Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography

Tulsi Anna*, Sandeep Chakraborty, Chia Yi Cheng, Vishal Srivastava, Arthur Chiou, Wen Chuan Kuo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Leaf senescence provides a unique window to explore the age-dependent programmed degradation at organ label in plants. Here, spectral domain optical coherence tomography (SD-OCT) has been used to study in vivo senescing leaf microstructural changes in the deciduous plant Acer serrulatum Hayata. Hayata leaves show autumn phenology and change color from green to yellow and finally red. SD-OCT image analysis shows distinctive features among different layers of the leaves; merging of upper epidermis and palisade layers form thicker layers in red leaves compared to green leaves. Moreover, A-scan analysis showed a significant (p < 0.001) decrease in the attenuation coefficient (for wavelength range: 1100–1550 nm) from green to red leaves. In addition, the B-scan analysis also showed significant changes in 14 texture parameters extracted from second-order spatial gray level dependence matrix (SGLDM). Among these parameters, a set of three features (energy, skewness, and sum variance), capable of quantitatively distinguishing difference in the microstructures of three different colored leaves, has been identified. Furthermore, classification based on k-nearest neighbors algorithm (k-NN) was found to yield 98% sensitivity, 99% specificity, and 95.5% accuracy. Following the proposed technique, a portable noninvasive tool for quality control in crop management can be anticipated.

Original languageEnglish
Article number1167
JournalScientific reports
Volume9
Issue number1
DOIs
StatePublished - 1 Dec 2019

Fingerprint

Dive into the research topics of 'Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography'. Together they form a unique fingerprint.

Cite this