You may have tried a new product or applied extra fertilizer or water this year, but do you know if the investment was profitable for your operation? With lower commodity prices, it is more important than ever to evaluate if your production inputs and practices are really paying off. Harvest provides a great opportunity to think through your production-related questions and determine what practices and inputs you should be evaluating next year.
Nebraska's On-Farm Research Network can help you design and evaluate an experiment that will provide reliable information specific to your operation.
Precision Ag Makes On-Farm Research Easy
Giltner farmer Brandon Hunnicutt, part of the On-farm Research Network, conducts trials that provide reliable information to inform his farm management decisions.
Precision agriculture technologies have greatly enhanced the ease and accuracy with which we can evaluate the profitability of many practices. With precision agriculture technologies, inputs such as water, fertilizer, and seed can not only be distributed at different rates across a field, but also tracked and geo-referenced. Field trials can be set up using prescription mapping software, minimizing the need for flagging treatments. Using yield monitors, yield data for individual field treatments can be quickly evaluated, and the hassle of using a weigh wagon to collect grain weights for each treatment is eliminated.
The time and effort required to design, implement, and analyze a sound on-farm research comparison is well worth the confidence you will gain about the profitability of various practices. Brandon Hunnicutt, a Nebraska On-Farm Research Participant from Giltner encourages producers to try a comparison on their farm.
"We have so many tools — RTK, auto steer, monitors, and ease of recording data — that make it really simple to do an on-farm research study," Hunnicutt said. "It doesn't take a lot of time, and in the end you will benefit. You not only gain information for your own farm, but as you collaborate with others you begin to see how things will work overall, and come up with valuable ideas of other things to try implementing on your farm."
Forming Your Question
So how do you get started? The first step is to formulate a good question. A good question focuses on a single practice and clearly identifies what will be measured. Start by identifying a "yes" or "no" question. Past participants have explored a number of topics, including:
Does starter fertilizer increase my corn yields?
Does increasing my planting population by 4,000 seeds/acre increase my profit?
Do growth promoters increase soybean yields?
Is variable rate nitrogen application more profitable than a single application rate?
Do soybeans planted in April have higher yields than those planted in May?
Once a question is identified, treatments are selected that address the question. For example, to answer the question "Do growth promoters increase soybean yields?," we may have two treatments:
Soybeans planted with a growth promoter in furrow
Soybeans planted without a growth promoter application
Once the treatments are selected, it is necessary to plan the research design.
Designing Your Experiment
Crop performance within a field will often differ due to inherent variability. Because of this, a side-by-side comparison often does not give reliable information because we do not know if the yield difference observed is due to the differing management practice or inherent variability. Proper experimental design can help obtain reliable information. Randomization and replication are important components of a well-designed, on-farm research study. Randomization ensures that favoritism is not given toward a treatment. Replication reduces the possibility that results are due to chance rather than the treatment.
These two factors separate demonstration plots from on-farm research experiments, which are designed to draw conclusions with confidence and ultimately lead to wise business decisions. Two experimental layouts are typically used for on-farm research:
the paired comparison design
the randomized complete block design.
Data collected from a well-designed experiment can be statistically analyzed and interpreted to determine whether real differences are present among treatments. For more information on experimental designs and statistical analysis, view the "Grower's Guide to On-Farm Research" at go.unl.edu/2014onfarmzmag.
Getting Started
UNL Extension's On-Farm Research Network has been helping producers evaluate on-farm research for over 25 years. Contact your local extension educator to plan your on-farm research studies for 2015.
