| Title: | Calculate the Relative Crystallinity of Starch by XRD and FTIR |
|---|---|
| Description: | Functions to calculate the relative crystallinity of starch by X-ray Diffraction (XRD) and Infrared Spectroscopy (FTIR). Starch is biosynthesized by plants in the form of granules semicrystalline. For XRD, the relative crystallinity is obtained by separating the crystalline peaks from the amorphous scattering region. For FTIR, the relative crystallinity is achieved by setting of a Gaussian holocrystalline-peak in the 800-1300 cm-1 region of FTIR spectrum of starch which is divided into amorphous region and crystalline region. The relative crystallinity of native starch granules varies from 14 of 45 percent. This package was supported by FONDECYT 3150630 and CIPA Conicyt-Regional R08C1002 is gratefully acknowledged. |
| Authors: | Claudio Pozo Valenzuela [aut, cre], Saddys Rodriguez-Llamazares [aut] |
| Maintainer: | Claudio Pozo Valenzuela <[email protected]> |
| License: | GPL-2 |
| Version: | 0.1.0 |
| Built: | 2025-02-15 05:09:47 UTC |
| Source: | https://github.com/cran/cryst |
Allow to calculate the relative crystallinity of starch by XRD. The basic concept of Bruckner approach involves obtaining a smoothed line that separates the amorphous and crystalline starch of an X-ray diffraction pattern. This smoothed line is achieved by applying a moving average smoothing method to the original pattern.
crystMW(pattern, N = 41, iter = 100)crystMW(pattern, N = 41, iter = 100)
pattern |
matrix. The matrix of X-ray diffraction pattern. The first row corresponds to Bragg angle 2 |
N |
numeric. N length of the smoothing window (number of variables). Defaults to 41. |
iter |
numeric. Iter number of iterations. Defaults to 100. |
Calculate the relative starch crystallinity of XRD pattern by Bruckner method.
An object of class crystMW, which is a list with the following components:
original |
Original matrix of X-ray diffraction patterns. |
background |
Estimation of the background shape (curve of the amorphous starch). |
corrected |
Estimation of residual crystalline area (curve of the crystalline starch). |
summary |
Summary calculation of crystallinity. Total area under the curve of the diffraction pattern (A.U.); Amorphous area (A.U.); Crystalline area (A.U.); Relative crystallinity (%). |
Claudio Pozo Valenzuela [aut, cre] and Saddys Rodriguez-llamazares [aut]
Bruckner, S. (2000). "Estimation of the background in powder diffraction patterns through a robust smoothing procedure." Journal of Applied Crystallography 33(3 Part 2): 977-979.
data(XRD) # Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[,c("Bragg_angle","A")])) # List of crystallinity components crs <- crystMW(pattern, N = 41, iter = 100) # Original matrix original <- crs$original # Background shape background <- crs$background # Curve of the crystalline starch corrected <- crs$corrected # Summary calculation of crystallinity summary <- crs$summarydata(XRD) # Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[,c("Bragg_angle","A")])) # List of crystallinity components crs <- crystMW(pattern, N = 41, iter = 100) # Original matrix original <- crs$original # Background shape background <- crs$background # Curve of the crystalline starch corrected <- crs$corrected # Summary calculation of crystallinity summary <- crs$summary
Allow to calculate the relative crystallinity of starch by XRD. The basic concept of Frost approach involves obtaining a smoothed line that separates the amorphous and crystalline starch of an X-ray diffraction pattern. This smoothed line is achieved by applying a Savitzky-Golay smoothing method to the original pattern.
crystSG(pattern, N = 101, iter = 400, p = 2)crystSG(pattern, N = 101, iter = 400, p = 2)
pattern |
matrix. The matrix of X-ray diffraction pattern. The first row corresponds to Bragg angle 2 |
N |
numeric. N length of the smoothing window (number of variables). Defaults to 101. |
iter |
numeric. Iter number of iterations. Defaults to 400. |
p |
numeric. Filter order. Defaults to 2. |
Calculate the relative starch crystallinity of XRD pattern by Frost method.
