Corn Product Characterization: Response to Planting Populations

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Corn Product Characterization Response to Different Planting Populations - 2020

 

 

Trial Objective

 

For over a decade, Bayer has been using an innovative planter technology, the Genotype by Environment Narrative planter (GEN), to help understand and characterize corn product performance in response to plant population and location. This internally-developed tool provides the technical field teams the ability to simultaneously plant multiple corn products at different seeding rates across a field. These unique planting capabilities generate over 100,000 detailed yield observations each season across diverse growing conditions. This program provides data for our agronomy experts to optimize product performance and recommendations for all corn-growing regions in the United States. The objectives of this research were to:

  • Evaluate all new Bayer corn products using seeding rates ranging from 18,000 to 50,000 seeds/acre across multiple locations in the United States.

  • Provide growers with product-specific planting recommendations.

  • Assess new products in as many yield environments as possible over a two-year period.

  • Provide growers with insight for their specific situation and the product they selected.

 

Research Details

 
  • This research included 123 testing locations across the United States.
  • The products tested were selected by the regional field teams as important in that geography.
  • Testing locations targeted diverse environments (yield environment, crop rotation, tillage practice, etc.).
  • Agronomic management practices used in this study mimicked local best management practices.
  • Products tested were both first-year commercial and pre-commercial corn products.  
  • The experimental design was a split-plot randomized complete block (RCB) with 2 replications. Corn product was the main plot and seeding rate was the sub plot.
  • Small plots were used: four 35-foot rows per plot with a row width of 30 inches.
  • Seeding rates were as follows:  
    • Low-yielding acres: 18,000, 24,000, 28,000, 32,000, 38,000, and 44,000 seeds/acre
    • High-yielding acres: 24,000, 32,000, 36,000, 40,000, 44,000, and 50,000 seeds/acre

 

Understanding the Results

 
 
  • Product-specific data on the response to plant population allows for customized recommendations for new corn products specific for a grower’s geography. 

  • Multiple years of data allow agronomists to determine the influence of weather on corn product performance. This adds to the robustness of the recommendations generated in this system. 

  • The relative responsiveness of a product to plant population can change depending on the yield environment and management. 

Corn Product Characterization: Response to Different Planting Populations - 2019

 

 

Trial Objective

 

For over a decade, Bayer has been using an innovative planter technology, the Genotype by Environment Narrative planter (GEN), to help understand and characterize corn product performance in response to plant population and environment. This internally-developed tool provides the technical field teams the ability to simultaneously plant multiple corn products at different seeding rates across a field. These unique planting capabilities generate over 100,000 detailed yield observations each season across diverse growing conditions. This program provides data for our agronomy experts to optimize product performance and recommendations for all corn-growing regions in the United States. The objectives of this research were to:

  • Evaluate all new Bayer corn products using seeding rates ranging from 18,000 to 50,000 seeds/acre across multiple locations in the United States.
  • Provide growers with product-specific planting recommendations.
  • Assess new products in as many yield environments as possible over a two-year period.   
  • Provide growers with insight for their specific situation and the product they selected.

 

Research Details

 
  • Approximately 125 testing locations across the U.S. were used.
  • Products were tested that are targeted by the regional field teams as important in that geography. 
  • Testing locations were selected to target diverse environments (yield environment, crop rotation, tillage practice, etc.).
  • Agronomic management practices used in this study mimicked local best management practices. 
  • Products tested were both first-year commercial and pre-commercial corn products. 
  • The experimental design was a split-plot RCB with 2 replications. Corn hybrid = main plot; Seeding rate = sub plot.
  • Small plots were used: four 35-foot rows per plot with a row width of 30 inches. 
  • Seeding rates were as follows: 
    • Low-yielding acres: 18,000, 28,000, 32,000, 36,000, 40,000, and 48,000 seeds/acre
    • High-yielding acres: 24,000, 32,000, 36,000, 40,000, 44,000, and 50,000 seeds/acre

 

Understanding the Results

 

  • Product-specific data on the response to plant population allows for customized recommendations for new corn products specific to a yield environment.
  • Multiple years of data allow agronomists to determine the influence of weather on corn product performance. This adds to the robustness of the recommendations generated in this system.
  • The relative responsiveness of a product to plant population can change depending on the yield environment and management.

 

Key Learnings   

 

The information generated in this program drives innovation within Bayer while it provides data to the farmers who rely on our premium genetics to deliver top yields. The data that these trials generate help growers optimize product placement and seeding rates of Bayer corn products to maximize the return on their investment in our corn products. 

  • Consult with your Technical Agronomist, who has access to this data, early in the year for information on the performance of all our newest products.

  • Visit the population optimizer tool for seeding rate recommendations for your region. 

  • Visit Climate FieldView™ seed scripts at https://climate.com/2020-seed-scripts to see how this data is being used to develop specific corn product recommendations. Pairing the product-level seeding rate characterization with the specific agronomic environment of your operation can optimize your system.

 
 
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