ORCID ID: orcid.org/0000-0002-7465-845X
Twitter ID: erikmurchie
2006 - current
Associate Professor and Lecturer in Crop Science, University of Nottingham.
1996 to 2005
Postdoctoral Research Assistant (PDRA): Department of Molecular Biology and Biotechnology, University of Sheffield, U.K and International Rice Research Institute, Philippines.
Post doctoral Research Associate, Institut National de la Recherche Agronomique (INRA), Versailles, France
I study photosynthesis in crop plants. In particular my group is interested in the regulation of photosynthesis in response to environmental factors in all types of cropping systems. Why is this important? It is clear that photosynthesis operates below optimal efficiency in the field and if we could improve this it would have an impact on grain yield. I use crops such as wheat and rice to understand the genetic basis for processes such as photoprotection.
We also study how the use of controlled environment systems can be optimised to bring photosynthesis and resource use efficiency closer to their maximum. This has relevance for horticulture and so-called vertical farming. I have an active research programme using LEDs to develop smart growth systems.
Photosynthetic physiology: Infra red gas exchange, chlorophyll fluorescence quenching analysis
Plant canopy analysis : light interception, analysis of radiation use effiicency, field analyses of chlorophyll fluorescence, novel techniques for 3-D imaging of plant canopies and modelling analysis of photosynthesis in plant canopies
Plant biochemistry : Protein analysis (electrophoresis) , pigment analysis (HPLC), microarray RNA analysis
I convene the following modules:
Applied Plant physiology: cell to crop (D223P8), Level 2. This module covere essential aspects of plant biochemistry and physiology as it relates to the fundamental processes of capture of water, minerals and radiation.
Resource capture by Crops (D24C08), Level 4. This Masters module covers the processes by which crops acquire water and radiation. It focusses on basic principles and leads to agricultural case studies.
Crop Monitoring and Phenotyping (D24CO3). This Masters module is practical based and builds on the principles learnt in D24CO8, giving students the chance to get to grips with monitoring crops in the field, developing their own field crops research proposal and measuring radiation use efficiency.
I also contribute lectures to the following modules:
Plant responses to environmental Stress (D224P5)
Plants and the Light environment (D224P5)
Research Techniques in Agriculture, PLant and Animal Science (D224Z4)
World Agroecosystems (D224P4)
Temperate Field Crops (D24AO2)
Genetic Improvement of Crop Plants (D23BA7)
Applications of Biology (D211A1)
Optimising photosynthesis in crop canopies
My group studies the factors that regulate and limit photosynthesis in crop plants. We examine the fundamental processes in crop plants such as light harvesting, carbon assimilation and energy dissipation and identify targets and strategies for improvement of crops in both optimal and suboptimal (stressful) environments. We also work with novel agricultural systems such as those which are making use of novel lighting technology in horticulture. The rate of leaf and canopy photosynthesis is becoming more important as a target for raising crop yields. We know this from studies that identify total biomass accumulation rate as a limiting factor (Murchie et al, 2009).
The processes of harvesting and converting photosynthetically active radiation in plants are capable of operation with a very high efficiency at the molecular level. However the upscaling of these processes to plants, canopies and agroecosystems involves losses caused by metabolic and environmental factors and we measure this as a reduction in radiation - use efficiency (RUE)*.
Highlighted Funded projects
Wider and faster: high-throughout phenotypic exploration of novel genetic variation for breeding high biomass and yield in wheat, International Wheat Yield Partnership and BBSRC. 2016-2019
Measurement of Plant Growth and Health in LED horticulture (MePGHOL), Innovate UK, 2013-2017.
As Co-I: Indo-UK Centre for the improvement of Nitrogen use Efficiency in Wheat (INEW), BBSRC funded2016-2019
SCPRID, Exploiting wheat alien introgressions for increased photosynthetic productivity, BBSRC, India ministry of science and technology, Bill and Melinda Gates Foundation, 2013-2017
Current Lab members
Dr Lorna McAusland (2016) : high-throughout phenotypic exploration of novel genetic variation for breeding high biomass and yield in wheat.
