Wisconsin On-Farm Testing
"Where science meets the field"
Originally written July 31, 2008. Last updated
October 07, 2015
Data collection forms
Farmers today have an increasing number of tools for managing crops. New developments
in precision farming technologies, biotechnology, and advancements in pesticides,
equipment, and other ag inputs are converging and arriving at the farm-gate at an
unprecedented rate. The great number of new technologies can often be overwhelming
to many farmers. Sifting through the milieu of technologies to find the tools
that really work on-farm is a challenge for farmers and the consultants and agronomists
that serve and support production agriculture.
Often farmers use these technologies with little or no evaluation prior to use.
Industry heavily invests in research and development of these technologies. Thus,
product "ramp-up" is fast and products are often marketed and distributed quickly
in an attempt to recover investments in the early phases of technology adoption.
Often farmers, usually at great expense, must learn and re-learn management of these
technologies as new and improved versions are released.
e-learn management of these
technologies as new and improved versions are released.
On-farm testing improves the reliability of crop management decisions. The objective
of an on-farm trial is to determine how different management options perform compared
to each other under your environment and cropping system. In general, there are
two major categories of performance trials. The first is replicated trials that
try to account for field variability with repeated comparisons. Examples include
trials conducted by universities and by public and private plant breeders. The other
general type is non-replicated demonstrations such as yield contests, on-farm yield
claims, demonstration trials and farmer observation and experience.
Types of error that can occur with management decisions
||Truth about population
|Decision based on sample
||Type I Error
|Fail to Reject Ho
||Type II Error
Your management decision
Condition of your guess (hypothesis)
Decide to implement practice
Decide not to implement practice
Difference is real and increases profitability
Difference is not real and decreases profitability
The key to an on-farm test is that it must make repeated and unbiased side-by-side
comparisons of the practices in question. These repeated comparisons are called
replications. With replication, we can use simple statistical formulas to decide
if one practice or "treatment" differs enough from the other to be sure the difference
was not due to chance.
A well conducted performance test on your farm or in cooperation with neighbors
using similar management practices is an important part of evaluating new agronomic
practices for efficient and profitable crop production.
Treat the majority of the field with what you think is the correct management decision.
Leave a reference strip (pass or round) of the alternative management decision somewhere
in the field and compare the reference strip to the rest of the field. Do this on
3 or 4 fields and average the responses.
Example of a field reference strip evaluating plant population.
Key ingredients of an on-farm testing program include:
- Selection of treatments to be tested. Limit the number of treatments to no
more than four and include one well-known treatment as a check. The check should
"set the bar" (control) for the other treatments and usually is the practice
already in place on the farm.
- Replication. Choose a uniform area in the field. Each practice should be
repeated (replicated) three times in the trial. Arrange the plots so that each treatment
is used once in each replication. Treatments should be arranged in a different order
in each replication (randomized). See Figure 1.
Fig. 1. Three treatments and one check treatment replicated 3 times in complete blocks.
Low - Soil Fertility Gradient (or yield potential, organic matter, pH, etc.)
Plot size. Optimum plot size for on-farm tests may vary greatly with the
size of uniform land area, number of treatments and size of equipment. About one-tenth
of an acre is appropriate for many tests. Plots should be similar in size. Avoid
using field edges in plots. Field edges should be left as borders.
Management. Each plot should be managed exactly the same and as close as
possible to the conditions which normally occur on your farm.
Measurement. Keep accurate and up-to-date records, walk the area every few
weeks during the season. Note obvious strengths and weaknesses of the treatments
plus any general problems with the test. Depending on the test, take stand counts
of the crop, ratings of weed control, disease or insects. Weigh the yield of each
plot, take a moisture sample, and adjust yields to the same moisture content.
Analysis. Use averages over replicates to compare treatments. A well-conducted
test will have small differences among plots of the same treatment and some large
difference between treatment averages. Consider all-important traits and not just
Time. Data from one field in one year may be misleading. About two to three
years of your own tests in conjunction with other reliable information should be
adequate to select treatments to be practiced on larger acreage. One year's data
may be adequate to discard poor treatments from the test. Replace discarded treatments
with new treatments in any tests conducted next year.
