rus
Issue #4/2024
. N. Baranova, O. V. Shelepova, A. A Zolotukhina, G. V. Nesterov, K. A. Sudarikov, V. V. Latushkin, A. A. Gulevich
Application of Optical Methods to Assess Physiological Damage to Wheat Flag Leaves
Application of Optical Methods to Assess Physiological Damage to Wheat Flag Leaves
DOI: 10.22184/1993-7296.FRos.2024.18.4.320.330
The study explores the possibility of using hyperspectral imaging and RGB photography as a fast and reliable method for determining the chlorophyll content to assess the state of the photosynthetic apparatus. The results of an evaluation of the relationships between the spectral characteristics of the flag leaves reflectivity of wheat, the characteristics of their color and chlorophyll content under conditions of the presence and absence of flooding are presented. It has been revealed that the most accurate assessment of the state of plants can be derived based on the NDVI705 vegetation index obtained by hyperspectral data processing.
The study explores the possibility of using hyperspectral imaging and RGB photography as a fast and reliable method for determining the chlorophyll content to assess the state of the photosynthetic apparatus. The results of an evaluation of the relationships between the spectral characteristics of the flag leaves reflectivity of wheat, the characteristics of their color and chlorophyll content under conditions of the presence and absence of flooding are presented. It has been revealed that the most accurate assessment of the state of plants can be derived based on the NDVI705 vegetation index obtained by hyperspectral data processing.
Теги: chlorophyll content flag leaf hyperspectral imaging image processing vegetation indices wheat вегетационные индексы гиперспектральная съемка обработка изображений пшеница содержание хлорофиллов флаговый лист
Application of Optical Methods to Assess Physiological Damage to Wheat Flag Leaves
E. N. Baranova 1, 2, 3, 4, O. V. Shelepova 2, A. A Zolotukhina 5, G. V. Nesterov 5, K. A. Sudarikov 4, V. V. Latushkin 4, A. A. Gulevich 1
All-Russia Research Institute of Agricultural Biotechnology, Moscow, Russia
N. V. Tsitsin Main Botanical Garden of Russian Academy of Sciences, Moscow, Russia
Moscow Timiryazev Agricultural Academy Russian State Agrarian University, Moscow, Russia
Institute of Development Strategy, Moscow, Russia
Scientific and Technological Centre of Unique Instrumentation of the Russian Academy of Sciences, Moscow, Russia
The study explores the possibility of using hyperspectral imaging and RGB photography as a fast and reliable method for determining the chlorophyll content to assess the state of the photosynthetic apparatus. The results of an evaluation of the relationships between the spectral characteristics of the flag leaves reflectivity of wheat, the characteristics of their color and chlorophyll content under conditions of the presence and absence of flooding are presented. It has been revealed that the most accurate assessment of the state of plants can be derived based on the NDVI705 vegetation index obtained by hyperspectral data processing.
Keywords: hyperspectral imaging, vegetation indices, image processing, chlorophyll content, flag leaf, wheat
Article received: 01.04.2024
Article accepted: 18.04.2024
Introduction
Crop growth conditions are determined by the relationship between plant physiological processes and environmental factors such as solar radiation, temperature, water and mineral nutrients availability. A number of studies have shown the possibility of assessing the crop performance based on measuring the chlorophyll content in leaves at certain stages of crop development [1, 2]. The content of photosynthetic pigments closely correlates with the physiological state of the plant and its productivity. At the initial stages of stress, changes in chlorophyll content in plants may be insignificant, but as stress intensity increases, its content decreases more rapidly than other pigments. The flag leaves of wheat represent the main photosynthetic tool that provides nutrition and filling of the ear after fertilization. For this reason, disturbances in the formation of this leaf at such transition stages as booting and heading, as well as flowering, can significantly limit the productivity of wheat plants [3]. The state of the photosynthetic system and its productivity are most clearly identified by the number and ratio of pigments that ensure the efficient operation of converting light energy into chemical energy and located in the lamellar membranes of chloroplasts.
