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The What, When, and How of Peak Integration: Part 3. How.

When confronted with a chromatogram which contains peaks which are difficult to integrate what can be done?  In this final installment we will look at the use of advanced integration options for integrating problematic peaks.

How to Integrate Problem Peaks?

In order to accurately quantify peaks try to avoid problems such as rising baselines and produce the best possible resolution between peaks.
In the real world rising baselines and resolution problems are often inevitable, therefore, spending some time familiarizing yourself with the advanced integration settings in your data system will allow you to properly integrate challenging chromatograms - these settings include threshold, slope sensitivity, baseline reset points, and different integration methods, such as, valley-to-valley.  Remember to always use the same integration method every time to provide consistent results (Figure 1).

Figure 1: Common peak integration errors.

As a reminder; each CDS will have its own unique set of parameters which can be used to integrate chromatographic peaks.  Table 1 details some of the common settings which can be found.1

Parameter Function
Sampling Rate (Peak Width)
  • Sampling rate in Hertz (number of data points per second) that the detector signal is sampled by the CDS
  • Some CDS may acquire at a high fixed rate of 100 Hz regardless of sampling rate setting
  • Faster chromatography (UHPLC or capillary GC) require higher sampling rates to correctly model peaks
Peak Threshold
(Detection Threshold or Slope Sensitivity)
  • Parameter used to determine if a peak is detected or not.  The peak start is determined when the value or slope selected is exceeded (start threshold)
  • Selecting too low a value results in integration of background noise.  Too large a value minimizes noise - this also results in small peaks not being identified and integrated
  • Some CDS will allow the use of a front and back slope setting
Smoothing (Bunching)
  • Adding several consecutive data points to obtain an average time slice value equivalent to a slower sampling rate
  • Can also be used to reduce noise in the chromatogram
Baseline Drift Tolerance
  • Determines how far the baseline may be from the original position at the end of the eluted peak
Minimum Area (Peak Area Reject)
  • Sets the minimum peak area or height for reporting peaks.  This parameter is independent of data acquisition and the integration method and applies only to the integrated peak areas
Integrate Inhibit
  • Disables integration for a specific period in each injection.  Typically used at the start of an injection to avoid solvent front effects or baseline perturbation
  • The first peak after the end of the inhibition period is typically defined as baseline regardless of what is happening
Height Reject
  • Height reject is used to set noise rejection.  All peaks whose heights are below this value will not be reported.
  • Specifies the algorithm for shoulder detection
  • Shoulders detected using the second derivative of the peak
  • Shoulders occur when two peaks are so close together that no valley exists between them.
Negative Peaks
  • Allows the detection of negative peak apices whose curvatures have the opposite sign of positive peaks

Let’ consider some of the types of integration methods which can be used, in particular, with poorly resolved peaks, when they can be used, and any errors associated with the integration results generated.

Drop perpendicular (Figure 2, image 1)

The drop method involves addition of a vertical line from the valley between the peaks to the horizontal baseline, drawn between the start and stop points of the peak group.  The drop perpendicular and Gaussian skim methods produce the least error in all situations (i.e. peaks of very different sizes). 

Errors when using the perpendicular drop method can occur under the following situations:

  • If the peaks are approximately the same size, and tailing or fronting is ignored, the amount of the peak tail from the first peak hiding under the second peak should be about the same as the amount of peak front from the second peak hiding under the first. If this is the case, the errors should cancel and peak areas should be fairly accurate.
  • If the second peak fronts significantly or if the first peak has a strong tail, the weighting will be distorted, with corresponding errors. If the peak ratio is large — for example, 20:1 — the larger peak will be little affected by the minor contribution of the smaller peak, but the smaller peak will have excess area contributed by the major peak. In this case, the accuracy for the larger peak should be much better than for the minor peak.
  • When the resolution between the peaks is so small that a clear valley is not present the perpendicular drop will grossly over-integrate the peak. A peak skim would be more appropriate in this situation.

Valley to valley (Figure 2, image 2)

Valley to valley sets start and stop points at the valley between the peaks, thus interpreting each peak separately.  This method consistently produces negative errors for both peaks and is, therefore, seldom an appropriate integration method.  However, if a known baseline disturbance is present under a set of eluted peaks, valley-to-valley may be suitable. In some gradient runs, there may be a small, broad rise in the baseline of blank runs that is consistent enough to allow valley-to-valley integration. In this case, however, the valleys between peaks should reach nearly to the baseline extended from before to after the peak group.