Pracha Tree-Intong (2016): Abiotc stress tolerance and photoprotection in diverse rice accessions. Thai Government Funding
Chuan Ching Foo (2015): Photoprotection in crops
Hayley Smith (2012) : Optimising photosynthesis, growth and development of plants in LED-based horticulture. Funded by EPSRC CASE Award with Greengage lighting
Kannan Chinnathambi (2013): Exploiting wheat alien introgressions for increased photosynthetic productivity. Funded by BBSRC/Indian Council for Agricultural Research
Alexandra Burgess (2013): Novel traits for improved biomass production in under-utilised crop species: optimisation of canopy structure and photosynthesis. Funded by Crops for the Future Research Centre and U. Nottingham (UK) (U.Nottingham Malaysia)
Tiara Herman (2013) : Reducing losses in rice leaf photosynthesis in suboptimal environments (Joint with Dr Asgar Ali, funded by Malaysian Government)
Umar Mohammed (2013): Improving rice drought tolerance
Previous funded projects :
Genetic Manipulation of photoprotection and photooxidative stress tolerance in rice (BBSRC Grant BB/G003157/1)
Removing the inefficiencies of 3-dimensional canopy photosynthesis by the manipulation of leaf light response dynamics and architecture (BBSRC grant BB/J003999/1) 2012-2015
What is photoprotection and why is it important for crop photosynthesis ?
Photoprotection refers to a suite of regulatory chloroplast processes which are induced when the amount of light absorbed exceeds that which can be utilized in photosynthesis. They are thought of as 'protective' because they prevent the over-excitation of chlorophyll which increases the likelihood of reactions with molecular oxygen and hence oxygen radical production. They cause a down-regulation of photosynthesis and the quantum yield of CO2. Non-photochemical quenching' or NPQ is integrated closely with photochemical processes and essentially help to regulate the balance between the harvesting of light energy and the harmless dissipation of excitation energy within the chloroplast. Models have shown that delayed recovery of NPQ should result in a reduction of canopy carbon gain of up to 30 %.
Two components of NPQ are the xanthophyll cycle and the thylakoid membrane protein PsbS. Recent work suggests that these regulate different aspects of NPQ , with PsbS responsible for a shift between light-harvesting and dissipative states, and the xanthophyll cycle altering the rate of induction and relaxation of NPQ.
We are analyzing rice plants which have been transformed to possess altered levels of PSBS and xanthophyll cycle pool sizes and hence altered patterns of NPQ. We are quantifying leaf photosynthesis in fluctuating light levels and apply this knowledge to canopy - level studies and test the current models of canopy carbon gain.
Xanthophyll cycle carotenoids such as zeaxanthin are also powerful membrane anti-oxidants and increased pool sizes have been shown to improve tolerance to high light and temperature stress. We will test this effect in rice plants.
Previous lab members:
Dr Alex Burgess
Dr Renata Retkute
Dr Stella Hubbart
Dr Liang Zhao
Dr Ian Smillie
Dr Rea Kourounioti
Dr Aryo Feldman
Dr Mubarak Nagoor
Dr Stanley Noah
BURGESS, ALEXANDRA J., RETKUTE, RENATA, POUND, MICHAEL P., MAYES, SEAN and MURCHIE, ERIK H., 2017. Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems Annals of Botany. mcw242 POUND, MICHAEL P.AND FRENCH, ANDREW P.AND FOZARD, JOHN A.AND MURCHIE, ERIK H.AND PRIDMORE, TONY P., 2016. A patch-based approach to 3D plant shoot phenotyping Machine Vision and Applications. 1-13
MICHAEL POUND, ALEXANDRA J BURGESS, MICHAEL H WILSON, JONATHAN A ATKINSON, MARCUS GRIFFITHS, AARON S JACKSON, ADRIAN BULAT, GEORGIOS TZIMIROPOULOS, DARREN M WELLS, ERIK H MURCHIE, TONY P PRIDMORE and ANDREW P FRENCH, 2016. Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping Biorxiv. Available at: <http://biorxiv.org/content/early/2016/05/12/053033>