published five academic papers, one UKIPO patent, and were awarded six academic and industrial research grants. Both CropQuant and AirSurf were invited to be part of the Pan-European Plant Phenotyping Network (EMPHASIS) led by Nottingham University.
Our crop phenomics solutions and Agri-Tech innovations on bread wheat, brassica, and other crop species have attracted much attention from EI's main funders such as BBSRC, Innovate UK, and EPSRC. The Zhou laboratory was invited by BBSRC to be involved in Harvest 2050 and other industry-related activities, while our projects have been featured as stand-out examples of UK-based Agri-Tech innovation. Recently, our bespoke farming robot for CropQuant, Project Sheila, was invited to exhibit at REAP 2017, an event organised by Agri-Tech East, KTN and Innovate UK.
Visiting and affiliated colleagues.
2017-08-10 Software applications Github - for the Leaf-GP paper
2017-09-26 Software applications Github - for the CropQuant paper
A developmental framework for complex plasmodesmata formation revealed by large-scale imaging of the Arabidopsis leaf epidermis.
Fitzgibbon, J., Beck, M., Zhou, J., Faulkner, C., Robatzek, S., and Oparka, K. (2013). The Plant Cell: 25: 57–70.
CalloseMeasurer: a novel software solution to measure callose deposition and recognise spreading callose patterns.
Plant methods: 8: 49.Zhou, J., Spallek, T., Faulkner, C., and Robatzek, S. (2012).
Spatio-temporal cellular dynamics of the Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting.
Beck, M., Zhou, J., Faulkner, C., MacLean, D., and Robatzek, S. (2012). The Plant Cell: 24: 4205–19.