Pinning Down Tailing Peaks, Part 2: Quantitative Measurement -

Pinning Down Tailing Peaks, Part 2: Quantitative Measurement

Oct 1, 2009
By: John V. Hinshaw
LCGC Europe
Volume 22, Issue 9

In the world of practical chromatography, peak shapes only approach an ideal Gaussian statistical distribution. Solute band shapes are perturbed by extracolumn volumes, nonideal retention processes and strong adsorptive interactions as they move from inlet to column to detector. The first instalment in this series discussed some reasons for the appearance of distorted peak shapes in gas chromatography (GC) and presented various ways of expressing the degree of peak tailing.¹ Beyond just cosmetic appearance, however, chromatographers have good reasons for concern over the effects of peak tailing: distorted peak shapes affect the measurement of peak height and area and they degrade the resolution of adjacent solutes. The extent of these effects depends not only upon the degree of peak tailing, but also on the size of peaks relative to the noise level and baseline drift, as well as in relation to each other. Significant peak tailing increases uncertainties as a result of noise and drift; even large isolated peaks can be misquantified when they tail. This "GC Connections" instalment discusses the effects of tailing on the quantitative measurement of single peaks.

Of course, few peaks stand alone in complete resolution from their neighbours. The determination of the size of partially merged symmetrical peaks is a difficult task that is complicated by disparities in peak sizes as well as by peak tailing. Selective response such as that provided by diode-array detection (DAD) or mass-selective detection (MSD) can deconvolve merged peaks, but when provided with nonselective detection methods analysts must resort to baseline approximations. This will be the subject of a subsequent instalment.

Which Peak Tailing Measurement to Use?

The previous instalment¹ presented several peak tailing measurements: the ratio of peak back to front widths at a percentage of the peak height, a related pharmacopoeial measurement, the ratio of the back and front peak areas and some statistical determinations. Back to front ratios are the simplest and most widely recognized expressions of peak asymmetry — this metric, taken at 10% of the peak height, is used in this instalment.

For the interested reader, Ettre wrote about the origins and significance of various peak tailing measurements in LCGC North America in 2003.²

Measuring the Size of Tailing Peaks

A 2004 "GC Connections" instalment³ discussed the basics of peak detection with chromatography data systems. In that article, synthetic generated peak areas were measured as a function of the size of the peaks in relation to their minimum detectable quantities (MDQ) and the noise level for peaks with constant asymmetries of 1.5, which were intended to model an average amount of peak tailing. This month's "GC Connections" extends the measurement of peak areas across a range of peak asymmetries in another paper experiment.

The determination of peak starting and ending baseline points for integration and height measurements is affected by peak tailing. Figure 1 illustrates what happens when peak tailing increases with a constant baseline — no noise, no drift. In Figure 1(e), an inset shows the peak magnified by 20 times in the y-direction. Peak detection found the end of the peak while a significant portion had yet to be eluted, so that a small area, filled in gray, is missing from the peak area measurement that spans the base points. Figure 2 is a graph of the measured peak area as a function of the peak asymmetry: at an asymmetry of 3.0 the measured peak area has decreased by 800 μV-s, or a little more than 5%, compared with a symmetrical peak.

Figure 1

The slight upward slope in the baseline is a minor effect compared with the loss of overall peak height as the asymmetry increases. The height of the strongly tailing peak in Figure 1(e) is slightly less than 50% of the height of the nontailing peak in Figure 1(a). The decrease in peak height affects quantitative measurements based upon peak height, but more importantly, it reduces the ratio of the peak height to the baseline noise — a measurement related to the signal-to-noise (S/N) ratio. The loss of peak height as asymmetry increases degrades the MDQ for a peak compared to the same substance if its peak shape were more symmetrical. A 50% loss in peak height translates to a 50% increase in the MDQ; this is a good reason to keep peak tailing under control.

Figure 2

In the case of a standalone peak on an otherwise flat baseline, the return of the second derivative to within a set threshold level is an indicator of baseline end, as shown in Figure 3. In this example, the threshold is set larger than optimum to accentuate its effect. The approach of peak derivatives toward their threshold levels on the back side of the peak is slower for all derivatives, including the first derivative (not shown), than is the initiation at the start of the peak.

Figure 3

The end of the baseline is found before the peak has been completely eluted, relative to how it is found at the start of the peak, because of the peak tail. This asymmetry in the derivative values, which reflects the asymmetry of the peak itself, causes its area to be underestimated unless further processing can be performed to revise the baseline endpoint. It would seem logical to select a much lower threshold setting to move the baseline end to a later time and reduce the area measurement shortage for the peak in Figure 1(e) compared with the peak in Figure 1(a). In fact, setting the threshold level 40 times smaller for the peak in Figure 1(e) does increase the measured area to 14934 μV-s, or within 0.5% of the area of the peak in Figure 1(a). The threshold choice has a strong influence when noise is present, as discussed later in this article.

There are many methods with which to determine the base points of a single standalone peak. One integrates the detector signal and compares the incremental area attributed to two or more data slices to an area threshold for peak start and stop. But in this case, the incremental areas attributed to individual data slices at the end of a tailing peak will be less than at the start and so the peak areas will again be underestimated if the threshold is too large. There are additional, more involved calculations and baseline corrections that many commercial chromatography data systems employ to help minimize the effects of peak asymmetry.

The extent of asymmetry-related effects will depend upon the data processing software, of which there are many flavours to be found in chromatography laboratories. The simple examples shown here are not intended to represent any particular data system: they are for illustrative purposes only. I found it easy to misconfigure, on purpose, one of the commercial systems by overriding the defaults to create a method that underestimated the areas of tailing peaks. The default settings did fairly well but the best results were obtained by using the onscreen interactive tools for configuring the system to process tailing peaks correctly. This involved setting appropriate detection thresholds and filtering parameters and the results were quite good. In any case, chromatographers should examine baseline allocations carefully and regularly. Do not settle for default data processing settings — use the built-in tools of your data system to optimize peak detection and measurement.