Journal of Environmental Quality 31:1424-1432 (2002)
© 2002 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
Optical Properties of Intact Leaves for Estimating Chlorophyll Concentration
Gregory A. Carter* and
Bruce A. Spiering
Earth Science Applications Directorate, National Aeronautics and Space Administration, Stennis Space Center, MS 39529
* Corresponding author (gcarter{at}ssc.nasa.gov)
Received for publication January 17, 2001.
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ABSTRACT
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Changes in leaf chlorophyll content can serve as relative indicators of plant vigor and environmental quality. This study identified reflectance, transmittance, and absorptance wavebands and band ratios within the 400- to 850-nm range for intact leaves that could be used to estimate extracted leaf chlorophyll per unit leaf area (areal concentration) with minimal error. Leaf optical properties along with chlorophyll a, b, and a + b concentrations were measured for the planar-leaved sweetgum (Liquidambar styraciflua L.), red maple (Acer rubrum L.), wild grape (Vitis rotundifolia Michx.), and switchcane [Arundinaria gigantea (Walter) Muhl.], and for needles of longleaf pine (Pinus palustris Miller). Generally, reflectance, transmittance, and absorptance corresponded most precisely with chlorophyll concentrations at wavelengths near 700 nm, although regressions were also strong in the 550- to 625-nm range. A power function was superior to a simple linear function in yielding low standard deviations of the estimate (s). When data were combined among the planar-leaved species, s values were low at approximately 50 µmol/m2 out of a 940 µmol/m2 range in chlorophyll a + b at best-fit wavelengths of 707 to 709 nm. Minimal s values for chlorophyll a + b ranged from 32 to 62 µmol/m2 across species when band ratios having numerator wavelengths of 693 to 720 nm were used with the application of a power function. Optimal denominator wavelengths for the band ratios were 850 nm for reflectance and transmittance and 400 nm for absorptance. This information can be applied in designing field portable chlorophyll meters and in the landscape-scale remote sensing of plant responses to the environment.
Abbreviations: A, absorptance • R, reflectance • s, standard deviation of the estimate • T, transmittance
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INTRODUCTION
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MANY DELETERIOUS ENVIRONMENTAL influences that inhibit plant growth, ranging from nutrient deficiencies to anthropogenic pollution, can result in decreased leaf chlorophyll contents (Hendry et al., 1987). In turn, leaf optical properties in the visible spectrum are strongly dependent on chlorophyll and thus may serve as relative indicators of plant vigor and environmental quality. A number of studies have determined that spectrally similar changes in leaf spectral reflectance, transmittance, or absorptance occur in response to various stressors including dehydration, flooding, tropospheric ozone, herbicides, and deficiencies in ectomycorrhizal development and N fertilization, among species that ranged from grasses to conifers and deciduous trees (for a review see Carter and Knapp, 2001). Owing to the in vivo absorption properties of chlorophyll, these spectral changes were maximum in the green–yellow and far-red spectra. For leaves or entire canopies, such spectral changes can provide early or even pre-visible indications of plant stress (Cibula and Carter, 1992; Carter et al., 1996).
A greater understanding of relationships between leaf optical properties and contents of chlorophyll and other pigments would be expected to yield improved methods of evaluating plant responses to the environment at a variety of measurement scales. Several recent studies have evaluated relationships of leaf chlorophyll concentration with leaf reflectance or derived reflectance indices throughout the visible to near-infrared spectrum at high spectral resolution. These studies indicate that the strongest relationships with chlorophyll occur in the green spectrum near 550 nm (Buschmann and Nagel, 1993; Blackburn, 1999) or the far-red spectrum near 700 nm (Chappelle et al., 1992; Carter et al., 1995, 2000; Yoder and Pettigrew-Crosby, 1995; Datt, 1999; Luther and Carroll, 1999; Moran et al., 2000), or that reflectances in these spectral regions are approximately equal in sensitivity to chlorophyll (Gitelson and Merzlyak, 1994, 1996, 1997; McMurtrey et al., 1994; Gitelson et al., 1996; Lichtenthaler et al., 1996; Datt, 1998; Carter and Knapp, 2001). However, other studies indicate that indices based on reflectance near 680 nm are most effective in estimating chlorophyll content (Blackburn, 1998a,b). Although relationships of chlorophyll concentration with leaf transmittance or absorptance have received far less attention, a few studies indicate relationships with chlorophyll to be most precise near 700 nm (Yoder and Daley, 1990; Carter et al., 2000; Carter and Knapp, 2001).
