Determination of the extent to which anatomical stomatal characters determine leaf transpiration, temperature and CO2 assimilation in wheat

Stomatal density is known to vary significantly between and within species (Weyers & Lawson, 1997). Manipulations to increase stomatal numbers per unit leaf area has not only have the potential for greater CO2 diffusion for photosynthesis (Tanaka et al., 2013) but could also enhance leaf cooling, ensuring the leaf is maintained at temperatures optimal for photosynthesis. On the other hand reductions in numbers could increase water use efficiency (Franks et al., 2015). Stomatal density therefore offers a potential target for manipulation, for altering CO2 and water fluxes between the plant and atmosphere. However as described above density alone does not determine stomatal conductance and stomatal function must also be considered. Stomata must adjust to changing environmental conditions (e.g. sun and shade fleck) and the speed of stomatal responses greatly influences gaseous fluxes (Lawson et al 2010; Lawson & Blatt, 2014). Stomatal density is also thought to be closely correlated with stomatal size, with greater stomatal densities being correlated with smaller stomata and smaller stomata are generally assumed to be faster in their responses to environmental cues (McAusland et al. 2016) highlighting the close link between anatomy and function.
Increased stomatal conductance, and therefore transpiration, has been shown to result in increased evaporative leaf cooling and yield (Lu et al., 1998). Additionally, increased stomatal responsiveness to environmental cues is one approach that can lead to improved canopy temperature reductions and yield. Thus, screening wheat germplasm for differences in stomatal anatomy and behaviour under selected environmental changes can help identify genotypes with desired canopy temperature characteristics. The aims of this research are to characterize stomatal features and responses that allow optimal leaf temperature and photosynthesis in a wheat MAGIC population in order to identify novel genetic targets for wheat breeding.