The laboratory method for measuring the concentration of chlorophyll in plant leaves, based on spectrophotometry [4, 5] is the gold standard in characterizing the condition and diagnosing damage to the photosynthetic apparatus. However, due to the need for sample preparation, it is very labor-intensive, time- and resource-consuming, and is also limited in the ability to determine the spatial distribution of pigment content in the field. Currently, alternative non-invasive methods for monitoring the physiological state of plants using hyperspectral and multispectral imaging have been proposed [6, 7]. To reduce hyperspectral data, vegetation indices were proposed [8], which are a mathematical combination of the reflectivity of plants in the spectral ranges most sensitive to pigment content. However, most of these indices were developed for dicotyledonous plants, and to a lesser extent tested on monocots, in particular, wheat. The most accessible option for multispectral imaging is the registration, processing and interpretation of RGB images [9, 10] in order to assess the color characteristics of vegetation.
The aim of this study was to compare the efficiency of determining the chlorophyll content in wheat flag leaves using hyperspectral and RGB imaging. For this purpose, a correlation analysis of the relationship between the color characteristics, the spectral reflectance of the samples and the content of pigments in them, obtained using spectrophotometric analysis, were carried out.
Materials and Methods
Plant Material
Durum spring wheat plants of the cultivar Orenburgskaya 10 (Triticum durum Desf.) were grown in specially designed mesh containers 30 × 9 × 9 cm under the conditions of Synergotron ISR‑01 (ISR, Moscow) simulating natural lighting parameters with daylight hours 16/8, temperature conditions 26/22 and natural humidity conditions. 99 plants were cultivated in Synergotron and the same regimes were maintained throughout the experiment. To identify the effects of temporary flooding at the exit stage, we used imitation of temporary flooding conditions characteristic of field conditions during more than a month’s rainfall, especially for areas with low relief. The duration of root flooding corresponded to 14 days, while the humidity was maintained in the range of 80–100% humidity. During this period, a transition was observed from the stage of booting (with the flag leaf extending at a right angle) to heading (with an increase in the length and area of the flag leaves), accompanied by a change in color with a clear decrease in chlorophyll. At this stage, when the ear was already partially or completely extended from the sheath, flag leaves were prepared for analysis using a acousto-optical hyperspectrometer [10] and Alvium 1800 U camera, equipped with a lens with a focal length of 25 mm and an angular field of 16.5°, photographed and analyzed to determine the quantitative content of chlorophyll. The sample size of 15 wheat plants is the minimum acceptable to obtain reliable data from a randomized sample [11].
Experimental Determination of Chlorophyll in Wheat Flag Leaf
To obtain experimental values for the content of chlorophyll a, chlorophyll b, as well as their total content, spectrophotometric analysis was carried out, described in detail in [12]. For analysis, a section of a wheat flag leaf was used at a distance of 1.5 cm from the base of the leaf, and the area and weight of the area were recorded.
The absorption spectrum of the prepared solutions, measured on a Spekol 1300 spectrophotometer (Analitik Jena AG, Jena, Germany), makes it possible to accurately estimate the optical density D at the red peaks of chlorophyll a (Chl a) and chlorophyll b (Chl b), i. e. at wavelengths 648.6 nm and 664.1 nm. Measurements of the content of chlorophyll a (D648.6) and chlorophyll b (D664.1) were carried out in triplicate analytical replicates and the resulting average values were used in the calculations.
Registration and Processing of Hyperspectral Data
Spectral imaging of wheat plant samples illuminated by a 150 W halogen source was carried out using an acousto-optic hyperspectrometer. The leaves were placed on a white homogeneous plate with a spectral reflectance close to 1. As a result of the shooting, spectral images of the samples and the reference plate were obtained in the range of 450–850 nm with a step of 2 nm.
In order to eliminate the influence of spectral and spatial inhomogeneity of illumination of the samples, characteristics of the radiation receiver and optical distortions, such as vignetting, dependence of the transmission of optical components and the efficiency of acousto-optical diffraction on wavelength, data correction was carried out using the uniform field method [13].