Grower Return ($/A) = (Weighted Price per Bushel x Bushels per Acre)
- Treatment costs per acre
Handling cost = $0.017 per bushel
Hauling cost = $0.04 per bushel
On-farm drying cost = $0.015 per point per bushel
Weighted Price per Bushel = $?.?? per bushel = 50% November Average Cash price +
25% March CBOT Futures price ($0.15 basis) + 25% July CBOT Futures price ($0.10
basis). November Average Cash price derived from Wisconsin Ag Statistics; CBOT Futures
prices derived from closing price on first business day in December.
Variations in yield and other measurements because of variations in soil and other
growing conditions lower the precision of the results. Statistical analysis makes
it possible to determine, with known probabilities of error, whether a difference
is real or whether it might have occurred by chance.
The data tables contain a number labeled "LSD" which stands for least significant
difference. LSDs at the 10% level of probability are shown. Where the difference
between two selected treatments within a column is equal to or greater than the
LSD value at the bottom of the column, you can be sure that in nine out of ten chances
that there is a real difference between the two treatment averages. If the difference
is less than the LSD value, the difference may still be real, but the experiment
has produced no evidence of real differences.
Statistics are only a tool to help prevent us from deceiving others and ourselves.
Growing conditions in any particular year can have large effects on certain practices.
Two years of replicated data are a minimum for supporting most practices. On-farm
testing is not a quick cure for anything, but it should greatly accelerate innovation
and adoption of new practices by providing reliable, quantitative answers that apply
directly to a producers situation. Treatments frequently differ in performance and
these differences may vary with management practices, weather patterns, soil conditions,
and other environmental and management practices. Replicated trials which take into
account field variability are the most reliable and need to be part of informed
selection of new practices for profitable crop production.
How To Use Research Results To Select Top-Performing Treatments
Below are suggested steps to follow for selecting top-performing treatments for
next year using these trial results:
Use multi-environment average data. Consider single location results with
Begin with trials in the zone(s) nearest you.
Compare treatments with similar maturities within a trial. You will need to divide
most trials into at least two and sometimes three groups with similar average harvest
moisture - within about 2% range in moisture.
Make a list of treatments with the highest yield within each trial.
Evaluate consistency of performance of the hybrids on your list over years
and other zones.
Scan results from other years. Be wary of any treatments on your list that had poor
performance. Choose two or three of the remaining treatments that have relatively
high performance over many years.
Check to see if the treatments you have chosen were entered in other zones.
Repeat this procedure with about three maturity groups to select top-performing
treatments with a range in maturity, to spread weather risks and harvest time.
Observe relative performance of the treatments you have chosen based on these trial
results in several reliable, unbiased trials and be wary of any with inconsistent
You might consider including the treatments you have chosen in your own test plot,
primarily to evaluate the way hybrids stand after maturity, dry-down rate, grain
quality, or ease of combine-shelling or picking.
Remember that you don't know what weather conditions (rainfall, temperature) will
be like next year. Therefore, the most reliable way to choose treatments with greatest
chance to perform best in on your farm is to consider performance over a wide range
of locations and climatic conditions.
You are taking a tremendous gamble if you make treatment selection decisions based
on yield comparisons in only one or two local test plots.
Resources for On-Farm Testing
This Web site allows you to locate individual fields and, by virtue of its satellite
view option, develop an initial impression of the suitability of the field for an
on-farm research trial (uniformity or variability for field features). If you create
your own Google account, you can create and store custom map sets for your future
reference that include field place markers, field boundaries, or line field features
(e.g., gullies). You can also share your custom maps with other users. With Google Maps Labs features enabled (Distance
Measurement Tool, LatLng
Marker), you can also measure
linear distances (how wide is the field?) andvirtually
"drop" a latitude/longitude marker over the field
for future georeference.
USDA Web Soil Survey
This Web site allows you to locate individual fields and identify the mapped soil
units for that field. From this site, you can create and print PDF-formatted versions
of the soils map for a given field. You can also download the spatial dataset for
the soils of the field for future use in GIS software programs (e.g., Farmworks,
MapWindow, ArcView, etc).
This Web site is actually an on-line statistical analysis tool developed group of the
Pacific Northwest Conservation Tillage Systems Information Source; a consortium
between Oregon State Univ, Washington State Univ, and the Univ of Idaho. This on-line
program allows you to perform simple statistical analysis procedures on simply designed
research datasets. If you are familiar with fundamental statistical analysis procedures,
this site will be relatively easy to use. If not, you may want to consult with someone
who is familiar with these things.
Purdue Collaborative On-Farm Research -
Purdue University identified on-farm research programs, presentations, references and useful Web sites to help researchers plan and work with on-farm research trials.
