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K-State Agronomy eUpdates

Department of Agronomy

Kansas State University

1712 Claflin Rd.

2004 Throckmorton PSC

Manhatan, KS 66506

785-532-6101

agronomy@ksu.edu

Extension Agronomy

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

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 2017. Last year, we had on-farm projects in diverse areas around Kansas, setting up tests involving primarily corn and soybeans, with a few studies on sorghum as well. Funding support from Kansas Corn and Kansas Soybean is helping to increase our on-farm network.

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 state, regional or local scale, under a wide set of growing conditions and soil types.

There are no losers in this program. All parties will benefit. Farmers involved in this collaborative research effort will be empowered to solve their own problems and will have greater confidence in making decisions related to their production practices. The standard practice of the program involves producers having a question, then researching the answer on their own farm and soil with a simple strip trial designed with the assistance of K-State researchers. With this information, K-State Extension specialists will be able to check the validity of previous findings conducted with traditional research in small plots and more controlled environments, and to identify and communicate areas for future research.

The on-farm research collaborative project is farmer-run research; thus, 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 of improving yields and/or minimizing input costs, increasing overall efficiency.

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 empower our producers to make sound decisions with confidence and will aid researchers in identifying and communicating areas for future research.

Who are the key players?

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

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

3. K-State Extension State and Area Specialists: K-State faculty will assist Extension agents and Kansas farmers in developing the protocols, implementing trials and analyzing the data 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 (two or three) 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 interests 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.

Protocols:

Crops: Corn / Soybean / Sorghum / Winter Canola

Topics:

·         Seeding Rates

·         Planting Dates

·         Row Spacing

·         Hybrid/ Variety Selection

·         Tillage

·         Others

 

How many factors need to be evaluated?

The idea is to perform “simple” on-farm experiments evaluating one or two factors at a 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 of “treatments” or “variables” are usually needed. For example, if corn seeding rate is being 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.

Replications?

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.

Precision Ag technologies

In addition, on-farm studies in 2016 evaluated new technologies and added Precision Ag tools to the evaluation of variability and determination of zone management. Utilization of satellite imagery and precision soil sampling, in combination with yield monitor data, allowed us to obtain high-resolution for spatial variability within a field in order to investigate crop production issues and properly address them. Below is an example of some fields for which utilization of satellite imagery in combination with other data layers allowed us to obtain “management-zones” from low, medium, and high productivity area within the field.

Farmers interested in participating in this project can fill out an interest form online at:

http://bit.ly/KSUONFARMPROJECT

 

 

 Ignacio Ciampitti, Cropping Systems Specialist, K-State On-Farm Research Project Coordinator
ciampitti@ksu.edu

 

K-State Area Extension Agronomists:

 

Lucas Haag, Northwest Area Crops and Soils Specialist, lhaag@ksu.edu

 

AJ Foster, Southwest Area Crops and Soils Specialist, anserdj@ksu.edu

 

Stu Duncan, Northeast Area Crops and Soils Specialist, sduncan@ksu.edu

 

Doug Shoup, Southeast Area Crops and Soils Specialist, dshoup@ksu.edu