2021
Boots on the Ground: Validation of Benchmarking Process Through an Integrated On-Farm Partnership
Category:
Sustainable Production
Keywords:
Field management Nutrient managementSoil healthTillageYield trials
Lead Principal Investigator:
Shawn Conley, University of Wisconsin
Co-Principal Investigators:
Project Code:
MSN240704
Contributing Organization (Checkoff):
Leveraged Funding (Non-Checkoff):
If the budget for collaborators exceeds available NCSRP funding, or additional states would like to participate, they are encouraged to request complementary funding from their local State Soybean Board to leverage the NCSRP funding. This has been the case during the previous NCSRP-funded benchmarking project.
Show More
Institution Funded:
Brief Project Summary:

This is part of a 3-year collaborative project with the primary goal of evaluating agronomic practices with greatest potential for increasing soybean yields for a given combination of climate and soil (a “technology extrapolation domain [TED]”). Evaluations will help to demonstrate key management factors in each state and across the region that can be used by producers to increase soybean yield, input efficiency, and profit while minimizing the environmental footprint. Because on-farm trials will be run across a wide range of climates and soils, results will also be useful to producers in states other than those in the project.

Key Benefactors:
farmers, agronomists, Extension crop specialists

Information And Results
Project Deliverables

Briefly, the proposed project will have four major activities:
(1) Design on-farm trials. In the proposed project, we will follow a novel approach that will allow us to (i) efficiently locate field experiments, (ii) determine which practice(s) to evaluate, (ii) scale out results from these experiments to other farmer fields, and (iii) quantify regional production and ROI impact from targeted production changes. The project will leverage from the outputs of our previous 3-year benchmarking project. First, our approach will determine trial locations using the Technology Extrapolation Domain (TED) spatial framework that delineates geographic regions with similar climate-soil conditions (Rattalino Edreira et al., 2018). Second, we will determine which practice(s) to test in each TED based on a list of candidate explanatory factors for yield gaps derived from our previous analysis of farmer survey data (Mourtzinis et al, 2018). We will first use legacy data (existing data from on-farm research groups and previous NCSRP-funded benchmarking project) to evaluate the robustness of the proposed approach. Such evaluation will compare the ROI in on-farm trials following the current “business-as-usual” model versus the prescient selection model proposed here.

Our prescient approach will strategically locate on-farm trials to represent TEDs with largest soybean planted area in each state. In other words, we will prioritize environments where the potential impact of on-farm research is the largest. Fields will be chosen to be representative of the “average” farmer in each TED, that is, with yields and practices that do not deviate substantially from the average in the region. We will use data from our previous project as a benchmark to determine average yield and dominant set of practices for each TED (Mourtzinis et al, 2018). We will ensure that fields are located near an automatic weather station—understanding on-site weather conditions will allow proper interpretation of the results. Once we have determined the location of the field trials, we will determine what practice to test for (or to omit) based on (i) what the farmer is currently doing, versus a (ii) list of candidate management practices explaining yield gaps in each TED derived from our previous NCSRP benchmarking project (Rattalino Edreira et al 2016; Mourtzinis et al 2017). When designing the specific treatment for each TED, the aim will be to have a ‘system comparison’ in which we modify a management practice, but we also fine-tune other practices so that we fully capture the yield benefit associated with that change. The treatment will aim to increase farmer profit by increasing yield, or by reducing costs, or both, and doing so in a way that maximize profit and minimize environmental footprint.

The map, in the proposal, shows a (preliminary) selection of TEDs where we would like to conduct on-farm trials. These TEDs account for the majority of soybean acreage in the US NC region, and we have already identified a set of candidate explanatory factors for yield gaps in each of them through our previous NCSRP-funded project. The TED framework will help disseminate results from the on-farm trials to other producer analog soybean fields with similar climate-soil conditions. As we mentioned previously, because on-farm trials will be run across a wide range of climates and soils, results from the project will also be useful to producers in states other than those included in the proposal. Using the TED framework as basis for site selection will help on-farm research groups to better complement and coordinate their field trials to make sure that they will not have an excessive number of field trials located in one single region with similar climate and soil, while other important regions (in relation with soybean area) are not covered.

