On-Farm Trials Design & Creation
Create on-farm strip trials, RCBD plots, split-plot designs, checkerboards, and zone-based trials in GeoPard. Assign treatments, export machine-ready files, and prepare for spatial analysis.
1 min Tutorial
Create field trials in GeoPard directly on top of your field and zones map.
Keep each plot georeferenced. Assign one-factor or two-factor treatments. Export one machine-ready layer. Then evaluate results against yield, soil, topography, and as-applied data.
Smart trial placement
GeoPard helps you place trials where results stay clean and unbiased.
It can automatically find suitable trial areas, keep layouts away from field and zone boundaries, and respect buffer spacing so products do not mix between neighboring plots.
You stay in control. Adjust placement, move trials, fine-tune buffers, or delete layouts before execution.
This reduces trial setup time, avoids biased comparisons, and improves the ROI of every on-farm test.
Who it’s for
Farmers, agronomists, dealers, retailers, and researchers who want practical on-farm comparisons in real field conditions.
Why create trials in GeoPard
GeoPard stores each trial as a spatial field layer, not just a spreadsheet row.
Each plot, strip, or block stays linked to its exact field position. That makes later analysis much more useful.
You can evaluate trial outcomes by:
yield performance
soil and management zone characteristics
topography and other variability layers
economic return by treatment
Use this workflow when you want trials that are easy to execute in the field and strong enough to analyze after harvest.
What this module adds
GeoPard supports field trials as a dedicated data layer alongside Zone Maps.
Key capabilities:
draw trial plots directly on the Zones Map page
reuse trial locations when creating a new zones map
visualize trials on the field page when the related zones map is selected
export trials merged with the zones map into one application-ready file
What you need before you start
A field boundary in GeoPard
A saved Zones Map, or a clear trial area on the field
Treatments to compare, such as seeding rate, fertilizer rate, hybrid, variety, fungicide, or product dose
Machine width and travel direction for clean execution
Trial layouts supported
Plot Grid (RCBD)
A classic randomized complete block design for statistically stronger treatment comparisons. GeoPard creates a rectangular grid where each block contains all treatments in randomized order. Best for structured trials where you need cleaner, more publishable results and relatively uniform conditions within each block.
Split-Plot
A two-factor trial design with a second treatment dimension inside the main plots. Best when you want to test interactions such as the same rates across different hybrids or varieties. This is practical when one factor is harder to change in the field and the second factor needs to repeat consistently inside it.
Zone Strip
Creates strips inside management zones, following zone boundaries and clipping to fit each zone. Best when you want to compare treatments within specific soil types, productivity zones, or other agronomic zones.
Field Strip
Creates full-length strips across the entire field, crossing all zone boundaries. This is a practical setup for real farm equipment and easy application, especially for large-scale comparisons under varying field conditions.
Checkerboard
Creates alternating treatments across a grid pattern, spreading each treatment throughout the trial area. Useful for exploratory trials and for fields with strong spatial variability.
When to use split-plot
Use split-plot when you need two treatment dimensions in one trial.
A common example is the same rates tested across different hybrids or varieties.
This helps you measure interaction effects and compare ROI by both factors.
Which layout should you choose?
Plot Grid (RCBD): best when you want the strongest treatment comparison.
Split-Plot: best when you want one factor nested inside another, such as the same rates across different hybrids.
Zone Strip: best when you want to compare treatments inside different management zones.
Field Strip: best when you want easy machine execution across the full field.
Checkerboard: best for exploratory trials on fields with strong spatial variability.
Practical setup recommendations
Compare seeding or nitrogen rates with commercial machinery
Field Strip
Match strip width to implement width. Use 4-6 replications.
Compare the same rates across multiple hybrids or varieties
Split-Plot
Put rate in the main dimension. Put hybrid in the second dimension.
Compare hybrids, varieties, or products in a uniform area
Plot Grid (RCBD)
Use 3-6 blocks. Keep shuffle on.
Compare treatments inside productivity or soil zones
Zone Strip
Use the same zone map you already trust for agronomy.
