Baseline shifts

The ELSD is not plagued with the problem of baseline shift and is significantly more sensitive however it presents other disadvantages, such as the strong non-linearity of the detector response and the possibility of interference from non-volatile compounds in the sample matrix [87]. The HPLC method using traditionally reversed-phase solvents and a hybrid column/pre-column has demonstrated the separation of ethoxylated homologues of broadly distributed linear AEOs... 

The calibration experiments are performed with a constant amount of liquid inside the calorimetric vessel and, in this case, no baseline shift is observed between the initial and final periods. 

Suspended particles may cause a baseline shift in the spectrum as outlined above. The shift may be evaluated after an algorithm proposed by Huber and Frost ", yielding the turbidity (see also van den Broeke... 

The movement of a fiber-optic probe and/or the hbers leading to/from a probe or cell can also induce baseline shifts in the recorded spectra. These shifts are usually minor and can be eliminated with proper preprocessing of the data (e.g. derivatives). (A detailed description of preprocessing techniques can be found in Chapter 12)... 

As was pointed out in Section 4.2.1, the plot of absorbance versus concentration becomes less than linear beyond a threshold concentration due to non-negfigible interactions between absorbing molecules. The baseline shifts discussed above may equally give rise to deviations from Beer s Law. Upstone discusses fluorescence (which may be removed by inserting a cutoff filter between sample and detector) and peak shifts due to changes in pH. ... 

The NIR spectrum depends not only on the chemical composition of the sample, but also on some physical properties such as the size, form, particle distribution and degree of compression of the sample. This is useful in some cases as it enables the spectroscopic determination of some physical parameters of the sample. However, physical differences can lead to multiplicative effects in the spectrum, which, together with other additive effects such as baseline shift or chemical absorption, can complicate calibration models and detract from the quality of the results of quantitative analyses if not properly understood and accounted for. 

The use of second-derivative spectra eliminated the baseline shifts observed during the reaction (which could be due to changes in the amounts or size distribution of particles, or small amounts of probe fouling). 

Figure 1. The assignments of FTIR-RA spectra of unaged epoxy free and coated films on steel have been given previously ( ). It should be noted that this aged specimen exhibited extensive filiform corrosion after 7 months exposure. Figures 2 show the spectral changes at different exposure periods. These spectra have been normalized for the baseline shift resulting from the reflection change of the steel substrate due to exposure and corrosion.

In addition to chemical information, NIR spectra also contain information about the physical characteristics of samples and systems that can manifest itself, for example, as a baseline shift caused by scattering differences. On the one hand, this information is extremely useful in characterising particle size [102],... 

Because column performance decreases with age, it is important to keep good records of its performance. Entries useful to keep track of are chromatogram number, sample identification number, amount injected, volume injected, solvents used (A and B components), column characteristics (ID number, packing, size), back pressure, flow rate, detector setting (UV, absorbance units full scale at given wavelength), gradient conditions, results (retention time of desired product), remarks (baseline shifts, unusual wash profile, etc.), and date. 

Figure 2.9 and Table 2.1 summarize the effects of a number of common row pretreatments, discussed below, in correcting for unwanted signal variations such as addictive (baseline shifts), multiplicative (baseline drifts), and global intensity variation effects. 

After transformation, the mean value of each signal is equal to 0 for this reason, row centering removes systematic location differences, namely baseline shifts, from a set of signals, as it is shown in Fig. 2.9A. 

The first PC quantified the moisture content as evident from the strong contribution around 1930 nm region, which represents the combination band of the -OH stretching and -OH bending vibrations. The second PC quantified the baseline shift due to changing sample density as a result of changing compression pressures. The third PC quantified the changes in MCC structure as evident from its resemblance with NIR spectrum collected on the 100% MCC powder sample. The root mean-square errors of prediction for different sample properties are summarized in Table 14. 

Although these factors are fairly similar to those described in Chapter 3, there are some relevant differences. In effect, in PCA (and hence in PCR), the factors explain most of the variance in the X-domain regardless of whether such variance is or is not related to the analyte, whereas in PLS they are calculated so that they explain not only variance in the spectral variables but also variance which is related to the property of interest. A typical example might be a series of graphite furnace measurements where a baseline shift appears due to some... 

Some integrators may have a facility that can override the automatic logic of the microprocessor to fit such special circumstances, such as unavoidable baseline shifts, special treatment of certain fused peaks or of "negative peaks."... 

Figure 11.6 Influence of solid pigments on the NIR absorbance spectra of colored polypropylene carpets. Note that as the carpets change from dark blue (bottom trace) to cream color (top trace) the baseline shift increases, the baseline tilt increases, and the intensity of the absorbance peaks decreases. Reprinted with permission from Rodgers (2002).7...

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