Effects of heavy metals on the absorbance and reflectance spectra of plants

Abstract.

Published work on the reflectance of vegetation growing over soil mineralizations is reviewed. Experimental work was carried out on several species grown in a glasshouse and was extended to a pilot field study. In the laboratory studies, the most general effects of Cd, Cu, Pb or Zn were growth inhibition. A detailed study of the leaf pigments of pea plants showed that the chl a/chl b ratio (chl=chlorophyll) decreased under conditions of Cd or Cu stress but showed little effect with Pb or Zn. However, the absorption spectra of chloroplast pigments were not found to show any wavelength shifts with metal treatments, indicating that new spectral forms of chlorophyll were not produced as a stress response. A decrease in the total chlorophyll content of leaf tissue (fresh weight basis) was correlated with an increase in visible-wavelength leaf reflectance (R) of pea plants. R at infrared wavelengths of 0.85 μm, 1.65 μm and 2.20 μm decreased in metal-treated plants, compared with controls. Although experiments with other species, and a review of published literature, indicate that reflectance effects are dependent on species, phase of growth cycle and environment, the existence of correlations between R at certain wavelengths and the metal concentrations to which roots are exposed was confirmed using oak trees growing naturally in the area of a copper-arsenic mineralization in south-west England. Metal (Cu or As) concentrations in the soil were strongly negatively correlated (p > 99 per cent) with R at 1.65 μm and 2.20 μm, and positively correlated (p > 95 per cent) with R at 0.660 μm, in close agreement with the experiments on pea plants. The inclusion of the relevant infrared bands on Earth resource survey instruments is likely to enhance their usefulness for detecting heavy metal stress in plants.     

Airborne measurement of hot spot reflectance signatures

The so-called hot spot is a fine directional signature of the surface reflectance observed for phase angles close to zero. In this paper, we analyze and discuss several such signatures acquired from the airborne POLDER and HyMap instruments during the DAISEX'99 campaign over agricultural crops. The observed signatures are very similar to those acquired from space at a resolution of several tens of kilometers [J. Geophys. Res. 107 (2002)], which provides further evidence that the hot spot is a scale-free feature. The hot spots can be fitted by a two-parameter function (amplitude and width) of the phase angle derived from canopy radiative transfer modeling. The model predicts that the amplitude is directly related to the leaf reflectance, while the width is a function of the canopy structure. The retrieved leaf reflectance values over a wide spectral range are in very good agreement with noncoincident laboratory measurement. The retrieved half widths are on the order of 1° with no significant variability between the analyzed targets. There is an apparent spectral variability in the half width, a feature in contradiction with the modeling, although the variations are not larger than the uncertainties.     

Variability of high-resolution crop reflectance spectra

Abstract

High-spectral-resolution reflectance spectra from ground and helicopter measurements of agricultural crops and soils were analyzed to determine spectral variability in the visible and near-infrared (0 4-2 38 μm), using a procedure previously applied to thermal infrared emittance spectra of the atmosphere and to reflectance spectra of soil samples. Five spectral basis functions were sufficient to describe separately the ground and helicopter data, six or, at most, seven are sufficient to describe the pooled data. Thus, five to seven relatively broad band measurements, together with basis functions developed in this analysis, are sufficient to describe the variability of both data sets, to within differences that are probably associated with the measurement process and instrument noise.     

重金属捕集剂二甲基二硫代氨基甲酸对6种重金属螯合固化性能的量子化学研究

为探讨二甲基二硫代氨基甲酸盐螯合重金属离子的作用机理,本文采用密度泛函理论,在B3LYP/6-31++G（d,p）和B3LYP/LanL2DZ混合基组水平上,分别计算了二甲基二硫代氨基甲酸离子（DDC^-）和铬、铜、钴、锌、铁、镉6种重金属离子形成配合物的前线轨道能级、配位能△E、考虑基组重叠误差后的配位能△E_BSSE、零点振动能校正后的配位能△E_ZPE及自然电荷分布。研究结果表明:上述二甲基二硫代氨基甲酸配合物的稳定性与能级差△ε及配位能△E_BSSE、△E_ZPE的绝对值密切相关,△ε及△E_BSSE、△E_ZPE的绝对值越大,配合物越稳定。6种二甲基二硫代氨基甲酸重金属配合物的稳定性由大到小的顺序为:[CrDDC]²⁺>[CuDDC]⁺>[CoDDC]⁺>[ZnDDC]⁺>[FeDDC]⁺>[CdDDC]⁺。在形成配合物的过程中,电子从配体DDC^-流向重金属离子,电荷转移越多,配位能的绝对值越大。     

