Systematic optimization of yield-enhancing applications in soybeans - Haverkamp, Bryson (Kansas State University, 2015)
High soybean [Glycine max.] commodity prices in recent years have led to an increase in use of yield enhancing and protecting products. These products need to be evaluated to determine if the use of multiple inputs has a positive impact on yield and how these inputs interact with agronomic practices. The objectives of this study were to evaluate products individually and collectively in input systems, examine interactions between varieties and input systems (IS), seeding rates (SR) and IS, and row spacing (RS) and IS. Field experiments were conducted at high-yielding locations in Kansas and Minnesota in 2012 to 2014 to meet these objectives. Sixteen treatments consisting of individual inputs and inputs combined in systems were evaluated in one experiment. A second experiment evaluated the variety by IS interaction by constructing 18 treatments from a factorial combination of six glyphosate [N-(phosphonomethyl) glycine] resistant varieties and three IS’s: untreated control (UTC), SOYA (combination of possible yield-enhancing products representative of those currently being marketed), and SOYA minus foliar fungicide (SOYA – foliar F). A third experiment evaluated the SR by IS interaction by constructing 12 treatments from a factorial arrangement of six SR’s and two IS’s: UTC and SOYA. A fourth experiment evaluated the RS by IS interaction by constructing 12 treatments from a factorial arrangement of three RS’s and four IS’s: UTC, fungicide and insecticide seed treatment plus foliar fungicide (STFF), SOYA, and SOYA – foliar F. Very few interactions between IS and agronomic practices were detected in any of the experiments. Varieties had an effect on multiple growth parameters but yield differences were marginal; linear-plateau and non-linear models found that seeding rates that maximized yield in this study were similar to University recommendations; and in general, narrow rows produced the greatest yields. The use of inputs and IS’s typically increased seed mass and yield above the UTC across all experiments. However, given current costs and soybean prices, yield response to IS’s was not great enough to cover the additional costs. Overall, it appears producers would be better served by focusing on agronomic practices rather than implementing input systems.
Keywords: Soybeans; Row spacing; Inputs; Agronomic practices; NDVI; Canopy coverage; Agronomy (0285)