Adapting roots to a hotter planet could ease pressure on food supply
Supercomputer-powered 3D imaging of root systems to help breeders develop climate-change adapted plants for farmers

Date:
July 29, 2021
Source:
University of Texas at Austin, Texas Advanced Computing Center
Summary:
The shoots of plants get all of the glory, with their fruit and
flowers and visible structure. But it's the portion that lies below
the soil - - the branching, reaching arms of roots and hairs pulling
up water and nutrients -- that interests some plant physiologist
and computer scientist the most.



FULL STORY ==========================================================================
The shoots of plants get all of the glory, with their fruit and flowers
and visible structure. But it's the portion that lies below the soil --
the branching, reaching arms of roots and hairs pulling up water and
nutrients - - that interests plant physiologist and computer scientist, Alexander Bucksch, associate professor of Plant Biology at the University
of Georgia.


==========================================================================
The health and growth of the root system has deep implications for
our future.

Our ability to grow enough food to support the population despite a
changing climate, and to fix carbon from the atmosphere in the soil are critical to our, and other species', survival. The solutions, Bucksch
believes, lie in the qualities of roots.

"When there is a problem in the world, humans can move. But what does the
plant do?" he asked. "It says, 'Let's alter our genome to survive.' It evolves." Until recently, farmers and plant breeders didn't have a
good way to gather information about the root system of plants, or make decisions about the optimal seeds to grow deep roots.

In a paper published this month in Plant Physiology, Bucksch and
colleagues introduce DIRT/3D (Digital Imaging of Root Traits), an
image-based 3D root phenotyping platform that can measure 18 architecture traits from mature field- grown maize root crowns excavated using the Shovelomics technique.



==========================================================================
In their experiments, the system reliably computed all traits, including
the distance between whorls and the number, angles, and diameters of
nodal roots for 12 contrasting maize genotypes with 84 percent agreement
with manual measurements. The research is supported by the ROOTS program
of the Advanced Research Projects Agency-Energy (ARPA-E) and a CAREER
award from National Science Foundation (NSF).

"This technology will make it easier to analyze and understand what
roots are doing in real field environments, and therefore will make it
easier to breed future crops to meet human needs " said Jonathan Lynch, Distinguished Professor of Plant Science and co-author, whose research
focuses on understanding the basis of plant adaptation to drought and
low soil fertility.

DIRT/3D uses a motorized camera set-up that takes 2,000 images per
root from every perspective. It uses a cluster of 10 Raspberry Pi micro-computers to synchronize the image capture from 10 cameras and
then transfers the data to the CyVerse Data Store -- the national cyberinfrastructure for academic researchers -- for 3D reconstruction.

The system generates a 3D point cloud that represents every root node
and whorl -- "a digital twin of the root system," according to Bucksch,
that can be studied, stored, and compared.

The data collection takes only a few minutes, which is comparable to an
MRI or X-Ray machine. But the rig only costs a few thousand dollars to
build, as opposed to half a million, making the technology scalable to
perform high- throughput measurements of thousands of specimens, which
is needed to develop new crop plants for farmers. Yet, the 3D scanner is
also enabling basic science and addresses the problem of pre-selection
bias because of sample limitations in plant biology.



========================================================================== "Biologists primarily look at the one root structure that is most common
- - what we call the dominant root phenotype," Bucksch explained. "But
people forgot about all of the other phenotypes. They might have a
function and a role to fulfill. But we just call it noise," Bucksch
said. "Our system will look into that noise in 3D and see what functions
these roots might have." Individuals who use DIRT/3D to image roots will
soon be able to upload their data to a service called PlantIT that can
perform the same analyses that Bucksch and his collaborators describe
in their recent paper, providing information on a wide range of traits
from young nodal root length to root system eccentricity. This data
lets researchers and breeders compare the root systems of plants from
the same or different seeds.

The framework is made possible by massive number-crunching capabilities
behind the scenes. These are provided by the Texas Advanced Computing
Center (TACC) which receives massive amounts of data from the CyVerse Cyberinfrastructure for computing.

Though it takes only five minutes to image a root crown, the data
processing to create the point cloud and quantify the features takes
several hours and requires many processors computing in parallel. Bucksch
uses the NSF-funded Stampede2 supercomputer at TACC through an allocation
from the Extreme Science and Engineering Discovery Environment (XSEDE)
to enable his research and power the public DIRT/2D and DIRT/3D servers.

DIRT/3D is an evolution on a previous 2D version of the software that can derive information about roots using only a mobile phone camera. Since
it launched in 2016, DIRT/2D has proven to be a useful tool for the field.

Hundreds of plant scientists worldwide use it, including researchers at
leading agribusinesses.

The project is part of ARPA-E's ROOTS program, which is working to
develop new technologies that increase carbon storage within the soil
and root systems of plants.

"The DIRT/3D platform enables researchers to identify novel root traits
in crops, and breed plants with deeper, more extensive roots," said
ARPA-E ROOTS Program Director Dr. David Babson. "The development of
these kind of technologies will help promote climate change mitigation
and resilience while also giving farmers the tools to lower costs and
increase crop productivity.

We're excited to see the progress that the team at PSU and UGA has made
over the course of their award." The tool has led to the discovery of
several genes responsible for root traits.

Bucksch cites a recent study of Striga hermanthica resistance in sorghum
as the kind of outcome he hopes for users of DIRT/3D. Striga, a parasitic
weed, regularly destroys sorghum harvests in huge areas of Africa.

The lead researcher, Dorota Kawa, a post-doc at UC Davis, found that
there are some forms of sorghum with Striga-resistant roots. She derived
traits from these roots using DIRT/2D, and then mapped the traits to
genes that regulate the release of chemicals in the roots that triggers
Striga germination in plants.

DIRT3D improves the quality of the root characterizations done with
DIRT/2D and captures features that are only accessible when scanned in 3D.

The challenges facing farmers are expected to rise in coming years, with
more draughts, higher temperatures, low-soil fertility, and the need to
grow food in less greenhouse-gas producing ways. Roots that are adapted
to these future conditions will help ease pressure on the food supply.

"The potential, with DIRT/3D, is helping us live on a hotter
planet and managing to have enough food," Bucksch said. "That is
always the elephant in the room. There could be a point where
this planet can't produce enough food for everybody anymore,
and I hope we, as a science community, can avoid this point by
developing better drought adapted and CO2 sequestering plants." ========================================================================== Story Source: Materials provided by University_of_Texas_at_Austin,_Texas_Advanced_Computing Center. Original written by Aaron Dubrow. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Suxing Liu, Carlos Sherard Barrow, Meredith Hanlon, Jonathan
P Lynch,
Alexander Bucksch. DIRT/3D: 3D root phenotyping for
field-grown maize (Zea mays). Plant Physiology, 2021; DOI:
10.1093/plphys/kiab311 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/07/210729143426.htm

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