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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #166256
Title: IMPLEMENTATION AND VALIDATION OF SENSOR-BASED SITE-SPECIFIC CROP MANAGEMENT THROUGH ON-FARM RESEARCH

Author
item SHANNON, D - U OF MO
item PALM, H - U OF MO
item Kitchen, Newell
item Sudduth, Kenneth - Ken

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/26/2004
Publication Date: 7/1/2005
Citation: Shannon, D.K., Palm, H.L., Kitchen, N.R., Sudduth, K.A. 2005. Implementation and validation of sensor-based site-specific crop management through on-farm research. In: Mulla, D.J., editor. Proceedings of the 7th International Conference on Precision Agriculture, July 25-28, 2004. Precision Agriculture Center, University of Minnesota, St. Paul, MN. [unpaginated CDROM]

Interpretive Summary: Farmers who have used precision agriculture technologies for managing soil and crop variability within fields have requested assistance in developing guidelines on how to apply these technologies. The real challenge is that many farmers are finding it difficult to translate information obtained from sensors into agronomic decision rules in a way that will be meaningful for their particular farm. They realize that precision agriculture guidelines must be part of an overall strategy of best management practices for integrated crop management and must meet sound economic principles. This project=s objective was to help farmers take sensor based information and develop on farm research studies. An additional goal was to develop precision agriculture guidelines and procedures based on the results of this on-farm research. In the first year of this project, findings from the on-farm research were mixed. However, the farmers learned enough about the process of gathering information and implementing precision agriculture that they were anxious to build on their efforts for a second year. As an example, one producer used a soil sensor to map a field into three different productivity levels. He varied corn seed rate and nitrogen fertilizer based on these areas and was able to make $9 more per acre than if he had used his normal practices. Guidelines developed from experiments on these five farms will allow producers to better manage within field variability for production efficiency, environmental stewardship, and profitability.

Technical Abstract: Site specific crop management (SSCM) is a collection of rapidly evolving concepts and technologies. Changes in one component nearly always affect the other components, often in complicated ways. This complexity, along with the need to integrate SSCM guidelines into an overall strategy of best management practices for integrated crop management, makes them difficult to develop and deliver. This project focuses on using on farm research to develop guidelines for sensor based SSCM. Five cooperating producers in Missouri conducted on farm SSCM experiments of their own choosing. Sensor based data layers collected at each producer's site included soil electrical conductivity, topography, remote sensing, and previous years' yield maps. Information on historical land use and management were also obtained. These data were used to develop the on farm experiment and/or to evaluate within field variability. The first year of on farm research helped participants understand the complex nature of SSCM, and the potential economic and environmental benefits of sensor based data. As an example, one producer used soil electrical conductivity along with historical yield maps to delineate productivity zones. Corn seeding and nitrogen fertilizer rates were varied for these zones and compared to constant rate strips. A partial budget analysis showed a $22/ha increase in return with variable rate application. In this example, yield was improved and seed and fertilizer costs were reduced when compared to the farmer's standard practice. SSCM guidelines developed from these five farms will lead to the overall project goal of developing and delivering methods and tools that allow producers to manage within field variability for production efficiency, environmental stewardship, and profitability.