How understanding plant architecture builds food security
Climate change threatens crop yields in the UK and around the world. Plants are highly sensitive to their environment and whilst rising CO2 levels may be beneficial to plants, increased heat, potential droughts and floods plus extreme weather events can be catastrophic.
By better understanding ‘canopy architecture’ (all the plant components above ground), we will learn more about how plants behave and adapt to their environment and how this influences their ability to produce our food.
The height, number and dimensions of leaves and biochemical composition of plants all influence how they interact with the environment. This is especially the case for light. Plants are photoautotrophs, using energy from the sun to grow and produce yield through the process of photosynthesis, therefore the amount of sunlight they intercept is key to the amount of food they can produce.
But not all light is equal. Light is made up of different colours corresponding to different wavelengths, and plants process these colours differentially. Wavelengths in the red and blue ranges are the most important for photosynthesis, whilst green and far-red wavelengths are absorbed less easily. Canopy architecture will also influence the local light environment, whereby the structural traits of plants, and the pigments they contain within their leaves, will determine the relative proportion of each of these wavelengths and therefore the efficiency of photosynthesis.
Figure 1. The arrangement of plants will determine how light is intercepted for use in photosynthesis, but will also change the wavelengths, i.e., the colour, of light.
Climate change is expected to have a severe impact on the ability of plants to harvest light. Increased cloud cover and a rise in dust and pollution will disrupt light wavelengths, so it is vital understand more about which plants are best equipped to adapt to these changes.
"It is high time we encourage nature and revert to a more natural and biodiverse landscape to prevent, and hopefully reverse, the effects of climate change."
Within my research, I use a combination of plant physiology, computer science and mathematical modelling to understand how different architectural traits can influence the interception of light, and how, in turn, this effects photosynthesis. I use advanced image analysis methods to produce three-dimensional computerised models of plants so that I can model their function (figure 1). This includes state-of-the-art methods such as deep learning, a type of machine learning and artificial intelligence that aims to mimic the human brain and the way it learns. In my work, deep learning is used to identify different organs on plants and thus help quantify how their structures differ. I want to find which plant architectures are most suitable for a given environment (or location) to help maximise crop yields. Moreover, I wish to identify which canopy architectures are likely to be more suitable for future environments where the colour of light, temperature or precipitation has changed.
My side research interests revolve around the use of alternative cropping practices to increase the sustainability and resilience of our agricultural systems; intercropping - the growth of two or more crops simultaneously in close proximity, agroforestry - the combination of trees with pastures for livestock and/ or crops, vertical farming- growing plants in stacked layers, and urban agriculture- the growth of crop plants for food in urban environments such as cities, including allotments, home gardens and public fruit trees, can all provide benefits over the conventional agricultural practice of growing a single crop per field. Many of these benefits may arise through a better use of growth resources including light, water, and nutrients. Other benefits arise as a result of increased diversity of the agricultural system; whereby growing multiple crop or plant species leads to beneficial interactions with other wildlife such as pollinators, birds or mammals.
I am interested in which combination of species is most beneficial for resource capture and how resilient the systems will be in the face of climate change. This can be simple, such as incorporating trees and agroforestry as wind breaks to prevent soil erosion and crop damage, or to prevent damage caused by extreme weather such as floods, or more complex, such as altering the balance between pests and predators to encourage sustainable pest management. I also hope to use advanced image analysis combined with weather forecasts and predictions to identify target areas of land which would benefit from conversion to alternative cropping.
I am keen to engage other researchers in the field of agriculture and climate change but also the farming community and policymakers to facilitate a transition to a more robust agricultural future. I would like to see policy changes aimed at improving the resilience and sustainability of our agriculture systems. This could include incentives to farmers who use alternative cropping practices, incorporating trees, natural barriers or natural pest and disease defences on their land. Opportunities in this area should become more apparent as the UK transitions towards a system of providing ‘green’ payments to farmers who improve the environment – known as ‘public money for public goods’, a key component of The Agricultural Act 2020. It is high time we encourage nature and revert to a more natural and biodiverse landscape to prevent, and hopefully reverse, the effects of climate change.
Durand M, Matule B, Burgess AJ, Robson TM (2021). Sunfleck properties from time series of fluctuating light. Agr For Met, 308-309: 108554
Gibbs JA, Burgess AJ, Pound MP, Pridmore TP, Murchie EH (2019). Recovering Wind-induced Plant Motion in Dense Field Environments via Deep Learning and Multiple Object Tracking. Plant Phys.
Burgess AJ, Gibbs JA, Murchie EH (2018). A canopy conundrum: can wind-induced movement help to increase crop productivity? JXBot.
Burgess AJ, Retkute R, Herman T, Murchie EH (2017). Exploring Relationships between Canopy architecture, light distribution, and photosynthesis in contrasting rice genotypes using 3D canopy reconstruction. Front in Plant Sci.