Login

Proceedings

Find matching any: Reset
Add filter to result:
UAV-based Crop Scouting for Precision Nutrient Management
1O. S. Walsh, 1K. Belmont, 1J. McClintick-Chess, 1J. Marshall, 1C. Jackson, 2C. Thompson, 2K. Swoboda
1. University of Idaho
2. Take Flight LLC

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. 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 SPAD readings can be useful for yield potential prediction in wheat. Wheat chlorophyll content was estimated using SPAD meter. 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.

Keyword: Precision agriculture, UAV-based methodology