Developing and refining best management practices for optimum yields
Sustainable Production
Field management Nutrient managementSoil healthTillageYield trials
Lead Principal Investigator:
C Gregg Carlson, South Dakota State University
Co-Principal Investigators:
David Clay, South Dakota State University
Sharon Clay, South Dakota State University
Darrell Deneke, South Dakota State University
Ron Gelderman, South Dakota State University
Robert Hall, South Dakota State University
Stephanie Hansen, South Dakota State University
David Horvath, South Dakota State University
Larry Janssen, South Dakota State University
Kurt Reitsma, South Dakota State University
Peter Sexton, South Dakota State University
Jim Stone, South Dakota State University
+10 More
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Brief Project Summary:

Increasing yields in a highly variable environment requires the development of adoptable systems that link advantages in crop genetics with an improved understanding of ecosystems functioning. This project creates a structure where locally-led production and management questions are identified and tested. The project will result in flexible BMPs with a goal of creating a roadmap for reaching a soybean yield of 100 bushels per acre. The project involves both field research and writing a draft for the Soybean BMP manual. The research will be discussed at workshops, presentations and targeted meetings.

Unique Keywords:
#best management practices, #crop management systems, #soybean educational activities, #soybean on-farm research, #soybean production management
Information And Results
Project Deliverables

Final Project Results

Results 1. The Beresford trial was abandoned due to a high degree of experimental error (Coefficient of variation >50%) as the result of a severe drought. At Brookings the yield response to changing plant densities at each maturity group (MG-0, -I, -II) was similar for both row-space treatments with little difference. At Brown County, in the MG-0 trial, the slopes of the regression line yield response of the two row-space treatments to changing plant densities were different. At the lowest plant density the 30-inch rows yielded 2 bu. /acre better than the 8-inch rows. At the highest plant density the 8-inch rows yielded 6 bu. /acre better than the 30-inch rows. In the MG-I trial, the slopes of the regression line yield response of the two row-space treatments to changing plant densities were again different. At the lowest plant density the 30-inch rows yielded 9 bu. /acre better than the 8-inch rows; however, at the highest plant density both row treatments yielded the same. In 2012, the yield response to changing plant densities (slopes) was small in both row-space treatments. Objective 2: Observations of winter rye/forage crop grown after corn and ahead of soybeans. The appears to be potential for producing a rye cover crop or biomass/forage crp after corn and ahead of soybeans. However, much depends on moisture availability and in a drought year soybean yield will suffer unless the rye is killed early. Where drought following the rye biomass crop is a concern, the results of this study suggest that forage sorghum or a surghum/cowpea blend, appear to be lower risk crops than either sunflowers or soybeans. Research Results 1: NO-TILL COVER AND FORAGE DOUBLE CROP SOYBEAN RESEARCH.

The Northeast Research Station had adequate moisture early in the spring; however, after harvesting 13 tons/acre of forage rye off the site, the soil moisture was almost depleted. The double crop soybean yield of 8.7 bushels/acre can be attributed to the subsequent drought in the growing season. The Ben Culver site yielded 52 bushels/acre of soybeans following a harvest of 11 tons/acre of rye forage. A conventional soybean field on one side and a no-till field on the other side of the double cropped site yielded 56 and 57 bushels per acre respectively. At the Jesse Hall site, the soybeans no tilled into rye, winter wheat, and triticale cover crops yielded 49.4, 52.5, and 48.4 bushels per acre respectively; the check yielded 47.1 bushels/acre. An observation at this site was the increase in the number of earth worms in the cover cropped areas compared to the non-cover cropped areas. At the Lon Hall site, double cropped soybeans following foraged rye yielded 44.4 bushels/acre. The check and field (surrounding 74 acres) yields were 38.8 and 46 bushels to the acre respectively. The highest yielding rye forage variety, X79-8, yielded 2.93 tons dry matter per acre. Research Results 2: Variable rate planting of soybeans. Due to lack of moisture in 2012, the Bridgewater site was not analyzed due to lack of sufficient yield data. However the Hayti site provided good information to analyze. Our soybean yields based upon plant population showed interesting results. While we had soybean plant populations from a wide range, very little yield difference was realized. One might conclude based upon figure 2 that variable rate plant populations for soybeans may not be beneficial. When analyzing our individual locations at each site, interesting results were noticed. Economic optimum plant populations for 2012 were sporadic across the plot at Hayti. The economic optimum plant populations at each site were (from north to south) 139059, 105941, 206548, 152470, 202434, and 143381 plants per acre. When comparing the yield data to the shallow electrical conductivity readings in the field, a correlation appears present. This can be explained due to the intolerance of soybeans to grow in areas with higher salts (higher E.C. readings). Economic optimum plant population appears to behave similarly to yield in the presence of electrical conductivity. One could conclude soybeans need salinity to optimize growth, however too much salinity may be detrimental. Based upon yield data from 2012 we can conclude variable rate plant population systems in this particular field would not have been beneficial to soybean production. However, more years of research data are needed to come to a full conclusion. Based upon spatial data correlation, we can conclude shallow E.C. readings may be a good indicator of yield potential at various points within the field. More research will be needed in this area as well to better understand the relationship between economic optimum plant populations in soybeans and yield. Research Results 3: Landscape features impact on soil available water, corn biomass, and gene expression during the late vegetative stage. Crop yields at summit positions of rolling landscapes often are lower than toeslope yields. The differences in plant response may be the result of many different factors. We examined corn (Zea mays) plant productivity and gene expression, as well as soil water and nutrient availability in two landscape positions located in historically high (lower backslope) and moderate (summit/shoulder) yielding zones to gain insight into plant response differences.

Growth characteristics and gene expression and soil parameters (water, N and P content) were determined at theV-12 growth stage of corn. At tassel, plant biomass, N content, and soil water was measured. Soil water at V12 and tasseling was 35% lower when the summit/shoulder compared with the lower backslope. Plants at the summit had 16% less leaf area, biomass, and N and P uptake at V12 and 30% less biomass at tassel compared with plants from the lower backslope. Transcriptome analysis at V12 indicated that summit/shoulder-grown plants had 708 down-regulated and 399 up-regulated genes compared with backslope-grown plants. Gene set and sub-network analyses indicated alterations in growth and circadian response, and lowered nutrient uptake, wound recovery, pest resistance, and photosynthetic capacity in summit/shoulder-grown plants. Reducing plant populations, to lessen demands on available soil water, and applying pesticides, to limit biotic stress, may ameliorate negative water stress responses.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.