Maintaining High Standards for Precision Agriculture

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field dataJeff Bezos’s most recent annual report for Amazon[1] has brought high standards to the forefront of public discussion. In agriculture, high standards have driven us for generations, and every farmer I know gives their all every day to build an operation to be proud of. High standards, Bezos notes, are domain-specific. While we know uniform emergence when we see it, and we know how to count yield estimates on our 300-bushel corn, precision ag is an area in which many farms don’t yet have world class data.

Understanding [that high standards are domain specific] is important because it keeps you humble. You can consider yourself a person of high standards in general and still have debilitating blind spots. There can be whole arenas of endeavor where you may not even know that your standards are low or non-existent, and certainly not world class. It’s critical to be open to that likelihood.

 

What does good precision ag data look like?

Frequent

Good precision ag data is captured frequently. Whether you have wireless data transfer or you bring your USB sticks in on a weekly basis, take the time to bring data to your home base and upload it to your management software. Keep copies of the raw files in dated folders.

 

Reconciled

Good precision ag data is reconciled promptly. Print a report of the data brought in, share it with your operators, and ask ,“Which field did we run out of seed on? Is the variety split shown here?” Ensure the data you’re capturing matches reality, and when it doesn’t, make those edits. Data reconciliation is easiest while memories are fresh.

 

Calibrated

Calibrate your combines, and after you’ve finished a field, use the scale weights for the field to post-calibrate your data. Sensors are imperfect, load cells drift, and there’s no way to be certain you’re calculating your ROI right unless you know the actual number of bushels you brought in from the field. When you have multiple combines in a field, your yield data won’t be useful without post-calibration.

 

Standardized

Good precision ag data is standardized. For example,

  • Soil data is in the same place as yield data.
  • All yield data is in the same place, even if you’ve switched from green to red to yellow.
  • You know where your fertilizer buggy went.
  • You know where you reworked your tile lines.
  • You can run a yield comparison by planted variety before you place your next seed order.

 

Informative

Good precision ag data includes feedback loops. You put all this effort into high data standards so you can ask questions about how to improve your operation, turn to your data, and have that question answered. Analyzing your strip trials as soon as they’re harvested, for example, lets you make better purchasing decisions for the coming year; reviewing your soil fertility levels over time enables you to conduct land rent analyses; and you can hone your yield expectations for your soils to evaluate ROI by zones.

Maintaining high standards for your precision ag data empowers you to take your farming operation to a higher level. Frequent capture, prompt reconciliation, calibration, and standardization enable well informed decision-making, and better decision-making lifts up your entire farm. FamilyFarms Group can help you optimize your farm operations, enhancing efficiency and reducing waste to help your family farm grow into the future.

In a side-by-side comparison of some of the industry’s top production management software, including FarmersEdge, SMS, MapShots, and Climate, you can see that FieldIQ™ offers the most comprehensive suite of tools, features, and support. 

 

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[1] http://phx.corporate-ir.net/External.File?item=UGFyZW50SUQ9NjkyMDIxfENoaWxkSUQ9NDAyOTkyfFR5cGU9MQ==&t=1

Written By

Allison Jonjak

Allison Jonjak

Precision Ag Analyst | ajonjak@familyfarmsgroup.com

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