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

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:

Background

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)

Phytomorph (University of Wisconsin)

Lemnatec (Germany)

Greenhouse scale

• 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.