Methods of baseline correction

There are several methods that seek to correct this phenomenon by extracting from the absorbance measured what is not due to the analyte. These are in fact corrections made to the baseline from measurements undertaken at different wavelengths. 

Supposing that variations in the baseline could be represented by a function A = k . To find k and n, a region of the spectrum is located in which the analyte 

Substracting x and y from A2 leads to the calculation of the corrected absorbance, according to 

This last equation, which is independent of the concentration of the reference solution yields satisfactory results. This method requires only to have at one s disposal a spectrum of the pure compound. 

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Tliis concludes the discussion of baseline correction methods a summarv-and recommendation.s arc provided in Table 3.4. 

It is often necessary to determine the statistical error involved in this calculation, following the procedures given in Section 19.5. If the background count distributions around Ci and Ca appear to be horizontal, it is often advisable to take averages of several ehannels preceding the FEP and several channels following the FEP in order to obtain a more representative baseline correction. There are several more so-phistieated methods of baseline eorrection, but their discussion is beyond the scope of this ehapter. 

The aim of baseline correction is to separate the analyte signal of interest from signal which arises due to changes in mobile phase composition or stationary phase bleed and signal due to electronic noise. Several baseline correction methods have been proposed in literature. 

However, there are some methods that are reasonably automated to be used as part of a calibration model. The list of baseline correction methods presented in the following section is not exhaustive, and there are many other ways of autocorrecting the spectrum baseline as a chemometric preprocessing step. 

The generation of variable seismic excitation has been extensively studied. The method developed by Shinozuka (1971) remains the most popular. This method has been extended and modified by others to take into account nonstationarity of processes (Deodatis 1996). A spectral-representation-based simulation algorithm has been developed by Deodatis (1996). The simulation uses the coherency function and allows the generation of acceleration as well as displacement time histories. This latter is necessary while performing non linear structural analysis. A recent method developed by Benmansour et al. (2012) solves the problem of integrability of seismic motion to avoid the use of baseline correction. 

The BLC performs several different types of baseline leveling operations on a spectrum two-point level, multipoint level, function fit, interactive polynomial, or auto level. These five methods are capable of baseline correcting a wide variety of data. Note that in the two-point level and the multipoint level methods, the baseline is leveled at a value that is the average of the baseline points. This allows the methods to be applied to both transmission and absorbance spectra. For the interpretation of both nonpolarized and polarized IR spectra, the two-point and the multipoint methods are usually used. 

The IR spectra are finally analyzed to determine the effluent concentration from each reactor channel. The quantification of species concentration is performed using either univariate or multivariate calibration methods. For non-overlapping peaks, like CO, C02, and N20, we can use univariate calibration. This is simply performed by baseline correction, the peak areas and/or peak heights and then converting these values... 

Different baseline correction methods vary with respect to the both the properties of the baseline component d and the means of determining the constant k. One of the simpler options, baseline ojfset correction, nses a flat-line baseline component (d = vector of Is), where k can be simply assigned to a single intensity of the spectrum x at a specific variable, or the mean of several intensities in the spectrum. More elaborate baseline correction schemes allow for more complex baseline components, such as linear, quadratic or user-defined functions. These schemes can also utilize different methods for determining k, such as least-squares regression. 

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. 

Tlic first set of preprocessing tools discussed are those that operate on each sample. Table 3.1 lists the four methods discus.scd normalizing, weighting, smoothing, and baseline corrections. Norntalization can be used to remove... 

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. 

Phase 2 - data preprocessing. There are many ways to process spectral data prior to multivariate image reconstruction and there is no ideal method that can be generally applied to all types of tissue. It is usual practice to correct the baseline to account for nonspecific matrix absorptions and scattering induced by the physical or bulk properties of the dehydrated tissue. One possible procedure is to fit a polynomial function to a preselected set of minima points and zero the baseline to these minima points. However, this type of fit can introduce artifacts because baseline variation can be so extreme that one set of baseline points may not account for all types of baseline variation. A more acceptable way to correct spectral baselines is to use the derivatives of the spectra. This can only be achieved if the S/N of the individual spectra is high and if an appropriate smoothing factor is introduced to reduce noise in the derivatized spectra. Derivatives serve two purposes they minimize broad... 

The most accurate measurements of peak areas are those obtained by means of electronic data reduction with integrators or computers. The vast majority of laboratories now have electronic or computer methods for determining peak areas. Two main features are required for electronic processing of chromatographic data accurate digitization of the analog signal and software. The software is required for the detection of peaks, correction for baseline drift, calculation of peak areas, retention times, and concentrations of components in the sample, and production of the final report.5... 

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