High-Throughput Field Phenotyping of Plants Sri Harsha Atluri [email protected] 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.