An integrated sensing pipeline to map the genetic loci associated with canopy radiation use efficiency in Sorghum

George-Jaeggli B1,2, Potgieter A3, Watson J3, Mace E1,2, Hunt C1,2, Hathorn A4, Eldridge M1, Laws K1, Chapman S4,5, Borrell A1, Jordan D1 and Hammer G4

  1. Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Warwick, Queensland, Australia.
  2. Agri-Science Queensland, Department of Agriculture & Fisheries, Warwick, Queensland, Australia.
  3. Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Toowoomba, Queensland, Australia.
  4. Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.
  5. Agriculture & Food, CSIRO, St Lucia, Queensland, Australia.

Cereal yield advances are slowing down and will have to come from biomass production and resource use efficiency, such as improvements in photosynthetic capacity or radiation use efficiency as further improvements in harvest index are becoming more difficult to achieve. Sorghum, which is a C4 crop with more and more re-sequenced genomes and large phenotypic diversity, is an ideal model to study natural variation in traits related to photosynthetic capacity and biomass production. We have developed remote (UAV) and proximal (tractor based) sensing platforms and a data-analysis pipeline which integrates outputs from the various sensors to estimate traits related to dynamic crop growth and canopy photosynthetic capacity, such as canopy radiation use efficiency, for hundreds of field plots. We have used these remote-sensing platforms over the last two field seasons to screen an association panel largely consisting of around 700 sorghum conversion lines, which are short, early-flowering lines developed from a diverse set of exotics through the introgression of dwarfing and photoperiod-insensitivity alleles. Our aim is to map the genetic loci and identify candidate genes associated with photosynthetic capacity in sorghum and potentially other related C4 cereals and use this information to breed lines with greater resource efficiency and yield potential.