On-farm Research Collaborative Project: Non-biased, Research-based, and Grower-driven

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K-State Extension state specialists, area agronomists, and county/district agents are again seeking to collaborate with producers in establishing on-farm and large-scale research plots in 2015. Last year, we had on-farm projects in diverse areas around Kansas, setting up tests involving corn, soybean, and grain sorghum. In 2015, we will be collaborating with the Kansas Ag Research and Technology Association (KARTA) on these tests, along with K-State’s Lucas Haag, Ajay Sharda, Terry Griffin, and Extension agents and area agronomists.

The goal of our on-farm research collaborative project is to establish a network of on-farm research collaborators with the main purpose of providing research results on production practices at the regional or local scale, under a wide set of growing conditions and soil types.

Among other benefits, this will help agronomy researchers at K-State check the validity of previous scientific findings conducted in small plots and in more controlled environments.

The on-farm information will be produced and used by farmers. Farmer participation is the key component of this project and farmers will be the main beneficiary.

Why should I get involved in this project?

1. The project has a main goal to improve yields and/or minimizing input costs, increasing overall efficiency at the local level.

2. The project will help producers learn the best ways to design an on-farm test so they can obtain reliable information on a specific question related to their own farms.

3. The outcomes from this project will aid other growers in Kansas.

Who are the key players?

1. Kansans farmers: Farmers are the main players, the ones who will implement the trials and collect the data.

2. Extension Agricultural Agents: The agents are the “gatekeepers” of this project. They work very closely with farmers and can assist, if needed, with information and/or help on implementing the trials.

3. K-State Extension State Specialists and Area Agronomists: K-State faculty will assist Extension agents and Kansas farmers in developing the protocols, implementing trials, and analyzing the research information generated at the on-farm scale.

Research data (small-plots) vs. On-farm data (large-plots): What is the main different between these concepts?

Information produced at research stations has the following features:

  1. Small plot size = small variability (“controlled conditions”)
  2. Intensive sampling = usually related to a graduate student project, with many samples taken throughout the growing season
  3. More complex and more treatments can be evaluated
  4. Small sample size = measurements may be less representative of “real” farm conditions

On-farm data have the following features:

  1. Large plot size = higher variability due to uncontrollable variation within each plot
  2. Less intensive sampling
  3. Less complex and fewer treatments can be evaluated
  4. Large sample size = measurements may more closely represent “real” farm conditions

Are the on-farm protocols the same for all environments and farmers or should they be farmer- or site-specific?

Farmers have their own interest and specific questions that need to be properly addressed. Protocols will be designed to fit each farmer’s situation. Some of the diverse topics that we have discussed include: corn/ soybean/ sorghum seeding rates; corn/ sorghum hybrids; sorghum/ soybean row spacing; corn/ soybean/ sorghum planting dates; full or limited irrigation; and other topics.


Corn / Soybean / Sorghum / Winter Canola


  • Seeding Rates
  • Planting Dates
  • Row Spacing
  • Hybrid/ Variety Selection

How many factors need to be evaluated?

The idea is to perform “simple” on-farm experiments evaluating one or two factors at the time.

How many levels for each factor?

This will depend on the availability of space in the field, but to properly understand the optimum crop management level, 4 to 5 levels are usually needed. For example, if corn seeding rate is evaluated, five seeding rates will allow the grower to properly identify the optimum seeding rate for each specific farm environment. The diagram below presents an example of 5 test levels for a seeding rate study.


To obtain statistically sound and solid recommendations, a minimum of 3 replications are recommended.

Are crop production practices environment-specific?

The example in the graphic below shows how the optimum plant density to maximize corn grain yield will vary according to different environments. For the low yielding environment (<100 bu/acre), the economically optimum plant density was about 15,000 to 20,000 plants per acre; while for the high-yielding site, economically optimum maximum plant density is about 25,000 plants per acre. Therefore, different yield potentials in different environments have different “optimum” crop production practices to maximize net returns.

Goal for the next 5 years

This project has as a goal to establish a network of on-farm research trials with the purpose of fine-tuning crop production recommendations to local environments. The end result will hopefully be to generate practical information that will either improve yields or minimize input costs.

Our goal will only be possible if farmers collaborate with us and vice versa, in a reciprocal approach.

Farmers interested in participating in this project can get more information by directly contacting Ignacio Ciampitti at 785-410-9354 or Ciampitti@ksu.edu or by contacting their county Extension Agricultural Agents or Area Extension Agronomists.

-- Ignacio Ciampitti, Crop Production and Cropping Systems Specialist, K-State On-Farm Research Project Coordinator and KARTA collaborator