Processing of RGB-images
In parallel with spectral photography, RGB images were recorded while maintaining the lighting and observation conditions of the samples. Since it is known that RGB space does not always correctly reflect the green color value of plants [14], images were converted into the HSV (Hue, Saturation, Brightness) color model, where Hue is a color tone that varies from 0 to 360°. By averaging the values over the area of each sample, data on the color characteristics of the samples were obtained to reveal their relationship with chlorophyll content determined by the laboratory method.
Results
Analytical Determination of Chlorophyll Content in Wheat Flag Leaf Under Flooding
Laboratory determination of the content of chlorophyll a (Chl a), chlorophyll b (Chl b) and total chlorophyll content in the flag leaf of wheat according to the described method is presented in Table 1.
Correlation Analysis of the Relationship Between Chlorophyll Content, Vegetation Indices and Color Characteristics
After processing the RGB images, we obtained calculated Hue values for each wheat sample. Table 2 shows the average values of color characteristics and pigment content in leaves of control plants and those grown under flooding conditions.
The Pearson correlation coefficient (r), which is a mathematical measure of the correlation between two quantities, in the case is a model of the relationship between Hue and Chl sum (the total sum of Chl a and Chl b) of the samples was r = 0.67.
As a result of the study, the correlation coefficient was r = 0.83. If we build a correlation for each type of chlorophyll, we get the following: between Hue and Chl a r = 0.77, and between Hue and Chl b r = 0.87. Using HSV to determine chlorophyll content is perhaps most productive on leaves with lower chlorophyll content.
Using the algorithm described in [15], the spatial distributions of 10 vegetation indices sensitive to the concentration of chlorophyll in plant leaves were obtained: CIRE, MSR705, MTCI, MCARI, MCARI/OSAVI, NDVI705, OSAVI, RECAI, RSI, SR705. Since a specific area of the wheat flag leaf was selected for the analytical analysis of chlorophyll content, the average values of the set of indices for each sample were determined by manually selecting image areas related to the part of the leaf used for spectrophotometric analysis. A correlation analysis of the relationship between the analytical content of total chlorophyll in the samples and the values of vegetation indices averaged over its area was carried out using linear regression (Table 3).
The strongest relationship was found between spectrophotometric analysis of the total chlorophyll content and the vegetation index – Normalized Difference Vegetation Index NDVI705 [15] (r = 0.91). The resulting empirical linear models that determine the relationship between chlorophyll content and the Hue color characteristic and the NDVI705 vegetation index are shown in Fig. 1a and 1b, respectively.
Since, as a result of correlation analysis, the NDVI705 index showed a closer relationship with the chlorophyll content, by applying the resulting empirical model to each spatial element of the NDVI705 index map, the distribution of the total chlorophyll content in the wheat flag leaf samples was obtained (Fig. 2).
Discussion
Root flooding caused by heavy precipitation or temporary waterlogging is a common cause of decreased productivity of wheat, since this type of cereal, unlike rice and corn, is not capable of forming aerenchyma in the roots and cannot normalize respiration and, accordingly, energy processes to provide transpiration turgor. This causes disruption of the photosynthetic system and leads to a significant increase in CO2 concentration in the intercellular space [17]. Stomatal regulation is disrupted and is aggravated by excessive water loss, which is not compensated by upward influx. Degradation of the photosynthetic system leads to loss of green color. The leaves take on an olive and/or yellowish tint (Fig. 2). This change in color tone can be determined using RGB imaging, but quantifying chlorophyll content using it has shown lower efficiency than analyzing hyperspectral data from samples. The correlation of spectrophotometric determination of chlorophyll content with data obtained by processing hyperspectral and RGB images analysis demonstrates good prospects for using this approach for the rapid and reliable determination of chlorophyll content as indicators of the state of the photosynthetic apparatus. The ability to determine the spatial distribution of chlorophyll concentrations can significantly reduce the number of labor-intensive analytical spectrophotometric analyzes of the content in wheat leaf samples.
Conclusion
According to data obtained, it can be stated that the prospects for applying vegetation indices and color tone values obtained using the processing of hyperspectral data and RGB images are quite high. The estimation based on narrow-band vegetation indices significantly exceeds the accuracy of the results obtained using RGB imaging, however, for a preliminary assessment, provided there is good lighting, both methods can be considered as an alternative to spectrophotometric analyzes that require a lot of time and complex sample preparation.
