How to Measure Leaf Disease Damage Using Image Analysis in ImageJ

An example of image processing techniques for image-based quantification of leaf disease damage using ImageJ.

This new 13-page article introduces simple image processing and analysis techniques to quantify leaf disease damage using ImageJ, an open-source image processing program. These techniques are not meant to replace crop scouting or disease diagnosis by a plant diagnostic laboratory, but rather to provide a supplemental tool for making quantitative measurements of leaf disease damage. Similar techniques are also available for plant growth assessment, including plant height, plant width, and canopy cover area. The image processing and analysis techniques introduced in this article are fairly simple to use and thus can be adopted not only by researchers, but also by producers, crop consultants, Extension agents, and students. Written by Lillian Pride, Gary Vallad, and Shinsuke Agehara, and published by the UF/IFAS Horticultural Sciences Department.

Simple Imaging Techniques for Plant Growth Assessment

Overhead canopy images of various crops converted to binary images using ImageJ for canopy cover measurements.

Quantification of plant phenotypic traits, such as height, width, stem diameter, and leaf area, is often performed manually in the field; however, these measurements can be performed more quickly and precisely through simple imaging techniques using an image processing program. This new 5-page publication of the UF/IFAS Horticultural Sciences Department, written by Shinsuke Agehara, describes simple imaging techniques for plant growth assessment using the public domain program ImageJ.