Automated sorghum phenotyping and trait development platform
Bottlenecks in our ability to collect accurate, high-resolution, phenotypic data on energy crops such as sorghum limit how efficiently we can combine this information with genomic data to identify, and as necessary modify, the genes and alleles needed to produce superior strains for cultivation. More specifically, enabling the capacity to use sensing data from ground-based mobile and airborne platforms for automated phenotyping would greatly advance plant breeding to maximize energy potential for transportation fuel. Our interdisciplinary team at Purdue University, with support from our industrial partner, IBM Research, and a consultant, Scott Chapman, from the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia's national science agency, are developing an automated, high-throughput system, called the Automated Sorghum Phenotyping and Trait Development Platform, which is designed to help end users quantify variations in sorghum field performance and agricultural productivity and detect associations in the sorghum genome. We will develop this disruptive technology system based on airborne and ground-based mobile sensor systems whose accuracy in collecting relevant phenotypic data will be confirmed during development by ground referenced measurements obtained by our phenotyping teams using in situ and near proximal sensors as well as biomass harvester yield data.