Optimizing application of image analysis tools to determine physical characteristics of fine roots

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


To understand the vital role of roots in plant growth, it is essential to know the dynamics and distribution of the plant root system. Research in this area has been limited severely by labor intensive techniques used for determination of physical characteristics of roots, especially fine roots. Nowadays, with development of various image analysis applications, it is possible to use methods that speed the process of fine root quantifying and, therefore, allow many more samples to be collected and processed for study. The accuracy of root measurements and time required greatly depend on the capabilities of the image acquisition equipment and the employed root preparation technique. At the same time, the optimal use of image analysis software can improve dramatically both precision and measuring speed. Our objective was to examine some fine root measuring issues common to most image analysis applications. These problems include choosing the proper image resolution, determining the appropriate threshold range and image parameters to measure, as well as reducing the impact of non-root objects on measurement accuracy. Using a numerical example, we describe techniques that can be used to minimize these problems and optimize the precision and accuracy of measurements. Our results suggest that optimal scanning resolution can be determined based on prior determination of root diameter and the minimum root diameter in an image must contain no less than three pixels. We also found that variation in measured root length can by minimized by determining threshold ranges. By applying numerical filters to images, we were able to decrease background noise ; however determination of the optimal filter ranges needed to be performed individually for each application and depend on the size of scanned roots and image resolution. The combined effect of using optimal image resolution, threshold ranges, and numeric filters can increase the efficiency of fine root image analysis in terms of precision and speed.

Original languageEnglish
Pages (from-to)11-20
Number of pages10
JournalEnvironmental Control in Biology
Issue number1
StatePublished - 1 Jan 2006


  • Background noise
  • Fine roots
  • Identification threshold
  • Image analysis
  • Spatial resolution

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Plant Science


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