Cells to Fields: crop movement characterisation across scales of order

There is an urgent need to improve crop yield (tonnes per hectare) in order to meet the needs of a growing global population and declining fertile agricultural land base. This proposal tackles a much-ignored factor in agriculture and plant science. Plants 'move' in response to moderate wind and this occurs on a daily basis, sometimes continually during growth. Wind induced canopy movement has a large number of effects on plant biology including the alteration of the plant microenvironment with consequences for photosynthesis and plant productivity. For example we found that movement, affected by mechanical properties, has a strong effect on the rate at which light levels change in the canopy, by altering 'light fleck' properties. This has strong implications for canopy photosynthesis (Burgess et al (2016) Frontiers in Plant Science 7, 1392; Burgess et al (2021) Plant. Cell Environ. 44, 3524-3537). It appears that movement enables the production of more rapid 'lightflecks' and increases light levels in lower leaf levels, enhancing photosynthesis at the canopy level.

We recently developed the techniques to generate high resolution 3D models of field grown wheat and rice canopies and developed approaches for 'tracking' moving canopies using the detection of wheat ears (Gibbs et al. Plant Physiology 181, 28-42 (2019)). Despite work on mechanical failure in high wind speeds, we currently have no methods for quantitative assessment of canopy motion in the field resulting from lower windspeeds that can be used to predict its influence on photosynthesis and yield/productivity over seasons. This presents a glaring critical knowledge gap, with methodologies needed across agriculture and ecology. There are likely to be many applications, especially remote sensing of canopy movement in relation to climate change.

A chance meeting in 2021 between physicists working on lung cilia motion (U.Cambridge) and crop / plant scientists working on field canopy motion (U. Nottingham) led to the idea that microscopic imaging methods could be scaled up to whole plant canopies. Cilia are fine hair like structures that protrude from a variety of cells and beat back and forth, in a manner reminiscent of plant leaves moving in the wind. After some tests in the field in 2021, it was confirmed that the method would be applicable but we lack resources to continue.

The multiDDM approach developed in U. Cambridge at the microscopic level simplifies biological movement to a core set of parameters that represent motion across all length scales. Within this programme, the multiDDM approach will be applied to large scale video capture of field-grown wheat plants.

Using plots of wheat with contrasting canopy mechanical properties, we will set up platforms in the field at several scales: frames and tripods (1-2m); cherry picker (5- 6m) and drones (>10m). We will capture videos of movement in relevant periods of growth alongside windspeed sensor data placed close to the cameras. We also will collect physiological and photosynthesis data for the models. Using the field data, the MultiDDM method will be used to generate frequencies and amplitudes of oscillation according to windspeed. The Nottingham group will utilise their existing knowledge of 3D canopy modelling to simulate light fluctuations accordingly. These light fluctuations will be used to model photosynthesis of the crop canopy over critical growth stages and provide the first quantitative prediction of the role of windspeed in crop yield. We expect this will provide new targets for crop breeding.

We will make these methods available to the community and publish findings, extending the method to other aspect of movement and features of canopies such as humidity and temperature and gas exchange.

Whilst we have begun to understand the traits that may influence canopy movement and potential impacts on biological processes we are prohibited by the complexity of the interactions which combine biological and physical factors and the currently available analysis. This project addresses this by reducing complex movement to a few simple parameters that can be transferred to canopy models amenable for the calculation of productivity .

DDM is a technique developed for the study of diffusion of particles in suspensionsm then used for the motility in microorganisms. The team of P.Cicuta was the first to use it on eukaryotic cells, and developed it for oscillatory motions. The driving forces, scales and mechanics are different between 10-micron motile cilia and <1m wheat plants, but the properties one wants to extract from a video sequence are similar: frequencies of oscillation, scale of collective motion (coherence), directionality and presence of waves.

We will set up several scales of analysis by collecting videos of wheat canopies in the field at 1- 2m, 5- 6m and over 10m, We will apply cellular-level methodology (MultiDDM) capturing supporting data on photosynthesis, hyperspectral reflectance, weather conditions with the associated videos. We will refine both cell- and field- based methods for movement characterisation with state of the art methods developed in the Cambridge lab. This involves filtering the raw high-speed video and reducing the file size to a few kb. To achieve this a fine-tuning the acquisition parameters (field of view, frame rate, length of movies, stability of the camera is needed.
We will advance on our previous empirical models of photosynthesis in static and dynamic canopies. We will correlate frequency and amplitude with the wind speed and direction. Ray tracing provides the means for modelling of light dynamics. We will use it to provide 3D canopy distortions for a set of typical windspeeds informed by biomechanical properties.