Quantification of plant morphology and leaf thickness with optical coherence tomography

Journal Article (2020)
Author(s)

Jos de Wit (TU Delft - ImPhys/Computational Imaging)

Sebastian Tonn (Universiteit Utrecht)

Guido Van den Ackerveken (Universiteit Utrecht)

J Kalkman (TU Delft - ImPhys/Computational Imaging)

Research Group
ImPhys/Computational Imaging
Copyright
© 2020 J. de Wit, Sebastian Tonn, Guido van den Ackerveken, J. Kalkman
DOI related publication
https://doi.org/10.1364/AO.408384
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 J. de Wit, Sebastian Tonn, Guido van den Ackerveken, J. Kalkman
Related content
Research Group
ImPhys/Computational Imaging
Issue number
33
Volume number
59
Pages (from-to)
10304-10311
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Abstract

Optical coherence tomography (OCT) can be a valuable imaging tool for in vivo and label-free digital plant phenotyping. However, for imaging leaves, air-filled cavities limit the penetration depth and reduce the image quality. Moreover, up to now quantification of leaf morphology with OCT has been done in one-dimensional or two-dimensional images only, and has often been limited to relative measurements. In this paper, we demonstrate a significant increase in OCT imaging depth and image quality by infiltrating the leaf air spaces with water. In the obtained high-quality OCT images the top and bottom surface of the leaf are digitally segmented. Moreover, high-quality en face images of the leaf are obtained from numerically flattened leaves. Segmentation in three-dimensional OCT images is used to quantify the spatially resolved leaf thickness. Based on a segmented leaf image, the refractive index of an infiltrated leaf is measured to be 1.345 ± 0.004, deviating only 1.2% from that of pure water. Using the refractive index and a correction for refraction effects at the air-leaf interface, we quantitatively mapped the leaf thickness. The results show that OCT is an efficient and promising technique for quantitative phenotyping on leaf and tissue level.

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