COLLEGE OF AGRICULTURE & HOME ECONOMICS
WASHINGTON STATE UNIVERSITY
ON-FARM TESTING: A GROWER'S GUIDE
Baird Miller, Ed Adams, Paul Peterson, andRuss Karow
This guide provides growers already doing on-farm testing (OFT) with a tool to refine
their testing system. It also provides growers considering on-farm testing for the first time a
basic background in testing theory and procedures. The guide is narrowly focused on one type
of test--replicated strips. This type of test is similar to testing done by university researchers
and is the easiest to statistically analyze and interpret.
ON-FARM TESTING TERMINOLOGY
Before we discuss on-farm testing, you must understand the following terms and concepts
used in field testing.
Check Plots: A check plot or control represents your current practice. It does not receive the
new technology being tested. This might be your conventional tillage practice,
fertilizer applied in the usual manner, the variety you currently grow, or a crop
not receiving a fungicide application. The check plot and the treated plot differ
only in the specific treatment comparison being made. Aside from this, plots
must be managed exactly the same to avoid biasing the results.
In a tillage experiment, the check plot could be your normal plow operation
and the new technology might be a sweep chisel. Aside from the two tillage
treatments, all other production practices must be the same: planting date,
fertilizer rate, variety, weed and disease management.
In some situations, the new technology incorporates several practices. For
example, if a conventional till-plant operation is compared to no-till seeding,
different tillage, fertilization and seeding systems are being compared. A fair
comparison can only be made between the two complete systems, not any given
part of either system.
Replication: Replication, meaning repetition, is used to determine whether the difference
between plots is due to chance variation always present in fields or caused by
the treatments) being evaluated. Through replication, average treatment effect
values can be obtained. Comparisons between average values are always more
accurate than those between single plots. Replicating your check and treatment
plots at least three or more times will give you much greater confidence in
Trials are generally replicated in both space and time. Replication in space means
that several strips of each treatment are placed in a field (replication on-site)
or that single strips of each treatment are placed in several fields across the farm
(replication over sites). Replication in time is repeating the trial over several years.
Climatic conditions, soils, and other factors can change significantly from
location to location and year to year. It is critical that final conclusions about
a new practice be made only after being evaluated over several years and/or at
Randomization assures that any one treatment is not biased or favored in any
way. To randomize a trial, randomly mix the order and placement of replicated
check plots and treatments (Fig. 1). You may draw treatment numbers out of a
hat or flip a coin as you assign treatments to plots. If treatments are assigned to
plots in a nonrandom fashion, you may unknowingly introduce bias.
Soil Condition A
C T C C TT
C = Check Plot
T = Treated Plot
Figure 1. An example of a completely random plot design, with a check plot (C), a treated plot (T), and 3 replications.
Notice the entire trial area is kept within a uniform soil condition. Other plot arrangements are possible.
The following example shows how these basic ideas are used in an on-farm testing situation:
Sam is interested in comparing two varieties, his old favorite "Standby" and a new
variety "Newlife." Standby is planted in two fields and Newlife in two adjacent fields.
On average, Newlife yields 64 bushels/acre while Standby yields 54. Is Newlife better
than Standby? There is replication -- two fields of each variety. Varieties could have been
assigned to fields by some random process, so there is randomization. However, we do not
have a true check plot. Despite the fact that the fields are side by side, they may be quite
different in soil type, past management, etc. The difference in yield between Newlife and
Standby may merely be a reflection of field differences rather than variety differences. In
order to have a meaningful test, both varieties should have been grown in the same field
with Standby as a check plot. Growing a strip of each variety in each of the four fields
would have been a valid test.
The steps involved in laying out an on-farm test are:
1. Establish your goal and objectives.
2. Determine what treatments you will use and what your check plot or control will be.
3. Select a site.
4. Determine how best to lay out your plots on the selected site.
5. Determine what data you will collect and how you will collect it.
6. Determine how the data will be evaluated.
7. Determine how the data will be shared with others.
GOALS AND OBJECTIVES
Every OFT project must have a goal and specific objectives. Goals are statements of
the overall theme of your experiment. A goal, for example, may be to reduce soil erosion
on your farm.
Objectives are statements of the problem you wish to evaluate in your project. These are
the ideas you want to test or questions you want to answer. Objectives are measurable and relate
to your overall goals. The objectives will determine what is measured and the type of data you
will collect during the project. For example, you might postulate that a no-till seeding system
will leave more surface residue than the seeding system you now use. The trial you establish
would involve a comparison between the two systems. One objective will be to determine if
the residual levels are different between the two seeding systems. Residue levels would be one
type of data collected as part of the trial.