Variability of biome reflectance directional signatures as seen by POLDER

Reflectance measurements acquired with the spaceborne POLDER instrument are used to analyze the variability of land surface directional signatures as a function of vegetation cover type. The reflectance directional signatures are quantified by the three parameters of a modified version of the Ross-Li reflectance model. The variability of the estimated parameters with respect to the seven MODIS biome classes was found to be higher within the classes than between classes, with the exception of the desert targets that show more isotropic reflectances. A limited number of standard BRDFs (typically 5 in the red and near infrared) capture most of the variability of the directional reflectance measurements, supporting the idea that different land surfaces have similar directional signatures. Over vegetation targets, they are characterized by a strong increase toward backscattering and much smaller variations in forward directions. The results express the diversity in structural situations within a given biome class and indicate that, at the resolution of the POLDER sensor, i.e. a few kilometers, the BRDF contains little information on the dominant vegetation type. We show that standard directional signatures may be used to correct the reflectance measurements for directional effects with an RMS error on the order of 0.011 in the red and 0.015 in the near infrared.     

Computer simulation of the skin reflectance spectra

The reflectance spectra of the human skin in visible and near-infrared (NIR) spectral region have been calculated using the Monte Carlo technique, and the specular and internal reflection on the medium surface is taken into account. Skin is represented as a complex inhomogeneous multi-layered highly scattering and absorbing medium. The model takes into account variations in spatial distribution of blood, index of blood oxygen saturation, volume fraction of water and chromophores content. The simulation of the skin tissues optical properties and skin reflectance spectra are discussed. Comparison of the results of simulation and in vivo experimental results are given.     

Hyperspectral reflectance features of water hyacinth growing under feeding stresses of Neochetina spp. and different heavy metal pollutants

Spectral signatures of water hyacinth grown with biocontrol agents (Neochetina eichornia and N. bruchi) and various heavy metal pollutants were collected at the plant canopy level using a hand-held spectrometer to detect the biocontrol agent and heavy metal-induced plant stresses and the interaction between the two stressors. Water hyacinth was grown in 65l tubs, each with a single element from one of: As (1 mg l^?1), Au (1 mg l^?1), Cu (2 mg l^?1), Fe (0.5, 2 and 4 mg l^?1), Hg (1 mg l^?1), Mn (0.5, 2, and 4 mg l^?1), U (1 mg l^?1), and Zn (4 mg l^?1), with the exception of the control treatment. Three weeks after the metal treatments, the weevils were added to each tub, including those of the control treatment. Spectral measurements were taken before and after the addition of the weevils. Several spectral indicators of plant stress including red edge normalized difference vegetation index (RE-NDVI), modified red edge NDVI (mNDVI₇₀₅), modified simple ratio (mSR), photochemical reflectance index (PRI), and red edge position (REP) calculated using first derivative and linear extrapolation and water band index (WBI) were used to identify the plant stresses of water hyacinth. The spectral indicators of both metal and weevil plant stressors were correlated with the leaf chlorophyll content from the SPAD-502 readings at the end of the experiment. Correlations of mNDVI₇₀₅ with SPAD-502 readings were the highest followed by the indicators of REP. Cu-, Hg-, and Zn-treated plants showed significantly lower chlorophyll contents compared with the control treatment. A similar trend with four additional treatments (As, Fe-M, Mn-L, and Mn-H) was seen after the release of the weevils, indicating plant stress due to feeding by the biocontrol agent. However, adult and larval feeding was significantly reduced by Cu, Hg, and Zn elements, of which Cu was the most stressful. These results indicate that hyperspectral remote sensing has potential as a tool to determine the health status of water hyacinth from a remote location, to inform management interventions in control of the weed. However, its usage at a larger scale requires further studies.     

