Matrix interfering

The co-extraction of other matrix-interfering components with similar properties. 

Figure 16.24, Three tests devised by B rout man for testing the fiber/matrix interfate (a) shear test, (b) tension test, (c) friction test.

GC coupled with low-resolution MS (LRMS) provides the required sensitivity and selectivity for the determination of PCBs. Nevertheless, the use of high-resolution mass spectrometry (HRMS) at a resolution between 6000 and 10 000 in El mode allows complete removal of the contribution of matrix interfering compounds, achieving low limits of detection (20-100 fg). Therefore, this is the technique of... 

Two frequently encountered analytical problems are (1) the presence of matrix components interfering with the analysis of the analyte and (2) the presence of analytes at concentrations too small to analyze accurately. We have seen how a separation can be used to solve the former problem. Interestingly, separation techniques can often be used to solve the second problem as well. For separations in which a complete recovery of the analyte is desired, it may be possible to transfer the analyte in a manner that increases its concentration. This step in an analytical procedure is known as a preconcentration. 

When not enough is known about the matrix, absorption effects (7.3) cannot be estimated, and comparison of standard and unknown (7.8) may be unreliable. Somewhat less likely consequences of such lack of knowledge are errors due to interfering lines and to shifts in x-rav spectra, which can affect both the analytical-line intensity and the background (8.8). Sometimes a quick examination of all the characteristic lines that can be excited in a sample is helpful in giving useful knowledge about the matrix. 

Biological matrices are very complex apart from the analytes, they usually contain proteins, salts, aeids, bases, and various organie eompounds. Therefore, effeetive sample preparation must inelude partieulate eleanup to provide the component of interest in a solution, free from interfering matrix elements, and in an appropriate concentration. 

In 1978, Ho et al. [33] published an algorithm for rank annihilation factor analysis. The procedure requires two bilinear data sets, a calibration standard set Xj and a sample set X . The calibration set is obtained by measuring a standard mixture which contains known amounts of the analytes of interest. The sample set contains the measurements of the sample in which the analytes have to be quantified. Let us assume that we are only interested in one analyte. By a PCA we obtain the rank R of the data matrix X which is theoretically equal to 1 + n, where rt is the number of interfering compounds. Because the calibration set contains only one compound, its rank R is equal to one. 

More than one analyte can be quantified simultaneously in the presence of interfering compounds. The required measurements are identical to RAFA a data matrix X of the unknown sample and a calibration matrix with the analytes X. ... 

Z is a coefficient which relates the concentration of the analyte in the unknown sample to the concentration in the calibration standard, where = bc. R is a residual matrix which contains the measurement error. Its rows represent null spectra. However, in the presence of other (interfering) compounds, the residual matrix R is not random, but contains structure. Therefore the rank of R is greater than zero. A PCA of R, after retaining the significant PCs, gives ... 

Figure 3 Example of an untreated control chromatogram with the interfering peak (11) eluting at 18 min, solvent peaks (1-3), matrix component peaks (4, 7-10, 12), and instrumental noise (5, 13)...

A second problem was that some lots of control commodities contained one or more extractable interferences, i.e., co-extractives that interfered with one or more of the analytes for the particular commodity and could not be removed during cleanup. This problem was addressed by either using controls from different sources for specific analytes or by blending controls to obtain a matrix with a sufficiently low level of interference to allow accurate determination of recovery. 

The shape of the matrix peaks depends on the nature of the sample and also on the composition of the HPLC solvent system. For an HPLC column, a low level of detection requires that interfering peaks in the samples be minimal. 

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