SELECTION OF TREATMENTS
When selecting treatments for a trial, keep them simple and few, no more than 3, including
the check plot. As treatments increase in number, so do the number of plots, and the complexity
of the OFT project.
Choose treatment comparisons that represent significantly different production practices.
Until you have a significant amount of experience in on-farm testing, avoid making treatment
comparisons of minor production practices.
Always include an appropriate check or control plot. For instance, you might wish
to compare deep placement of fertilizer versus broadcast application. Knowing that surface
applied fertilizer is often less efficient than deep placed fertilizer, it may be tempting to increase
the surface applied rate in order to try to equalize treatments; however, this would confound
the study. If placement is the main objective, different fertilizer rates should not be included
as treatments. It is very important that production inputs other than the treatments being
tested remain constant. If management inputs are changed between treatments, the results
may be biased due to the input differences.
The most common problem with on-farm trials is lack of recognition that field variation
can mask or conceal treatment differences. Take special care to plan and organize the field plot
layout to assure that all treatments have an equal opportunity to perform. Choose a field site
with the greatest possible uniformity. Regardless of whether you have a 40-ft by 100-ft plot or
a 100-ft by quarter-mile plot, a uniform field location is critical. When choosing a site consider
previous crop history (fertilizer rates, herbicides, tillage, etc.), drainage, soil texture, soil depth,
topography, pest infestations, and bordering influences such as trees, runoff from neighboring
fields, lack of fencing from animals, and other factors. Avoid placing trials in runoff areas, near
fence lines or in field corners. These areas are often subject to multiple or irregular applications
of fertilizer and herbicides.
The characteristics of a uniform field site depend on the type of test being conducted.
Pay particular attention to things that strongly influence your treatments. For example, when
testing a soil-applied herbicide, soil organic matter content, pH, and texture consistency are
important. In a fertility trial, the soil must have uniform drainage, soil depth, organic matter
content, and soil nutrient levels. For variety or tillage comparisons, the overall soil productivity
level should be constant within the field site. Use your county soil survey maps of the fields
being considered to help you select the site.
Consider site access when selecting a plot location. Is the site easily accessible for
mid-season treatment applications and data collection? If early or differential harvest is
likely (such as with an alternate crop), can you get at the site with harvest equipment without
destroying other crops? Will you hold a tour of your site? If so, is there ready access for visitors
and their vehicles?
After selecting a site, actual plot layout must be considered. Two different layouts or designs,
the completely random design and randomized complete block design, are commonly used.
Completely random designs are used if the test site is known to be very uniform, without
differences in soil characteristics, fertility levels, slope, and previous crop. Layout of the plots
might look like those in Figure 1. In this design, all treatments have an equal chance of being
assigned to any given plot. It is possible to have identical treatments side by side.
Use a randomized complete block design when it is not possible to obtain a uniform test
site. For example, the test site may have different slopes, previous crops, soil depths, etc. In this
case, treatments are grouped into sets called replications. Each replication contains a complete
set of treatments. Each replication is placed in a uniform area. Using such an arrangement allows
all treatments to have equal potential to perform. Through this design, the effects of replications
can be removed or "blocked out" when analyzing the data. Plot layout might look like that in
Soil Condition A
C T C T
C = Check Plot
T = Treatment Plot
Figure 2. An example of a randomized complete block plot design with a check plot (C, treatment plot (T),
and 3 replications. Each block of treatments (replication) is kept within a uniform soil condition.
An alternative approach is to include variation equally across all the treatments in a test.
As an example, field strips can include the field variation by running the strips perpendicular
to the variation. A layout of this type is shown in Figure 3. You must be extremely careful to
include the same variation equally across all treatments to have a valid test. Establishing
treatments within a uniform area is still the best method.
C = Check Plot
T = Treated Plot
Figure 3. An example of a replicated strip trial, using a completely random design. Strips have been laid out
so that each treatment has the same amount of soil variability.
Plot size is determined by field size, uniformity of the field, equipment used and area needed
to carry out a particular treatment. Adjust plot lengths so that each treatment is within a
reasonably uniform area or so that each uniformly covers the field variation as discussed above.
