125-10 Multispectral Canopy Reflectance Measurements and Digital Imaging to Determine Soybean Maturity.

Poster Number 227

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Applied Soybean Research: II

Monday, November 16, 2015
Minneapolis Convention Center, Exhibit Hall BC

Brandon Davis, University of Missouri, Columbia, MO
Poster Presentation
  • Brandon_Multispectral poster 2.0 without logos.pdf (1.5 MB)
  • Abstract:
    In-field phenotyping can be time consuming and costly.  Multispectral imaging may provide a quick means to quantitatively measure developmental stages of soybean.  In 2014, three soybean maturity groups (MG) 3, 4, and 5, each with two cultivars and two planting dates were examined at the University of Missouri Lee Farm near Portageville and Bradford Research Center near Columbia, MO.  Canopy reflectance measurements of the red (670nm), near infrared (NIR, 780nm), and red edge (730nm) wavelengths were taken weekly using a Holland Scientific Rapidscan.  These measurements were used to determine the normalized difference vegetation index (NDVI) and the normalized difference red edge index (NDRE).  The NDVI increased gradually until mid-flowering, remained relatively stable until past full pod, and declined rapidly as soybeans approached physiological maturity. Unlike NDVI, the NDRE index continued to increase past mid flowering until mid pod fill, and decreased gradually after full pod.  Visible images were taken with an off-the-shelf digital camera to measure canopy development and to derive a dark green color index (DGCI).  The DGCI increased in a manner similar to NDRE and decreased similarly to NDVI.  Initial analyses indicate that the multispectral reflectance indexes and digital imaging, individually and in concert, can be used to discriminate between key soybean developmental stages and may hold promise for high throughput phenotyping.

    See more from this Division: ASA Section: Agronomic Production Systems
    See more from this Session: Applied Soybean Research: II