IBERS (Institute of Biological, Environmental and Rural Sciences) hosts a vast collection of Miscanthus germplasm comprising sterile triploid hybrids such as M. × giganteus and members of its progenitor species, M. sinensis and M. sacchariflorus. Species within this collection show enormous diversity in biomass-related traits, including flowering time, which is considered important for both quantity and quality of biomass. We collected data for flowering time over 4 years from a trait trial in Aberystwyth. The trial contained 244 genotypes with diverse flowering times. The observed data were then compiled with collected meteorological data and analysed using machine learning. A regression model was built to allow for the prediction of flowering time based upon the meteorological conditions, including degree days and soil moisture deficit estimated using Penman-Monteith. We discuss the units of temperature and moisture availability, referred to as the hydrothermal time constant, required to reach flowering and investigate their potential variability for all areas of the UK.
|Number of pages||20|
|Journal||Aspects of Applied Biology|
|Publication status||Published - 2011|
- modelling flowering time