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Why On Farm Research?

The biggest advantage of doing on farm research instead of small plots is the possibility to have large treatment plots on top of spatial variability in the real farmer condition. Generating data in the same region and crop system is the best way to extrapolate research results.

Key Objective

The major objective of this on farm precision agriculture research area is to conduct large plot experiments mainly in Louisiana to build a network knowledge database of crop yield response site-specifically to guide variable rate inputs application. Joining this network, you will help with valuable data for science and have one field trial mapped for Free depending on LSU Precision Ag Team and equipment availability.

Joining the network you will have one field of about 40-80 acres mapped for electrical conductivity and one NDVI image using drones equipped with active sensors and multispectral cameras during your crop growing season. Not all farmers that join the network will be mapped due to limitations of resources.

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Let's use the data

Researchers need Geo-referenced data generated on farm to deliver a better crop management information to the farmer. Sharing your field data with a state institution to generate official agronomic recommendations is a great advantage on how to get unbiased results. Farmers own the data. The experiments results will be released just for members of the network. Join it, it is free. Researchers from LSU reserve the right to use the data in perpetuity for the sake of science. However, the researchers will not sell or share the data to other parties, without farmer consent.

Farmer requirement

The only requirement is to have yield mapping and variable rate fertilizer capabilities.

The farmer provides:

  • Field Boundary
  • Planting date
  • A field of at least 40 acres.


  1. The need of minimum of 40 acres is to be able to design experiments with treatment plot size of about 0.5 acre each
  2. Yield loss will be compensated if occurs, but until now we did not have any yield loss running trials compared to farmer practices

The advantages to join an academic network is to:

  • Have unbiased analysis and state official recommendations as a proxy to improve spatial crop management recommendations.
  • Have confidentially of sharing data for your own benefit and for the science.
  • Fully use of all resources available in your farm machinery.
  • Empower your technical team and consultants with non-traditional statistical data analysis.

A brief story of On-Farm Precision Experimentation

In the late 1990s, crop scientist Donald Bullock at the University of Illinois realized that the recently commercialized, GPS-linked variable rate technology and yield monitoring made it possible to conduct large-scale, randomized, on-farm field trials inexpensively. He explained in a personal interview that by that time, great enthusiasm had developed about site-specific agriculture, and farmers’ new capabilities to tailor input application rates on sub-field bases. Bullock knew, however, that by that time a good deal of empirical work had been published, or was known to have been conducted, that rejected the idea that a site’s yield potential, by itself, could not provide much meaningful information about optimal input application management.

Therefore, Bullock was skeptical about the effectiveness of using yield maps to guide input application management and thought that more information about yield response to factors of production would be needed to provide farmers with much profitable advice about site-specific input management. He and others also knew that the inference space of small-plot field trials was quite limited—that, “It was difficult to take information from an experiment the size of a basketball court in one location, and use it to come with input application advice for a field across the road—let alone across the state”.

Bullock decided to try to develop field trial software that would allow other researchers to apply his idea of using precision technology to conduct large-scale trials. He asked Ronald Milby, then an employee of Growmark Illini FS, to use his software development skills to write the computer code, developing the software as an extension of ESRI’s ArcGIS software package.

Milby and Bullock thus developed the Enhanced Farm Research Analyst, which they made freely available to interested researchers, a number of whom used it in empirical work. However, EFRA was designed to be compatible with the Windows XP operating system, and once that system was replaced by Microsoft, Bullock and Milby did not adapt EFRA to work with the newer operating systems and did not have funding to offer much technical support to users. Even after EFRA software became incompatible with commercially available computer operating systems, Donald Bullock continued to believe that large-scale, on-farm agronomic field trials should be conducted to inexpensively generate high-quality and high-quantity yield response data.

In 2012, he teamed up with University of Illinois agricultural economist David Bullock to win seed grant funding from the University of Illinois College of Agricultural, Consumer, and Environmental Sciences’ Future Interdisciplinary Explorations program. With that funding, they continued to use EFRA, working with one participating central Illinois farmer to run a 2014 field trial. The results of that experiment were encouraging, so along with colleagues, they wrote a proposal for and received a four-year, $4-million USDA-NIFA-AFRI Food Security grant, which they titled “Using Precision Technology in On-farm Field Trials to Enable Data-Intensive Farm Management”, and call “DIFM” for short.

In independent research, in 2015 Bruce Maxwell and colleagues at Montana State University began using a similar methodology to conduct on-farm precision experiments in Montana wheat fields, investigating the effects of N fertilizer on grain yield and protein content one nine fields from four farms. That research was initially funded by the Montana Research and Economic Development Initiative, and later by the Montana Fertilizer Advisory Council. In 2018, Maxwell’s group and the existing DIFM project joined forces.

Beginning in 2002, Dr. Luciano Shiratsuchi used Bullock and Milby’s EFRA software to design and conduct on-farm precision experiments as an EMBRAPA scientist in Brazil. Shiratsuchi obtained funding from various Brazilian sources and conducted on farm trials in Bahia state frontier called Luis Eduardo Magalhaes and in the Cerrados region in general. On those initiatives, the relationship with big producers and the understanding of the real demand of a farmer give his group a new perspective to run agricultural research, that is to conduct research on the farmer cropping system, using their own modern variable rate applicators to put out trials automatically and use yield monitors to evaluate the results. He began collaborative research efforts with DIFM personnel, starting in 2014, when David Bullock, Don Bullock and Robert Dunker from University of Illinois visited him in Sinop in the state of Mato Grosso (biggest grain producer in the country). In that time he was coordinating nationally for row crops an on farm precision experimentation project in Embrapa Agro Silvopastoral. In 2017 and 2018, Shiratsuchi conducted four very large-scale (100+ ha) OFPEs in the Brazilian states of Mato Grosso, and Mato Grosso do Sul. In 2018, he took a position to conduct research, extension and teaching in precision agriculture at Louisiana State University to expand his possibility to collaborate effectively on this thematic. He is now a member of the DIFM research team and will conduct trials in Louisiana, Texas and Brazil, mainly with cotton and sugarcane.

Haying Tao a lead scientist in Precision Ag Technologies from Washington State University is also a member of this group since the beginning of the DIFM project. She was able to contribute very strategically in the practical use for farmers, specially in adoption and extension in general.

Now the Core DIFM Team sum up efforts with other Universities (Kansas State University, University of Nebraska-Lincoln, Ohio State University, Purdue University, University of Minnesota, Michigan State University, University of Wisconsin, Oklahoma State University, Mississippi State University, Cornell University - Ithaca, North Dakota State) in a multistate project called "Frontiers in On-Farm Experimentation funded by USDA (2020- 2025) lead by Dr. David Bullock from University of Illinois.

Different than the traditional on farm research that is to conduct research on farm, "On farm precision experimentation" is conducted considering spatial variability and appropriated spatial statistical designs and modern techniques of analysis, such as machine learning, to support a better variable rate input application towards a better profit, more food and less harm to the Environment.

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