/AnMtgsAbsts2009.54753 Evaluation of Ground-Based Active Remote Sensors for Nitrogen Management in Irrigated Maize.

Wednesday, November 4, 2009: 3:00 PM
Convention Center, Room 319, Third Floor

T.M. Shaver, D.G. Westfall, R. Khosla and R. Reich, Soil and Crop Sciences, Colorado State Univ., Fort Collins, CO
Abstract:
Recent advances in precision agriculture technology have led to the development of ground-based active remote sensors that determine normalized difference vegetation index (NDVI).  Studies have shown that NDVI from active sensors is highly related with leaf N content as well as N and water stress in maize (Zea mays).  Remotely sensed NDVI imagery can provide valuable information about in-field N variability in maize and significant linear relationships between sensor NDVI and maize grain yield have been found suggesting that an N recommendation algorithm based on NDVI could optimize N application.  Therefore, a study was conducted to determine the performance of the two most prominent active sensors (NTech’s GreenSeeker™ red and Holland Scientific’s Crop Circle™ amber) by studying their relationships with applied N rate and grain yield.  The NDVI readings from both sensors had high R2 values with applied N rate and grain yield at the V12 and V14 maize growth stages.  Therefore, an N recommendation algorithm was developed for use at the V12 maize growth stage for both the amber and red sensors.  These algorithms calculated very similar N recommendations.  Also, each sensor NDVI N recommendation algorithm calculated unbiased N recommendations suggesting that each was a valid estimator of required N at maize growth stage V12 to achieve optimum grain yield.  The amber and red sensors both perform very well in the determination of N variability in irrigated maize at the V12 and V14 growth stage and the integration of these sensors and the appropriate N application algorithms into an on-the-go fertilizer application system would increase the spatial accuracy of N application on fields that are spatially variable if these algorithms are shown to be stable over time and space.