High-Throughput Field
Phenotyping of Plants
Sri Harsha Atluri
Sriharsha.atluri@ttu.edu
Background
World population is likely to exceed 9 billion by
2050
Will we be able to meet the food requirements
Background
The DNA and the environment (soil type,
weather, nutrition, pest, diseases, etc.)
influence how a plant will develop and
grow. This is the reason why two plants
having exactly the same DNA (genotype)
do not always look alike (phenotype).
Background
DNA sequencing have greatly improved
genotyping efficiency and reduced
genotyping costs. Methods for
characterizing plant traits (phenotypes),
however, have progressed much more
slowly.
Background
Let us assume a mapping population:




25 crosses each represented by 200 lines = 5,000
lines.
2 field replicates = 10,000 plots per treatment
2 treatments (dry land and irrigated for example)
Using a single row, 1-m wide by 4-m long plots and
ignoring the need for walkways or borders the net
row-length would be: 10,000 *2*4 = 80,000 meters
(about 50 miles).
Background


A person walking 3km/h would need about 27 hours
to visually score traits assuming no stopping.
Halting at each plot for 30 seconds would require an
additional 167 hours (about 7days).
High throughput phenotyping is needed
Project goal
High throughput phenotyping of individual
plants or lines in field environment for use
by breeders and biotechnologists.
State of the art (CSA News)
Greenhouse scale
Phytomorph (University of Wisconsin)
Lemnatec (Germany)
• Individual plants = positive
• Greenhouse = negative (too different
from real world)
Field scale
The Maricopa Agricultural Center’s high-clearance tractor in operation over
young cotton plants at Maricopa, AZ. Replicated sets of sensors allow
simultaneous measurement of plant height, foliage temperature, and foliage
color (spectral reflectance). GPS provides positional accuracy under 2 cm.
Photo by Michael Gore
Field scale
Researchers at CSIRO use a remote-controlled gas-powered model helicopter
called the “phenocopter” to measure plant height, canopy cover, and temperature
throughout a day. Pictured here are Scott Chapman (left), a principal research
scientist at CSIRO, and Torsten Merz, developer of the phenocopter.
Our tool
Corobot explorer
Problems to solve
 Navigation
Position Accuracy less than 2 cm is required
Detect and recognize a Plant

Imaging (RGB, hyper spectral, infrared)
 Data
handling
Store data so that the data can be efficiently interpreted
Navigation tasks
•Plant detection
•Plant mapping
RTK GPS
RTK GPS
LiDAR
Source: Weiss, U., et al. Plant detection and mapping for agricultural robots using a 3D LIDAR sensor. Robotics and Autonomous Systems,
59(2011) 265-273
Test field
References:
• Wikipedia
•Dr. Eric Hequet
•Dr. Hamed Sari-Sarraf
• RTK Library – www.rtklib.com
• Weiss, U., et al. Plant detection and mapping for agricultural robots using a
3D LIDAR sensor. Robotics and Autonomous Systems, 59(2011) 265-273.