Date of Award
Master of Science (MS)
Plant and Environmental Science
Michael T. Plumblee
Jeremy K. Greene
Kendall R. Kirk
John D. Mueller
The adoption of precision agriculture technologies and developing specific product use recommendations in cotton and soybean production could help farmers reduce input costs and optimize overall farm profitability. The objectives of this research were to evaluate whether or not the use of variable rate seeding in cotton could increase profitability and to determine the rainfast interval of commonly used insecticides in cotton and soybean production. The first trial, variable rate seeding in cotton, was implemented at the Edisto Research and Education Center near Blackville, SC across five years to evaluate variable rate seeding in cotton. Results from trials in South Carolina across five years to compare variable rate seeding with six different uniform seeding rates indicated that using variable rate seeding in did not appear to improve overall profitability over the optimum uniform seeding rate, but more data are needed with the strategy under variable circumstances (additional varieties, irrigation versus dryland, etc.) to test the reliability of the approach.
The second trial, insecticide efficacy at various washoff intervals, was evaluated in cotton and soybean at the Edisto REC in 2021 and 2022. After various intervals of simulated rainfall events (ranging from < 0.5 hour up to 24 hours after application of insecticide), the contact efficacy of selected insecticides against numerous important insect species in cotton and soybeans was minimally reduced, suggesting that commonly used insecticides can have a short rainfast interval (< 0.5 hour) in the crops. These results should caution against the common practice of automatic reapplication of insecticide following a rainfall event and encourage an assessment of insect control before retreatment, potentially reducing input costs.
Smith, Kyle, "Precision Management of Inputs in Cotton and Soybean Production in South Carolina" (2023). All Theses. 3974.