Plant phenotyping is one of the most costly and labor-intensive activities in a breeding program. High-throughput phenotyping methods have been broadly used to estimate crop traits under different scenarios using different tools, and remote sensing is a promising technology that can provide rapid access to a large number of plots in short periods of time. Canopy temperature taken by thermal cameras and biomass dynamics through normalized vegetation index (NDVI) acquired with multispectral cameras, both on board unmanned aerial vehicles (UAV) or airborne, are already a reality at CIMMYT. Besides these applications, this technology is currently being tested in maize and wheat research programs for further applications, such as plant height, plot volume and disease detection. Research in this field of expertise is required and real advances will have an impact within CIMMYT and in the global phenotyping research community.
The candidate will be responsible for the entire remote sensing component of the experiments. This includes the UAV flight campaign and using UAV for making a flight plan and executing flights with different sensors in different locations. Image processing, data extraction and analysis will be essential tasks.
Background in remote sensing and excellent skills in GIS and statistics are essential. Knowledge of maize and wheat physiology is a plus.