The goal of this study was to provide a further evaluation of relationships between leaf optical properties in the 400- to 850-nm wavelength (
) range and areal chlorophyll concentration. Leaves at various stages of autumnal senescence representing five species of vascular plants were sampled to provide a broad range in chlorophyll concentrations. Thus, data analysis emphasized the selection of optimal wavebands for estimating chlorophyll concentration rather than relationships of leaf optics to physiological activity during the growing season. Linear and nonlinear regressions determined the narrow wavebands (approximately 1.6 nm) in which leaf reflectance (R), transmittance (T), and absorptance (A) were most strongly correlated with chlorophyll concentration. Additionally, this approach was used to identify R, T, and A band ratios that might correlate more strongly with chlorophyll than R, T, or A at specific alone. Although indices derived from more complex computations such as derivatives may also correlate well with leaf chlorophyll concentration (e.g., Datt, 1999), these are not addressed herein.
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MATERIALS AND METHODS
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In a descriptive rather than experimental approach, regression analyses were used to evaluate relationships of extracted chlorophyll with intact leaf optical properties for naturally occurring sweetgum, red maple, wild grape, switchcane, and longleaf pine. Mature leaves that ranged in color from green to yellow as a result of various degrees of pigment loss during autumn and winter senescence were collected from the woodlands of Stennis Space Center, Mississippi, during December 1998 through February 1999. All planar leaves had been produced during the 1998 growing season. Most pine needles sampled also were produced in 1998, although some needles 2 to 3 yr in age were included to provide a greater representation of yellowed needles. Leaves were selected solely on the basis of apparent chlorophyll content, as indicated by leaf color, from among several plants of each species and remained attached to the stem prior to collection. Sun- and shade-adapted leaves were included randomly in the samples for all species. Only one species was sampled on a given day. Immediately after removal from the stem, leaves were placed into plastic bags and stored atop water ice in a dark, insulated container to minimize dehydration. The cooled yet unfrozen samples were then returned to the laboratory for the measurement of intact leaf optical properties and extracted chlorophyll.
For 42 leaves of each planar-leaved species, R and T were measured throughout the 400- to 850-nm spectrum with a spectroradiometer (Model 1500; Geophysical Environmental Research, Millbrook, NY) attached via fiber optic to an integrating sphere (Model LI1800-12S; LI-COR, Lincoln, NE) and methods described by Mesarch et al. (1999). After warming to room temperature to avoid surface condensation, a leaf was clamped into position over the sample port on the sphere wall where a 1.65-cm2 circular area was irradiated by the beam from a tungsten halogen lamp. Light reflected from the leaf was transmitted from the sphere interior through the fiber optic to the spectroradiometer for measurement of reflected spectral radiance. The spectroradiometer recorded data at wavelength intervals of approximately 1.6 nm. Similar measurements were made for stray light caused by imperfect collimation of the lamp beam and light reflected from a white reference (Spectralon SRT-05-99; Labsphere, North Sutton, NH) while the adaxial leaf surface faced the sphere interior. Spectral R was computed by subtracting stray spectral radiance from the spectral radiances reflected by the leaf and reference, and then dividing leaf reflected radiance by reference reflected radiance. This quantity was multiplied by 100 to yield units of percent. The term T was measured by illuminating the adaxial leaf surface such that light passed through the leaf into the integrating sphere. Radiance reflected from the white reference then was measured while the abaxial surface faced the sphere interior. Transmitted radiance was divided by reference radiance then multiplied by 100 to yield T in units of percent.
For the needle-leaved longleaf pine, R and T were measured for 42 samples. Each sample was composed of five or six needles spaced approximately 1 mm or less apart and arranged in parallel across the sample port of the integrating sphere. Reflected and transmitted radiances were recorded as above. An additional transmission scan was taken without needles in the sample holder to enable the correction of radiance values for light that passed between needles (Mesarch et al., 1999). A high-resolution digital camera and image processing software (ENVI v. 3.1; Research Systems, 1998) were used to determine the percentage of irradiance that was not intercepted by the needles. In pine as well as the planar-leaved species, A was computed as 100 - (R + T).
