Using yield data

by Deborah Jeanne Sergeant

Making every acre count helps farmers increase their profits. The headlands on a farm often represent an area overlooked for their profits. Quirine Ketterings and Sunoj Shajahan presented “Turning Yield Data Into Action: How Much Yield Do We Give Up on Headlands?” at the recent Corn Congress, presented online this year by Cornell University.

Ketterings said it’s important for farmers to know their yield for five reasons: yielding inventory tracking, troubleshooting whole farm nutrient balances, calculating return on investment, evaluating trends over a year and matching crops with soils.

“Knowing yields helps you troubleshoot and identify issues you could be having,” Ketterings said. Knowing which nutrients are low, farmers can figure out why and understand how their management strategy effects yield and quality. This can include a tally of loads, yield checks, truck scales, farm scales and yield monitors.

“Yield monitors have some advantages in the information we get,” Ketterings said. But they are not the only way to measure. “We can do a lot at the farm level to address items on the list.”

Yield monitor data offer farm, field and within-field information. Calibration is important for accuarate information. “It’s important for data cleaning after harvest,” Ketterings said. Data cleaning training is available at nmsp.cals.cornell.edu/guidelines/factsheets.html. For further information, email gmk2@cornell.edu.

“We still have funding in place to do training on post-harvest data cleaning skills,” Ketterings said.

Cornell’s nitrogen guidelines offered two options: corn yield potential for the soil type as per the Cornell soil database and recommendations based on corn nitrogen equation, and actual corn yield measured with three years of data under current nitrogen guidelines.

“If a farm has its own yield data, it’s better than book data,” Ketterings said. If a farm has three to four years of data, the farmer can drop the lowest yielding year.

The yield potential project currently has 200,000 acres of data that’s been cleaned. Roughly half are grain yields; the other half are silage yields.

Eighty percent of the acres in the database are from 2015 through 2019 and include 69 soil types for grain and 63 soil types for silage with at least 40 yield data points.

“When we include soils with mean/median between 0.90 and 1.10, we have 90 grain and 98 silage soil types represented,” Ketterings said. “All reliable data obtained through 2019 are included. A couple of farms lost their data due to the usual issues of malfunctioning sensor, incorrect data storage or other things.”

Shajahan presented about data that included and did not include headlands.

“Individual reports showed yield differences between headland yield and yield in the remainder of the field,” he said. He attribued the losses in the headland areas to soil compaction, treeline competition and pest damage.

“Soil compaction reduces yield,” he said. “Treeline competition for nutrients and water reduces the yield.”

The headlands’ proximity to the treeline increases pest pressure. “Headland yields were lower – 14% for grain and 16% for silage – than yields in the non-headland areas,” Shajahan said. This can quickly add up to substantial losses for some producers.

“What we recommend is if the field yield hit is large, repair the headland with management,” Shajahan said. This could include vertical tillage or subsoiling to increase overall productivity and return on investment.

Shajahan also suggested reducing crop inputs without further loss of yields in headlands, rotating the main crop on headlands and choosing perennial hay and conservation uses for these areas.

“Across a large acreage, potential yield grain averaged 4%, but could range from very small to less than 25%,” he said. “Use farm yield data to guide management changes.”

2021-02-16T10:37:10-05:00February 16, 2021|Mid Atlantic|0 Comments

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