Fourth derivative analysis of Red Sea coral reflectance spectra

Reflectance spectra of coral colonies and associated sand and rubble were obtained over the fringing reefs of Eilat, Israel using two GER 1500 radiometers. The overall spectral response curve of Red Sea corals displayed the same three inflection points reported for Pacific corals, with notable differences between in vitro and in situ measurements. Fourth derivative analysis of relatively pure spectra (filling the sensor's field of view) allowed for differentiation of coral and non-coral targets with 95–99% accuracy. The characteristic peaks revealed by the fourth derivative match those obtained on Hawaiian corals.     

Interference of salt and moisture on soil reflectance spectra

This article portrays the effects of salt and moisture on soil reflectance spectra and their consequent influences on the estimation of soil salinity and soil moisture contents (SMC). It is amid to demonstrate and discuss how the interference of salt and moisture, as soil constituents, on soil spectra can affect the estimation of either soil salinity or SMC when spectral variabilities are used as predictive variables. To achieve this objective, a data set was obtained from a test area where soil salinity and SMC were largely varied. Furthermore, the Inverted Gaussian (IG) modelling approach, which has been successfully used for the estimation of soil salinity under laboratory conditions and for the estimation of SMC for non-saline soil, is used in this study. Using the IG function, the near-infrared (NIR) and the shortwave infrared (SWIR) regions of the salt-affected soil spectra, with various amount of moisture, were fitted to an IG curve. Parameters of the fitted curve such as functional depth, distance to the inflection point and area under the curve were then used as predictors in a multi-regression analysis to quantify the effect of soil salinity and SMC on soil spectra. The results suggest that a combination of salt and moisture in soil causes anomalies and therefore variations in neither salt nor moisture contents can be modelled accurately on the basis of quantification of soil reflectance. These results suggest that further studies are required to determine a set of calibrating coefficients that can be used to eliminate the background spectral effects caused by either soil salinity or SMC.     

Salinity modelling by inverted Gaussian parameters of soil reflectance spectra

This paper presents an approach to estimate soil salinity through modelling of soil spectra using an inverted Gaussian (IG) function. The approach is tested on experimental datasets including measurements of soil physicochemical properties and their spectral reflectance which are obtained under controlled laboratory conditions. The near-infrared (NIR) and shortwave infrared (SWIR) region of the salt-affected soil spectra were fitted to an inverted Gaussian curve. Parameters of the fitted curve, such as functional depth, distance to the inflection point and area under curve, were then used as predictors in regression analysis to estimate soil salinity levels. The results suggest a successful estimation of salinity levels, especially, for soil samples treated with epsomite and bischofite solutions. Amongst the calculated IG parameters, the area under fitted curve resulted in the most accurate estimations. The results demonstrate the relative utility of high spectral resolution data for estimating soil salinity under laboratory controlled conditions.     

Spectral reflectance changes accompanying a post-fire recovery sequence in a subarctic spruce lichen woodland

A sequence of burned surfaces aged 0, 1, 2, 25 and 80 years was investigated regarding changes in the spectral distribution of reflected light. Controls were introduced to isolate diurnal and seasonal effects. The results show gradually increasing reflectance with increasing age of burn. With the establishment of vegetation a new set of absorption and reflectance criteria are established substantially altering the spectral characteristics. The apparent effect of a mature forest canopy is ambiguous. Diffuse and overcast conditions reduce the reflectance for all surfaces. Further work is suggested to reinforce results for surfaces with low sampling replication.     

Feasibility of neural network approach in spectral mixture analysis of reflectance spectra

In the present work, we perform spectral mixture analysis using Chi‐square minimization (χ² minimization) procedure and test the feasibility of applying an inverse technique, neural network (NN) approach, for the spectral unmixing. The training of NN is carried out using the Levenberg–Marquardt algorithm (LM) with the initial weights for training being chosen randomly. The experiments are performed in the laboratory by mixing young, matured and dead leaves of a sequoia tree in various proportions and reflectance spectra of these mixtures are recorded. The proportions are chosen to model a few near‐real situations like different kinds of vegetation in a forest (by mixing young leaves and matured leaves) and trees damaged in a forest fire or affected by certain virus (by mixing matured and dead leaves) and a combination of all these (by mixing young, matured and dead leaves). The spectral mixture analysis employing χ² minimization and the inverse procedure utilizing NN with two hidden layers yielded consistent results in accordance with the proportion of each kind of leaf.     

