Development of Analytical Model to Describe Reflectance Spectra in Leaves with Palisade and Spongy Mesophyll

Remote sensing plays an important role in plant cultivation and ecological monitoring. This sensing is often based on measuring spectra of leaf reflectance, which are dependent on morphological, biochemical, and physiological characteristics of plants. However, interpretation of the reflectance spectra requires the development of new tools to analyze relations between plant characteristics and leaf reflectance. The current study was devoted to the development, parameterization, and verification of the analytical model to describe reflectance spectra of the dicot plant leaf with palisade and spongy mesophyll layers (on the example of pea leaves). Four variables (intensities of forward and backward collimated light and intensities of forward and backward scattered light) were considered. Light reflectance and transmittance on borders of lamina (Snell's and Fresnel's laws), light transmittance in the palisade mesophyll (Beer-Bouguer-Lambert law), and light transmittance and scattering in the spongy mesophyll (Kubelka-Munk theory) were described. The developed model was parameterized based on experimental results (reflectance spectra, contents of chlorophylls and carotenoid, and thicknesses of palisade and spongy mesophyll in pea leaves) and the literature data (final R<sup>2</sup> was 0.989 for experimental and model-based reflectance spectra). Further model-based and experimental investigations showed that decreasing palisade and spongy mesophyll thicknesses in pea leaves (from 35.5 to 25.2 µm and from 58.6 to 47.8 µm, respectively) increased reflectance of green light and decreased reflectance of near-infrared light. Similarity between model-based and experimental results verified the developed model. Thus, the model can be used to analyze leaf reflectance spectra and, thereby, to increase efficiency of the plant remote and proximal sensing.

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Publication Details

Journal
Plants
Published
2024-11-20
DOI
https://doi.org/10.3390/plants13223258
Citations
5
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
2.29

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article

Development of Analytical Model to Describe Reflectance Spectra in Leaves with Palisade and Spongy Mesophyll

Kseniya Grebneva, Daria Ratnitsyna, Yuriy Zolin, Oleg O. Bondarev et al.
5 citations
Plants
Remote Sensing in Agriculture
2.29
article

Development of Analytical Model to Describe Reflectance Spectra in Leaves with Palisade and Spongy Mesophyll

Kseniya Grebneva, Daria Ratnitsyna, Yuriy Zolin, Oleg O. Bondarev, Lyubov Yudina, Ekaterina Berezina, Anastasiia Kior, Vladimir Sukhov, Ekaterina Sukhova, Alyona Popova
article en
5 citations

Abstract

Remote sensing plays an important role in plant cultivation and ecological monitoring. This sensing is often based on measuring spectra of leaf reflectance, which are dependent on morphological, biochemical, and physiological characteristics of plants. However, interpretation of the reflectance spectra requires the development of new tools to analyze relations between plant characteristics and leaf reflectance. The current study was devoted to the development, parameterization, and verification of the analytical model to describe reflectance spectra of the dicot plant leaf with palisade and spongy mesophyll layers (on the example of pea leaves). Four variables (intensities of forward and backward collimated light and intensities of forward and backward scattered light) were considered. Light reflectance and transmittance on borders of lamina (Snell's and Fresnel's laws), light transmittance in the palisade mesophyll (Beer-Bouguer-Lambert law), and light transmittance and scattering in the spongy mesophyll (Kubelka-Munk theory) were described. The developed model was parameterized based on experimental results (reflectance spectra, contents of chlorophylls and carotenoid, and thicknesses of palisade and spongy mesophyll in pea leaves) and the literature data (final R<sup>2</sup> was 0.989 for experimental and model-based reflectance spectra). Further model-based and experimental investigations showed that decreasing palisade and spongy mesophyll thicknesses in pea leaves (from 35.5 to 25.2 µm and from 58.6 to 47.8 µm, respectively) increased reflectance of green light and decreased reflectance of near-infrared light. Similarity between model-based and experimental results verified the developed model. Thus, the model can be used to analyze leaf reflectance spectra and, thereby, to increase efficiency of the plant remote and proximal sensing.

PlantsVol. 13(22)
N. I. Lobachevsky State University of Nizhny Novgorod (RU)
Russian Science Foundation
Life in Land
Openalex Percentile: Top 12%
Remote Sensing in Agriculture
2.29
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