(2) Conduct on-farm trials. Based on our previous experience conducting field experiments, a large (but not excessive) number of field trials (that are not concentrated too much in a local area) is needed to detect statistically significant effect of changes in management practices and make robust recommendations. We would like to conduct a minimum of 8 field trials (one trial per farmer field) in each year and each state. Each field trial will consist of 3-4 replicated strips (size: ~40 by 500 ft) where the treatment determined by the UW-UNL core team, in consultation with the state collaborator, will be implemented. The goal is to compare the yield and profit measured for that treatment against the one attained by the producer for the rest of the field using his/her average management. We will conduct the on-farm trials over 3 years to account for year-to-year weather variation, particularly, in-season precipitation, which can be locally variant. The collaborator in each state and his/her technician will be responsible for conducting field trials following UW-UNL guidelines, input results into a digital file, and send it to the core team. Our collaborators will also request farmers to report information about their yield, field location, and detailed information on crop/field/input management, such as planting date, soybean variety, tillage method, etc. as well as to submit grain samples to UW for seed composition. Individual field data and producer contact information will remain confidential. Indeed, the TED framework will ensure confidentiality of producer data because, once a field has been contextualized relative to its climate and soil, the exact field location has no value. Participating farmers will also complete a grower production survey to get input costs for economic analysis. Given the funding cycle of NCSRP we propose to initiating a third year for the project where we can establish research plots and identify farms to serve as on-farm learning laboratories where collaborators can sponsor field days and events to communicate results locally. Collaborators will request a no-cost extension till Dec 2021 to ensure that experiments are concluded satisfactorily and data are processed. PIs will also evaluate results from years 1-2 to decide how/what to evaluate in the third year.

(3) Data analysis. Once the data are provided, they will need to be standardized into a single, consistent format, error-checked, and then inputted into a digital database. We will use a range of state-of-art methods to analyze the data from field experiments, including remote sensing, crop modeling, spatial analysis, and advanced statistical techniques (e.g., machine learning). We will make use of the expertise on analysis of farmer data acquired by the UW-UNL team during the previous benchmarking project to retrieve detailed data on weather, soil, and topography for each field-year trial. UW and UNL will be responsible for data analysis and will collaborate with faculty at the Statistical Departments at UNL, UW and ISA to validate our statistical analyses. Our analysis will be based on the aggregated database and results of the analysis will not specifically pinpoint individual producer fields. The database will be saved in a secured server, which will be accessible only to those involved in the project. After the end of the project, the state-specific databases (yield, management, soil, weather) will be (with NCSRP permission) turned over to the on-farm groups for use by them, particularly if they want to continue the annual on-farm trials to build longer term databases for their use in knowing more about their producer constituents.

(4) Communication and dissemination of results. Results of the proposed project will be disseminated to producers and public via peer-reviewed scientific and Extension publications, presentations at scientific conferences and Extension events sponsored by universities, natural resources districts, growers’ associations, and proprietary organizations that market their products to soybean producers. Individual state and combined regional reports will be posted and distributed through various webpage portals such as www.coolbean.info, SRRI, and the NE CropWatch website (http://cropwatch.unl.edu/). UW will organize team meetings at the ASA/CSSA/SSSA meetings and/or Commodity Classic. Moreover, participating farmers will be actively involved with this research project. Given the project timeline, additional funding will be required to see this third year of research through harvest.

Final Project Results

Updated January 18, 2022:
For the third and last year of the project, the core team has developed and distributed detailed field protocols and data collection methods to ensure consistency in the experiments conducted across states. State collaborators were requested to identify fields before February 1, 2022. The number of fields to be harvested for 2021 are (54).

The NE-WI core team actively promotes and distributes output from this project. In-season live Twitter interviews with participating growers occurred in the 2021 growing season with farmers in IA and WI. The core team also developed an Extension publication with year 2 results that was widely distributed and is housed on SRII and www.coolbean.info. In short, the “Improved system” increased yield by 3.2 bu/ac (5.5 bu/a in 2019) and profit by $31/a ($51/a in 2019). Protein, oil, and AA data were also collected. For more information, please see the full publication entitled: Boots on the Ground 2020 On-Farm Trials Report:

The NE-WI core team has been actively utilizing the legacy data from the initial NCSRP project and others on-farm networks across the NC US region. To date, we have published eight manuscripts from these legacy data (listed below) and another one is in preparation. We have also synthesized all of the data from the original Benchmarking project into an Extension publication entitled: Benchmarking Soybean Production Systems in the North Central US. This publication has been shared with all collaborators and published through multiple venues.

