Actual Data Acquisition
Structure parameter N denotes the species and thickness of plant leaf in practice. In this study, only scattering caused by thickness differences
of the same species was taken into account to avoid alternating influence. Epipremnum aureum was used as a representative plant because the thickness of different locations for the same leaf decreases gradually from
leaf root to leaf apex. It is theorized that the chlorophyll and water content are distributed symmetrically for the same
leaf; therefore, the spectra variations from different locations of a leaf analysis are caused by light scattering.
Samples and Spectroscopic Measurements
Six Epipremnum aureum leaves with different green and sapless levels were selected. All of them were healthy and homogeneous in color without anthocyanin
pigmentation or visible symptoms of damage. Spectra of six different locations per sample were measured (shown in Figure 2a),
36 sample spectra (shown in Figure 2b) were obtained as predictor variables for two different response variables: water and
Figure 2: (a) Sample used in the experiment and (b) the spectra of leaves.
An Ocean Optics (Dunedin, Florida) spectrometer and diffuse reflectance sample accessories Y style fiber were used for spectra
measurement. The light source was a white light. A white panel (Spectralon, Labsphere, North Sutton, New Hampshire) was used
as a 100% reflectance standard for all measurements. The parameters of the spectrometer were as follows: spectrum scanning
range, 350–1050 nm; number of pixels, 3648; integration time, 15 ms; average time, 20 ms; width of smooth window, 3.
The data were stored in the form of R (reflectance). Because of the low spectral intensity of the halogen lamp used below
450 nm and the resulting noise in the measured spectra, only reflectance data above this wavelength were considered.
Each leaf was cut into two parts and arranged for the measurement of chlorophyll and water content, respectively. The half
for chlorophyll was cut into fragments and extracted with 80% aqueous acetone solution and then centrifuged. The absorption
spectra of the acetone extract was measured with the same spectrophotometer. The concentration of chlorophyll (a) and (b)
was calculated based on the absorbance measured at 646.6, 663.6, and 730 nm according to the Porra formula (22). Another half
was used to obtain water content by roasting. First, fresh weight (FW) was recorded using an analytical balance and leaves
were dried at 105 °C in an oven for 15 min. Then the temperature was dropped down to 80 °C until the leaf weight was constant.
Leaf relative water content (RWC) was calculated using the following equation:
Commonly, the methods for correcting light scattering can be divided into two types. One is aimed to modify the additional
spectra information caused by scattering that is usually regarded as a baseline shift of the spectra. The additional information
is modeled and corrected in a more elaborate preprocessing stage. Representatives of these methods are multiplicative scattering
correction (MSC) (23) and extended multiplicative scattering correction (EMSC) (8). Another method looks at the geometrical
space constructed by the scattering information. Then the scattering effects are eliminated by projecting the raw spectra
onto the orthogonal complement of the space, for example orthogonal signal correction (OSC) (24).
The method of optical pathlength estimation and correction (OPLEC) (25) is the combination of two ideas. It adopts the scattering
model presented by Martens (as in reference 7), employs the theory of orthogonal projection, and eliminates parts of independent
scattering effects with chemical matter concentration. Then, based on the assumption that there are J kinds of matter independent from each other, two established equations of linear regression are used to model the dependent
scattering on the target concentration statistically. Consequently, the scattering effects are absolutely corrected without
any pure spectrum information.