Acknowledgments
The study was carried out within the framework of the state assignment of the GBS RAS (No. 124030100058-4) (analysis of plant responses to abiotic stress and analytical determination of chlorophyll content in plant samples); as part of the implementation of the state assignment of the Scientific and Technical Center of the UP RAS (project FFNS‑2022-0010) (development of methods for recording and processing spectral images); in accordance with assignment No. 0431-2022-0003 (ARRIAB RAS), in accordance with agreement No. 075-15-2020-905 on the provision of grant No. 2744‑r (NC “Agricultural Technologies of the Future”, under the grant of RGAU-MTAA) of the Ministry of Science and Higher education of the Russian Federation (experiment setting and planning). The results of the work were obtained using the equipment of the Center for Collective Use of the Scientific and Technological Center for Unique Instrumentation of the Russian Academy of Sciences (STC UP RAS) [http://ckp.ntcup.ru] as well as using the Synergotron ISR11.02.220 Modules (Institute of Development Strategy).
AUTHORS
E. N. Baranova, PhD in biological sciences, senior researcher, All-Russian Research Institute of Agricultural Biotechnology of the Russian Academy of Sciences, Moscow, Russia; junior Researcher, N. V. Tsitsin Main Botanical Garden of the Russian Academy of Sciences, Moscow, Russia; Associate Professor, K. A. Timiryazev Moscow Agricultural Academy Russian State Agrarian University, Moscow, Russia; scientific consultant, ANO Institute for Development Strategy, Moscow, Russia.
ORCID: 0000-0001-8169-9228.
O. V. Shelepova, PhD in biological sciences, senior researcher, N. V. Tsitsin Main Botanical Garden of Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-2011-6054.
A. A. Zolotukhina, research engineer, Scientific and Technological Center for Unique Instrument Engineering of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-1043-7014.
G. V. Nesterov, research engineer, Scientific and Technological Center for Unique Instrument Engineering of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0009-0000-8647-6170.
K. A. Sudarikov, research engineer, ANO Institute of Development Strategy, Moscow, Russia.
ORCID: 0009-0005-8734-1223.
V. V. Latushkin, PhD in biological sciences, senior researcher, ANO Institute of Development Strategy, Moscow, Russia.
ORCID: 0000-0003-1406-8965.
A. A. Gulevich, senior researcher, All-Russian Research Institute of Agricultural Biotechnology of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-4399-2903.
CONFLICT OF INTERESTS
The authors declare that they have no conflict of interests. All authors took part in preparation of the article and supplemented the manuscript in terms of their scope of work.
CONTRIBUTION OF THE COMPOSITE AUTHORS
The article has been prepared based on the work of all composite authors.
E. N. Baranova 1, 2, 3, 4, O. V. Shelepova 2, A. A Zolotukhina 5, G. V. Nesterov 5, K. A. Sudarikov 4, V. V. Latushkin 4, A. A. Gulevich 1
All-Russia Research Institute of Agricultural Biotechnology, Moscow, Russia
N. V. Tsitsin Main Botanical Garden of Russian Academy of Sciences, Moscow, Russia
Moscow Timiryazev Agricultural Academy Russian State Agrarian University, Moscow, Russia
Institute of Development Strategy, Moscow, Russia
Scientific and Technological Centre of Unique Instrumentation of the Russian Academy of Sciences, Moscow, Russia
The study explores the possibility of using hyperspectral imaging and RGB photography as a fast and reliable method for determining the chlorophyll content to assess the state of the photosynthetic apparatus. The results of an evaluation of the relationships between the spectral characteristics of the flag leaves reflectivity of wheat, the characteristics of their color and chlorophyll content under conditions of the presence and absence of flooding are presented. It has been revealed that the most accurate assessment of the state of plants can be derived based on the NDVI705 vegetation index obtained by hyperspectral data processing.
