What is in this article?:
- Farmer tracks profits using data by management zone per field
- Dealing with spatial variability
- First payback: drainage
- Put data to work for fertilizer application
- What about variable-rate plant population?
- About Jeremy Hopper
It takes “devotion to do precision ag” at Jeremy Hopper’s level, says Jason Hamlin, North Delta Crop Consulting, Dyersburg, Tenn. If a piece of precision equipment goes on the fritz mid-harvest, for example, or a prescription file is bad, “you have to be willing to stop and fix it. It’s one thing talking about this and another thing implementing it. A lot of people try it and quit.”
What’s next for this “numbers” guy? “The easy stuff, we’ve done now,” Hopper says. “Where we go from here is a question. The next steps — variable-rate population, hybrid changes within fields — these will take a lot more time and energy.”
Jeremy Hopper, Tiptonville, Tenn., uses precision data to make many agronomic and management decisions.
Put data to work for fertilizer application
Hopper varies fertilizer applications (VRA) based on composite soil sampling within management zones. “At first we sampled by 2.5-acre grids,” but he found it tough to predict fertilizer needs based on those results. He concluded that sampling by productivity zones is more useful on his farm. The industry is moving that way, too, says Wilson, the Illinois agronomist, especially with wider use of soil mapping tools like Veris EC.
Hopper uses his yield data to estimate crop removal rates of phosphorus and potassium, and applies maintenance levels by zone most years. When fertilizer prices are favorable, he’s prepared to build soil levels in lower-testing zones. Variable-rate lime applications offer the clearest payback for VRA on his farm, Hopper says. He feels site-specific pH management is “less subjective than for N, P and K.”
Hopper’s data sets also let him compare seed performance in different environments on his farm. “We hardly ever commit to a new seed the first year. We try it in side-by-side trials.”
In 2013, he and Bob Williams, a University of Tennessee Extension expert, set up trials in a challenging field that includes some of Hopper’s poorest ground and some of his top ground. The high degree of variation is reflected in the field’s nearly flat distribution of yield data points between 70 and 200 bushels per acre. What’s the best strategy for a field like this? “Should we plant a high-end variety on the whole field, a defensive variety on the whole field? What would be more profitable?”
To help answer that question, Hopper compared a racehorse hybrid with high yield potential in productive environments, and a workhorse, or defensive, hybrid in two uniform areas of about 3 acres each — a high-productivity block and a low-productivity block. The test blocks were planted in randomly placed strips 36 and 18 rows wide. These same trials are being replicated on several other farms in west Tennessee “so we can see how they perform in different yield, weather and soil environments,” Hopper says.
What did Hoppers’ numbers tell him about hybrid placement in this variable field?
Averaged over both test blocks, the racehorse hybrid out-yielded the workhorse hybrid by 8 bushels per acre in 2013, a wet year. But that’s just one field and one year, Hopper notes. He’ll wait to see how these two hybrids performed on other farms in the region before he chooses seeds for next year. But “I might stay with the higher yield-potential variety.”