In the past two decades, precision agriculture has seen a massive influx of technology. And the progress is still rolling. Precision is an agricultural technology that, unlike genetics or chemistry, doesn’t take a dozen years to hit the next promise.
Most advances in precision ag equipment have focused on answering one of two questions: How do I increase efficiency by reducing waste, or how do I add to the convenience of the operator? In essence, products such as automatic section control on sprayers, spreaders and planters along with automatic steering have not necessarily aided our ability to increase production outright. But, by giving us options to select the right product, at the right rate, in the right place, at the right time, they have made field operations more efficient.
But what if you want to take the next step? Variable-rate fertilizer applicators have given us the ability to implement a right-product, right-place, right-rate fertility strategy and increase productivity, but that practice is not all that new. What if we had a piece of equipment that allowed us to select the right corn hybrid or soybean variety for different parts of each field?
I recently worked on MFA’s first dual-hybrid planter. It is rolling across fields this season changing from one seed variety to another based on data cataloged for zones throughout the field.
Multi-variety planting is not an enormous challenge when it comes to equipment. Our team mounted two meters with seed-delivery hoses coming from both bulk tanks, which deliver different hybrids. The meters are electrically driven, so there is no problem with chains.
The real challenge begins with identifying where to change hybrids and why. How do you identify hybrids to best fit different areas of the field? Finally, how do you determine a plant population that is appropriate for each zone and for the hybrid that fits that zone?
To anyone in MFA’s Nutri-Track program, this concept should sound familiar; tailoring the product and amount to the need of each acre, but with seed instead of fertilizer.
Selecting the right fertilizer and rate for each acre becomes simple math for a computer when compared to past yield history and soil-test levels. But, how do you determine the right seed and population for each unique soil type and yield environment?
From the MFA precision agriculture team’s perspective, making recommendations for multi- variety planting was a challenge in selecting the right data to get the best answers.
When I started looking at the fields to be planted this year, I was lost in the data. We had more than 10 years of yield data, Veris data, elevation data, soil-test data and most importantly, firsthand experience in these fields. That may sound like a lot of information but, in my opinion, you can never have too much data.
I worked on my theories and drew different zones within these fields trying to identify what was causing yield changes in each area. But, you can look at the data all day and never get the whole story. After talking to the farmer and MFA Crop-Trak consultant, we were able to identify what drives yield in each area and get a game plan together to address problems or take advantage of each acre.
At a basic level, data can tell us where to draw a line between two field zones that differ, but experience tells us why they are different and what characteristics to look for in the variety you need for that zone. I am not a seed expert, but by interpreting the data we had collected, I was able to help our seed specialist do a better job of selecting hybrids. Our options were expanded because we didn’t need a one-size-fits-all hybrid.
Making incremental increases in yield doesn’t have to be as complicated or expensive as setting up a multi-variety planter. Maybe you just want to change the population to account for soil and fertility variability. Or, maybe you just want to make sure you aren’t limiting yield based on fertility levels. Either way, it starts with collecting the data.
The future of precision agriculture is not just equipment. It’s data. More than that, it’s interpreting data to build the insight you need to make better management decisions.
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