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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 2 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.

Approaches for remote sensing can be used to estimate the influence of changes in environmental conditions on terrestrial plants, providing timely protection of their growth, development, and productivity. Different optical methods, including the informative multispectral and hyperspectral imaging of reflected light, can be used for plant remote sensing; however, multispectral and hyperspectral cameras are technically complex and have a high cost. RGB imaging based on the analysis of color images of plants is definitely simpler and more accessible, but using this tool for remote sensing plant characteristics under changeable environmental conditions requires the development of methods to increase its informativity. Our review focused on using RGB imaging for remote sensing the characteristics of terrestrial plants. In this review, we considered different color models, methods of exclusion of background in color images of plant canopies, and various color indices and their relations to characteristics of plants, using regression models, texture analysis, and machine learning for the estimation of these characteristics based on color images, and some approaches to provide transformation of simple color images to hyperspectral and multispectral images. As a whole, our review shows that RGB imaging can be an effective tool for estimating plant characteristics; however, further development of methods to analyze color images of plants is necessary.

In environmental conditions, plants can be affected by the action of numerous abiotic stressors. These stressors can induce both damage of physiological processes and adaptive changes including signaling-based changes. Development of optical methods of revealing influence of stressors on plants is an important task for plant investigations. The photochemical reflectance index (PRI) based on plant reflectance at 531 nm (measuring wavelength) and 570 nm (reference wavelength) can be effective tool of revealing plant stress changes (mainly, photosynthetic changes); however, its efficiency is strongly varied at different conditions. Earlier, we proposed series of modified PRIs with moderate shifts of the measuring wavelength and showed that these indices can be effective for revealing photosynthetic changes under fluctuations in light intensity. The current work was devoted to the analysis of sensitivity of these modified PRIs to action of drought and short-term heat stress. Investigation of spatially-fixed leaves of pea plants showed that the modified PRI with the shorter measuring wavelength (515 nm) was increased under response of drought and heat; by contrast, the modified PRI with the longer wavelength (555 nm) was decreased under response to these stressors. Changes of investigated indices could be related to parameters of photosynthetic light reactions; however, these relations were stronger for the modified PRI with the 555 nm measuring wavelength. Investigation of canopy of pea (vegetation room) and wheat (vegetation room and open-ground) supported these results. Thus, moderate changes in the measuring wavelengths of PRI can strongly modify the efficiency of their use for the estimation of plant physiological changes (mainly photosynthetic changes) under action of stressors. It is probable that the modified PRI with the 555 nm measuring wavelength (or similar indices) can be an effective tool for revealing photosynthetic changes induced by stressors.

Natural and artificial extremely low-frequency magnetic fields (ELFMFs) are important factors influencing physiological processes in living organisms including terrestrial plants. Earlier, it was experimentally shown that short-term and long-term treatments by ELFMFs with Schumann resonance frequencies (7.8, 14.3, and 20.8 Hz) influenced parameters of photosynthetic light reactions in wheat leaves. The current work is devoted to an analysis of potential ways of this ELFMF influence on the light reactions. Only a short-term wheat treatment by 14.3 Hz ELFMF was used in the analysis. First, it was experimentally shown that ELFMF-induced changes (an increase in the effective quantum yield of photosystem II, a decrease in the non-photochemical quenching of chlorophyll fluorescence, a decrease in time of changes in these parameters, etc.) were observed under the action of ELFMF with widely ranging magnitudes (from 3 to 180 µT). In contrast, the potential quantum yield of photosystem II and time of relaxation of the energy-dependent component of the non-photochemical quenching were not significantly influenced by ELFMF. Second, it was shown that the ELFMF treatment decreased the proton gradient across the thylakoid membrane. In contrast, the H + conductivity increased under this treatment. Third, an analysis of the simplest mathematical model of an H + transport across the thylakoid membrane, which was developed in this work, showed that changes in H + fluxes related to activities of the photosynthetic electron transport chain and the H + -ATP synthase were not likely a mechanism of the ELFMF influence. In contrast, changes induced by an increase in an additional H + flux (probably, through the proton leakage and/or through the H + /Ca 2+ antiporter activity in the thylakoid membrane) were in good accordance with experimental results. Thus, we hypothesized that this increase is the mechanism of the 14.3 Hz ELFMF influence (and, maybe, influences of other low frequencies) on photosynthetic light reactions in wheat.