Spectral unmixing of normalized reflectance data for the deconvolution of lichen and rock mixtures

In subarctic regions the ubiquitous presence of rock encrusting lichens compromises the ability to map the reflectance signatures of minerals from imaging spectrometer data. The use of lichen as an endmember in spectral mixture analysis (SMA) may overcome these limitations. Because lichens rarely completely occupy the Instantaneous Field of View (IFOV), it is difficult to define a lichen endmember from an image using visual or automated endmember extraction tools. Spectral similarity of various crustose/foliose lichen species in the short wave infrared (SWIR) suggests that spectral unmixing of rock and lichens may be successfully accomplished using a single lichen endmember for this spectral range. We report the use of a spectral normalization method to minimize differences in SWIR reflectance between five lichen species (U. torrefacta, R. bolanderi, R. geminatum, R. geographicum, A. cinerea). When the normalization is applied to reflectance spectra from 2000-2400 nm acquired for a lichen encrusted quartzite rock sample we show that only a single lichen endmember is required to account for the lichen contribution in the observed mixtures. In contrast, two such endmembers are required when the normalization is not applied to the reflectance data. We illustrate this point using examples where endmembers are extracted manually and automatically, and compare the SMA results against abundances estimated from digital photography. For both the reflectance and normalized reflectance data, SMA results correlate well (R²>0.9) with abundances estimated from digital photography. The use of normalized reflectance implies that any field/laboratory lichen spectrum can be selected as the lichen endmember for SMA of airborne/spaceborne imagery.     

Effects of lichens on the reflectance spectra of granitic rock surfaces

The objective of this study was to determine the effect of lichen cover on the spectral reflectance characteristics of granitic rocks. Rock samples collected from bedrock exposures and talus slopes were granodiorite, tonalite, granite, and quartz-diorite. The lichens found on these rocks varied in color, i.e., black, dark brown, medium gray, olive-green, yellow-green, green, orange, and orange-red. The visible and near infrared reflectance spectra (400–1100 nm) of the rock and lichen samples show that lichens can affect the rock's spectra. These changes are dependent on the reflectance contrast between the rock surface and the lichen covering.     

A multi-angle spectrometer for automatic measurement of plant canopy reflectance spectra

The paper describes the design and operation of a multi-angle spectrometer (MAS) for automatic measurement of near-field spectral reflectances of plant canopies at hourly intervals. A novel feature of the instrument is a rotating periscope connected to a spectrometer via a fiber optic cable. Canopy reflectances are calculated for multiple view azimuths, at a single zenith angle from measurements of spectrometer dark current, incoming solar irradiance and reflected radiances. Spectral measurements are made between 300 and 1150 nm wavelength at a band-to-band spacing of 3 nm, and a bandwidth (full-width, half maximum) of 10 nm. Preliminary data analysis showed that the canopy reflectance model of Kuusk [Kuusk, A. (1995). A fast, invertible canopy reflectance model. Remote Sensing of Environment 51, 342-350] reproduced the observed large differences in visible and near-infrared (NIR) reflectances, but the model was unable to predict quantitatively the observed variations in the measured reflectance spectra with azimuth, particularly in the NIR. Discrepancies between model and measurements are likely due to the inhomogeneous nature of the forest canopy in contrast to the assumption of a uniformly absorbing turbid medium in the model. Measurements using the MAS can be used to investigate directional dependences of reflectance indices and for testing BRDF models used to separate geometrical and plant physiological contributions to the reflectance signals. The MAS provides continuous sampling of reflectance indices which can be compared with canopy properties such as chlorophyll content and photosynthetic capacity.     

Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis

The dynamics of foliar chlorophyll concentrations have considerable significance for plant-environment interactions, ecosystem functioning and crop growth. Hyperspectral remote sensing has a valuable role in the monitoring of such dynamics. This study focussed upon improving the accuracy of chlorophyll quantification by applying wavelet analysis to reflectance spectra. Leaf-scale radiative transfer models were used to generate very large spectral data sets with which to develop and rigorously test refinements to the approach and compare it with existing spectral indices. The results demonstrated that by decomposing leaf spectra, the resultant wavelet coefficients can be used to generate accurate predictions of chlorophyll concentration, despite wide variations in the range of other biochemical and biophysical factors that influence leaf reflectance. Wavelet analysis outperformed predictive models based on untransformed spectra and a range of spectral indices. The paper discusses the possibilities for further refining the wavelet approach and for extending the technique to the sensing of a variety of vegetation properties at a range of spatial scales.     

电化学传感器在水质重金属检测中的应用

中国工业快速发展伴随而来的水质重金属污染问题正日益影响着人们的正常生活,寻求快速准确的水质重金属检测方法是十分迫切的.众多水质检测传感器中,电化学传感器具有检测灵敏、操作简单、成本低、便携等优势,在水质重金属检测领域占据了十分重要地位,拥有广阔的前景.本文重点介绍了用于水质重金属检测的几种电化学传感器,包括它们的构造、分类及其检测原理.并对应用于水质重金属检测的电流型电化学传感器和电位型电化学传感器进行了详细说明,介绍了阳极溶出伏安法和离子选择性电极法在内的几种电化学分析方法,以及近年来相关研究的现状.     

Detection of leaf and canopy EWT by calculating REWT from reflectance spectra

The spectral characteristics of and the interaction between leaves and light were analysed based on the optical absorption coefficients of foliar water and biochemical components. The equations for calculating the radiative-equivalent water thickness (REWT) of leaves and canopy were presented based on the difference in reflectance at 945 and 975 nm. Because of the direct reflection on leaf surface and the leaf internal scattering, the REWT derived from the Beer–Lambert principle was different from the leaf or canopy equivalent water thickness (EWT). Two independent datasets at canopy or leaf scales were designed to calibrate and validate the relationships between EWT and REWT. The results show that (1) the leaf or canopy REWT can be calculated from the reflectance difference between 945 and 975 nm; (2) the leaf REWT was 3.3 times larger than the EWT with a significant determination coefficient (R ²) of 0.80 for our dataset and 0.86 for the Leaf Optical Properties Experiment (LOPEX'93) dataset; (3) the canopy REWT was 1.4 times larger than the EWT with a significant R ² of 0.56 for the winter wheat canopy spectral dataset in 2002, and 0.61 for the 2004 dataset. Therefore, the leaf or canopy EWT can be detected by calculating REWT from the difference in reflectance at 945 and 975 nm. Furthermore, because the relationship between REWT and EWT reflected the interaction of light with leaves or canopy, the multiple scattering optical pathlength in the near-infrared (NIR) bands can also be calculated by the ratio of REWT to EWT.     

水质重金属检测技术研究进展

水质重金属检测技术的发展对治理水质污染工作具有十分重要的意义.对近年来水质重金属检测技术方法以及该领域的研究进展进行综述,主要介绍了原子吸收光谱法、原子荧光光谱法,电感耦合等离子体法,紫外-可见分光光度法,高效液相色谱法,电化学分析法和生物检测法,对这些技术的工作原理、仪器和特点等方面进行阐述,比其在水质重金属检测过程中的利与弊进行探讨,最后对该领域的研究方向进行了展望.     

The biochemical decomposition of slash pine needles from reflectance spectra using neural networks

An artificial neural network was used to control for leaf water absorption during the estimation of lignin-cellulose and nitrogen concentration from the reflectance spectra of fresh slash pine needles. The inputs to the neural network comprised of spectral indices based upon wavelengths at the centre or wings of known absorption features of the biochemical compounds of interest. The results indicate that the neural network provides more accurate estimates of water concentration than when using spectral indices alone. More importantly, lignincellulose concentrations were estimated with an accuracy of around 3 per cent relative to mean value. However, an accuracy of only 24 per cent relative to mean value was achieved for estimates of nitrogen concentration.