In the next year, this project will create data sets that will be used for precision agriculture applications. This last year we used aerial information to better understand yield variability across landscapes. While useful, it did not provide enough information to clearly identify yield limiting factors. This next year, this aerial information will be completed by collecting hyperspectral data from selected on-farm production fields. The hyperspectral scanner will collect information from over 400 bands. We will explore the use of large data analysis techniques to evaluate to ability to use this information to identify the yield limiting factors in these production fields. Funding for the sensor was provided by NSF on a precision farming project. This effort will be combined with efforts to determine the barriers limiting the adoption of precision farming techniques.
On-farm studies provide information that producers use to reduce the economic risks associated with new products, test the efficiency of components within their current operation, and test innovative new ideas and concepts. In the project, a producer chooses his/her treatments based on their interest or desire prior to implementation. SDSU agronomists assist in experimental design, treatment application, scouting, and analysis. At the completion of the project, reports are distributed to the farmer collaborator and they are posted SD Soybean Research and Promotion on-farm web site. Farmers use results from the study to identify treatments that might be success on their farm and reduce the economic risks associated with new products. To date, over 450 experiments have been conducted by SD farmers.

1) Continue the on-farm research program in 2021;
a. Farmers last year were very interested in using UAV as a scouting tool and approximately 30 experiments were conducted. We anticipate that this interest will continue in 2021. Other studies that most likely will continue are the use of new products, treatment of soybeans with rhizobia at V2 to V4, seeding rates, and fertilizer applications.
b. This year we are purchasing a hyperspectral remote sensing scanner that can be placed on a UAV-helicopter. This hyperspectral scanner represents the next generation in sensing and will collect 270 band between 400 (blue) and 1000 nm (near infrared). This sensor will have the capacity to measure subtle changes in reflectance and how stress including diseases and nutrients influences these spectral changes in soybeans.
i. This sensor is being purchased by an associated on-farm study project funded by NSF: Testing a responsible innovation approach for integrating precision agriculture (PA) technologies with future farm workers and work. The collaborating institution with this project is the University of Vermont. This project is determining the human barriers to precision farming adoption and providing funding to purchase equipment hire students that will help identify yield limiting factors.
ii. This sensor and UAV will be used in the on-farm studies next year.
2) Continue research designed to determine the importance of soil health in optimizing soybean yields (partially funded by NRCS and NREC); and
3) Deliver information to producers through Soy100, AgOutlook, SD on-farm web-site, news releases, radio interviews, and SDSU websites.
a. In addition, SDSU students are using data collected in the on-farm studies in several classes.
i. Seniors are using the on-farm studies for their final project in the Agronomy Capstone class (PS475)
ii. Junior and Seniors in the PA Sensor class (PRAG 428) are using data from the soybean on-farm website for their class project report.
iii. The goal of these classes is to help students match solutions to problems and create locally based, flexible, high profit roadmaps, which will be validated in research conducted in producer’s fields when appropriate.

Some the deliverables produced by this paper are short term and some are long term. Short term deliverables include information provided to farmers can use to reduce their costs and improve their profitability and graduating students who have an improved understanding on how to integrate on-farm studies into the decision process. Findings from these studies are shared with the collaborating farmer, and loaded onto the web page that was created in 2016, as quickly as possible. Long-term impacts are improved understanding on how to improve soil health for soybean production and the development of UAV tools that improve our ability to identify yield limiting factors. In addition, this database is being used to train the next generation of agronomists. These agronomists will improve production efficiency for their entire careers. These future agronomists are trained in the SDSU Capstone class, PS475 and Sensor, PRAG 428 where they use the posted experiments to create economic and environmentally sustainable management plans. This year, we will prepare hard copy of reports that will be available at SD Soybeans Research and Promotion headquarters and other farmer events.

Updated February 3, 2022:
See attached report

View uploaded report

Updated February 3, 2022:
See attached report

View uploaded report

Data will be shared with producers through multiple mechanism. First, individualized project reports will be prepared and distributed to the farmer collaborators. Second, reports will be placed on the on-farm web-site. In addition, this year hard copies of these reports will be prepared and distributed through multiple mechanisms including farmer meetings, Soy100, training sessions, summer field tours, and IPM School, In addition, articles will be placed on extension.sdstate.edu, and in newspapers. A majority of the proposed study will take place in farmer fields where we work one on one with individual farmers. The findings will provide unbiased data for SD crop growers.