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The Consortium for Advanced Sorghum Phenomics (CASP)

Pacific Northwest National Laboratory (PNNL)
ARPA-E Award: 
Richland, WA
Project Term: 
09/15/2015 to 09/14/2019
Project Status: 
Technical Categories: 
Critical Need: 

TERRA project teams will integrate the agriculture, information technology, and engineering communities to design and apply new tools to the development of improved varieties of energy sorghum, a crop used to produce biofuel. Producing the large amounts of biomass needed for biofuels to displace petroleum requires significant improvements to the productivity and efficiency of biofuel crops. The teams will enhance methods for crop phenotyping (identifying and measuring the physical characteristics of plants), which are currently time-intensive and imprecise. The new approaches will include automated methods for observing and recording characteristics of plants and advanced algorithms for analyzing data and predicting plant growth potential. These innovations will accelerate the annual yield gains of traditional plant breeding and support the discovery of new crop traits that improve water productivity and nutrient use efficiency.

Project Innovation + Advantages: 

Pacific Northwest National Laboratory (PNNL), along with its partners, will use aerial and ground-based platforms to identify traits required for greater production yield and resistance to drought and salinity stresses to accelerate sorghum breeding for biofuel production. The project will combine plant analysis in both outdoor field and indoor greenhouse environments as each provides unique advantages; and will use robotics and imaging platforms for increased speed and accuracy of data collection. Traditionally aboveground biomass is measured by harvesting, drying, and weighing the plant material. As an alternative approach, the team will develop non-destructive high-throughput methods to measure biomass over time. Drought tolerance will be measured by mapping water stress and using sensors to compare the difference between the canopy temperature and air temperature. The overall goal of the project is to understand the traits related to increasing biomass yield and drought/salinity stress, and to predict those traits in the early stages of plant development, before those traits become apparent using current methods.

Potential Impact: 

If successful, the PNNL team will develop an integrated phenotyping solution to accelerate bioenergy plant breeding by identifying the traits needed to yield greater amounts of biomass from plants able to withstand greater environmental stress.


Improved biofuel crops could lead to increased production of domestic biofuels, reducing dependence on foreign sources of transportation fuels.


Increased use of biofuels could significantly reduce CO2 emissions from transportation, and improved varieties of biofuel crops could use less water and be more resistant to environmental stress.


Advanced crop and breeding techniques could speed up and lower the cost of developing improved crop varieties for biofuels and other agricultural applications

Innovation Update: 

(As of May 2018)
The CASP team is seeking to develop high-biomass sorghum with superior drought/salinity tolerance. The team uses a multi-modal sensor suite of LiDAR, multispectral cameras, and thermal cameras mounted on an unmanned aerial vehicle (UAV) to detect traits indicative of improved yield and drought tolerance. Data-processing software then translates UAV-based imagery into plant trait measurements. To link the phenotypes observed to specific DNA sequences, the team has applied large collections of diverse sorghum germplasm for genome-wide association studies to field phenotypic data and identified over 200 genetic markers associated with drought tolerance and/or biomass accumulation. This information allows researchers to more confidently identify genetic markers associated with the traits measured and identify genes specific to plant life stage.


In 2017, the team completed a proof-of-concept project on field corn with a major U.S. seed company, collecting data over breeding trials and demonstrating the successful collection of plot-level traits. The UAVs developed by Blue River Technology (BRT), a member of the CASP team, can produce field maps that provide breeders and growers with unprecedented insight into crop and plant health. In 2017, John Deere acquired BRT for its expertise in applying computer vision, machine learning, and robotics to agriculture.


For a detailed assessment of the PNNL project and impact, please click here.


ARPA-E Program Director: 
Dr. David Babson
Project Contact: 
Dr. Christer Jansson
Pacific Northwest National Laboratory
Lawrence Berkeley National Laboratory
Blue River Technology, Inc.
Release Date: