Economic advantage to fungicidal products
Sustainable Production
Abiotic stressField management SustainabilityWater supply
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Kurt Turner, South Dakota State University
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

The research involves applying various fungicides to soybeans at the R2 growth stage. Yield will be reported for the various brand named and generic products.

Unique Keywords:
#biomediation, #water quality & management, #watershed water quality
Information And Results
Project Deliverables

Objective1?SDSU soybean CPT data for yield from 2001 to 2009 were provided by Dr. Robert Hall. Since some genotypes (cultivars) were not repeated in all locations every year and only a few cultivars were common between years, we analyzed these data by mixed linear model approaches from year to year.
Objective 2: Fifteen cultivars obtained from three different seed companies were grown in six locations in Eastern South Dakota. These six locations included: South East farm (2011 and 2012), Brookings (2011 and 2012), North East farm (2011 and 2012), Bancroft (2011 and 2012), Geddes (2011 and 2012), Warner (2011), and Bath (2012), where Warner and Bath are near each other. A randomized complete block design with three replications in each location was employed. Seed yield and protein and oil contents have been collected for two both years. In addition, yield components including pod number per plant, seed number per pod, and seed index were measured for all 12 environments.
We analyzed the data with different approaches: (1) environment-wide correlation analysis; (2) variance component analysis with mixed linear model approaches; (3) conditional variance component analysis with mixed linear model analysis; and (4) both conventional and conditional stability analysis.

Final Project Results

For Objective 1: Based on our nine years data analyses, we have the following conclusions:
(1) Environmental (location) conditions played the largest role on yield (33~91%).
(2) Seed providers had significant but small impact on soybean yield production (0.4~14.7%).
(3) Differences among cultivars were important but not as environmental conditions (1~17%).
(4) Genotype-by-location interactions had some impacts on yield production, but not very large (2~23%).
For Objective 2, we found that correlation patterns between yield and agronomic traits varied among locations for both years, indicating that soybean yield production are related to different phenotypic traits. For example, plant height and biomass are more related to high yield in low yielding areas while yield components are more related to yield under high yielding environments. Stability analyses also showed the similar conclusion. Thus, based on our investigation, we conclude that phenotyping breeding should be considered to optimize soybean production in both low yielding and high yielding environments in South Dakota.

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.