• Azzari, G. et al. 2019. SATELLITE MAPPING OF TILLAGE PRACTICES IN THE NORTH CENTRAL US REGION FROM 2005-2016. Remote Sensing of Environment 229: 417-429. https://doi.org/10.1016/j.rse.2018.11.010
• Andrade, J.F. et al, 2019. Assessing the influence of row spacing on US soybean yield using experimental and producer survey data. Field Crops Research 230: 98-106. https://doi.org/10.1016/j.fcr.2018.10.014
• Rattalino Edreira, IR et al. 2020. From sunlight to seed: assessing limits to solar radiation capture and conversion in agro-ecosystems. Agricultural and Forest Meteorology. 280 107775. doi: https://doi.org/10.1016/j.agrformet.2019.107775
• Matcham, E., S. Mourtzinis, S. P. Conley, J. I. Rattalino Edreira, P. Grassini, A. Roth, S. N. Casteel, I. A. Ciampitti, H. J. Kandel, P. M. Kyveryga, M. A. Licht, D. S. Mueller, E. D. Nafziger, S. L. Naeve, J. Stanley, M. J. Stanton, and L. E. Lindsay. 2020. Management Considerations for Early and Late-Planted Soybean in the North Central US. Agronomy Journal 1-16 doi:10.1002/agj2.20289.
• Rattalino Edreira, J. I., S. Mourtzinis, G. P. Azzari, J. Andrade, S. P. Conley, J. E. Specht, and P. Grassini. 2020. Combining field-level data and remote sensing to understand impact of management practices on producer yields. Field Crops Research 257 107932 doi: https://doi.org/10.1016/j.fcr.2020.107932.
• Mourtzinis, S et al. 2020. Assessing approaches for stratifying producer fields based on biophysical attributes for regional yield-gap analysis. Field Crops Research. 254 107825 https://doi.org/10.1016/j.fcr.2020.107825.
• Mourtzinis, S., J. Andrade, P. Grassini, J. I. Rattalino Edreira, H. J. Kandel, S. L. Naeve, K. Nelson, M. Helmers, and S. P. Conley. 2020. Assessing benefits of artificial drainage on soybean yield in the North Central US region. Agricultural Water Management 243 106425 doi: https://doi.org/10.1016/j.agwat.2020.106425.
• Shah, A.D., T. R. Butts, S. Mourtzinis, J. I. Rattalino Edreira, P. Grassini, S. P. Conley and P. D. Esker. 2021. An interpretable machine learning assessment of foliar fungicide contribution to soybean yield in the north-central United States. Scientific Reports 11:18769. https://doi.org/10.1038/s41598-021-98230-2.

Despite the reduced funding, by the end of this 3-year project, we will have validated a novel research approach that utilizes self-reported on-farm production practices, together with on-farm validation, to identify management practices with greatest impact on farm yield and profit. Consequently, we will strengthen state-to-state research collaboration through the managed coordination of the on-farm partnership, build farmer-to-farmer networks and identify and communicate key management practices that increase soybean productivity and return of investment. We will also build a framework through our farmer-to-farmer networks, farmer video profiles, and field labs to communicate findings directly to farmers from farmers.

Across states and the two first years of the project, the improved treatment averaged 62.2 bu/ac, which represents a 7% increase compared to the control treatment (58 bu/ac). In the improved treatment, seed protein content was slightly decreased whereas oil content was slightly increased. But total protein and oil production were increased by 6 and 8% respectively due to the higher yield of the improved treatment. Using the median soybean price for the 2011-2021 period ($9.7/ac), the improved treatment resulted in an average +$31/ac extra profit. The additional profit derived from the improved management was higher than $10/ac in 70% of the cases.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.