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Private Applicator Training for Pesticides
Private applicator certification is required before an agricultural producer can purchase or use a restricted use pesticide.
Using Feedlot Manure as a Crop Nutrient Source
Factsheet that reviews the steps to obtain a manure application rate based on crop need, soil and manure testing.
Southeast Research Farm Seminars @ Dakota Farm Show
Join SDSU Extension for a series of educational presentations during the Dakota Farm Show from January 6-7, 2026, at the USD DakotaDome (1101 N Dakota St, Vermillion, SD 57069).
Animal Health & Care
The health and well-being of animals matters to all who care for them.
SDSU Extension helps agritourism producers promote their strengths
January 09, 2026
In 2019, Good Earth Farm owners Nancy and Jeff Kirstein had to make a decision. The barn on their Lennox-based property, originally constructed in 1897, needed attention.
Community Education in South Dakota Schools: Benefits, Strategies, and Opportunities
Three school districts in South Dakota have community education programs. Learn more about the benefits of community education programs and how to support established programs.
Artificial Insemination (AI) Checklist
A checklist to prepare for artificial insemination for cattle.
Range Roundup: Virtual Fencing Project Takes Place at the Cottonwood Field Station
Virtual fencing (borders without physical barriers) has started making waves in the cattle industry, and it can be used to implement precision grazing management. Our team is researching its use and utility at the SDSU Cottonwood Field Station starting this summer.
Range Roundup: Dormant Season Wildfire Project in Northwestern South Dakota
Two of the main environmental conditions that drive post-wildfire rangeland recovery include health of the rangeland ecosystem prior to the wildfire and climatic variables, such as precipitation or drought after the fire event.
Range Roundup: Precision Agriculture Range Project With Producer Participation
SDSU Extension researchers started a new precision agriculture range project using remote sensing, machine learning, and ground-collected vegetation samples to develop an application to measure forage quality and quantity throughout the state in near real-time.