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Agronomy Journal Abstract - Crop Economics, Production & Management

Evaluating Management Factor Contributions to Reduce Corn Yield Gaps

 

This article in AJ

  1. Vol. 107 No. 2, p. 495-505
    unlockOPEN ACCESS
     
    Received: July 10, 2014
    Accepted: Oct 25, 2014
    Published: January 5, 2015


    * Corresponding author(s): fbelow@illinois.edu
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doi:10.2134/agronj14.0355
  1. Matias L. Ruffoa,
  2. Laura F. Gentryb,
  3. Adam S. Henningerc,
  4. Juliann R. Seebauerd and
  5. Frederick E. Below *d
  1. a Bioceres Semillas, Santa Fe, Argentina
    b Illinois Corn Growers Assn., Urbana, IL
    c Monsanto, Rushville, IL
    d Crop Sciences Dep., Univ. of Illinois, Urbana, IL 61801-4730

Abstract

The need to intensify agricultural production due to a growing human population requires yield gaps to be closed. In 2009 and 2010, five management factors were assessed for their individual and cumulative contributions to reducing the corn (Zea mays L.) yield gap and yield components in a corn–soybean [Glycine max (L.) Merr.] rotation. Five management factors (plant population, transgenic insect resistance, fungicide containing strobilurin, P–S–Zn fertility, and N fertility) were evaluated. An incomplete factorial design with these factors resulted in 12 treatments, including two controls: high technology (HT) and standard technology (ST), comprising all five factors applied at the supplemental or the standard level, respectively. The HT control yielded 2.9 Mg ha−1 (2.12–3.50 Mg ha−1 across sites and years) more grain (28%) than the ST control, demonstrating the yield gap between traditional farm practice and attainable yield using available technologies. All management factors except plant population were necessary for reducing the yield gap. Fungicide and Bacillius thuringiensis gene (Bt) traits provided the greatest yield increases compared to the ST system. Averaged over sites and years, if each factor was withheld from the HT system, yield decreased by decreasing kernel number. Increased plant population reduced the yield gap when all other inputs were applied at the supplemental level. Kernel number was more significant for increasing yield than kernel weight. The yield contribution of each factor was greater when applied as part of a full complement of supplemental inputs than when added individually to the standard input system.

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