Optimizing digital image analysis to quantify root architectural parameters using thin rhizotrons.

Abstract

Roots grown in small chambers or rhizotrons combined with image analysis could be effective for screening traits of root morphology and architecture prior to field experimentation. The objective of this study was to evaluate and compare digital images of root systems with conventional root scans (RSCN) for several sorghum varieties grown in rhizotrons. Plants were grown in duplicate in slim (1.5‐cm thick) rhizotrons angled 15° to the vertical, filled with sandy topsoil and subsoil at field capacity (FC) or 50% available water content (AWC) in a split‐plot design in a glasshouse (16/24°C). Root growth visible on the glass surface was recorded weekly, and roots were washed out 42 and 90 days after sowing for digital imaging of the root systems on pin boards (PBI). The roots were then sub‐sampled to quantify the baseline root parameters from digital RSCN using WinRhizo® software with a flat‐bed scanner. Rhizotron images revealed little of the root system (1–2%) but PBI “recovered” up to 70% of the total root length (TRL) measured by RSCN. A high a priori image contrast, increased image resolution (9.1–12 megapixels) and optimized contrast threshold between roots and background were the key parameters in quantifying the roots from digital images. PBI revealed significant differences in rooting patterns, especially distribution of root length density (RLD) in the profile, which is useful for selecting varieties with improved resource capture. However, the root diameters estimated in the PBI were significantly larger than those measured by RSCN due to lack of contrast, root clustering and overlay.Not Available