Chlorophyll Extraction
After leaf optical properties were measured, chlorophyll concentrations of the same leaves were determined. Six circular disks, each 6.25 mm in diameter, were punched from the same general area of the leaf for which optical properties were measured. The disks were placed immediately into 8 mL of 100% methanol, and pigments were allowed to extract in the dark at 30°C for 24 h. Absorbances of the clear extract at 652.0, 665.2, and 750 nm were recorded and concentrations of chlorophylls a, b, and a + b were computed as described by Porra et al. (1989). Chlorophyll concentrations computed in this manner were reported to compare favorably with those determined by atomic absorption spectroscopy of magnesium (Porra et al., 1989). Chlorophyll concentration of the extract (nmol mL-1) and the total one-sided area of the leaf disks of 1.84 cm2 were used to compute leaf chlorophyll concentrations in units of µmol/m2 of projected (one-sided) leaf area. Total projected leaf areas for computing chlorophyll concentration in pine needles were determined by use of the digital camera and image analysis.
Statistical Analysis
Coefficients of determination (r2) and standard deviations of estimation (s) were used to evaluate linear and nonlinear relationships of leaf chlorophyll concentration with R, T, A, and band ratios at 1.6-nm intervals throughout the 400- to 850-nm spectrum. The reported r2 values were adjusted downward slightly to account for sample size and the number of parameters in the regression function (SAS 6.0 [SAS Institute, 1997]; Table Curve 2D v. 4.0 [SPSS, 1998]). Analyses were conducted for samples combined among the four planar-leaved species as well as for individual species.
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RESULTS
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Leaf Chlorophyll Concentrations
The selection of leaves that ranged in color from green through yellow resulted in broad ranges in chlorophyll a, chlorophyll b, and chlorophyll a + b (total chlorophyll) concentrations for each species (Table 1). There was also substantial variation in the chlorophyll a/b ratio within each species. Among species, wild grape exhibited the smallest and switchcane the largest ranges in chlorophyll concentration. Ranges in chlorophyll a/b were greatest in sweetgum and longleaf pine.
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Table 1. Concentrations of chlorophyll a, chlorophyll b, and total chlorophyll, and chlorophyll a/b ratio values, for each species (42 samples per species).
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Data Combined among Species
Because the statistical procedures were identical and results similar among species, the analytical procedures used for each species are demonstrated below with data combined among the four planar-leaved species. When a simple linear function was employed for regressions of leaf total chlorophyll (a + b) concentration with R, T, or A, maximum r2 values of 0.82, 0.81, and 0.85 occurred in the 706- to 715-nm range (Fig. 1)
. When curvature of the regression was allowed by using a quadratic function, a maximum r2 of 0.87 and 0.89 occurred at 709 nm for R and A, respectively. A maximum r2 of 0.83 occurred at 603 nm for T, although the relationship with T at 703 nm (T703) was essentially as strong with an r2 of 0.82 (Fig. 1). Interestingly, r2 minima occurred near 675 nm in all cases.
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Fig. 1. Coefficient of determination (r2) versus wavelength () for relationships of leaf total chlorophyll (a + b) concentration with leaf reflectance (R), transmittance (T), and absorptance (A). Regressions were based on linear or quadratic models as indicated atop the figure and data combined among the four planar-leaved species (168 samples).
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Optimal of R, T, and A to be used in denominators of simple band ratios were identified by dividing R, T, or A at the best-fit indicated in Fig. 1 by R, T, or A at each throughout the 400- to 850-nm range and regressing total chlorophyll concentration against ratio value. This ensured that denominator R, T, or A was divided into a numerator that correlated strongly with chlorophyll owing to its in vivo absorption properties. The resulting r2 values were greatest at 0.81 to 0.89 when the denominator incorporated R or T from the near-infrared, or A from the violet–blue spectrum (Fig. 2)
. This was true when either the linear or quadratic regression functions were employed.
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Fig. 2. Coefficient of determination (r2) versus denominator wavelength () for relationships of leaf total chlorophyll (a + b) concentration with leaf reflectance (R), transmittance (T), and absorptance (A) band ratios. Regressions were based on linear or quadratic models as indicated atop the figure and data combined among the four planar-leaved species (168 samples). Ratios were computed by dividing R, T, or A at the best-fit indicated in Fig. 1 by R, T, or A, respectively, at each throughout the 400- to 850-nm spectrum. Where numerator and denominator were identical, ratio values remained at unity regardless of chlorophyll concentration, yielding r2 = 0. These points were deleted from the figure to eliminate r2 = 0 spikes.
