429-13 Precision Sensing for Improved Wheat Production.
Poster Number 1039
Wheat is one of the Idaho’s most important crops and one of the main cereals grown in 42 of 44 Idaho counties. This project is aiming to improve wheat production in Idaho by 1) developing sensor-based N rate calculator, 2) enhancing the variety testing program by utilizing precision agriculture methodologies. Remote sensors and precision cameras allow for accurate assessment of plant health. Development of sensor-based calculator for making nitrogen (N) rate recommendations would help Idaho wheat growers to improve N use efficiency by recommending N based on yield potential. Idaho wheat producers rely on timely, comprehensive, scientifically sound information on varieties in terms of yield, quality, and tolerance to stress. Assessment of pest and disease pressure is an important aspect of variety testing. Re-emergence of Fusarium head blight in Idaho wheat fields is of great concern. Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs), aircrafts that can fly without a human operator on-board. Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. We are working on establishing a UAV-based methodology for: 1) in-season prediction of wheat yield potential – and prescribing N fertilizer rates, and 2) detection and monitoring of wheat disease (Fusarium head and others) and pest incursions that can be utilized to evaluate wheat varieties within the nurseries and to identify promising genotypes. The research component of this project will enhance the technical knowledge on application of UAV systems in wheat production by developing a system for remote wheat crop assessment. At seeding, one widely grown wheat variety in each nursery were fertilized with five N rates: 0, 75, 150, 225, and 300 lb N/a). The plots were scanned once per month utilizing the Bormatec MAJA (conventional aircraft) and 3D Robotics 8X+ (quad-copter) small UAV airframes. The tandem Canon SX260 (one with near infrared image collection capabilities and another with natural light) were used to collect the wheat reflectance measurements – Normalized Difference Vegetative Index (NDVI). The same day, the experimental plots were scanned with the ground-based handheld GreenSeeker sensor (Trimble Navigation Ltd., Sunnyvale, CA) to calibrate and correlate the UAV-based readings with the ground-based readings. The relationship between NDVI values and harvested grain yield (determined with regression analysis, SAS v9.4 (SAS Institute, Inc., Cary, N.C.)) will be used to develop wheat yield potential prediction model and the N rate calculator. Furthermore, sticky traps – Yellow Cards (Alpha Scents Inc., West Linn, OR) and petri dishes – were installed on the UAV to collect real-time information on airborne wheat pathogens, including Fusarium head blight. The traps were analyzed to identify the levels of disease/insect pest pressure.