Strip plot width is determined by the width of equipment used to apply treatments (e.g., planter,
sprayer, etc.) and/or harvest plots. The width of the established treatment should be larger than
the harvest width. This way there will be a uniform harvest width and errors in harvesting will
not affect side by side treatments. Typical treatment plots are between 1/10 and 1/2 acre.
DATA COLLECTION AND RECORD KEEPING
Written records of steps taken in conducting on-farm trials are important for two reasons.
First, detailed records are often required to interpret data. Sometimes the results are unclear.
Thinking about them further and looking over documentation usually brings explanations
to light. Second, written documentation preserves the details of your OFT project so you can
share information with others.
Five record sheets are included in the back of this manual to show the type of records
you should keep: 'On-Farm Research Field Record Log,' 'On-Farm Research Management
Summary,' 'On-Farm Research Costs Summary,' 'On-Farm Research Income Summary,' and
'Rainfall Record Sheet.' Also, keep required record sheets on any pesticide applications.
The following information includes the baseline data needed to document and interpret
a valid, unbiased test. This information is easily entered on the record sheets.
OFT Trial Description. Clearly state the goals, objectives, treatments and
experimental design of the trial.
Field History. Record differences in soil type and other obvious variations
within the test site and the previous cropping history. Include crop rotation,
tillage practices, previous crop and variety, fertilizer and pesticides applied.
Make a diagram showing the layout of the field trial.
Soil Test and Fertility Program. Sample soil from the intended harvest areas
using university guidelines. Send samples to a reputable laboratory for analysis.
Make fertilizer applications based on soil test results. Record the quantity and
form of fertilizer applied.
Soil Moisture at Seeding. If your soil samples are taken near the time of
seeding, record the depth to moisture and depth of moisture. Have your soil
samples evaluated for available soil moisture.
Planting Conditions. Record the crop, variety, seeding rate (pounds per acre and
seeds per pound), planting date, soil temperature, type of planter, seeding depth,
row spacing, residue levels and any other conditions that might influence the
stand establishment and crop production.
Field Operations and Observations. Record all field operations in diary
format. Take notes on the methods of your field operations, such as the type
of equipment, depth of tillage operations and materials applied to either the
whole field or to just one treatment.
Weather. General observation of growing season weather conditions is all that is
required. If practical, place a rain gauge at the test site. After each storm, record
rainfall in the rainfall record sheet and empty the rain gauge. A little oil in the
rain gauge will prevent the water from evaporating before you can get out to the
field to measure it.
Insects, Weeds and Disease. Make notes on the presence and density of insects
and diseases, date of infestation, and extent or severity of damage. Record similar
observations for persistent weeds. Note differences between treatments, if any,
due to pests. If pesticide treatments are being compared, take more detailed data
to evaluate crop injury and level of control of different pest species.
Crop Growth and Development. During the growing season make and record
observations of plant growth and development. Record the date each treatment
reaches a critical growth stage. It is just as important to record that you see no
differences among treatments at a certain growth stage as it is to record obvious
differences. For example, critical stages in cereal crop development include
emergence, tillering, stem elongation, booting, and heading. Record crop stage
at the time of treatment applications, such as spraying or top dressing. When
abnormal conditions occur, such as drought, note the differences in plant growth
or response among treatments.
It is important to plan ahead and identify what should be measured, and when and how to
take measurements. What you will measure depends on the project's objectives.
If the purpose is to increase yield, then a measure of yield is required. If the objective of
a new practice is to increase soil moisture, then soil water tests are needed. If the purpose is to
increase net farm profit, then you must analyze costs and returns (including yield).
If you need help in deciding what to measure and how to measure it, consult your county
extension agent. Without appropriate data and a method to measure treatment differences, your
trial will have little value or could lead to inaccurate conclusions. Remember, the more you plan
and document, the greater confidence you can have in your results.
Yield estimates are needed to make production and economic comparisons between
treatments. To be valid, yield measurements must be taken from comparable areas in each
treatment plot. You must measure the size of the harvest area. Measure plot lengths with a
measuring tape or other reliable measuring device before or immediately after you harvest
each plot. These distances are then multiplied by the width of the combine header to arrive
at the harvested area. Harvested area is used to calculate yield per acre. An example of yield
calculation is shown in the data analysis section of this manual.
Harvest the middle portion of each treatment plot. This assures that the yields are not
affected by a condition bordering the treatment. Yields can be measured with a local truck
scale, a weigh wagon, or using the barrel method. Harvest equipment must be completely
empty and clean before each treatment is harvested.
