Project Details:

Title:
Boots on the Ground: Validation of Benchmarking Process through an Integrated On-Farm Partnership

Parent Project: Boots on the Ground: Validation of Benchmarking Process Through an Integrated On-Farm Partnership
Checkoff Organization:North Central Soybean Research Program
Categories:Crop management systems
Organization Project Code:MSN218698
Project Year:2020
Lead Principal Investigator:Shawn Conley (University of Wisconsin)
Co-Principal Investigators:
Patricio Grassini (University of Nebraska)
Keywords: Best Management Practices, BMP's, Farmer profit, Intensification, On-Farm Research, ROI, Seed Composition, Soybean, Yield, Yield gap

Contributing Organizations

Funding Institutions

Information and Results

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Project Summary

Analysis of producer survey data performed during our previous 3-year NCSRP-funded benchmarking project revealed: (1) an average yield gap of 20-30% between current farmer yield and potential yield as determined by climate, soil, and genetics, and (2) a number of agronomic practices that, for a given soil-climate context, can be fine-tuned to close the gap and improve soybean producer profit. We propose here to leverage on the previous investment made by NCSRP by working with on-farm groups to bring the yield gap analysis “back to the farm”. This project will focus on showing how the producer survey data can be used to identify and strategically evaluate management changes in on-farm research settings across the US NC region. Some of these settings can also be used in highly publicized field day events, where soybean producers can observe how a key yield-enhancing management practice often cannot be fully optimized without some adjustment needed in other management practices a producer also uses (i.e., exploiting synergies).

Traditional field research has relied too much on trial and error (i.e., random allocation of trials, subjective decisions on what technology to evaluate, etc.), with little capacity to extrapolate results to farmer fields and quantify impact relative to enhancing net profit beyond extra cost of any required production input. Clearly, there is an opportunity to make field research more efficient and impactful and, by doing so, increase coordination and exploit synergisms among on-farm research groups. Such an optimization requires a robust spatial framework that delineates geographic areas with similar climate and soil and, hence, where a similar yield response to a given set of technologies is expected. This framework can definitively help determine the number and location of trials, guide extrapolation of results from research plots to farmer fields, quantify impact at local and regional levels, and, ultimately, increase the return on investment (ROI) made on on-farm research. For example, there may be an on-farm research group evaluating the same technology at multiple locations with similar climate and soil. This offers an opportunity to be more efficient, for example, by testing a different technology at some of these locations or by reallocating some of the experiments somewhere else to evaluate the same technology in an environment with different climate and soil. To summarize, we believe that, in addition to more “boots on the ground”, there is need for a framework that can help make on-farm research more efficient and impactful.

On-farm trials can evaluate a small number of technologies due to logistics and cost constraints. Hence, it is crucial to choose technologies that are most likely to improve soybean producers’ yield and profit. On-farm research has relied too much on unrealistic expectations from researchers/industry and anecdotic evidence rather than on a clear understanding of producers’ realities and problems. We believe that our previous analysis of producer survey data provides an excellent starting point to prioritize on-farm research because we have now identified more than 10 management practices that explain yield gaps in producer soybean fields in the US NC region. Another problem associated with traditional on-farm research is the strong focus on evaluating changes in single factors (e.g., late versus early planting) without sufficient attention on ‘background’ management (that is, other managements practices besides the one evaluated). A major problem with this one-factor-at-a-time approach is that the potential benefit of a technology may not be fully realized if other management factors need some adjustment for full optimization of that technology. Thus, a robust evaluation of agricultural technologies should include tactical changes in other management practices in order to exploit the synergisms among them. For example, evaluation of early planting date should include application of seed treatment, monitoring of soil temperature and weather forecasts to ensure optimal plant stand establishment, and optimization of MG. To summarize, there is an urgent need for a shift from the current ‘single-factor comparison’ model to a more meaningful and farmer-oriented “system comparison”.

Project Objectives

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.

Project Deliverables

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. We will also 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 ROI.

Progress of Work

Final Project Results

Benefit to Soybean Farmers

The potential impact of the outcomes derived from this study is significant. For example, on-farm validation of the identified management strategies across all examined regions will impact 60 million acres of soybean across the North Central region. Farmers within the regions where planting date was a significant management factor would realize a production increase of 4.7M bushels per day (0.24 bu/acre/day yield increase on 19.5 million acres). This figure of impact was estimated based on analysis of on-farm yield data performed during our previous Benchmarking project. We will build a framework through our farmer-to-farmer networks, farmer video profiles, and field labs to communicate findings directly to farmers from farmers.

Performance Metrics

Please see attached KPI document.

Project Years