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

Lead Research Organisation: University of Nottingham
Department Name: Sch of Biosciences

Abstract

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.

Technical Summary

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.

Planned Impact

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.

Publications

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Durand M (2021) Diffuse solar radiation and canopy photosynthesis in a changing environment in Agricultural and Forest Meteorology

 
Description Background
Canopy movement or excitation (non-tropic and without lodging) that results from slight to moderate wind speeds is rarely considered in the context of crop improvement and remains largely unexplored. This proposal builds on our recent published evidence (Burgess et al, Front. Plant Sci (7)1392 (2016)1 that such canopy movement is a missing '4th dimension' of crop photosynthesis that has not been accounted for. High resolution 3D reconstruction showed that canopy movement has a large impact on canopy photosynthesis (up to 17 %). This highly inter-disciplinary project will provide proof of concept that physical plant properties determine optimal movement behaviour beneficial to canopy photosynthesis in low/moderate windspeeds and increase crop yield in field environments.
We suggest that canopy movement has unexploited effects on canopy light dynamics increasing the probability of photon penetration to more efficiently distribute light energy (this may increase canopy light absorption) and increasing the frequency and distribution of high light events within canopy layers. We cannot control wind but plant mechanical properties can be altered to favour beneficial responsiveness in low wind. There is little evidence that this property has been exploited in breeding. We wish to form a deep understanding of the relationship between movement, photosynthetic properties and plant mechanical properties.
We will test 3 main hypotheses. (1) Movement determines the probability that photon penetration will occur. (2) Optimal movement behaviour in a light to moderate wind (2 - 8 m s-1) is a fast 'flutter' in the upper regions of the canopy but with strong stem stiffness, providing greater photon penetration, efficient energy distribution, increased lightfleck frequency, higher induction state (3) genetic variation in wheat canopy movement can be exploited to improve photosynthesis.

Outcomes

Recovering Wind-induced Plant Motion in Dense Field Environments via Deep Learning and Multiple Object Tracking.

Wind-induced plant motion is an important feature of most agricultural systems yet it remains understudied. This is partly due to the complexity of the field environment; though image sequences showing plant motion are readily available, the cultivation of crop plants in dense field stands means that detecting features and characterising their general movement traits is extremely difficult to achieve. Here we present a robust method for characterising motion in field grown wheat plants (Triticum aestivum) from time-ordered sequences of RGB images. A dataset of 290 images was collected and annotated for ear tips from which a series of crops and augmentations were applied to increase variation and resolution when training a convolutional neural network (CNN). This approach enables the detection of wheat ears in the field without the need for camera calibration or a fixed imaging position. Videos of wheat plants moving in the wind were also collected and split into their component frames. Ear tips were detected using the trained network, then tracked between frames using a novel probabilistic tracking algorithm to approximate movement. This data can be used to characterise key movement traits such as periodicity. To our knowledge this is the first example of tracking of plant features in order to obtain more detailed static plant properties and could form the basis of new methodologies for assessing plant structure and function in the field; with automated data extraction possible for informing lodging models, breeding programmes and linking movement properties to canopy light distributions and dynamic light fluctuation.

2021 was delayed due to Covid but we have attained new data on light dynamics in canopies using fast light sensors and collaboration with a group in Finland (Matt Robson) that uses a fast spectroradiometer. We spent time adapting a Licor 6800 photosynthesis analyser to measure the effects of 0.2 - 0.3 s light transients, mimicking windflecks and as of the end of 2020 we have 2 paper in preparation on this.

In 2021 we published a new paper which compared windflecks to sunflecks using 3d modelling of photosynthesis in a wheat canopy (See Durande et al 2021). The conclusion is that variation in 3D structure alters the friquency and duration of sunflecks and windflecks.
Exploitation Route 1. The precise dynamics of light fluctuations determine productivity. Here we develop the methodologies and principles for quantifying this effect with respect to a newly emerging area of canopy movement.
2. The physical properties of plants needed for trait selection associated with movement will be identified and these may be taken up by breeders.
Sectors Agriculture, Food and Drink,Environment

 
Description CropRay: How does canopy architecture determine the composition and characteristics in lower leaf layers?
Amount £30,000 (GBP)
Organisation Gatsby Charitable Foundation 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2021 
End 03/2022
 
Title Deep learning for object tracking in an arable field 
Description we present a robust method for characterising motion in field grown wheat plants (Triticum aestivum) from time-ordered sequences of RGB images. A dataset of 290 images was collected and annotated for ear tips from which a series of crops and augmentations were applied to increase variation and resolution when training a convolutional neural network (CNN). This approach enables the detection of wheat ears in the field without the need for camera calibration or a fixed imaging position. Videos of wheat plants moving in the wind were also collected and split into their component frames. Ear tips were detected using the trained network, then tracked between frames using a novel probabilistic tracking algorithm to approximate movement. This data can be used to characterise key movement traits such as periodicity. To our knowledge this is the first example of tracking of plant features in order to obtain more detailed static plant properties and could form the basis of new methodologies for assessing plant structure and function in the field; with automated data extraction possible for informing lodging models, breeding programmes and linking movement properties to canopy light distributions and dynamic light fluctuation. 
Type Of Material Model of mechanisms or symptoms - non-mammalian in vivo 
Year Produced 2019 
Provided To Others? Yes  
Impact To our knowledge this is the first example of tracking of plant features in order to obtain more detailed static plant properties and could form the basis of new methodologies for assessing plant structure and function in the field; with automated data extraction possible for informing lodging models, breeding programmes and linking movement properties to canopy light distributions and dynamic light fluctuation. 
URL http://www.plantphysiol.org/content/181/1/28
 
