with a sufficient precision, needs a minimum signal-to-noise ratio of 9–10. To be
accurate, the S/N ratios are calculated by the average values of the noise race and the
addition of the corresponding standard deviations multiplied by factors of 3 for LOD
and 9 (or sometimes 10) for LOQ. The S/N ratio approach can be applied to analyses
of standard solutions revealing the sensitivity of the analytical systems (as also valid
for the calibration curve approach). But measurements of real samples considering
the matrix effects can also be used. This works sufficiently for samples with more or
less homogenous matrices, but it is a huge challenge to calculate LOD or LOQ
values for analyses of very heterogenous sample sets. Here, the matrix affects
heavily and the noise level and, consequently, the calculated S/N ratios. In these
cases, the LOQ can only be estimated by a thorough evaluation of all measurements.
To present data correctly, for all measurements with no signals or signals below
the LOD the term ‘not detected’ or ‘n.d.’ should be used. If a signal falls between the
both threshold values, the compound is identified or detected but cannot be quantified. Here, the usage of the term
joint approach, the determination of recovery rates (see Fig. 6.2). For this purpose,
precleaned or ultra-pure matrices (e.g. calcinated sea sand as substitute matrix for
sediment or soil samples) are spiked with defined amounts of the target analytes.
Then, the spiked samples are processed in the same way as the real samples and get
analyzed. To calculate the recovery rate, the determined concentrations or amounts
are related to the original spiked amounts or concentrations. These values reflect all
losses during the analytical process. High recovery rates provide evidence for a
sufficient accuracy of the method and can be used for correction of the values
determined for the real samples. Such correction can also be achieved in a very
smart way, if an internal standard calibration method is used. Adding the internal
standard directly to the sample (water, soil, sediment, oil, . . .) prior to any analytical
handling allows to determine indirectly all losses during the analytical procedure.
Assuming the same loss for both target analyte and internal standard, the recovery
rate is automatically considered by the calibration.
Another approach to correct losses and inaccuracies e.g. during evaporation or
injection volumes, is the usage of surrogate standards (see Fig. 6.2). They are used
similar to internal standards but are not applied for calibration. They are added to the
original sample or individual fractions with known concentrations are traced through
the analytical procedure till quantitative measurement. The discrepancy between
initially added amount and finally determined one can also be used as correction
factor to consider inaccuracies during the various process steps (extraction, fractionation, evaporation . . .).
Finally, the reproducibility or the variance of results can be evaluated by multiple
recovery rate determination. Beside the average values (pointing to accuracy) the
standard deviation reflects the reproducibility. Both parameters together characterize
the precision as one key parameter assessing the quality of quantitative analyses.
6 Analytical Quality Control
131
accurate, the S/N ratios are calculated by the average values of the noise race and the
addition of the corresponding standard deviations multiplied by factors of 3 for LOD
and 9 (or sometimes 10) for LOQ. The S/N ratio approach can be applied to analyses
of standard solutions revealing the sensitivity of the analytical systems (as also valid
for the calibration curve approach). But measurements of real samples considering
the matrix effects can also be used. This works sufficiently for samples with more or
less homogenous matrices, but it is a huge challenge to calculate LOD or LOQ
values for analyses of very heterogenous sample sets. Here, the matrix affects
heavily and the noise level and, consequently, the calculated S/N ratios. In these
cases, the LOQ can only be estimated by a thorough evaluation of all measurements.
To present data correctly, for all measurements with no signals or signals below
the LOD the term ‘not detected’ or ‘n.d.’ should be used. If a signal falls between the
both threshold values, the compound is identified or detected but cannot be quantified. Here, the usage of the term
joint approach, the determination of recovery rates (see Fig. 6.2). For this purpose,
precleaned or ultra-pure matrices (e.g. calcinated sea sand as substitute matrix for
sediment or soil samples) are spiked with defined amounts of the target analytes.
Then, the spiked samples are processed in the same way as the real samples and get
analyzed. To calculate the recovery rate, the determined concentrations or amounts
are related to the original spiked amounts or concentrations. These values reflect all
losses during the analytical process. High recovery rates provide evidence for a
sufficient accuracy of the method and can be used for correction of the values
determined for the real samples. Such correction can also be achieved in a very
smart way, if an internal standard calibration method is used. Adding the internal
standard directly to the sample (water, soil, sediment, oil, . . .) prior to any analytical
handling allows to determine indirectly all losses during the analytical procedure.
Assuming the same loss for both target analyte and internal standard, the recovery
rate is automatically considered by the calibration.
Another approach to correct losses and inaccuracies e.g. during evaporation or
injection volumes, is the usage of surrogate standards (see Fig. 6.2). They are used
similar to internal standards but are not applied for calibration. They are added to the
original sample or individual fractions with known concentrations are traced through
the analytical procedure till quantitative measurement. The discrepancy between
initially added amount and finally determined one can also be used as correction
factor to consider inaccuracies during the various process steps (extraction, fractionation, evaporation . . .).
Finally, the reproducibility or the variance of results can be evaluated by multiple
recovery rate determination. Beside the average values (pointing to accuracy) the
standard deviation reflects the reproducibility. Both parameters together characterize
the precision as one key parameter assessing the quality of quantitative analyses.
6 Analytical Quality Control
131