Abstract—Accurate and timely assessment of the
physiological status of plants is crucial for resource optimization
and minimizing environmental impact in ecological monitoring
and agriculture. This study introduces a novel technique for
mapping pigment concentrations in plant leaves using
multispectral imaging. The key innovation of the proposed
approach is a multispectral camera equipped with
reconfigurable spectral filters, enabling application-specific
data acquisition. Combined with a data processing protocol, the
system achieves high measurement accuracy of leaf pigment
content even with limited spectral channels. The technique
includes camera calibration, spatiospectral correction, spectral
index selection, and nonlinear regression to develop empirical
models for estimating chlorophyll concentration. Validation
experiments on proximal sensing of lettuce (Lactuca sativa)
demonstrated that the ratio of Modified Chlorophyll Absorption
Ratio Index to Optimized Soil Adjusted Vegetation Index
achieved the best performance, with an R² of 0.81, an RMSE of
0.3 mg/L, and relative error of less than 20%. Limitations
include residual shading and interpolation artifacts, which
suggest opportunities for further improvement. The findings
highlight high potential of this technique for noninvasive and
high-throughput monitoring of plant health in both ecological
and agricultural contexts.
Keywords—precision agriculture, remote sensing, pigment
content mapping, spectral indices, multispectral imaging
Cite: Anastasia A. Zolotukhina, Anastasia V. Guryleva, Sergey S. Ladan, Oksana A. Gusarova, and Alexander S. Machikhin, "High-throughput Mapping of Leaf Pigment Content from Multispectral Data," International Journal of Environmental Science and Development vol. 17, no. 1, pp. 48-55, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).