Title High throughput chlorophyll fluorescence dynamics for wheat 
Description We have developed a method for the high throughput analysis of chlorophyll fluorescence (CF) , under fluctuating light, of leaf samples or whole plants. This allows kinetics of induction and relaxation of CF of a large number of leaf samples (typically up to 70) within one or two hours. Previously this would have taken one or two hours per sample. This method is bring written into a paper for submission for peer review : 'Title: A Rapid, high through-put procedure utilising chlorophyll fluorescence imaging to screen/ phenotype cereal leaf dynamic photosynthesis under controlled gaseous conditions' 
Type Of Material Biological samples 
Year Produced 2018 
Provided To Others? Yes  
Impact Method complete, still applying current research. 
 
Description Shanghai CAAS 
Organisation Chinese Academy of Agricultural Sciences
Country China 
Sector Academic/University 
PI Contribution Aided pre release with use of software and imaging techniques
Collaborator Contribution collaboration on use of ray tracing software and photosynthesis modelling. Support letter for research proposals.
Impact Aided securing current BBSRC grants with award letter
Start Year 2011
 
Description Viikki Plant Science centre (ViPS), Helsinki, Finland 
Organisation University of Helsinki
Department Viikki Biocentre
Country Finland 
Sector Academic/University 
PI Contribution With Dr Alex Burgess, set up and established a collaboration with Dr Matthew Robson who visited us in summer 2019 and co performed an experiment to measure light distribution changes in the field of whet in the UK
Collaborator Contribution Dr Matthew Robson who visited us in summer 2019 and co performed an experiment to measure light distribution changes in the field of whet in the UK. he has invited us to visit and talk about his research
Impact none yet
Start Year 2018
 
Description Keynote presentation, Japanese International Workshop on Plant Phenotyping, 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talk presented : 'canopy-environment interaction in crops'. Discussion and scoping exercises followed.
Year(s) Of Engagement Activity 2020
 
Description Organise meeting of the UK Rice Research Community 2019 at University of Nottingham 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact At U. Nottingham, I co organised the second meeting of the UKRRC. This is due to be held on the 2nd and 3rd May 2019.
The UK Rice Research consortium (UKRRC) has been established to highlight the breadth and quality of research in UK's based research institutions on rice, and to provide a focal point for building new networks both within the UK and with international partners.

Analysis shows that in previous years rice has mostly been used as a model organism for basic plant research, but recently this has changed to more applied research. For much of the world's poor, rice (O. sativa) provides the majority of daily calories. Rice productivity has more than doubled in recent decades, resulting from continued breeding efforts. However, to meet the demands imposed by the projected increase in population, rice production has to continue growing rapidly, while meeting challenges imposed by a changing climate. With the recent sequencing of >3000 different varieties, there is a huge genetic resource available for identifying polymorphisms associated with desirable traits e.g. tolerance to biotic or abiotic stress, yield, nutritional content etc., which in due course can be bred into major crop varieties.

The UKRRC is building upon genomic resources and large-scale phenotyping platforms, and works with international partners on fundamental science and applied breeding programmes to tackle food security challenges, as highlighted under Research and Partnerships.
Year(s) Of Engagement Activity 2019
URL http://ukrrc.org
 
Description Organising Monogram 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Erik Murchie cp - organised Monogram 2019 which is too be held in April 2019 . The Monogram Network meeting is the annual get together for the small grain cereal and grass research community. Academics, commercial scientists, and plant breeders gather to share the latest advances in scientific research, exchange ideas, and talk about collaboration. Monogram 2019 provides an exciting opportunity for sharing ideas and networking in a relaxed environment. Everyone from graduate students to established academics, commercial scientists and plant breeders are welcome to attend.
Year(s) Of Engagement Activity 2019
URL http://www.monogram.ac.uk/MgNW2019.php
 
Description invited speaker : CO2 assimilation in Plants from Genome to Biome 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact he growing concern over global food and energy security results from rising population, while land degradation and climate change continue to limit production. One of society's major challenges is to grow more biomass on less land, using less water, fertilizer, fungicides and pesticides than ever before. To accomplish this, a new "green revolution" that surpasses the rate of current crop and fuel production is required and improving photosynthetic CO2 assimilation is key to achieving this goal. The Gordon Research Conference (GRC), CO2 Assimilation in Plants from Genome to Biome, is among the most critical forums for bringing together the top plant scientists in the world, along with rising early-career scientists, to share and discuss the critical advances on this grand challenge. At this meeting scientists will present and discuss cutting edge, often unpublished research, that is geared toward the new "green revolution" and that will develop ideas and collaborations to guide and support research on carbon aspects of photosynthesis for years to come.
Year(s) Of Engagement Activity 2019
URL https://www.grc.org/co2-assimilation-in-plants-from-genome-to-biome-conference/2019/