Keywords: hyperspectral imaging, vegetation indices, image processing, chlorophyll content, flag leaf, wheat
Article received: 01.04.2024
Article accepted: 18.04.2024
Introduction
Crop growth conditions are determined by the relationship between plant physiological processes and environmental factors such as solar radiation, temperature, water and mineral nutrients availability. A number of studies have shown the possibility of assessing the crop performance based on measuring the chlorophyll content in leaves at certain stages of crop development [1, 2]. The content of photosynthetic pigments closely correlates with the physiological state of the plant and its productivity. At the initial stages of stress, changes in chlorophyll content in plants may be insignificant, but as stress intensity increases, its content decreases more rapidly than other pigments. The flag leaves of wheat represent the main photosynthetic tool that provides nutrition and filling of the ear after fertilization. For this reason, disturbances in the formation of this leaf at such transition stages as booting and heading, as well as flowering, can significantly limit the productivity of wheat plants [3]. The state of the photosynthetic system and its productivity are most clearly identified by the number and ratio of pigments that ensure the efficient operation of converting light energy into chemical energy and located in the lamellar membranes of chloroplasts.
The laboratory method for measuring the concentration of chlorophyll in plant leaves, based on spectrophotometry [4, 5] is the gold standard in characterizing the condition and diagnosing damage to the photosynthetic apparatus. However, due to the need for sample preparation, it is very labor-intensive, time- and resource-consuming, and is also limited in the ability to determine the spatial distribution of pigment content in the field. Currently, alternative non-invasive methods for monitoring the physiological state of plants using hyperspectral and multispectral imaging have been proposed [6, 7]. To reduce hyperspectral data, vegetation indices were proposed [8], which are a mathematical combination of the reflectivity of plants in the spectral ranges most sensitive to pigment content. However, most of these indices were developed for dicotyledonous plants, and to a lesser extent tested on monocots, in particular, wheat. The most accessible option for multispectral imaging is the registration, processing and interpretation of RGB images [9, 10] in order to assess the color characteristics of vegetation.
The aim of this study was to compare the efficiency of determining the chlorophyll content in wheat flag leaves using hyperspectral and RGB imaging. For this purpose, a correlation analysis of the relationship between the color characteristics, the spectral reflectance of the samples and the content of pigments in them, obtained using spectrophotometric analysis, were carried out.
Materials and Methods
Plant Material
Durum spring wheat plants of the cultivar Orenburgskaya 10 (Triticum durum Desf.) were grown in specially designed mesh containers 30 × 9 × 9 cm under the conditions of Synergotron ISR‑01 (ISR, Moscow) simulating natural lighting parameters with daylight hours 16/8, temperature conditions 26/22 and natural humidity conditions. 99 plants were cultivated in Synergotron and the same regimes were maintained throughout the experiment. To identify the effects of temporary flooding at the exit stage, we used imitation of temporary flooding conditions characteristic of field conditions during more than a month’s rainfall, especially for areas with low relief. The duration of root flooding corresponded to 14 days, while the humidity was maintained in the range of 80–100% humidity. During this period, a transition was observed from the stage of booting (with the flag leaf extending at a right angle) to heading (with an increase in the length and area of the flag leaves), accompanied by a change in color with a clear decrease in chlorophyll. At this stage, when the ear was already partially or completely extended from the sheath, flag leaves were prepared for analysis using a acousto-optical hyperspectrometer [10] and Alvium 1800 U camera, equipped with a lens with a focal length of 25 mm and an angular field of 16.5°, photographed and analyzed to determine the quantitative content of chlorophyll. The sample size of 15 wheat plants is the minimum acceptable to obtain reliable data from a randomized sample [11].
Experimental Determination of Chlorophyll in Wheat Flag Leaf
To obtain experimental values for the content of chlorophyll a, chlorophyll b, as well as their total content, spectrophotometric analysis was carried out, described in detail in [12]. For analysis, a section of a wheat flag leaf was used at a distance of 1.5 cm from the base of the leaf, and the area and weight of the area were recorded.
