Systems Level Analysis of Grasses to Enable Rapid Breeding Advancement

Humans rely on cereals such as rice, wheat, and maize as principal sources of calories, and on other grasses such as sugarcane and sorghum as energy sources, but these crops are not expected to meet global demand by 2050. To produce more food and fuel with fewer inputs, a variety of strategies to improve crop yields will need to be explored. These strategies may include: mining natural variation to breed crops that require less water; increasing crop temperature tolerance to expand the geographical range in which they grow; and altering the architecture of crops so they can be grown at greater density. A current bottleneck is the difficulty of efficiently quantifying plant traits (phenotypes) through time.  The development of high-throughput phenotyping technologies and flexible analysis tools that extract agronomically important traits is one focus of our research. In one study a diversity panel of 143 Brachypodium distachyon accessions was screened under control, drought, and heat conditions using a LemnaTec phenotyping platform and the resulting sensor data was examined for traits that approximate water-use-efficiency, biomass accumulation, tiller count, and plant water content. In another project we are using precision remote-sensing technologies for field phenotyping of hundreds of bioenergy and grain sorghum accessions in multiple environments. The genomes of the sorghum germplasm being phenotyped are being re-sequenced, enabling rapid breeding advancement through identification of key phenotype-to-genotype associations. In summary, the convergence of genome analysis and precision phenotyping will provide multi-dimensional insights into abiotic stress responses and intrinsic yield potential in plants.