Explore strong within-field variability
Checkerboard
Use smaller cells and more replications.
Step-by-step
2. Choose the trial layout
Pick the layout that matches your agronomic question and your machinery.
Use Field Strip for full-pass real-farm execution.
Use Plot Grid (RCBD) when you want tighter control and stronger statistics.
Use Split-Plot when you want a second treatment dimension, such as rate × hybrid.
Use Zone Strip when treatment response should be compared inside specific management zones.
Use Checkerboard for broad exploratory work on variable ground.
3. Set the geometry
Define the layout so it fits real field operations.
Set:
Replications
Angle
Width
Buffer
Blocks where relevant
Practical defaults:
match Width to machine working width
match Angle to travel direction or AB line
add Buffer where overlap risk exists
use more Replications when field variability is high
4. Define treatments
Enter the rates, products, or treatment values you want to compare.
For split-plot trials, define both factors before you build the layout.
A common setup is the same rate set repeated across several hybrids in the second dimension.
You can:
add or remove treatments
edit each treatment value
color-code treatments
generate treatment levels around a center rate using Treatment Difference
use Shuffle Layout to reduce positional bias
Typical trial factors:
seeding rate
nitrogen rate
fungicide rate
variety or hybrid
biological or stabilizer dose
5. Review the layout on the map
Check whether strips or plots fit the real field shape.
Make sure turns, headlands, waterways, and obstacles do not break the trial badly.
If needed, adjust width, angle, blocks, or treatment order and regenerate.
6. Save and visualize on the field
Save the trial layout.
GeoPard keeps it linked to the related Zones Map. When that Zones Map is selected later, the trial can be visualized on the field page.
This is useful for scouting, explaining the setup to operators, and checking treatment placement before execution.
Trial design parameters
Replications
Sets how many times the treatment set is repeated. More replications improve comparison quality and reduce the impact of local field variability.
Angle
Controls the orientation of the trial layout. Use it to align plots or strips with field direction, machine path, or operational preference.
Width
Defines the width of each strip or plot in meters. Usually match it to implement working width.
Buffer
Adds spacing between neighboring plots or strips. This helps reduce overlap and treatment interference.
Blocks
Defines the block structure used in layouts such as RCBD. Each block contains the full treatment set and helps account for field variability.
Treatments
Defines the treatment rates or values to compare, such as seeding rates, fertilizer rates, or product doses. Treatments can be enabled, edited, color-coded, added, or removed.
Treatment Difference
Quickly generates treatment levels around a center rate by percentage. Example: a 10% setting creates evenly spaced lower and higher treatment rates around the base value.
Shuffle Layout
Randomizes treatment placement inside the selected design. This helps reduce positional bias and improves comparison strength.
Best practices for better trial quality
Match strip width to the real machine width.
Keep strip direction aligned with travel direction whenever possible.
Use at least 3 replications for more reliable comparisons.
Add buffers if overlap or edge effect is likely.
In split-plot trials, put the harder-to-change field operation in the main dimension.
Repeat the second factor consistently inside each main plot.
Avoid placing the whole trial across very different productivity areas unless that is the actual question.
If variability is high, use blocks, zones, or historical productivity layers to control the comparison better.
Keep treatment names and rates clear before export.
Common mistakes to avoid
Strips that are narrower than the implement can apply accurately
Too few replications for a highly variable field
Ignoring headlands and overlap zones
Mixing factor order in split-plot trials and losing the second-dimension comparison
Comparing treatments later without checking actual applied rates
Using noisy, uncleaned yield data for the final conclusion
After harvest, do not rely only on planned treatment rates. Check the actual applied data and clean the yield dataset before drawing conclusions.
After harvest: analyze the trial properly
Creation is the first half.
For strong conclusions, combine the trial layout with cleaned yield, actual applied data, and field variability layers.
Recommended follow-up pages:
Related docs
Changelog
March 2026 — initial release of On-Farm Trial Layouts Design with spatial trial layouts, treatment setup, map visualization, and merged export with zones maps.
April 2026 — split-plot design added for two-factor trials, such as the same rates across different hybrids.
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