The effect of different baseline estimators on the limit of quantification in chromatography

✍ Scribed by David A. McNulty; Halliday J. H. MacFie

• Publisher: John Wiley and Sons
• Year: 1997
• Tongue: English
• Weight: 198 KB
• Volume: 11
• Category: Article
• ISSN: 0886-9383
• DOI: 10.1002/(sici)1099-128x(199701)11:1<1::aid-cem429>3.0.co;2-v

✦ Synopsis

The ASC guidelines published in 1980 (ASC Committee on Environmental Improvement, 'Guidelines for data acquisition and data quality evaluation in environmental chemistry ', Anal. Chem. 52, 2242-2249 (1980)) define the limit of quantification between a signal and its notional zero (baseline), i.e. the value of the signal without an analyte, as ten times the standard deviation of the signal's noise. If the value of the blank signal is estimated, the limit of quantification is dependent upon the variability of the estimated baseline rather than a simple multiple of the noise. It is shown that the limit of peak quantification (via numerical integration) of a Gaussian peak on an arbitrary background is strongly dependent upon the baseline estimator. In particular a peak should have a signal-to-noise ratio of approximately 60 : 1 using a linear baseline estimator and 10 : 1 for a cubic baseline estimator. Further, the expected standard deviation of peak parameters obtained via curve fitting is inflated by a factor of seven for a linear baseline estimator and two for a cubic baseline estimator.