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Data Collection

A picture of myself taking soil samples in a strip.

Just before the side-dress nitrogen fertilizer is applied to the corn fields, it is time to do a lot of field work. To begin, the PSNT (pre-side dress nitrogen test) is taken. They are soil samples taken in relation to the GPS points in the field. It requires 8 cores of soil from 12 inches deep. Along with that is sample of 8 cores at 8 inches deep to measure the concentration of other macro nutrients like potassium and phosphorous. Each field has a L, R, and an N strip. The N strip is where the extra fertilizer is added to. Depending n the size of the field, the number of points vary. In some fields there may be up to 19. That is 114 soil samples for one field!

Another job is to walk the greenseeker. The greenseeker is a device that measures Normal Digital Vegetative Index (NDVI). It is used to quantify vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs). This is one way to estimate the potential yield.

ndvi formula

The formula for NDVI. NIR stands for the near-infrared light reflected and Red is the amount red light absorbed.

Covering each strip does take a long time since there is only one greenseeker. It’s especially grueling during the heat and humidity of summer while keeping at a constant speed at 3 feet above the canopy.

A picture of myself walking the greenseeker at Aurora.

Drones flying can be very challenging.  Weather and surrounding objects play a large role in the success of a drone flight for a particular field.  The drone is responsible for taking multi spectral satellite images that measures the amount of reflected light by the plants from the sun.

A close view of the drone used to take light images.


It has been an insane period of time traveling across the New York from Peru, to Hudson Falls, and to Perry. In total 30 fields and 5 research plots were soil sampled, had greenseeker data, and drone images taken. A total of 3147 soil samples! The next part of the project is processing the data in order to make sense of it all.

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