Development of Crop Phenotype Database for Climate Change and Crop Modeling Research

Research Sponsored By: USDA
Principal Investigator: Soo-Hyung Kim
Project Description
In a rapidly changing climate, identifying crop phenotypic responses under a wide range of environmental conditions is imperative for understanding the climate impacts on crops and adapting crop systems to highly variable environments through developing novel genotypes and management practices. Sunlit controlled environmental chambers known as SPAR (Soil-Plant-Atmosphere-Research) provide unparalleled utilities in investigating plant performance under a wide range of environmental conditions with high precision. The environmental variables that can be controlled and monitored using the SPAR units include but not limited to, carbon dioxide concentrations, air temperature, humidity, soil moisture, and soil nutrients while allowing plants to grown in fully sunlit conditions. In addition, these units are uniquely capable of measuring canopy scale CO2 and H2O exchange rates in real-time. These capabilities of the SPAR units collectively make the SPAR units an ideal system to examine crop whole-plant and canopy responses under a wide range of environmental conditions from one extreme to the other extreme in their spectrums (e.g., chilling to heat stress). For example, the SPAR units provide researchers increased degrees of freedom to select combinations of multiple variables (i.e., CO2 and temperature) at different levels unlike field-based experimental systems where such capabilities are limited physically or financially prohibitive. Moreover, the experimental data collected from these chambers can be developed into a database with which crop simulations model can be formulated, calibrated, and validated. The overall goal of this research is to assess crop phenotypic characteristics of cultivars of major US crops (maize, potato, soybean and others) in a range of environmental conditions using the SPAR units, develop a crop phenotype database, and utilize the database for crop modeling and climate change research.