The powerful combination of data analysis, real-time sensing and application technologies show us a way to provide optimal growing conditions for plants in a way that sounds almost too good to be true. When growing nitrogen-dependent crops like corn, farmers who adopt advanced nitrogen optimization techniques will be rewarded with maximum yields at a reasonable cost.
Corn farmers know that the days of indiscriminately bombarding fields with fertilizer are coming to an end, to be replaced with more precise application of nitrogen. The difference between a bumper crop and a disappointment at harvest time is knowing how much nitrogen to apply to corn, and when to apply it.
A growing corn plant must receive enough of the element to satisfy its need for nutrients. Too little nitrogen starves the plant and lowers yield. Too much nitrogen does nothing for yield, wastes money and contaminates the environment. So how does a farmer know how much is enough?
Variable rate nitrogen technologies have been around for over a decade, offering farmers a delivery mechanism that reduces nitrogen’s impact on their wallet. These high-tech systems use maps to deliver nitrogen on a field, with the amount changing based on yield maps, soil samples and perhaps even satellite imaging.
Yet such systems are just one piece of the puzzle. True precision requires real-time analysis. Dynamic factors such as soil moisture levels and weather conditions constantly alter a plant’s nitrogen uptake. The complexity of the nitrogen cycle and the fickle nature of the element mean the right amount is always in flux, changing from day-to-day or hour-by-hour.
To make sense of the complexity, farmers need a simple tool that manages nitrogen application by integrating all the available technologies. Advanced data analytics can help farmers make better decisions today based on real-time conditions. Remote sensing, GPS tracking and intelligent controllers can work together to ensure the right amount of nutrients are delivered at the right time and in the right way to growing plants.
Such systems require an accurate model that accounts for a particular field’s soil type, nutrient levels, weather conditions and past growing history. Such a model would adapt to the present conditions using real-time site-specific field information.
The ultimate goal is to put decision-making tools in the hands of farmers that are both easy to understand and cost-effective, with a model that accounts for not just the biophysical outcomes, but also the economic ones. Such tools would help farmers to visualize possibilities based on current conditions and data from field experiments. This would include an analysis of crop yield and chemical losses so that the grower can make the best possible strategic and tactical choices under any given set of circumstances.
Research by Fridgen, Franzen and Ping has already laid the mathematical foundation for the visualization of management zones, but additional work must be done to incorporate spatial autocorrelation and economic implications in the analysis of nitrogen levels.
The development of data analytics tools and supporting technologies that get nitrogen right require further development. It is absolutely essential that the industry get this right, because the rewards for success in getting nitrogen right are as significant as the penalties for failure.
The most obvious payoff of advanced nitrogen optimization tools would be the extra bushels of corn at harvest. For the farmer struggling to make it through depressed commodity prices, big savings on input costs are hard to ignore. Yet the greatest benefit of all would be measured in the environment.
Failure to get nitrogen right imposes a stiff penalty. As much as nitrogen delivers a massive boost to corn yield, it has an even greater effect in promoting algae growth when fertilizer runoff hits a stream or lake.