Save a sample from each treatment to determine moisture content at harvest and any other
quality factors that may be important such as test weight and protein content. If moisture
contents differ between the treatments, yield must be corrected to a constant moisture.
The barrel method is a slow and time-consuming method to determine yield, but may be
useful if other methods are not available. It involves measuring the volume of grain yield using a
standard 55-gallon barrel. Treatment yields can be compared using the barrel method as long as
the test weights do not differ between the treatments. For example, with wheat you can use the
First, locate a standard barrel 22.5 inches in diameter. Each inch of depth holds
0.185 bushels, 6.3 bushels for a full 34-inch high barrel. Depending on the width
of the combine and length of the test strip, the barrel may have to be filled more than
once. Stop the auger before completely filling the barrel. Fill the barrel several times
if necessary and add the total inches of depth. Multiply the total inches of depth by
0.185 to determine total bushels harvested from the plot. Determine test weights for
each treatment. If the test weights are different, use the test weight of each treatment
to correct the barrel volume to a standard weight.
Data collected in the trial must first be converted to commonly used units prior to analysis
and summary. The following is an example, converting wheat yields to common units.
Combine header width:
Measured grain weight:
Wheat in bushels:
Yield in bushels per acre:
20 ft x 400 ft = 8000 sq ft
8000 sq ft/43,560 sq ft per acre= 0.18 acre
1000 lbs/60 lbs per bushel = 16.7 bushels
16.7 bushels/0.18 acre= 92.8 bushels/acre
Data analysis largely depends on how the project was designed and conducted. Using a
uniform field site, simple treatments, and a randomized complete block design, a research test
can be statistically analyzed and the results quickly evaluated and interpreted. Simple statistical
software packages are available through your county extension agent to do data analysis.
SUMMARY OF RESULTS
To interpret results from your on-farm trial, carefully summarize management history, data
collected, and observations made. Summary forms are provided in the back of this guide for this
purpose. The summarized results should address your goals and objectives. If your objective was
to reduce costs, equal or even lower yields may be an acceptable result as long as costs are
reduced and the net return has improved.
Take the time to share the results with your neighbors and county extension agents.
This flow of information and experience is necessary for the progress of agricultural production
Baird Miller is an extension agronomist with Washington State University.
EdAdams is a regional Water Quality Coordinator with Washington State University.
Paul Peterson is an area extension agent with Washington State University.
Russ Karow is an extension agronomist with Oregon State University.
FIELD RECORD LOG
I. Goal of On-Farm Test:
Objectives of On-Farm Test:
II. Experimental Design:
Treatment 1 Treatment 3
Treatment 2 Treatment 4
No. of applications Size of each treatment feet by feet
III. Field History:
IV. Soil Fertility:
Soil Test Results
V. Soil Moisture at Seeding Time:
VI. Planting Conditions:
Type of planter
Depth to moisture ft Depth of moisture ft
Available moisture inches
Total cropping season rainfall: inches
Variety Seeding rate
Seeding depth Row spacing
Diary of Field Operations and Observations
Date Treatment No. Field Operation Material Applied/Rate Comments (Crop stage, pests, etc.)
I I t
_____________ _________________________________ ________________________________ I ___________________________________________________ ______________________________________________________
Tillage operations: Field 1 2 3 4
Rainfall Record Sheet
Jan Feb Mar Apr May Jun Comments
Rainfall Record Sheet
July Aug Sept Oct Nov Dec Comments
Tillage operations: Whole Treatment
Field 1 2 3 4
Fertilizer applied (include application costs):
Pesticides applied (include application costs):
Other inputs (include cost of operation):
Fertilizer applied in Ibs/acre:
Pesticides identified and severity scores:
Weed species (before/after)
Insect species (before/after)
Pesticides Applied: Field 1 2 3 4
Use psticdes ith are.Appl the onl to lant, anmals or iteslistd onthe abel
When mixing and applying pesticides, fo~llow ll lbepeauiostoprtetyorsl
Washington State University
Larry G. James,
Interim Director, and the
U.S. Department of Agriculture
in furtherance of the Acts of
May 8 and June 30, 1914.
programs and policies are
consistent with federal and
state laws and regulations on
race, color, national origin,
religion, gender, age, disability,
and gender preference. Trade
names have been used to
simplify information; no
endorsement is intended.
Published July 1992. B