An object of class crystSG, which is a list with the following components:
original |
Original matrix of X-ray diffraction patterns. |
background |
Estimation of the background shape (curve of the amorphous starch). |
corrected |
Estimation of residual crystalline area (curve of the crystalline starch). |
summary |
Summary calculation of crystallinity. Total area under the curve of the diffraction pattern (A.U.); Amorphous area (A.U.); Crystalline area (A.U.); Relative crystallinity (%). |
Claudio Pozo Valenzuela [aut, cre] and Saddys Rodriguez-llamazares [aut]
Frost, K., et al. (2009). "Crystallinity and structure of starch using wide angle X-ray scattering." Carbohydrate Polymers 78(3): 543-548.
data(XRD) # Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[, c("Bragg_angle","A")])) # List of crystallinity components crs <- crystSG(pattern, N = 101, iter = 400, p = 2) # Original matrix original <- crs$original # Background shape background <- crs$background # Curve of the crystalline starch corrected <- crs$corrected # Summary calculation of crystallinity summary <- crs$summarydata(XRD) # Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[, c("Bragg_angle","A")])) # List of crystallinity components crs <- crystSG(pattern, N = 101, iter = 400, p = 2) # Original matrix original <- crs$original # Background shape background <- crs$background # Curve of the crystalline starch corrected <- crs$corrected # Summary calculation of crystallinity summary <- crs$summary
Allow to calculate the relative crystallinity of starch by FTIR. The basic concept of SUN approach involves obtaining a gaussian holocrystalline-peak in the 800-1300 cm-1 region of FTIR spectrum of starch which is divided into amorphous region and crystalline region.
fitFTIRc(spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 950))fitFTIRc(spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 950))
spectrum |
matrix. The matrix of FTIR spectrum baseline-corrected by drawing a tangentline in the 800-1300 cm-1 region. The first row corresponds to wavelength; the second row corresponds to intensity. |
mu |
numeric. Gaussian mean of holocrystalline-peak. Defaults to 1180. |
sigma |
numeric. Standard deviation of holocrystalline-peak. Defaults to 60. |
k |
numeric. Arbitrary scaling parameter. Defaults to 1. |
lim |
vector. Fitting points of holocrystalline-peak. Defaults to c(1190, 1160, 985, 950). |
Calculate the relative starch crystallinity of FTIR spectrum by SUN method.
An object of class fitFTIRc, which is a list with the following components:
original |
Original matrix of FTIR spectrum. |
gauss |
Gaussian curve fit. |
fit |
Summary of Non-Linear Least-Squares Model Fits. |
summary |
Summary calculation of crystallinity. Total area under the curve of the diffraction spectrum (A.U.); Amorphous area (A.U.); Crystalline area (A.U.); Relative crystallinity (%). |
Claudio Pozo Valenzuela [aut, cre] and Saddys Rodriguez-llamazares [aut]
Sun, Y., et al. (2014). "A new method for determining the relative crystallinity of chickpea starch by Fourier-transform infrared spectroscopy." Carbohydrate Polymers 108: 153-158.
# Convert data frame to matrix, select A-type starch spectrum <- as.matrix(t(FTIR[, c('wavelength','A')])) # List of crystallinity components crs <- fitFTIRc(spectrum = spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 955)) # Original matrix original <- crs$original # Gaussian curve fit gauss <- crs$gauss # Summary of Non-Linear Least-Squares Model Fits fit <- crs$fit # Summary calculation of crystallinity summary <- crs$summary# Convert data frame to matrix, select A-type starch spectrum <- as.matrix(t(FTIR[, c('wavelength','A')])) # List of crystallinity components crs <- fitFTIRc(spectrum = spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 955)) # Original matrix original <- crs$original # Gaussian curve fit gauss <- crs$gauss # Summary of Non-Linear Least-Squares Model Fits fit <- crs$fit # Summary calculation of crystallinity summary <- crs$summary
A dataset containing FTIR spectra of A-, B-, and C-type Starch.
data(FTIR)data(FTIR)
A data frame with 1038 rows and 4 variables
Wavelength. wavelength of FTIR spectrum
A. Absorbance of an FTIR spectrum of A-type starch (A.U.).
B. Absorbance of an FTIR spectrum of B-type starch (A.U.).
C. Absorbance of an FTIR spectrum of C-type starch (A.U.).
Produces a graph of the crystalline area of a FTIR spectrum of starch and the Gauss curve.
ftirplot(spectrum, gauss, lim = c(1190, 1160, 985, 950))ftirplot(spectrum, gauss, lim = c(1190, 1160, 985, 950))
spectrum |
matrix. The matrix of FTIR spectrum baseline-corrected by drawing a tangentline in the 800-1300 cm-1 region. The first row corresponds to wavelength; the second row corresponds to intensity. |
gauss |
matrix. The matrix of Gauss curve (gaussian holocrystalline-peak). |
lim |
vector. Regions of the FTIR spectrum comprising the fixing points of the Gauss curve. |
Claudio Pozo Valenzuela [aut, cre] and Saddys Rodriguez-llamazares [aut]
# Convert data frame to matrix, select A-type starch spectrum <- as.matrix(t(FTIR[, c('wavelength','A')])) # List of crystallinity components crs <- fitFTIRc(spectrum = spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 955)) # Original matrix original <- crs$original # Gaussian curve fit gauss <- crs$gauss # Plots the crystalline area of a FTIR spectrum ftirplot(spectrum=original, gauss=gauss, lim=c(1190, 1160, 985, 950))# Convert data frame to matrix, select A-type starch spectrum <- as.matrix(t(FTIR[, c('wavelength','A')])) # List of crystallinity components crs <- fitFTIRc(spectrum = spectrum, mu = 1180, sigma = 60, k = 1, lim = c(1190, 1160, 985, 955)) # Original matrix original <- crs$original # Gaussian curve fit gauss <- crs$gauss # Plots the crystalline area of a FTIR spectrum ftirplot(spectrum=original, gauss=gauss, lim=c(1190, 1160, 985, 950))
A dataset containing X-ray diffraction patterns of A-, B-, and C-type Starch.
data(XRD)data(XRD)
A data frame with 1527 rows and 4 variables
Bragg_angle. bragg angle of X-ray diffraction patterns (2).
A. intensity of an X-ray diffraction pattern of A-type starch (counts).
B. intensity of an X-ray diffraction pattern of B-type starch (counts).
C. intensity of an X-ray diffraction pattern of C-type starch (counts).
Produces a graph of the crystalline area of a X-ray diffraction pattern of starch and background.
xrdplot(pattern, background)xrdplot(pattern, background)
pattern |
matrix. The matrix of X-ray diffraction pattern. The first row corresponds to Bragg angle 2 |
background |
matrix. The matrix of background shape (curve of the amorphous starch). The first row corresponds to Bragg angle 2 |
Claudio Pozo Valenzuela [aut, cre] and Saddys Rodriguez-llamazares [aut]
# Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[, c("Bragg_angle","A")])) # List of crystallinity components crs <- crystMW(pattern, N = 11, iter = 100) # Original matrix original <- crs$original # Background shape background <- crs$background # Plots the crystalline area of a XRD pattern xrdplot(pattern=original, background=background)# Convert data frame to matrix, select A-type starch pattern <- as.matrix(t(XRD[, c("Bragg_angle","A")])) # List of crystallinity components crs <- crystMW(pattern, N = 11, iter = 100) # Original matrix original <- crs$original # Background shape background <- crs$background # Plots the crystalline area of a XRD pattern xrdplot(pattern=original, background=background)