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