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Be a data sharkBe a data shark

Use a data plan to help make decisions on the farm.

Dan Frieberg 1

February 7, 2018

3 Min Read

I’m not much of a billiards player but if you have ever watched a professional, you know that they run the table by constantly setting up the next shot and even two or three shots ahead. They have a master plan that they tweak shot by shot as they play.

That is one of the things I love most about working with so many of our industry’s best growers and their agronomic advisors, watching them develop a detailed plan and then executing that plan. Their use their data can help develop a plan to farm like a pool shark – constantly setting up their next shots. Let me share some examples on how these “planning sharks” use their data to set up future shots.

The seed decision for these sharks is data intensive, examining hybrid and variety selection and placement. In addition to using data to evaluate hybrids by yield and moisture, they consider likely operational field order. For the lighter, better drained fields that dry early for first planting, they query anonymous aggregated group data to evaluate yield by planting date – drilling down on similar soils, seed treatments and crop rotations. In similar fashion, they plan for those fields most likely to be harvested last, which can be based on distance from the home base, soils or rental agreement. The data challenge here is to find hybrids that will not only stand late in the harvest season but still yield competitively. Sometimes the highest yielding racehorse numbers don’t hold up when later harvest is considered.

Every detail by field is considered, even the probable destination for the crop – like which fields are closest to the ethanol plant that has a more favorable moisture scale for wetter corn? For on-farm storage, how many and which fields will fill up the bins first? And then anticipating the need to haul to the commercial elevator, which numbers offer the combination of high yields and lower harvest moisture?

Weed control also has a data-driven plan; using historic data to rotate traits and chemistry.

This plan-ahead mentality also extends to tillage and nutrients. Manure availability is planned years in advance, sometimes contracting with neighbors 2-3 years out. Crop rotation, crop residue, and field erodibility are all factored in. Commercial fertilizer applications are planned the year before and the year after each field gets a manure application. They use their soil test data to drive nutrient priorities and plan nutrient investments – using agronomic data to drive their plan versus what’s convenient in the moment. They might prepare their variable rate nutrient prescriptions nine months before the actual applications, allowing them to begin partnering with suppliers for the best terms.

Most impressive is how these data sharks plan for what you might not think is possible – the weather!   Their strategies for managing weather-driven variability involve planned checkpoints. For example, some fields receive planned split application of nitrogen. In-season data is used to tweak their planned variable rate application, which could include new sample data. Their plans aren’t reactive, like responding to yellow corn, where they know they’ve already lost yield at that point.  Their approach is a proactive, complex “if/then” decision model that includes a placeholder for incorporating in-season data.

Sometimes farming feels like being on a roller coaster.  One of the benefits of using your data to develop your farming plan is that you feel more in control and less likely to make decisions based on emotions.

About the Author(s)

Dan Frieberg 1

Premier Crop Systems

Dan Frieberg is CEO of Premier Crop Systems, LLC a crop data-analysis company based in West Des Moines, Iowa. For more information on Premier Crop Systems or data-driven decisions, visit www.premiercrop.com. Premier Crop Systems will push you to dig more deeply into your field data and find just how much power lies in the information layers that hide within your acres.

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