Study on the spectral response of Brassica Campestris L. leaf to the copper pollution

Abstract

Brassica Campestis L. was cultivated in the soil at the laboratory. The red edge, the visual spectrum and the near-infrared spectrum of Brassica Campestis L. leaf were used to explore the spectral response of Brassica Campestis L. leaf to the copper stress. As the Cu content in the soil gets increased, the copper level in Brassica Campestris L. leaf would be increased, and the chlorophyll level in Brassica Campestris L. leaf would be decreased. As a result, the visual spectral reflectance (A 1 ) of Brassica Campestris L. leaf is increased, and the blue-shift (moving towards the shorter waveband) degree (S) of the red edge (the ascending region of the reflectivity at 680-740 nm) gets increased. However, the near-infrared spectral reflectance (A 2 ) decreases. With the correlation coefficient R 2 more than 0.95, these parameters of A 1 , A 2 and S can be perfectly used to simulate and predict the copper level in Brassica Campestris L. leaf. red edge position, chlorophyll, plant spectrum, plant indicatorCopper pollution to the ecosystem has drawn worldwide attention [1,2] . To investigate and rehabilitate the polluted environment by the heavy metals, it is very critical to monitor and identify the polluted objects. The traditional chemical analysis is limited by scope, cost, time and labor. The vegetation-monitoring method of using the remote sensing technology is dynamic, much faster and able to provide a broader view and much more information [3,4] . This technique is becoming one of the significant methods for exploiting resource and preventing environmental pollution.As a dominant part of the terrestrial ecosystem, the vegetation has a direct impact on the holistic ecosystem. The vegetation may become an important index [5,6] to reflect the ecological pollution. When a plant is polluted by heavy metals, its leaf spectrum would be characteristically changed [7] . More and more researchers are engaged in the plant spectral response to the soil pollution and make much progress in the response mechanism [8][9][10][11] . However, there is no reported

A Wavelet-Based Area Parameter for Indirectly Estimating Copper Concentration in Carex Leaves from Canopy Reflectance

“…The main mechanism of such successful estimation originates from the strong correlation between Cu and chlorophyll ( Figure 4). Despite the element of Cu in plant leaves does not have evident absorption features, the high Cu concentration might trigger the decrease of foliar chlorophyll concentration, which can change the leaf reflectance spectrum [4,23,25,29]. This can be interpreted by that: the high concentration of Cu can stimulate the formation of free radicals and reduce the number of pores among mesophyll cells [1,3]; and chlorophyll concentration is a main influencing factor on leaf and canopy spectral characteristics in the visible region [16,47].…”

“…Numerous studies have focused on the retrieval of the spectrally active biochemical properties of plants (e.g., water, chlorophyll, and nitrogen) using physical or statistical models [8][9][10][11][12][13][14][15][16][17][18][19][20]. In contrast, much less progress has been made to estimate foliar heavy metal concentrations [21][22][23][24][25], which may be due to their very low concentrations in plant leaves (e.g., normally 5−30 mg•kg −1 for Cu) [26] and absence of evident physical absorption features existing for major constituents (e.g., water, chlorophyll, and starch) [27]. This makes it impossible to predict heavy metal concentrations directly from hyperspectral data.…”

“…This makes it impossible to predict heavy metal concentrations directly from hyperspectral data. Several studies with controlled experiments have found that chlorophyll concentrations in plant leaves tend to decrease with increasing heavy metal stress levels [4,23]. The reason for this relationship is that heavy metals are known to interfere with chlorophyll synthesis [4,28].…”

“…The reason for this relationship is that heavy metals are known to interfere with chlorophyll synthesis [4,28]. Consequently, the heavy metal stress in plant leaves would characteristically change the leaf reflectance spectrum, such as increasing reflectance over visible wavebands, decreasing reflectance over near-infrared wavebands and shifting the red edge position to shorter wavebands [23,29]. Hence, heavy metal concentrations could be theoretically predicted by capturing the indirect change of reflectance spectra caused by the decrease of chlorophyll concentration in plant leaves.…”

“…Hence, heavy metal concentrations could be theoretically predicted by capturing the indirect change of reflectance spectra caused by the decrease of chlorophyll concentration in plant leaves. In order to effectively capture the abovementioned change of reflectance spectra under heavy metal stress, some spectral parameters, such as vegetation index [22], band depth parameter [24], and position parameter [23,24], were employed for foliar heavy metal estimation. However, none of these studies have attempted to derive an area parameter (the sum of reflectance over a sensitive spectral region) from vegetation reflectance spectra.…”