Precision Ag 101

Running a precision software and mapping company, there are a few questions and comments that come around too frequently. Where do I start? What’s the cost? It will not work on my farm. Well to these questions, I have a standard response. “It depends!” The agronomist in me coming out. That being said, there are things we need to know to answer these questions. What are you doing now agronomically, manure history, liming needs, equipment, who’s spreading fertilizer, crop rotation, are we building grid system or a zone system? In this article, we will tackle the first question, “Where do I start?”.

  So, the biggest question in where to start is, do I need to Grid sample or Zone sample? To make this decision, look to your cropping history first. Do you have manure history in the last 30 years, liming is required, erratic phosphorus or potassium values in conventional soil tests? If you answer yes to any of these, Grid sampling is a good starting point. If you answer no, then Zones sampling is a good place to start. In the GK system you are going to need a “Yield Goal” map to drive the Grids. The Yield Goal map is usually similar to the Zone map. Below is a quick decision tree to decide which way to go. 

VRT

  No matter what happens in the GK Technology system, we suggest building a “Yield Goal” map; this may be the same patterns as your “Management Zones”. So, “Where to start?”, defining or creating “Management Zones” sounds like a very logical starting point. To build Management Zones, we suggest starting with the simple and easy to use data. Below is a list in order of what I use the most to the least. This is NOT saying any one is better or worse, this is the order of what we use the most to the least. NOTE- grower input is essential in this process.

  1 or 2: USDA – NAIP Imagery – 1 or 2 meter aerial imagery flown as part of the NIAP (National Ag Imagery Program), used for confirming FSA Acreage. Free beautiful aerial imagery, with one drawback, not enough of it, generally flown once every two to three years and no telling what time of the summer it will be. (2003 to present)

  1 or 2: USGS – Landsat 5 – 7 – 8 Satellite imagery. 30 meter satellite imagery collected every 16 days. Free with one blessing and curse. Landsat is on a sun-synchronizes orbit and on that 16th day, clouds or no clouds. (1984 to present).

  3: Topography – Elevation data can come from many sources, tractor RTK / GPS, LiDAR, NED, SRTM and IFSAR to name a few. Please note this layer can be used in many different ways. For the most part, this data is Free. It can be a difficult layer to utilize, awesome with our 3D viewer.

  4: Yield – This data is some of the best and some of the worst. People who take the time to understand the equipment and read the manual, usually collect good data. Multiple units in the field make huge challenges. (Quality dependent on you.)

  5: Aerial – Imagery flown by licensed pilots at higher elevations (1,000 to 6,000 feet) using cameras and specialized sensors. This is the most under recognized piece of data on the market. Wish more people used this source. Great images and generally fast turnaround times.

  6: EM 38 or Veris – Soil conductivity data that does a great job of differentiating wet holes from gravel from salinity. Excellent tool but please note, very water dependent.

  7: UAV – Imagery flown by Unmanned Arial Vehicles has been all over the news for the past years. Can be great data, but plagued with many problems (clouds / stitching issues / light angles). Unless you are doing stand counts, we do not need anything higher than 1 meter resolution.

  8: Miscellaneous – This data can be soils data, protein data, hand drawn data, field driven data or anything extra that can be used to define an area or zone of a field.

  You will notice that 1 and 2 are interchangeable. Landsat and NAIP are basically interchangeable. I use one more than the other depending on geography. Now that we have way too many decisions to make, I will step back and give you some ideas of what you really need. Inputs 1-3 will give us some excellent management zones. With the information from USDA & USGS, we can tell a lot about the past cropping history and find images that best represent the production of the field. In building zones creating yield goals, we make it a point not to get hung-up on that “1” year that it was just amazing. That data is great to know, but we believe firmly in building long term averages. So, we use equations to merge together multiple years of images, topography and yield. This gives us zones that truly show how the field produces on “average”. Final use for the topography is the driver for a 3D model, a huge decision maker.

  All too often, I see farmers want the 1 image of the 1 time when they knocked it out of the park (ex. 2016 Corn). All too often you will be putting excessive input into areas of the crop with average, or less than average, returns 9 out of 10 times. Not to mention that most fields have a “Little Flex” in them. On that year that you hit it out of the park, weather went your way, fair moisture, fair heat units, good pest control, good stands and finally a good harvest. All important factors, and if any one of them does not show up, the yields will be reduced. Having 30 years of input and grower knowledge goes a long way towards getting a strong starting point for any precision program. Adding in more layers later is not a problem, it is actually encouraged. If you have yield data, YES include it, but be very critical of it. Straight lines are usually man made or equipment / sensor errors.

  Below is a guide from the USGS to give you some guidance.
https://pubs.usgs.gov/of/2017/1034/ofr20171034.pdf

  To wrap up, the use of multiple inputs over multiple years will create solid and consistent “Management Zones”. These Management Zones can usually be used to set Yield Goals for Grid system. Recognize the benefit of multiple inputs vs single input system. Finally, know that a good system is a growing system that allows more inputs to be added to the system as the improved data becomes available and your knowledge grows.