Plant phenotyping is the measurement of physical and biochemical traits as they change in response to genetic mutation and environmental influences. Trait information, such as growth, development, adaptation, yield, quality, and resistance, is important to plant breeders to develop improved varieties. These qualities have traditionally been measured by scientists visiting a field, where individual scientists make visual assessments, which can be costly and time consuming. The practice is also imprecise, as two researchers may make different assessments because of different perspectives and human bias. Although traditional plant phenotyping methods are costly and imprecise, improvements to these methods can increase crop productivity and data accuracy.
Starting in 2012, the CIAT phenotyping team, working with university/industry partners, has advanced available techniques for breeders and the scientific community by using innovative technologies for above- and belowground phenotyping. To measure aboveground phenomics, CIAT scientists applied tools such as automated rainout shelters, boom irrigation systems, barcoded plots, and hyperspectral and multispectral remote sensing to test fields and create a simulation to mimic natural precipitation. Images taken from unmanned aerial vehicles (“drones”) and cameras placed on eight-meter-high towers provided scientists with precise real-time crop data, which can be used to help farmers make decisions, such as when to apply water and fertilizer. Remote sensing also allows scientists to produce rapid detection results about water- and nitrogen-use efficiency of plant varieties. This is particularly important in low-input/scarce environments.
This task has been made possible by the alliance between the Center and Japan, through the Science and Technology Research Partnership for Sustainable Development (SATREPS) project, supported by the Japan International Cooperation Agency (JICA) and the Japan Science and Technology Agency (JST). All of these entities see this technology as the means to speed up the development of new rice varieties.
To address the challenge of data collection for underground conditions, Ground Penetrating Radar (GPR) technology is incorporated into current phenotyping methods to provide new insights that help enhance cassava productivity. In collaboration with IDS Geo Radar, a private company, and Texas A&M University, CIAT applied a tool previously used to detect tree roots and metal pipes, and is adjusting the specifications to be able to detect cassava roots.
What has changed?
These improved phenotyping methods and tools are being tested and validated by CIAT and partners in the agricultural science community. In practice, these methods and tools provide breeders and scientists with more precise information to produce new and more effective crop varieties. Prior to this work, scientists and breeders were limited to using imprecise, costly, and only above-ground phenotyping. Now, with GPR technology in development, the agricultural science community will soon be able to rapidly observe the link between the root and the plant and appraise root crops such as cassava and sweet potato. This technology vastly improves the speed of phenotype information flow for cassava because assessments can be made while the roots are still planted.
In one example, these new phenotyping techniques were applied in a study with private partner Arcadia Bioscience to measure the performance of nitrogen-efficient rice lines. Results of the study can be viewed here.