Tangential skim (Figure 2, image 3)

Skim methods separate the small peak from the larger parent peak with separate baselines.  The parent peak is integrated from its starting point to the apparent end of the peak group.  The baseline for small peaks starts at the valley between the peaks and ends where the signal nears the baseline.  Area under the skimmed peak is added to the parent peak not to the skimmed peak.  The skim methods generate significant error for the shoulder peak. 

Exponential skim (Figure 2, image 4)

Used to create curvature in the skim line to approximate the underlying baseline of the parent peak. 

Gaussian skim (Figure 2, image 5)

Also referred to as new exponential skim method, it is used to reproduce the Gaussian shape of the parent peak.   

When integrating small peaks on the tail of larger peaks a good rule of thumb is, if the minor peak is < 10% of the height of the major one, skimming the peak is the appropriate integration technique. If the minor peak is > 10% of the height of the major one, a perpendicular drop to the baseline connecting the true baseline before and after the peak group is best.

peak integration

Figure 2: Peak integration methods. 1) Drop perpendicular, 2) valley to valley, 3) tangential skim, 4) exponential skim, 5) Gaussian skim.

For most chromatographic analyses, peak areas are used for quantitative calculations, although in most cases equivalent results may be achieved with peak height.  Peak area is particularly useful with tailing peaks, because peak heights may vary but area will remain constant providing more repeatable results.  In some circumstances the use of peak height over peak area may provide more accurate quantitation.  For example, for trace analysis when the peak of interest is very small, peak height reduces error sustained in small changes in peak start and end time variation. 

For poorly resolved peaks (Figure 3) peak height may be a better integration option than peak area.  It can be seen that there is very little overlap of the peaks at the center where peak height is measured; however, peak area measurements would give a larger error due to the overlap and contribution to the area measurements from both peaks.

Comparison of peak integration using area and height

Figure 3: Comparison of peak integration using area and height.

It should be noted that peak area can change with variation in HPLC flow rate while peak height will not (Figure 4).  Furthermore, both peak height and peak area measurements will be irreproducible if injection volume varies.

Effect of HPLC flow rate on peak height and area

Figure 4: Effect of HPLC flow rate on peak height and area.

All integration results may vary depending on:

  • Resolution between peaks
  • Area and height of peaks
  • Position of the peaks relative to the principle peak or with respect to each other
  • Peak size
  • Complex baseline

Integration options are likely to generate significantly different analytical results, therefore, analysts must decide which approach provides the optimum accuracy and this method must always be applied to the integration of peaks in the specific method.  The best integration technique can be determined by analyzing a set of known samples, during or before validation, and collect data for both peak height and area using a variety of different integration methods and parameters. Calculate the results using both techniques and use the method that gives the most accurate and precise results.

Further Reading

Integration Problems »

Integration Errors in Chromatographic Analysis, Part I: Peaks of Approximately Equal Size »

Integration Errors in Chromatographic Analysis, Part II: Large Peak Size Ratios »


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Integration Parameters 1 »

Integration Parameters 2 »

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Chromatographic Method Validation »

Top 10 Features of a successful Chromatography Data System - Part 1 »

Top 10 Features of a successful Chromatography Data System - Part 2 »

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Dr. Dawn Watson

This article was written by Dr. Dawn Watson.

Dawn received her PhD in synthetic inorganic chemistry from the University of Strathclyde, Glasgow. The focus of her PhD thesis was the synthesis and application of soft scorpionate ligands. As well as synthetic skills, this work relied on the use of a wide variety of analytical techniques, such as, NMR, mass spectrometry (MS), Raman spectroscopy, infrared spectroscopy (IR), UV-visible spectroscopy, electrochemistry, and thermogravimetric analysis.

Following her PhD she spent two years as a postdoctoral research fellow at Princeton University studying the reaction kinetics of small molecule oxidation by catalysts based on Cytochrome P450. In order to monitor these reactions stopped-flow kinetics, NMR, HPLC, GC-MS, and LC-MS techniques were utilized.

Prior to joining the Crawford Scientific and CHROMacademy technical team she worked for Gilson providing sales and support for the entire product range including, HPLC (both analytical and preparative), solid phase extraction, automated liquid handling, mass spec, pipettes, and laboratory consumables.

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