The absorption spectrum of the prepared solutions, measured on a Spekol 1300 spectrophotometer (Analitik Jena AG, Jena, Germany), makes it possible to accurately estimate the optical density D at the red peaks of chlorophyll a (Chl a) and chlorophyll b (Chl b), i. e. at wavelengths 648.6 nm and 664.1 nm. Measurements of the content of chlorophyll a (D648.6) and chlorophyll b (D664.1) were carried out in triplicate analytical replicates and the resulting average values were used in the calculations.
Registration and Processing of Hyperspectral Data
Spectral imaging of wheat plant samples illuminated by a 150 W halogen source was carried out using an acousto-optic hyperspectrometer. The leaves were placed on a white homogeneous plate with a spectral reflectance close to 1. As a result of the shooting, spectral images of the samples and the reference plate were obtained in the range of 450–850 nm with a step of 2 nm.
In order to eliminate the influence of spectral and spatial inhomogeneity of illumination of the samples, characteristics of the radiation receiver and optical distortions, such as vignetting, dependence of the transmission of optical components and the efficiency of acousto-optical diffraction on wavelength, data correction was carried out using the uniform field method [13].
Processing of RGB-images
In parallel with spectral photography, RGB images were recorded while maintaining the lighting and observation conditions of the samples. Since it is known that RGB space does not always correctly reflect the green color value of plants [14], images were converted into the HSV (Hue, Saturation, Brightness) color model, where Hue is a color tone that varies from 0 to 360°. By averaging the values over the area of each sample, data on the color characteristics of the samples were obtained to reveal their relationship with chlorophyll content determined by the laboratory method.
Results
Analytical Determination of Chlorophyll Content in Wheat Flag Leaf Under Flooding
Laboratory determination of the content of chlorophyll a (Chl a), chlorophyll b (Chl b) and total chlorophyll content in the flag leaf of wheat according to the described method is presented in Table 1.
Correlation Analysis of the Relationship Between Chlorophyll Content, Vegetation Indices and Color Characteristics
After processing the RGB images, we obtained calculated Hue values for each wheat sample. Table 2 shows the average values of color characteristics and pigment content in leaves of control plants and those grown under flooding conditions.
The Pearson correlation coefficient (r), which is a mathematical measure of the correlation between two quantities, in the case is a model of the relationship between Hue and Chl sum (the total sum of Chl a and Chl b) of the samples was r = 0.67.
As a result of the study, the correlation coefficient was r = 0.83. If we build a correlation for each type of chlorophyll, we get the following: between Hue and Chl a r = 0.77, and between Hue and Chl b r = 0.87. Using HSV to determine chlorophyll content is perhaps most productive on leaves with lower chlorophyll content.
Using the algorithm described in [15], the spatial distributions of 10 vegetation indices sensitive to the concentration of chlorophyll in plant leaves were obtained: CIRE, MSR705, MTCI, MCARI, MCARI/OSAVI, NDVI705, OSAVI, RECAI, RSI, SR705. Since a specific area of the wheat flag leaf was selected for the analytical analysis of chlorophyll content, the average values of the set of indices for each sample were determined by manually selecting image areas related to the part of the leaf used for spectrophotometric analysis. A correlation analysis of the relationship between the analytical content of total chlorophyll in the samples and the values of vegetation indices averaged over its area was carried out using linear regression (Table 3).
The strongest relationship was found between spectrophotometric analysis of the total chlorophyll content and the vegetation index – Normalized Difference Vegetation Index NDVI705 [15] (r = 0.91). The resulting empirical linear models that determine the relationship between chlorophyll content and the Hue color characteristic and the NDVI705 vegetation index are shown in Fig. 1a and 1b, respectively.
Since, as a result of correlation analysis, the NDVI705 index showed a closer relationship with the chlorophyll content, by applying the resulting empirical model to each spatial element of the NDVI705 index map, the distribution of the total chlorophyll content in the wheat flag leaf samples was obtained (Fig. 2).
