The Journal of Extension -

October 2014 // Volume 52 // Number 5 // Ideas at Work // v52-5iw9

Identifying Soybean Yield-Limiting Factors in Ohio

A process to identify soybean yield-limiting factors in Ohio with a team of farmers and Extension personnel was developed. The project uses farmer knowledge to identify sampling points in fields. Extension personnel collect soil, plant, and pest data throughout the growing season. Samples are sent to the Columbus campus of The Ohio State University for analysis. Upon completion of this multi-year project, multivariate statistics will be used to identify yield-limiting factors on a regional and statewide basis. Once yield-limiting factors are identified, Extension programming and field research will be developed to address the yield limitations.

Laura E. Lindsey
Assistant Professor and Extension State Specialist, Soybean and Small Grains
The Ohio State University
Columbus, Ohio 43210

Steven Prochaska
Associate Professor and Field Specialist, Agronomic Systems
The Ohio State University Extension
Marion, Ohio 43302

Harold D. Watters
Assistant Professor and Field Specialist, Agronomic Systems
The Ohio State University Extension
Bellefontaine, Ohio 43311

Gregory A. LaBarge
Associate Professor and Field Specialist, Agronomic Systems
The Ohio State University Extension
Marion, Ohio 43302

Yield Limitations to Soybean Production

From 1924 through 2013, soybean yield in Ohio increased at a rate of 0.37 bu/ac/yr, with a state average of 49 bu/ac in 2013 (National Agricultural Statistics Service, 2013). However, the theoretical maximum soybean grain yield is estimated to be 335 bu/ac (de Wit, 1967). This calculation is based on maximum light utilization for photosynthesis without other limitations (i.e., sufficient fertility, water, etc.). While the realization of the theoretical maximum yield is unlikely, the difference between theoretical and actual yield indicates that a great deal of yield potential is not achieved due to yield-limiting factors.

Creating a network of Extension personnel to collect on-farm data is not unique. Generally, data collection has been focused on one or two aspects of soybean yield limitations such as insects (Hodgson, Kemis, & Geisinger, 2012) or diseases (Sikora, Delaney, & Delaney, 2009). Davis, Kull, and Nelson (2012) discussed collecting a wide-range of data including soil fertility, soybean cyst nematode (SCN), and yield measurements through a yield-contest comparing a "standard practice" plot to an "investigative" plot. In 2013, we developed an on-going system of Extension personnel to help collect information to identify factors that are limiting soybean yield in Ohio. Our study is unique in that it involves many facets of potential yield-limiting factors such as soil fertility, pests, and management practices. Additionally, the reported here study uses GPS-referenced sampling techniques and combine yield monitors. Eventually, data will be used in a multivariate model to determine yield-limiting factors on a regional and statewide basis.

Assembling an Extension Team

Identification of soybean yield-limiting factors is a cooperative effort among Extension state specialists, field specialists, and county educators. Extension state specialists and field specialists developed common sampling protocols that are used by Extension educators to identify yield-limiting factors. Cooperating farmers volunteer to participate at winter Extension meetings.

Data collection includes a survey of management practices, soil fertility measurements, and pest ratings. To ensure quality data, Extension educators learn about the protocol at regularly held Extension in-service training meetings. Additionally, each educator receives a kit prior to the growing season to facilitate data collection. Kits contain a binder with the protocol, mileage reimbursement forms, and a list of contacts. All sampling materials are provided, which includes a hand-held GPS receiver with batteries, a soil sampling probe, a bucket, boxes for soil fertility samples, plastic bags for SCN soil samples, and paper bags for soybean leaf samples. Additionally, boxes with prepaid shipping labels are included to mail soil and leaf samples to Ohio State University for analysis. Because several educators are relatively new, support (if needed) to help collect samples and/or rate for pests is provided by graduate students and the Extension field specialists. This provides the educators with additional training to help them become more familiar with soil sampling and pest identification.

