Aggregating Yield Data and Other Production Factors for Better Decisions

There are many factors that can affect crop yields for a particular harvest season. This is why relying on a single part of the data collected will not lead to better decision making. The best approach is to aggregate data and other production factors before deciding on the next step.

 

Yield monitors, for example, can vary depending on the changes in grain yield. But without looking at the yield history, the solutions developed will be ineffective.

 

For example, yield patterns are influenced by row direction, water management, and tillage. All of these factors should be considered when making a decision.

 

But the data gathered should not be limited to one season alone.

 

A good piece of yield history data looks something like this: 

-Use of one center-pivot irrigation system from 1997 to 2000

-Furrow irrigation was installed at the southern end during the same period

-A ridge till system with 0.91 m spacing per row was employed for field management until 2000

-A half-pivot was installed in 2001 and 0.76 m row spacing was employed between 2001 and 2002

 

Based on the data listed, the next round of decisions can be made.

 

 

Questions that Drive Decisions

 

 

Farmers are aware that they have huge amounts of data at their disposal. But without the right technology, they will not be able to make timely decisions. However, they can start by asking questions that call for better decision-making.

 

During planting season, for example, some of the questions that need answering are related to: 

-Pest control in the field

-Areas in the field that need irrigating

-Harvest time and schedule

-Weather conditions during the season

 

During the planning phase, a farmer will have to think about: 

-Crops that will be cultivated during the season

-Seeds to choose that offer the best yield

-Soil conditions in the field

 

From here, a farmer needs to determine what factors are within and outside of their control. Pest and weather, for example, are two things they can’t control. But they can do something about crop protection and seed genetics.

 

No one knows data aggregation better than Gary Wagner of Crookston, Minnesota. He’s a farm-data veteran that uses 4 key data layers to drive profit and make better decisions. He has lectured internationally about the better use of aggregated data in meaningful ways.

 

His 4,600-acre farm is planted with corn and rotated with sugar beets, sunflowers, spring wheat, and soybeans. He uses zones, remote sensing imagery, and yield maps to gather data.

 

Through aggregated data, he discovered that some hillsides yielded 24 bushels per acre while other soybean fields average 44 bushels, 55 bushels, or better per acre. He then targeted fertilizer based on the aggregated data. The result is an average fertilizer cost at a field average increase of 6 bushels.

 

 

Importance of data tools in agronomy

 

-Data measurements help farmers manage their operations better and make decisions that are tailor-fitted to the needs of their farm, productivity, and profitability.

-Identify efficiencies and deficiencies for lower input cost and higher profits and production.

-Eliminate risk and volatility while strengthening relationships and opportunities in the supply chain. 

 

 

Precision Agronomics is located at 9438 West SR 28 in West Lebanon, IN and is proud to serve: Marshfield, Johnsonville, Foster, Stone Bluff, Bismarck, and the surrounding areas. Contact us today for more information!​

yield history - agronomist

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