101457 Uav-Based Scouting for Precision Nitrogen Management in Wheat.

Poster Number 470-530

See more from this Division: SSSA Division: Soil Fertility and Plant Nutrition
See more from this Session: Soil Fertility and Plant Nutrition Poster

Wednesday, November 9, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Olga Walsh1, Jordan R. McClintick-Chess1, Juliet M. Marshall2, Chad Jackson3, Craig Thompson4, Kristin Swoboda4 and Steven M. Blanscet5, (1)Parma Research & Extension Center, University of Idaho, Parma, ID
(2)Idaho Falls Research & Extension Center, University of Idaho, Idaho Falls, ID
(3)Aberdeen Research & Extension Center, University of Idaho, Aberdeen, ID
(4)Take Flight UAS, LLC, Boise, ID
(5)University of Idaho, Parma, ID
Poster Presentation
  • SW Drones, ASA16.pdf (2.0 MB)
  • Abstract:
    Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). 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. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of wheat yield potential – and prescribing nitrogen (N) fertilizer rates. Development of sensor-based calculator for making 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 wheat yield potential, quality, and tolerance to stress. The research component of this project aims to enhance the technical knowledge on application of UAV systems in wheat production by developing a system for remote wheat crop assessment. Five experimental sites were established at 5 locations in Southeast and Southwest Idaho in he spring of 2016. At seeding, wheat was fertilized with five N rates: 0, 75, 150, 225, and 300 lb N/a. The wheat plots were scanned utilizing 3D Robotics 8X+ (quad-copter) UAV twice in the growing season – early tillering (Feekes 2-3) and late tillering (Feekes 5-6). 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. Plant height has proved to be a useful yield potential prediction component. Plant height was measured on each day the sensor data is collected and at harvest. Previous work indicated that chnolophyll readings can be useful for yield potential prediction in wheat. Wheat chlorophyll content was estimated using SPAD meter (Spectrum Technologies Inc., Aurora, IL). 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. Upon collecting a robust multiple site-year data set, and verifying the yield potential equation, the sensor-based N rate calculator will be developed. Further analysis of data is required to determine whether the same algorithm can be used for irrigated and dryland wheat. Detailed analysis of GPS-tied data points is required to calibrate UAV vs handheld collected data.

    See more from this Division: SSSA Division: Soil Fertility and Plant Nutrition
    See more from this Session: Soil Fertility and Plant Nutrition Poster