Discussion
Root flooding caused by heavy precipitation or temporary waterlogging is a common cause of decreased productivity of wheat, since this type of cereal, unlike rice and corn, is not capable of forming aerenchyma in the roots and cannot normalize respiration and, accordingly, energy processes to provide transpiration turgor. This causes disruption of the photosynthetic system and leads to a significant increase in CO2 concentration in the intercellular space [17]. Stomatal regulation is disrupted and is aggravated by excessive water loss, which is not compensated by upward influx. Degradation of the photosynthetic system leads to loss of green color. The leaves take on an olive and/or yellowish tint (Fig. 2). This change in color tone can be determined using RGB imaging, but quantifying chlorophyll content using it has shown lower efficiency than analyzing hyperspectral data from samples. The correlation of spectrophotometric determination of chlorophyll content with data obtained by processing hyperspectral and RGB images analysis demonstrates good prospects for using this approach for the rapid and reliable determination of chlorophyll content as indicators of the state of the photosynthetic apparatus. The ability to determine the spatial distribution of chlorophyll concentrations can significantly reduce the number of labor-intensive analytical spectrophotometric analyzes of the content in wheat leaf samples.
Conclusion
According to data obtained, it can be stated that the prospects for applying vegetation indices and color tone values obtained using the processing of hyperspectral data and RGB images are quite high. The estimation based on narrow-band vegetation indices significantly exceeds the accuracy of the results obtained using RGB imaging, however, for a preliminary assessment, provided there is good lighting, both methods can be considered as an alternative to spectrophotometric analyzes that require a lot of time and complex sample preparation.
Acknowledgments
The study was carried out within the framework of the state assignment of the GBS RAS (No. 124030100058-4) (analysis of plant responses to abiotic stress and analytical determination of chlorophyll content in plant samples); as part of the implementation of the state assignment of the Scientific and Technical Center of the UP RAS (project FFNS‑2022-0010) (development of methods for recording and processing spectral images); in accordance with assignment No. 0431-2022-0003 (ARRIAB RAS), in accordance with agreement No. 075-15-2020-905 on the provision of grant No. 2744‑r (NC “Agricultural Technologies of the Future”, under the grant of RGAU-MTAA) of the Ministry of Science and Higher education of the Russian Federation (experiment setting and planning). The results of the work were obtained using the equipment of the Center for Collective Use of the Scientific and Technological Center for Unique Instrumentation of the Russian Academy of Sciences (STC UP RAS) [http://ckp.ntcup.ru] as well as using the Synergotron ISR11.02.220 Modules (Institute of Development Strategy).
AUTHORS
E. N. Baranova, PhD in biological sciences, senior researcher, All-Russian Research Institute of Agricultural Biotechnology of the Russian Academy of Sciences, Moscow, Russia; junior Researcher, N. V. Tsitsin Main Botanical Garden of the Russian Academy of Sciences, Moscow, Russia; Associate Professor, K. A. Timiryazev Moscow Agricultural Academy Russian State Agrarian University, Moscow, Russia; scientific consultant, ANO Institute for Development Strategy, Moscow, Russia.
ORCID: 0000-0001-8169-9228.
O. V. Shelepova, PhD in biological sciences, senior researcher, N. V. Tsitsin Main Botanical Garden of Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-2011-6054.
A. A. Zolotukhina, research engineer, Scientific and Technological Center for Unique Instrument Engineering of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-1043-7014.
G. V. Nesterov, research engineer, Scientific and Technological Center for Unique Instrument Engineering of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0009-0000-8647-6170.
K. A. Sudarikov, research engineer, ANO Institute of Development Strategy, Moscow, Russia.
ORCID: 0009-0005-8734-1223.
V. V. Latushkin, PhD in biological sciences, senior researcher, ANO Institute of Development Strategy, Moscow, Russia.
ORCID: 0000-0003-1406-8965.
A. A. Gulevich, senior researcher, All-Russian Research Institute of Agricultural Biotechnology of the Russian Academy of Sciences, Moscow, Russia.
ORCID: 0000-0003-4399-2903.
CONFLICT OF INTERESTS
The authors declare that they have no conflict of interests. All authors took part in preparation of the article and supplemented the manuscript in terms of their scope of work.
CONTRIBUTION OF THE COMPOSITE AUTHORS
The article has been prepared based on the work of all composite authors.
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