403-2 Using Aerial Imaging in a Large-Scale Roll-out of N Sidedress Recommendations for Potato.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Symposium--Use of Aerial Imagery for Nutrient Management

Wednesday, November 9, 2016: 10:50 AM
Phoenix Convention Center North, Room 231 B

Frits K. Van Evert1, Bert Meurs2, David van der Schans3, Johan Booij3, Willem van Geel3 and Corné Kempenaar2, (1)Wageningen University & Research Centre, Wageningen, NETHERLANDS
(2)Wageningen University and Research, Wageningen, Netherlands
(3)Wageningen University and Research, Lelystad, Netherlands
Abstract:
In the temperate climate of the Netherlands, soil nitrogen supply varies widely from year to year, from field to field and sometimes even within a field. Potato farmers can respond to this variability by measuring the progression of nitrogen uptake and applying an appropriate amount of sidedress N if and when needed. Indeed, sidedress recommendations based on physical measurements of crop and/or soil are commonly used. A crop reflectance-based N sidedress system for potatoes was developed 20 years ago that works well when reflectance measurements from a tractor-mounted sensor are used. This system has not been widely adopted, possibly because only a limited area can be covered with one (not inexpensive) sensor. Satellite imagery could in principle be used to cover a large area, but is often not available in the cloudy Netherlands. It is expected that Unmanned Aerial Vehicles (UAVs) can be used to obtain accurate reflectance measurements that cover a large area (hundreds of hectares). For 2017, we are planning a nation-wide roll-out of N sidedress recommendations in potatoes based on aerial imaging obtained with UAVs. We are partnering with Agrifirm Group, a large farmers’ cooperative, and a team of independent UAV operators. A key enabling factor is Agrifirm’s team of consultants. Another key enabling factor is Akkerweb (http://www.akkerweb.nl), a web-based portal that allows for safe and easy storage of spatial and temporal soil, crop, climate and management data; and provides a mechanism to deliver model-based recommendations. In this presentation, we outline the reflectance based recommendation system, given an overview of the entire workflow from ordering aerial images to delivering a N sidedress recommendation, and present results of the field experiments that were performed in 2016 to fine-tune the recommendation system.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Symposium--Use of Aerial Imagery for Nutrient Management