Future-Proofing Cotton Production by Building Resilient Photosynthetic Pathways
Creators: name: Sargent, Demi
Publisher: name: The Australian National University
Year: 2021

description: Climate change is projected to impact negatively on agricultural productivity through an increase in the incidence and severity of climate extremes such as heatwaves and droughts. Therefore, it is necessary to develop more productive and resilient crop cultivars. Crop yield improvement strategies include enhancing photosynthetic performance and resilience through overcoming the functional inadequacies of the carbon-fixing enzyme Rubisco. In order to sustain and improve cotton production under future climates, 'future-proofing' cotton cultivars to projected climate scenarios is required. Improving the thermal optima and photosynthetic properties through improving the kinetic properties of the key photosynthetic enzyme, Rubisco is a promising pathway to improving crop yield potential in more challenging future climates. This research aims to elucidate the potential to utilise photosynthetic traits from within the Gossypium genus in the development of climate-adapted germplasm. The first objective of this thesis is to interrogate the extent of diversity in photosynthetic performance and resilience between diverse species of Gossypium, and cultivars of Gossypium hirsutum. The second objective of this thesis is to characterise the temperature dependency of cotton photosynthesis and build an understanding of the thermal optima of various physiological and biochemical processes in diverse Gossypium species. This will provide novel information for simulating the effects of photosynthetic modification, thus quantifying the level of photosynthetic enhancement required to improve cotton yield under a variety of environmental temperatures. Analyses of photosynthetic gas-exchange measurements and a range of biochemical assays to analyse Rubisco catalytic properties under various temperature treatments underpinned this research. Through improvements made to modelling A/Ci response curves by developing plantecowrap, comparisons of VCmax (maximal rate of carboxylation) and J (maximal electron transport rate at saturating light) were more accurately modelled, making comparisons between Gossypium species more reliable. Importantly, this thesis unveiled substantial diversity of photosynthetic performance and temperature sensitivity between a total of 18 Gossypium species. Substantial diversity was uncovered between species for their photosynthetic responses to heatwave events, and the thermal optima of a range of photosynthetic processes including leaf-level photosynthetic rate (Asat), Rubisco carboxylation and electron transport. This diversity was linked to variation in their Rubisco catalytic properties, a likely result of substantial transoceanic dispersal of the genus around 5 million years ago. The Australian species from the C and G genomes were found to be some of the most resilient species to heatwave events. The Australian species also displayed the greatest thermal optima and magnitudes of VCmax, J and Asat. Notably, the Australian G genome species G. australe displayed superior photosynthetic performance and temperature sensitivity, underpinned by having the greatest mesophyll conductance and Rubisco catalytic properties at high temperatures. The potential of these traits was assessed through a series of photosynthetic modification simulations using the Diurnal Canopy Photosynthesis-Stomatal Conductance simulator (DCaPST), where the introgression of superior photosynthetic traits from G. australe into cotton may enhance biomass productivity by 4 - 5.5 %. Therefore, the findings from this thesis suggest that the future utilisation of photosynthetic traits from species such as G. australe could sufficiently enhance cotton photosynthesis, resulting in improved radiation use efficiency and biomass production. Further research is required to determine scenarios where this increase in biomass production would translate to improved fibre yield.