Rodale Institute On-farm Research -
is conducting independent agricultural research in composting, soil health, weed management, pest management, livestock issues, organic agriculture and certification, agro-forestry, and wastewater treatment. The Farming Systems Trial started in 1981 to study the transition from chemical to organic agriculture.
How to Conduct Research on Your Farm or Ranch -
USDA. Sustainable Agriculture Research and Education.
Learn how to conduct research at the farm level using these tips for crop and livestock producers, resources lists and real-life examples.
National Programs: Integrated Farming Systems
USDA. Agricultural Research Service.
"This Agricultural Research Service (ARS) national program, Integrated Agricultural Systems (IAS), is designed to facilitate the synthesis, evaluation, and transfer of information to all types of agricultural operations using a 'systems approach.'"
On-Farm Research Guide (PDF | 93 kb) -
Organic Farming Research Foundation (OFRF).
Presents an extensive overview of on-farm research.
2012 Organic Land Grant University Assessment (PDF | 1.42 MB) -
Organic Farming Research Foundation.
This document "tracks and reports organic programs and activity in the U.S. land grant university system. The specific details on organic research, education, and extension of each of the 72 land grant institutions investigated for this report are a rich source of information."
Century Experiment -
University of California - Davis. College of Agricultural and Environmental Sciences.
The University of California's Century Experiment (formerly known as LTRAS-Long Term Research on Agricultural Sustainability) is a 100-year study in which researchers "measure the long-term impacts of crop rotation, farming systems (conventional, organic and mixed) and inputs of water, nitrogen, carbon and other elements on agricultural sustainability."
Long Term Field Experiments in Organic Farming
International Society of Organic Agriculture Research.
Presents the results of twelve experiments about the "characteristics of Organic Agriculture regarding key parameters of soil fertility, crop yield and quality."
Whole Farm Case Studies: A How-To Guide
Oregon State University. Cooperative Extension Service.
Defines whole farm case studies, details how to design and conduct studies, and presents the pros and cons of this research approach.
Guidelines for On-farm Research
Ohio State University. Cooperative Extension Service.
Step-by-step guidelines are presented to help farmers conduct on-farm research that produces accurate results and answers their questions about agricultural production and management.
On-Farm Research Guidebook (PDF | 473 KB) -
University of Illinois. College of Agricultural, Consumer and Environmental Sciences. Department of Agricultural Economics.
Explains fundamental research principles. Provides guidelines to assist farmers conduct participatory on-farm research when transitioning to sustainable agricultural practices.
National Agricultural Library Thesaurus
United States Department of Agriculture.
Defines and searches the NAL Catalog (AGRICOLA) or Google Scholar for terms or resources about on-farm research.
Missouri Alternatives Center: Link List
University of Missouri. Cooperative Extension Service.
Links to hundreds of full-text Extension publications that address all kinds agricultural alternatives. Topics include on-farm research.
Mullen, Robert, Ed Lentz, Greg Labarge, and Keith Diedrick. 2008. Statistics and
Agricultural Research. Ohio State Univ. Fact Sheet. http://ohioline.osu.edu/anr-fact/pdf/Statistics_ag_research.pdfch.pdf"
Nielsen, RL (Bob). 2009. A Practical Guide to On-Farm Research. Purdue Univ Extension.
Sooby, Jane. 2001. On-Farm Research Guide. Organic Farming Research Foundation.
Taylor, Randy, Scott Staggenborg, Kevin Dhuyvetter, Terry Kastens, John Schmidt,
and Mike Schrock. Using Yield Monitors for On-Farm Research. Kansas State Univ.
Anderson, D. On-Farm Research Guidebook. University of Illinois. http://web.aces.uiuc.edu/vista/pdf_pubs/GUIDEBK.PDF
Other On-Farm Research Programs
Iowa Soybean Association On-Farm Network.
2010. A program of the Iowa Soybean Association.
Kansas Agricultural Research Association.
2010. A producer, industry, and university association.
Research. 2010. Univ of Nebraska Extension.
Ohio On-Farm Research. 2010.
Ohio State University Extension.
Pacific Northwest Conservation Tillage
Systems Information Source. 2011. A consortium between Oregon State Univ,
Washington State Univ, and the Univ of Idaho.
Penn State On-Farm Research Program. 2010.
Penn State University Extension.
Practical Farmers of Iowa. 2010.