Imaging Digs Deep to Improve Crops

Boosting the output of important food crops such as rice and maize to meet the needs of the world’s growing population requires improvements both above and below the soil. A new imaging technique could aid these efforts.

Developed by a team at the Georgia Institute of Technology and Penn State University, the new technique and accompanying software measures and analyzes plant root systems, essential to gathering water and nutrients. It “combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field,” the researchers wrote in the study.

Researchers are studying root systems of various food crops’ dried root systems. Among them are maize plants, shown here. Courtesy of Rob Felt/Georgia Institute of Technology.

“In the lab, you are just seeing part of the process of root growth,” said Dr. Alexander Bucksch, a postdoctoral fellow in Georgia Tech’s School of Biology and School of Interactive Computing. “We went out to the field to see the plants under realistic growing conditions.”

In the study, the researchers used digital photography to garner detailed images of mature plant root systems in the field. Using advanced computer technology in the lab, those images were analyzed for more than 30 parameters, including the diameter of tap roots, root density and detailed measuring of lateral roots.

Imaging of root systems is traditionally done in a lab, using seedlings grown in small pots and containers. Such studies provide information on the early stages of development, according to the researchers, but cannot directly quantify the effects of realistic growing conditions or field variations in water, soil and nutrient levels.

“Now we can measure entire root systems for thousands of plants to give geneticists the information they need to search for genes with the best characteristics,” Bucksch said.

Researcher James Burridge determines root phenotypes manually and with a prototype of the new imaging system. Courtesy of Penn State University.

The team has already put the system to work in South Africa, evaluating maize and cowpea plants. Specifically, the researchers compiled a cowpea reference data set consisting of approximately 1500 excavated root systems. Data generated will be used in subsequent analyses to help understand how changes in genetics affect plant growth.

In the future, the new technique and software could allow for the study of crop roots over an entire growing season, the researchers said, potentially providing new life cycle data.

“We have to feed an ever-growing population and we have to replace materials like oil-based fuels,” Bucksch said. “Integral to this change will be understanding plants and how they provide us with food and alternative materials. This imaging technique provides data needed to accomplish this.”

The work was funded by the National Science Foundation Plant Genome Research Program, the National Science Foundation BREAD program, the Howard G. Buffett Foundation, the Georgia Tech Center for Data Analytics and the Burroughs Wellcome Fund.

The research was published in Plant Physiology (doi: 10.1104/pp.114).

For more information, visit www.gatech.edu.