Title
Digital image correlation for full-field high resolution assessment of leaf growth Digital image correlation for full-field high resolution assessment of leaf growth
Author
Faculty/Department
Faculty of Sciences. Physics
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
New York ,
Subject
Biology
Source (journal)
Journal of plant growth regulation. - New York
Volume/pages
34(2015) :2 , p. 433-439
ISSN
0721-7595
ISI
000355220200020
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Changes in shape and size of the leaves are driven by several transient growth parameters. Being able to assess resulting changes at a high temporal and spatial resolution is a necessary tool for studying biochemical principles of leaf development, and for construction of leaf growth models. In this short communication, a technique based on the use of 2D digital image correlation (DIC) is presented to track leaf growth. A speckle pattern with orange fluorescent paint was applied on three leaves of the sycamore maple (Acer pseudoplatanus) at an arbitrary point in growth. For ten consecutive days, images of the growing leaves were analyzed with DIC, revealing leaf growth patterns. The patterns were similar for three leaves, and results corresponded both with literature data of leaf growth and with leaf area measurements using manual segmentation of leaf images. We demonstrate that DIC can be applied for tracking leaf growth. Based on the results, a detailed macro-model for leaf growth can be developed or environmental effects on leaf growth can be assessed, amongst other possible applications.
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