Global Maize Project in the United States: Virginia

The Global Maize project being conducted near New Kent, Virginia, is comprised of several experiments designed to compare the effect of various agronomic practices thought to increase corn productivity with standard farmer practices. One of the experiments has been evaluating the use of decision support systems (DSS) to optimize in-season N applications. The specific objective of this experiment is to compare yield and N use efficiency (NUE) of side-dress fertilizer application rates prescribed by: 1) the Virginia Corn Algorithm using a GreenSeeker^(R) optical sensor (VCA), 2) the Maize-N computer simulation model (MN), 3) the Nutrient Expert^(R) for Maize computer simulation model (NE), and 4) standard yield goal based rate (STD). Field experiments were established at six locations between 2012 and 2014. The experimental treatments included a complete factorial design of four different pre-plant fertilizer application rates (0, 45, 90, and 135 kg N/ha) with the three different DSS prescribed rates and the standard rate.

There were no significant differences in grain yield among the various DSS for any of the six site-years. However, DSS did affect NUE (calculated as kg grain/kg N). In all site-years, the side-dress N rate recommended by the VCA resulted in significantly higher NUE compared with the STD. Using MN resulted in higher NUE in four of six site-years, while NE-derived N rates resulted in lower or not different NUE in four of six site-years. These results indicate that while additional site-specific calibration may be needed to improve the performance of some of the DSS evaluated, the use of an in-season DSS can improve NUE over a standard yield goal-based N rate recommendation.