Data processing baseline correction

Some extensions are not essential for CC, but greatly improve its capabilities. Interfaces to a data storage device and to a hard copy unit are valuable. Some facility for data processing afterwards (baseline correction and peak area determination) is desirable. 

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. 

Try out the effect of several modes for DC correction available with 2D data. Load the raw data of the magnitude mode 2D COSY spectrum D NMRDATA GLUCOSE 2D HH GHHCO 001001.SER and choose no, quad and qpol as BC mod in F2. Note that usually for Fl no baseline correction is applied in the time-domain, i.e. BC mod (F1) = no. Fourier transform the data and store the individual spectra using ascending processing numbers. Compare corresponding rows to inspect the effect of different baseline corrections. 

After processing in the time domain, Fourier transformation, phasing and basic processing (calibration, peak picking, integration) ahs been performed, additional processing steps to improve spectral quality are at your disposal. This includes operations common to both ID and 2D spectra e.g. baseline correction in the frequency domain, as well as operations specific to these different type.s of data sets. 

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 data processing can be divided into three phases. Phase 1 is the removal of poor quality spectra with an automated routine. Phase 2 is the data preprocessing of the spectra, which passed the quality test. This usually entails some type of baseline correction and normalization process. Phase 3 is multivariate image reconstruction where the spectra are classified and reproduced as color points... 

Data Analysis. After each experiment, the data files were processed in two steps. The first step consisted of correcting the raw data for baseline offset and calculating the lower order moments of the elution curve. This was achieved with an interactive graphics routine that allows estimation of the baseline and the range of the elution peak. The second step was determining the Fourier domain estimation of the parameters (2). The value of a and P determined by the moment analysis were used as initial estimates. 

The signal quality (= low detector noise) and sample rate should be sufficiently high to obtain correct results, otherwise post processing of the data is necessary, such as smoothing, baseline correction, etc. Even then the result of the integration in Eq. 6.126 depends very much on the extension of the baseline, and the obtained value of the second moment can be very inaccurate (Chapter 2.7, Section 6.5.3.3). 

Baseline drift correction is an indispensable part of a good chromatographic data processing procedure. The following questions have to be answered ... 

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