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As a result of the analysis demonstrated in Fig. 2, best-fit ratios were determined by dividing R or T at each by R850 or T850, or A at each by A400. Leaf chlorophyll concentration then was regressed with the resulting ratio values, and r2 was evaluated with respect to numerator (Fig. 3)
. This procedure determined any potential shifts in numerator , compared with the best-fit determined in Fig. 1, that might have occurred when R, T, or A was normalized with respect to denominators that were relatively insensitive to changes in chlorophyll concentration. Maximum r2 values resulting from the simple linear regression were 0.87, 0.85, and 0.84 for R, T, and A ratios, and occurred at numerator of 715 to 720 nm. Regressions using the quadratic function yielded a maximum r2 of 0.89 at somewhat shorter of 713 and 709 nm for R and A ratios, respectively. For T/T850, the quadratic regression yielded r2 maxima of 0.83 and 0.82 at 603 and 703 nm. Similar to results in Fig. 1, r2 minima occurred consistently at numerator near 675 nm.
Best-fit for the quadratic regressions of chlorophyll with R, T, A, and ratio values were used as reference points in an iterative process that determined an optimal regression function. In evaluating results from a variety of simple regression functions (Table Curve 2D), it was determined that a power function (y = a + bxc) was superior in yielding precise regression curves for individual species and for data combined among the four planar-leaved species. The results of this procedure yielded best-fit power regressions when for R, T, and A were 706, 698, and 707 nm, respectively, and numerator for R, T, and A band ratios with R850, T850, or A400 were 709, 707, and 707 nm, respectively (Fig. 4)
. Best-fit were similar when chlorophylls a and b were considered separately, although r2 values were considerably lower for chlorophyll b (Fig. 5)
.
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Fig. 4. Best-fit regressions of leaf total chlorophyll (a + b) concentration versus leaf reflectance (R), transmittance (T), absorptance (A), and band ratios. Regressions were based on a power function as indicated atop the figure and data combined among the four planar-leaved species. Regression parameters, including the coefficient of determination (r2) and standard deviation of the estimate (s), are listed for each regression (168 samples).
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Fig. 5. Best-fit regressions of leaf chlorophyll a and chlorophyll b concentrations versus leaf reflectance (R), transmittance (T), and absorptance (A) band ratios. Regressions were based on a power function as indicated atop the figure and data combined among the four planar-leaved species. Regression parameters, including the coefficient of determination (r2) and standard deviation of the estimate (s), are listed for each regression (168 samples).
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Individual Species
When linear relationships of total chlorophyll concentration versus R, T, and A were evaluated for individual species, maximum r2 and minimum s values occurred generally at near 700 nm (Table 2). As exceptions, R533 and R567 in red maple and longleaf pine corresponded more linearly with chlorophyll than did R near 700 nm. The range among species in optimal for R, T, and A in these regressions was greater in the green–orange spectrum (34, 37, and 20 nm, respectively) than in the far-red (9, 16, and 14 nm, respectively).
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Table 2. Best-fit wavelengths (), coefficients of determination (r2), and standard deviations of the estimate (s) for linear (y = a + bx) regressions of leaf total chlorophyll concentration versus reflectance (R), transmittance (T), or absorptance (A).
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Linear regressions of total chlorophyll with R/R850, T/T850, and A/A400 yielded maximum r2 and minimum s values when was near 700 nm in all cases (Table 3). Among species, best-fit ranged only 21, 15, and 20 nm in the green spectrum and 13, 16, and 14 nm in the far-red for R, T, and A, respectively.
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Table 3. Best-fit wavelengths (), coefficients of determination (r2), and standard deviations of the estimate (s) for linear (y = a + bx) regressions of leaf total chlorophyll concentration versus reflectance (R), transmittance (T), or absorptance (A) band ratios.
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When curvature of total chlorophyll versus R, T, or A regressions was allowed by using the power function, maximum r2 and minimum s values occurred in the green–orange spectrum as often among species as in the far-red spectrum (Table 4). However, the range among species in optimal was much greater in the green–orange than in the far-red spectrum (87, 78, and 35 nm versus 11, 14, and 16 nm for R, T, and A, respectively).
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Table 4. Best-fit wavelengths (), coefficients of determination (r2), and standard deviations of the estimate (s) for power (y = a + bxc) regressions of leaf total chlorophyll concentration versus reflectance (R), transmittance (T), or absorptance (A).
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For total chlorophyll concentration, the greatest r2 and minimum s values generally resulted from power regressions with R/R850, T/T850, and A/A400. As with power regressions for R, T, and A, maximum r2 and minimum s values occurred in the green–orange spectrum as often as in the far-red (Table 5; Fig. 6)
. Again, the range among species in optimal was much greater in the green–orange than in the far-red (87, 77, and 40 nm versus 22, 27, and 14 nm for R/R850, T/T850, and A/A400, respectively).
