Overlapping peaks evaluation

The height of the peak and area of the peak ai e traditionally used for calibration techniques in analytical chemistry. Peak maximum can also be evaluated by the height of a triangle formed by the tangents at the inflection points and the asymptotes to the peak branches. We propose to apply the tangent method for the maximum estimation of the overlapped peaks. 

Let us illustrate the method with a LC-UV-visible data set of three overlapping peaks (Fig. 34.10). The TFA results obtained with six candidate spectra, including the pure spectra are given in Fig. 34.11. The assignment of the right spectra by an evaluation of the correlation coefficients between input and output target is obvious. 

Fig. 10. Recorded reflectance curve with evaluation of fractionalized areas for determination of overlapping peaks 19>...

On-flow HPLC-NMR analysis can also be performed when sufficient material is available. It involves collecting the NMR data continuously as the sample passes through the probe. This is the most efficient method for stmcture evaluation by HPLC-NMR. The NMR data are represented in a 2-D plot where the x direction contains chemical shift information and they direction is representative of the LC retention time. The individual spectra can be extracted from the ID slices along the x axis if so desired. The resolutions in the individual spectra are of somewhat lower quality than in the stop-flow method however, the introduction of the second dimension allows for easy stmcture assignment even for overlapping peaks in the LC separation. As seen in Fig. 19, the on-flow HPLC-NMR characterization shows four distinct sets of resonances. 

To evaluate and optimize separation methods for overlapping peaks, there is a software tool called hilchromet. With hi chromet, the analyst has a tool for determining how well the chosen separation method in his chromatography data system really is it deals with symmetric as well as a symmetric peaks. 

X-ray spectra from real samples are complex. Their evaluation requires deconvolution of overlapping peaks and automatic background subtraction. Commercially available spectrum processing software fulfills these demands and, moreover, facilitates the operating procedures by use of a multi-channel analyser. 

With its unique deconvolution algorithms, AMDIS has proven its capabilities for the efficient removal of overlapping interferences in many GC-MS applications (Mallard and Reed, 1997). The deconvolution process is independent from the type of analyser and scan rate used to resolve overlapping peaks for substance identification as well as multi component residue analysis (Dimandja, 2004 Mallard et al., 2005 Zhang, Wu and Li, 2006). Without time-consuming manual data evaluation, AMDIS provides sensitive compound information even with complex background present (Halket et al, 1999). 

Our calculations show that the systematic errors for the evaluation of the triangle height are lower then for the peak height and peak ar ea. It is to be noted that tangent method allows estimating of the latent peak in the overlapped signals when peak area and peak maximum determination is impossible. 

After extraction, each phase may be studied independently in order to obtain a useful qualitative evaluation of the components in the original sample. The selectivity and specificity of fluorescence analysis can be especially beneficial in identification of PAHs. For example, some components could be identified by examining the fluorescence spectra of the organic and aqueous phases. Characteristic peak shapes may reveal identities of the components. For more complicated systems in which the spectra overlap, lifetime measurements may be used to identify components (27). 

Because of peak overlappings in the first- and second-derivative spectra, conventional spectrophotometry cannot be applied satisfactorily for quantitative analysis, and the interpretation cannot be resolved by the zero-crossing technique. A chemometric approach improves precision and predictability, e.g., by the application of classical least sqnares (CLS), principal component regression (PCR), partial least squares (PLS), and iterative target transformation factor analysis (ITTFA), appropriate interpretations were found from the direct and first- and second-derivative absorption spectra. When five colorant combinations of sixteen mixtures of colorants from commercial food products were evaluated, the results were compared by the application of different chemometric approaches. The ITTFA analysis offered better precision than CLS, PCR, and PLS, and calibrations based on first-derivative data provided some advantages for all four methods. ... 

This book is organized into five sections (1) Theory, (2) Columns, Instrumentation, and Methods, (3) Life Science Applications, (4) Multidimensional Separations Using Capillary Electrophoresis, and (5) Industrial Applications. The first section covers theoretical topics including a theory overview chapter (Chapter 2), which deals with peak capacity, resolution, sampling, peak overlap, and other issues that have evolved the present level of understanding of multidimensional separation science. Two issues, however, are presented in more detail, and these are the effects of correlation on peak capacity (Chapter 3) and the use of sophisticated Fourier analysis methods for component estimation (Chapter 4). Chapter 11 also discusses a new approach to evaluating correlation and peak capacity. 

GC data should be evaluated carefully. The main sterols of interest are cholesterol and lathosterol, the latter being a late-stage intermediate in cholesterol synthesis. Coprostanol is formed by the action of colonic bacteria on cholesterol and may vary considerably between mice. Peaks for coprostanol and other minor animal-derived sterols appear very close to, and may overlap with, that of cholesterol. Lathosterol is usually resolved between the cholesterol and the first phytosterol peak. Neutral sterol excretion should be reported as the sum of cholesterol, its precursors, and its derivatives. Evaluation excluding precursors is also appropriate. 

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