Timely Topics: The Value of Variable Rate Technology (VRT)

Contributed by Dr. Steve Philips

Director, IPNI North America Program

Part 2 (of 2 part series)

In his presentation at the 2015 InfoAg Conference, Dan Frieberg, President of Premier Crop Services, said of VRT, “Real world agronomy is integrated and complex; we can’t make what is truly complex simple –we can make it easy, but not simple.”"

Varying rates of fertilizer, seed, water, and other inputs across the field is the easy part. The challenge lies in choosing the information that goes into defining the management zones (MZ). The days of creating MZ solely from a yield map or grid soil sampling are behind us. Decision-making in precision agriculture (PA) has become more data-driven and our ability to incorporate multiple layers of agronomic data into MZ development is greater than ever before. So, which data layers are most valuable in creating reliable MZ?

Yield monitoring remains one of the most popular and commonly used data layers in defining MZ. Yield maps can provide a measure of the scale and location of variability in the field, but if used alone without properly understanding the data, they can be misleading. In his presentation at InfoAg 2015, Dr. Raj Khosla, professor of PA at Colorado State University, discussed the process of yield mapping, how to eliminate errors in yield maps (e.g., “cleaning” the data), and how to evaluate multiple years of yield data to create reliable “decision maps” for MZ delineation. Yield maps are good for answering “where” and “how much” variability exists in the field, but they don’t say anything about “why.”

Soil fertility and other soil properties are often highly correlated with yield as the why” in spatial variability. The best way to collect a soil fertility data layer is by grid sampling the field. The Plant Nutrition Today article “Grid Soil Sampling: How Small? How Often? How Useful?” addresses several questions about grid sampling procedures, but the consensus is that soil sampling density (e.g., grid size) is critical in developing quality soil maps.

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