Record keeping has always been important in farming. By keeping track of what was planted, sprayed, fertilized and harvested, growers could decide what to repeat or avoid the following year. Until recently these records were usually on paper, but now software platforms are available that can keep track of more data types more easily. What’s more, these systems can share the data with others and and can analyze the information based on multiple variables, helping the farmer make well-informed decisions.
The data collected throughout the season, along with historical data from previous years, can be used in a wide variety of ways. Scott Cogdill, Director of Agronomy Services for Proagrica, shares his recommendations for how to use data in planning for next season.
Step 1: Crop Selection
“The first step is to look at your crop rotation history,” Cogdill says. “Determine what crops you’re going to plant first. What traits did you plant the previous year and how does that affect what you should plant next year? Are there any residual carryover issues?”
As an example, Cogdill says, if there was downed corn in a field the previous season, you know there will be volunteer corn coming up the next season. If you know the trait package in that corn, you an choose the soybean variety you plant so you can properly control the volunteer corn. If the corn had a glyphosate trait in it, you might want to plant soybeans with the gluphosinate trait.
Step 2: Nutritional Needs
The second step is to look at past data around soil sampling and fertilizer application, Cogdill says. Use this to determine what your fertilizer needs will be next season. Make sure all necessary soil testing is done for this season, so this information is included in the decision-making process.
“By combining the soil type data, fertility data and the plant trait packages used in the past, you can make an informed decision on what variety to use on that field and where,” Cogdill says. “Using a geospatial data platform can really help automate this decision process by providing an understanding of the elevation and topography of the field as well, and it can create the input to go into the planter for variable-rate planting.”
Step 3: Pest and Weed Control
The third step is to look at your scouting data, Cogdill says. Look at weed, disease and insect pressures to have an understanding of what type of chemistries will be needed that will fall in line with the traits you have chosen to plant. Again, determine if there is any carryover or residual from the previous year that could change the direction of the chemistry plan.
Step 4: Yield Prediction
Another way data can be used that isn’t talked about that much, is in determining production levels for contracting, Cogdill says.
“Once you have the acreage totals for each crop, you can use that plus past yield data to come up with guidelines for contracting,” he says. “For instance, if a field has historically produced corn at 200 bu/acre, you could probably come to market at 130 bu/acre. This type of data can really help farmers determine what they can comfortably forward contract.”
Having all this data in a digital format that is backed up, repeatable and shareable with those who need access to it is really invaluable, Cogdill says. It can’t be lost like a single notebook, and eliminates the redundancy of paper record keeping.
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