The 4-dimensional plant: enhanced mechanical canopy excitation for improved crop performance

There is an urgent need to improve crop yield (tonnes per per hectare) in order to meet the needs of a growing global population and declining fertile agricultural land base. One of the current important targets for crop improvement is photosynthesis, a neglected trait in previous plant breeding efforts.

Photosynthesis requires the uptake of carbon dioxide by leaves and its 'conversion' into carbohydrates using water and absorbed solar energy. However high rates of photosynthesis, on which yield depends, are sensitive to environmental changes such as light intensity, temperature and other factors. Crop productivity is the sum total of photosynthesis in leaves in a canopy, many of which shade each other and have different ages. We can calculate the potential productivity of whole canopies based on leaf photosynthetic attributes and other physical and physiological factors. When we do this the theoretical productivity tends to be much higher than the measured productivity which is partly due to the way leaves respond when re-constructed into a large three dimensional canopy. In this state, plants exist as a community which has emergent properties that we cannot necessarily predict from plants grown individually. If we can eliminate the gap between the theoretical and measured productivity we can achieve a step change in productivity.

Photosynthetic rate is sensitive to light intensity. The difference in light intensities that exist within the canopy is significant and is affected by the architecture of the canopy i.e. the angle, shape and size of leaves and their position within 3 dimensional space. This means that the light intensity has great variability in space and time within canopies. Photosynthesis is not perfectly adapted to instantaneously match the fluctuations in light intensity - its lag results in substantial reductions in productivity and even water use efficiency.

This proposal tackles a much ignored factor. Plants 'move' in light to moderate wind and this occurs on a daily basis, sometimes continually during growth which shifts the light patterns within the canopy. In recent work we found that movement has a strong effect on the rate at which light levels change in the canopy with strong implications for canopy photosynthesis. Such movement of the canopy plays a major part in how fast or slow light flecks are generated, and where in the canopy they appear. It seems that movement may enable the production of more rapid 'lightflecks', enhancing photosynthesis at the canopy level. We don't consider high speeds that result in damage, but we do incorporate lodging in our assessments of canopy viability.

In a recent paper (Burgess et al (2016) Frontiers in Plant Science 7, 1392) showed that canopy movement has the means to alter photosynthetic responses at the canopy level. We also developed the techniques to generate high resolution 3D images of field grown wheat and rice canopies and for 'tracking' moving canopies. In this proposal we will bring these techniques together to produce models of canopies of rice and wheat and make these models move realistically in response to physical factors. At the same time we will use wheat and rice populations and panels with varied physical characteristics and responsiveness to wind and create data driven tracking movies of these canopies , making the 3D reconstruction move realistically. We will create methods for predicting light distribution in these canopies combining ray tracing techniques with field measurements of light distribution. We predict that the most productive property is for leaves to be highly responsive to wind at the top of the canopy but retaining a strong stiff stem.
At the same time we will measure photosynthesis and biomass production in wheat lines which are amenable to genetic analysis so that we can discover the hereditary basis for the movement. Therefore the results will be used in plant breeding.

Crop canopy architecture is hard to capture and quantify in the field in high resolution despite it being fundamental in determining both radiation use efficiency and final yield. One of the most important reasons is occlusion within dense canopies. At the University of Nottingham we developed, released and published accessible methods for full automated high resolution 3D canopy reconstruction using a RGB stereo approach, removing entire plants from the canopy and rapidly scanning. This was used to study key canopy light-driven processes.

The general architectural ideotype for enhanced photosynthetic performance in crops is relatively well understood, largely associated with upright leaves, but there is an understanding that dynamic photosynthetic responses are suboptimal.
Here we analyse an overlooked (but ubiquitous) event in nature - the movement of canopies in light to moderate wind. Our recent work (Burgess et al 2016, Frontiers in Plant Science, doi:10.3389/FPLS.2016.01392) used high resolution 3D reconstruction to show that gentle, non-tropic, non-fatal movement in canopies has a substantial impact on canopy photosynthesis (up to 17 %) and hence crop yield via alterations in canopy light dynamics.

In this proposal we will use new image tracking technology and high resolution 3D reconstruction (developed at Nottingham) to produce the world's first ideotype for optimised movement for enhanced photosynthesis in wheat and rice canopies. We will use tracking of plant motion to develop data-driven dynamic models of mechanically excited plants and altered canopy light distribution. In parallel we develop a mechanical model informed by plant physical and biomechanical properties. We will apply these new technologies to wheat populations growing in the field to uncover new mechanical traits that will be investigated by genome wide association studies (GWAS) and sequencing within the lifetime of the project.

If successful it will result in a step change in resource use efficiency and yield for many scenarios. Almost a billion people in the world are defined by the FAO as 'hungry'. A step change in yield would instantly alleviate this whilst for poor farmers it would help them to generate extra cash to lift them out of poverty and improve health and wellbeing. For the rest of the world it may result in a lowering of food prices which would benefit economies and prevent surplus depletion allowing security.
We will make all the tools produced by U.Nottingham and co-produced with Shanghai available for use as open source. This includes: software (ray tracing) which will be co-credited between Nottingham and Shanghai, a data driven and biomechanical model for predicting movement from physical traits, the tracking technology and software, the data from genetic analysis of the wheat populations.
1. Commercial and public plant breeders. Those attempting to genetically improve crop plants for higher yields and resource use efficiency (such as commercial and government plant breeders) will be provided with a source of novel traits and the tools for selection (models based on physical plant properties). Major crops would be wheat and maize (e.g. the maize and wheat improvement centre, CIMMYT, Mexico and International Rice Research Institute (IRRI). The GWAS data from analysis that occurs during or after this project could enable the generation of markers to use in these species and inform application in different crop species. This project is focusses on major cereals but equally applicable to any crop where biomass is important, for example brassicas, and bioenergy crops and secondary fuels which do not compete with food production, such as Miscanthus. The time taken would be restricted by the ability to introduce genes into crop plants by breeding, introgression and transformation. Possibly prototype plants could be available as soon as 5 years after the lifetime of this grant (allowing time to breed for stable mutant lines).
2. Food producers. This project is unique with high potential to improve crop biomass and grain yield. Rising global population and pressures upon land use caused by urbanization and erosion mean that higher productivity is essential to meet food security needs by 2050. If the gap between theoretical and actual production rates are closed then beneficiaries are universal because this would represent a sustainable improvement via inherent improvement in resource (radiation) use efficiency (RUE). Most notable are those in poor areas and marginal environments. An increase in RUE will have knock- on implications for nitrogen and water use efficiency.
3. International science and agriculture-related organisations. These data may be incorporated into predictive models of crop yield that are utilized by Food and Agriculture Organisation and other organizations such as the Intergovernmental Panel on Climate Change e.g. crop yield forecasts under differing environmental scenarios are used in producing advice for policymakers which part determines government policy.
4. Agricultural businesses producing seed and crop treatments, agricultural consultancy agencies would benefit from an advance in our understanding of the factors that limit crop yield, crop productivity and resource use efficiency and may invest more in the area of modeling of basic plant processes.
5. The public and environment. An improvement in crop yield or crop resource use efficiency results in the potential to reduce impact on the natural environment by reducing land cultivated and inputs of water and nitrogen (via the inherent improvement in photosynthesis). Public sector may benefit if the tools prove useful for imaging of processes relevant to the quality of life and society in general, e.g. in the imaging of plant canopies to aid in the realistic recreation of landscapes.