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Table 5. Best-fit wavelengths (), coefficients of determination (r2), and standard deviations of the estimate (s) for power (y = a + bxc) regressions of leaf total chlorophyll concentration versus reflectance (R), transmittance (T), or absorptance (A) band ratios. See Fig. 6 for results in the far-red spectrum.
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Fig. 6. Best-fit regressions in the far-red spectrum of leaf total chlorophyll (a + b) concentration versus leaf reflectance (R), transmittance (T), and absorptance (A) band ratios for each species. Regressions were based on the power function y = a + bxc. Regression parameters, including the coefficient of determination (r2) and standard deviation of the estimate (s), are listed for each regression along with the wavelength () for the numerator (42 samples per species).
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DISCUSSION AND CONCLUSIONS
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Present results largely agree with those of previous studies in that leaf optical properties in the green–orange and far-red spectra were almost equally sensitive to chlorophyll concentration (Gitelson and Merzlyak, 1994, 1996, 1997; McMurtrey et al., 1994; Gitelson et al., 1996; Lichtenthaler et al., 1996; Datt, 1998; Carter and Knapp, 2001). With the exception of using the 400 nm rather than 850 nm band in the denominator for A band ratios, results for T and A were similar to those for R. In terms of best-fit for ratio numerators, results for chlorophyll b were similar to those for chlorophyll a and total chlorophyll.
The high sensitivity to chlorophyll of leaf optics near 550 nm and 700 nm is explained by the relatively low in vivo absorptivities of chlorophyll in these spectral regions. The absorptivity of chlorophyll while it remains associated with chloroplast membranes is weak near 550 nm, and approaches zero near 720 nm (Rabideau et al., 1946). Thus, R, T, and A near 550 and 700 nm change measurably with even small changes in leaf chlorophyll concentration. In contrast, high absorptivities in the 400- to 500-nm range and near 680 nm (Rabideau et al., 1946) result in low sensitivities to small changes in chlorophyll concentration. This explains the consistently low r2 values for regressions with chlorophyll in these spectral regions (Fig. 1 and 3). Low r2 values beyond approximately 730 nm occurred because chlorophyll does not absorb appreciably in the near-infrared spectrum.
It is clear that specific at which R, T, or A correlate most strongly with chlorophyll can depend substantially on the regression function employed. Linear regressions consistently indicated maximum r2 and minimum s values at near 700 nm. When the power function was used, results for the green–orange spectrum were nearly equivalent to those near 700 nm. Power or quadratic regressions usually shifted optimal in the green–orange spectrum to longer , and optimal in the far-red spectrum to shorter compared with linear regressions. Thus, functions that allowed regression curvature shifted best-fit toward the 680 nm region of strong absorption by chlorophyll.
In summary, R, T, and A were most effective in estimating leaf concentrations of chlorophylls a, b, and a + b at wavelengths near 700 nm. Generally, R, T, and A corresponded most precisely with chlorophyll concentrations at wavelengths near 700 nm, although regressions were also precise in the 550- to 625-nm range. A power function was superior to a simple linear function in yielding low standard deviations of the estimate (s). When data were combined among the planar-leaved species, s values were low at approximately 50 µmol/m2 out of a 940 µmol/m2 range in chlorophyll a + b at best-fit of 707 to 709 nm. Minimal s values for chlorophyll a + b ranged from 32 to 62 µmol/m2 across species when band ratios having numerator wavelengths of 693 to 720 nm were used with the application of a power function. Optimal denominator wavelengths for the band ratios were 850 nm for R and T and 400 nm for A. Best-fit numerator in the green–orange spectrum were much more variable among species (519–646 nm) than in the far-red spectrum (693–720 nm). Thus, the selection of a narrow waveband in the far-red spectrum, such as 705 ± 5 nm, would probably yield the most accurate estimates of leaf chlorophyll concentration based on R, T, A, or band ratios for the mature leaves of most vascular plant species. Improved estimates are obtained in most cases when calibration regressions are developed for individual rather than combined species. The incorporation of a near-700-nm band in field portable chlorophyll meters and remote sensing systems may prove to be a highly useful approach in evaluating chlorophyll as an indicator of environmental quality.
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ACKNOWLEDGMENTS
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The authors thank Danelle Brommer for extracting the chlorophylls and providing extract absorbances. This paper was presented at the Remote Sensing 2000 Bouyoucos Conference, 22–25 Oct. 2000, Corpus Christi, TX.
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NOTES
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This project was supported by a grant from the Office of Technology Transfer, NASA, Stennis Space Center.
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REFERENCES
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TOP
ABSTRACT
INTRODUCTION
