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This article in AJ

  1. Vol. 103 No. 2, p. 529-535
     
    Received: July 2, 2010
    Published: Mar, 2011


    * Corresponding author(s): lpurcell@uark.edu
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doi:10.2134/agronj2010.0296

Association of “Greenness” in Corn with Yield and Leaf Nitrogen Concentration

  1. Robert L. Roriea,
  2. Larry C. Purcell *a,
  3. Morteza Mozaffarib,
  4. Douglas E. Karcherc,
  5. C. Andy Kinga,
  6. Matthew C. Marsha and
  7. David E. Longera
  1. a Dep. of Crop, Soil, and Environmental Sciences, Univ. of Arkansas, 1366 W. Altheimer Dr., Fayetteville, AR 72704
    b Dep. of Crop, Soil, and Environmental Sciences, Univ. of Arkansas Soil Testing and Research Lab at Marianna, P.O. Drawer 767, Marianna, AR 72360
    c Dep. of Horticulture, Plant Science Bldg., Univ. of Arkansas, Fayetteville, AR 72701

Abstract

Efficient use of N fertilizer has become crucial due to fertilizer costs and the impact of excessive N on the environment. Diagnostic tools for estimating plant N status have an important role in reducing N inputs while maintaining yield. The objective of our study was to quantify corn (Zea mays L.) leaf greenness with a digital camera and image-analysis software and establish the relationship with yield, leaf N concentration, and chlorophyll meter (or SPAD, soil plant analysis development) values. In 2008 and 2009, field experiments were conducted at five sites with N treatments ranging from 0 to 336 kg N ha−1 At tasseling, the ear leaf was sampled for color analysis and SPAD measurements, and then analyzed for total N. Hue, saturation, and brightness (HSB) values from digital images were processed into a dark green color index (DGCI), which combines HSB values into one composite number. Including calibration disks in images and changing the background color in photographs to pink greatly improved DGCI precision in 2009 over 2008. There was a close relationship (typically r 2 ≥ 0.70) of SPAD and DGCI with leaf N concentration. Within a location, yield increased linearly in most cases with both SPAD (average r 2 = 0.79) and DGCI (average r 2 = 0.78). Digital-image analysis was a simple method of determining corn N status that has potential as a diagnostic tool for determining crop N needs.

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Copyright © 2011. American Society of AgronomyCopyright © 2011 by the American Society of Agronomy