The world’s largest robotic field scanner has been inaugurated at the University of Arizona’s Maricopa Agricultural Center, or MAC, near Phoenix.
Mounted on a 30-ton steel gantry moving along 200-meter steel rails over 1.5 acres of energy sorghum, the high-throughput phenotyping robot senses and continuously images the growth and development of the crop, generating an extremely high-resolution, enormous data stream — about 5 terabytes per day.
The world’s largest robotic field scanner (white steel box) is mounted on a 30-ton steel gantry moving along 200-meter steel rails over 1.5 acres of energy sorghum at the Maricopa Agricultural Center. Image credit: Susan McGinley
The scanner is part of the U.S. Department of Energy’s Advanced Research Projects Agency-Energy, or ARPA-E, program known as Transportation Energy Resources from Renewable Agriculture, or TERRA. The overall goal of the multi-institutional effort that includes the UA is to identify crop physical (phenotypic) traits that are best suited to producing high-energy sustainable biofuels and match those plant characteristics to their genes, greatly speeding up plant breeding to deliver improved varieties to market.
The UA and TERRA hosted a recent field day, which included a demonstration of the “field scanalyzer” and other ground and air-based robotics for plant breeding, along with tractor-based sensors and presentations on data analytics platforms for energy crops.
“The Maricopa Agricultural Center looks like a farm, but really it’s a laboratory. Having the field scanner here is part of our transformation into the next phase of agriculture,” said Shane Burgess, UA vice president for Agriculture, Life and Veterinary Sciences, and Cooperative Extension; dean of the UA College of Agriculture and Life Sciences; and director of the Arizona Experiment Station.
“The LemnaTec Scanalyzer is the largest field crop data acquisition platform in the world,” Burgess said. “It’s the vanguard of systems integrating phenotype with genotype for improving agricultural production.”
The test plots include 176 lines, cultivars and hybrids of sorghum planted in an area about the size of a football field. About 1.25 acres (30,000 to 40,000 plants) are being scanned, with the data feeding into the onsite Maricopa Phenomics Center, a joint collaboration with USDA-ARS Arid-Land Agricultural Research Center and MAC. The University of Illinois is handling the big-data analytics.
Scientists expect to see numerous variations in plant height, leaf surface area, biomass, heat tolerance and other responses to local conditions.
“The system was installed in Maricopa because we are the best location in the United States to do drought and heat studies,” said Pedro Andrade-Sanchez, associate professor and precision agriculture specialist at MAC in charge of the field deployment of the sensor systems. “Our climate, the natural conditions of the low desert, is why we are here. We manage the environment to provide the best conditions to image these crop materials.”
The UA’s role is twofold: to provide and maintain the infrastructure (instrumentation, electric power and a very large data pipeline) under Andrade’s direction and to establish and conduct the plant experiments, involving a complex experimental design and precise placement of seeds in the ground to be georeferenced properly. Mike Ottman, extension agronomist in the UA School of Plant Sciences, is handling the agronomic aspects of growing sorghum.
“We know the genes, but where we’re stumbling is we don’t know the phenotype, meaning the physical characteristics of the crop — height, leaves, how fast it grows,” Ottman said. “In the past, someone with a clipboard and a pencil had to take notes on these things. Now we have several scanning instruments that can track a crop and take our notes for us. It’s called high throughput phenotyping, meaning you can characterize all of these plants in a hurry a couple of times a day, and far more objectively. You can note water stress, varieties that are drought tolerant and then look at the common genes.”
USDA-ARS research plant physiologist Jeff White is using the various remote sensing capabilities of the scanner — 3-D capability, thermal imagery, fluorescence — to measure leaf area and other characteristics. Crop simulation models, combined with the phenotyping data he obtains, will help infer plant/water interactions and transpiration. White’s role is to ensure that the data collected by the scanalyzer correlates with important characteristics of the crop involving growth and development.
Although currently set to measure plant traits best suited for biofuel production, the field scanner is a reference tool that eventually will be scaled down to specific objectives and breeding applications in other crops. Grains, green leafy vegetables and loblolly pines are among the possibilities.
“The conditions allowing us to phenotype for the most important traits for agriculture in Arizona are right here,” said Karen Schumaker, director of the School of Plant Sciences. “Ultimately, we will be able to examine more than just leaf characteristics in a field. At some point, this could be used for seed germination and breeding for below-ground root systems for drought — roots that spread deeper or wider below ground. It’s just the start.”
Source: University of Arizona