3D Canopy Architecture Modelling
Removing the inefficiencies of 3-dimensional canopy photosynthesis by the alteration of leaf light-response dynamics and plant architecture
Photosynthesis in plants is the uptake of CO2 by leaves and its assimilation into carbohydrates within specialized organs (chloroplasts), a process that requires the absorption of light by chlorophyll. However the rate of photosynthesis over a given period of time varies according to environmental changes such as light intensity, leaf age, temperature and other factors. This has consequences for productivity of crops which depend on high rates of photosynthesis for high yields. Productivity is the sum total of a large number of leaves in a canopy, many of which shade (or partly shading each other) and are usually 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. The reasons are unclear but a large part is thought to be due to the way leaves respond when re-constructed into a large 3D 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 very sensitive to light intensity. The difference in light intensities that exist within the canopy (an exponential decline from top to bottom) is significant and is affected by the precise architecture of the canopy i.e. the amount of leaf area per unit ground area, 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 e.g with frequent and transient appearance of ‘light-flecks’. The movement of the canopy plays a major part in how fast or slow light flecks are generated, and where in the canopy they appear. Photosynthesis should be optimized to these rapidly changing conditions, but there are indications that it is not. The environment can cause a ‘down-regulation’ of photosynthesis in the field and this can be measured by comparing actual leaf photosynthesis against the maximum. It is not clear how this down-regulation interacts with canopy architecture and the responses of leaves. One problem is that we do not have detailed images of crop canopies in 3 dimensions and we do not have sophisticated models that allow us to map the complex changes in light intensity to photosynthesis.
Crop canopies perform a number of important agronomic roles, some photosynthetic , others not. Therefore we need to understand the problem ‘in reverse’ – i.e. to take good 3D images of crop canopies, both still and moving, calculate the typical changes in light intensity that occur in that canopy and then change photosynthetic dynamics so that it matches those changes. We will grow canopies of productive crop plants, rice and wheat in a special glasshouse that will enable us to image crop canopies, when still, and produce 3D high resolution images using laser scanning and camera techniques. Novel techniques will be tested for detecting plant movement in wind and we will then distort these images to examine the effect of wind induced leaf ‘flutter’ and stem bending on light distribution. We will use these images in a mathematical ray-tracing program to finely map the changes in light that occur within the canopy. These changes will be used to predict which processes dominate the canopy-productivity process.
This is essentially a modelling and imaging project of plant canopies: we will begin the following phase by ordering rice mutants altered in key reactions identified from these models and grow these to test whole canopy productivity. If successful we can achieve a step change in productivity by eliminating any wasteful processes that occur within the canopy.
- Michael P. Pound, Andrew P. French, Erik H. Murchie & Tony P. Pridmore 2014 Automated Recovery of Three-Dimensional Models of Plant Shoots from Multiple Color Images Plant Physiology 166 (4), 1688-1698