Data Collection

A survey of management practices is filled out by the farmer, including questions regarding management practices (seeding rate, planting date, and variety selection), fertilizer practices, and pest management (pesticide timing and use). Measurements of soil and crop nutrient status are conducted through spring soil sampling for soil phosphorus, available potassium, soil pH, and cation exchange capacity, and soybean leaf samples for macro- and micronutrient concentration at R1. Pest ratings include soil samples for SCN egg counts and visual evaluation of presence of weeds, diseases, and insects. Visual evaluation of pests is conducted at the R3 and R5 soybean growth stages. Yield data is collected at harvest via weigh wagons or yield map from a combine yield monitor.

The data are collected from three areas within each soybean field (Figure 1). Ten to 15 samples are collected in a zigzag pattern and homogenized within each sampling area. Two sampling areas, identified by the farmer cooperator and GPS-referenced by the Extension educator, are historically "normal" yielding, while a third area is historically low yielding.

Figure 1.
Diagram Distributed to Extension Educators to Explain Sample Collection

Description: C:\Users\lindsey.223\Desktop\Unfinished Manuscripts\State Survey- JOE\sampling.gif

Data Dissemination

After soil and leaf samples are analyzed, results are provided to Extension educators to distribute to cooperating farmers. With three sampling areas per field, factors that differ among the areas are used to identify yield-limiting factors.

Regional data is presented at winter Extension meetings. These data are extremely useful in Extension programs because different parts of the state have different yield-limiting factors. For example, we identified low soil pH problems in northeastern Ohio, while in northwestern Ohio high soil pH can be a problem. Yield-limiting factors are discussed on a regional basis to provide the most relevant information to farmers.


In 2013, three state specialists, three field specialists, and 19 county educators participated in the project. Extension personnel collected soil and plant samples and scouted for pests on 65 farms in 33 counties. Forty percent of the Extension project participants had been in their current position for less than 5 years, and many were recent additions to the Agronomic Crops Team (Mullen, Thomison, Lentz, LaBarge, & Watters, 2007). The project provides new educators with the opportunity to connect with farmers in their county and gain experience in applied field research and data collection.

Data collection is ongoing and will be continued for at least 2 more years. Regional and statewide yield-limiting factors will be determined using multivariate statistics with assistance from The Ohio State University Statistical Consulting Service.

Fields with low soil phosphorus and available potassium will be used in future field studies to evaluate soybean yield response to fertilizer. This data will be used to revise the Tri-State Fertilizer Recommendations for Corn, Soybeans, Wheat, and Alfalfa, which was originally published in 1995 (Vitosh, Johnson, & Mengel, 1995).

Other impacts of the project are accrued via the on-farm visits with cooperators. When visiting with farmers, other production questions were addressed, such as marestail weed control, soybean response to added nitrogen, base saturation interpretation, and use of cover crops.


The project reported here is generously funded by the Ohio Soybean Council. We thank Extension educators, farmers, and graduate students who helped collect and analyze samples for the study.


Davis, V. M., Kull, L. S., & Nelson, J. A. (2012). Development of a team-based on-farm learning program while challenging soybean growers to increase yield. Journal of Extension [On-line], 50(4) Article 4RIB5. Available at:

de Wit, C. T. (1967). Photosynthesis: Its relationship to overpopulation. In A. San Pietro (Ed.), Harvesting the Sun (pp. 315-320). New York: Academic Press.

Hodgson, E. W., Kemis, M., & Geisinger, B. (2012). Assessment of Iowa soybean growers for insect management practices. Journal of Extension [On-line], 50(4) Article 4RIB6. Available at:

Mullen, R. W., Thomison, P. R., Lentz, E. M., LaBarge, G. A., & Watters, H. (2007). Delivering timely Extension information with the agronomic crops team in Ohio. Journal of Extension [On-line], 45(4) Article 4IAW4. Available at:

National Agricultural Statistics Service. (2013). Quick Stats 2.0. Retrieved from:

Sikora, E. J., Delaney, D. P., & Delaney, M. A. (2009). Developing an innovative team approach to address newly introduced disease of soybeans in the United States. Journal of Extension [On-line], 47(4) Article 4IAW7. Available at:

Vitosh, M. L., Johnson, J. W., & Mengel, D. B. (1995). Extension Bulletin E-2567. Tri-state fertilizer recommendations for corn, soybeans, wheat, and alfalfa. The Ohio State University. Retrieved from: