Baseline corrections derivatives

Selected entries from Methods in Enzymology [vol, page(s)j Boundary analysis [baseline correction, 240, 479, 485-486, 492, 501 second moment, 240, 482-483 time derivative, 240, 479, 485-486, 492, 501 transport method, 240, 483-486] computation of sedimentation coefficient distribution functions, 240, 492-497 diffusion effects, correction [differential distribution functions, 240, 500-501 integral distribution functions, 240, 501] weight average sedimentation coefficient estimation, 240, 497, 499-500. 

Figure 3.14. Wbise-free data with a baseline offset before (a) and after (b) baseline correction using a simple difference derivative.

FIGURE 5.38. Estimated spectrum of component B (solid line) with the 2-sd deviation band (dashed lines), derived from data without baseline correction. 

Hippe et al. discussed numerical operations for computer processing of (gas) chromatographic data. Apart from a baseline correction method, a method of reco -tion of peaks is described. The relationship between the convexity of an isolated peak and the monotonic nature of its first derivative is used to find the most probable deflection points. The munber of maxima and shoulders are used for a decision if the segment of the chromatogram contains an isolated peak or an unresolved peak complex. The number of shouders and maxima determine the total number of component peaks. 

Morton and Stubbs method (and the method using derivative curves, cf. 11.18) allows an efficient baseline correction if it is assumed that absorption varies linearly in the measurement range. Thus, in the situation represented in Fig. 11,24a, it is essential for quantification to correct absorbance A2 at the maximum X2 by subtracting the values indicated as x and y ... 

Thus, the derivative can be evaluated at any temperature by dividing the baseline-corrected excess heat capacity, ACP(T), by the integrated enthalpy A /f. By substituting this result into equation (16.19) one obtains... 

In this section, we present the development of an automated protocol for prostate tissue histology [164] from infrared spectroscopic imaging data as an example of the techniques described (Fig. 8.11). The data is three dimensional with x-y—axes representing the image plane and the 2-axis representing the spectral dimension. After data acquisition, two important pre-processing steps, namely baseline correction and de-noising, are performed. Since the entire data set is derived from human tissue samples, the spectra have similar characteristics and, therefore, a manually chosen set of pre-defined wave number could be used as the reference points for baseline correction. It is... 

The previously discussed standardization methods require that calibration-transfer standards be measured on both instruments. There may be situations where transfer standards are not available, or where it is impractical to measure them on both instruments. In such cases, if the difference between the two instruments can be approximated by simple baseline offsets and path-length differences, preprocessing techniques such as baseline correction, first derivatives, or MSC can be used to remove one or more of these effects. In this approach, the desired preprocessing technique is applied to the calibration data from the primary instrument before the calibration model is developed. Prediction of samples from the primary or secondary instrument is accomplished simply by applying the identical preprocessing technique prior to prediction. See Section 5.9 for a brief overview of preprocessing methods and Chapter 4 for a more detailed discussion. A few methods are briefly discussed next. 

Tablet spectra must usually be corrected for baseline shifting prior to analysis. Many techniques have been attempted, but second-derivative and multiplicative scatter correction calculations are most common. This baseline correction is critical even if an average tablet spectrum is used.

FIGURE 21 Dissolution profiles for buffered aspirin tablets obtained with the fiber-optic dissolution system (260-350 nm) and manual sampling with HPLC analysis. The dissolution was performed with USP apparatus 2 at 75 revolutions per minute. A second-derivative baseline correction was performed on the fiber-optic raw spectral data to correct for scattering due to the turbid solution. 

In this chapter we began by looking at the various ways in which a spectrum can be manipulated in order to carry out quantitative i analysis. These included baseline correction, smoothing, subtraction, derivatives, deconvolution, and curve-fitting. 

Li, N., Li, X.Y., Zou, Z.X., Lin, L.R, Li, Y.Q. (2011). A Novel Baseline-correction Method for Standard Addition Based Derivative Spectra and its Applications to Quantitative Analysis of benzo(a)pyrene in Vegetable Oil Samples, Analyst,... 

The various ways in which a spectrum can be manipulated in order to carry out quantitative analysis were examined. These included baseline correction, smoothing, derivatives, deconvolution and curve-fitting. The Beer-Lambert law was also introduced, showing how the intensity of an infrared band is related to the amount of analyte present. This was then applied to the simple analysis of liquid and solid samples. Then followed a treatment of multi-component mixtures. An introduction to the calibration methods used by infrared spectroscopists was also provided. 

General (DTA, DSC, TG, TMA, DMA) Variation of signal amplitude Signal and temperature calibration Accumulation and storage of data Baseline smoothing" Display and calculation of transition temperatures Display of multiple curx es Curve subtraction Derivative TA curve Baseline correction"... 

Plugge and van der Vlies have discussed the conformity index (Cl) for NIR analysis of ampicillin trihydrate [12,13]. The Cl is a metric used to determine the degree of conformity of a sample or batch with standards of known and acceptable quality. To use the Cl, reference spectra are first collected and baseline-corrected using a second-derivative or multiplicative scatter correction (MSC) spectrum. At every wavelength across the spectrum, the average absorbance and standard deviation are calculated for the baseline-corrected reference spectra, resulting in an average spectrum and a standard deviation spectrum. 

Figure 16-1 shows a typical output from a commercial IR spectrophotometer. Although the y-axis is shown as linear in transmittance, modern computer-based spectrophotometers can also produce spectra that are linear in absorbance. The abscissa in this spectrum is linear in wavenumbers with units of reciprocal centimeters. A wavelength scale is also shown at the top of the plot. Computer-based spectrophotometers can also produce a variety of other spectral formats such as linear in wavelength, baseline corrected, and derivative and smoothed spectra,... 

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