Optimising site-specific solar radiation modelling for its application in the horticultural, agricultural and photonics industries

Understanding how plants detect signals in light quality also opens up the possibility to influence plant physiology and growth in plant production environments by manipulating the spectral composition of light. In our ongoing project plant light responses have been studied in the context of spring phenology in the forest understorey. We have compiled a database of solar irradiance reaching the understorey of different forests, and use these data to interpret specific plant responses produced under different tree species and along environmental gradients through the year. To permit the identification of causal factors changing the spectral composition, our measurements are normalised against clear-sky modelled data.

This plant photobiological knowledge and methodological capability has huge application potential, allowing the actual light conditions to be brought closer to the expected optimal conditions for particular purposes in plant production. We will attune models of irradiance in controlled environments using measurements under practically-relevant scenarios to improve model accuracy in line with current approach for forest canopies. This will involve validation of site-specific modelled solar irradiance against precise on-site measurements for crop production, forestry and other photonics sectors. By incorporating these data into models that use environmental parameters to forecast yields and pest management, guidelines can be produced for optimising light conditions to specific purposes.

These guidelines will target an improvement in plant growing conditions, achieved by tailoring light to location in a way that optimises resource use of the natural input of sunlight. This information will enable growers to choose the most appropriate cladding materials for greenhouses and polytunnels, and supplemental lighting to match their environment-specific needs. These applications allow the optimisation of growth conditions with potentially huge efficiency savings to growers, producing economic benefits and improvements in quality and yield that address food security concerns.

Continued future expansion of this modelling to viticulture, forestry and material manufacturing would provide quality improvement possibilities, and better cost-and-energy efficiency to the respective sectors. In all, these varying fields that can be classified under bioeconomy and photonics should benefit from the actions taken in the proposed project.