Processing chromatographic data

Data processing in chromatography falls into three areas  

collecting and processing detector signals to produce chromatograms and the raw data such as retention time, peak area and peak width  

collating and analysing data to produce qualitative and quantitative information and to generate reports for transmission and for archiving and 

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Chau, F.-T. and Leung, A.K.-M., Application of wavelet transform in processing chromatographic data, Data Handling Sci. Technol., 22, 205-223, 2000. 

There are two main requirements for processing chromatographic data, accurate digitisation of the analogue detector signal and software to process the data. The software includes algorithms for detections of peaks, correction for base drift, calculation of peak areas and retention time, concentrations of components using stored detector response factors and production of the final analytical report. 

Application of Wavelet Transform in Processing Chromatographic Data... 

The mixture is identical in each example. The peaks are shown separated by 2, 3, 4, 5 and 6 (a) and it is clear that a separation of 6a would appear to be ideal for accurate quantitative results. Such a resolution, however, will often require very high efficiencies which will be accompanied by very long analysis times. Furthermore, a separation of 6o is not necessary for accurate quantitative analysis. Even with manual measurements made directly on the chromatogram from a strip chart recorder, accurate quantitative results can be obtained with a separation of only 4a. That is to say that duplicate measurements of peak area or peak height should not differ by more than 2%. (A separation of 4a means that the distance between the maxima of the two peaks is equal to twice the peak widths). If the chromatographic data is acquired and processed by a computer, then with modem software, a separation of 4a is quite adequate. 

Good chromatographic data systems allow users to perform data processing online but asynchronously. This means that data acquisition for the next sample on the list starts directly and the processing of the prior sample starts as soon as computer resources are available. 

Metabolites formed during the decolourization of the azo dye Reactive red 22 by Pseudomonas luteola were separated and identified by HPLC-DAD and HPLC-MS. The chemical structures of Reactive red 22 (3-amino-4-methoxyphcnyl-/fhydroxyl-sulphonc sulphonic acid ester) and its decomposition products are shown in Fig. 3.92. RP-HPLC measurements were carried out in an ODS column using an isocratic elution of 50 per cent methanol, 0.4 per cent Na2HP04 and 49.6 per cent water. The flow rate was 0.5 ml/min, and intermediates were detected at 254 nm. The analytes of interest were collected and submitted to MS. RP-HPLC profiles of metabolites after various incubation periods are shown in Fig. 3.93. It was concluded from the chromatographic data that the decomposition process involves the breakdown of the azo bond resulting in two aromatic amines [154],... 

Gas chromatographic data was obtained on a Tracor Model 220 gas chromatograph equipped with a Varian Model 8000 autosampler. The analysis column was a 1.7 m "U column, 4 mm id, filled with 3% SP-2250 packing (Supelco, Inc., Bellefonte, PA) held at 200 C. The injection temperature was 250 and the nitrogen carrier gas flow rate was 60 mL/min. The detector temperatures were 350 for electron capture and 190 for flame photometric. Detector signals were processed by a Varian Vista 401 which gave retention times and peak areas. 

Note As is often the case, the HPLC system will be under computer control, which is likely to be part of a data-handling system. Since the data generated from the OQ hardware tests typically require chromatographic data handling, the data-handling software should be validated beforehand. The data-handlingfLC control software installation and IQ/OQ implementation, which are not addressed in this chapter, may take a considerable amount of time. This is often the case since this process typically involves an initial client/server implementation. 

Despite these advancements in chromatographic data processing, peak detection and integration algorithms were crude, the user interface was cumbersome, and there was very little flexibility in the types of reports that these systems could generate. 

Very popular is the Savitzky-Golay filter As the method is used in almost any chromatographic data processing software package, the basic principles will be outlined hereafter. A least squares fit with a polynomial of the required order is performed over a window length. This is achieved by using a fixed convolution function. The shape of this function depends on the order of the chosen polynomial and the window length. The coefficients b of the convolution function are calculated from ... 

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. 

Another significant application of GC is in the area of the preparation of pure substances or narrow fractions as standards for further investigations. GC also is utilized on an industrial scale for process monitoring. In adsorption studies, it can be used to determine specific surface areas (30,31). A novel use is its utilization to carry out elemental analyses of organic components (32). Distillation curves may also be plotted from gas chromatographic data. 

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