Calculator
Example data table
| Sample | y_max | Baseline | Direct height | Noise RMS | SNR |
|---|---|---|---|---|---|
| A | 125.4 | 10.2 | 115.2 | 0.8 | 144 |
| B | 86 | 12.5 | 73.5 | 1 | 73.5 |
| C | 240.1 | 18.9 | 221.2 | 1.6 | 138.25 |
Formula used
For a peak apex signal y_max and baseline at the apex b(x):
Height = y_max − b(x)
If baseline drifts with position/time x:
b(x) = b0 + m·x
For a Gaussian peak with area A and full width at half maximum FWHM:
H = 2A·√(ln 2) / (FWHM·√π)
For a Lorentzian peak (area A, width FWHM):
H = 2A / (π·FWHM)
SNR = Height / Noise_RMS
If you have a linear calibration (C = (Height − intercept)/slope), the dilution factor multiplies concentration.
How to use this calculator
- Pick a signal unit that matches your chromatogram or spectrum.
- Enter the apex value (y_max) from your peak report.
- Select a baseline mode:
- Constant: enter a baseline value near the peak.
- Linear: enter intercept, slope, and the peak position/time.
- Optionally add noise RMS to compute SNR for method validation.
- If your software provides area and FWHM, enter them to estimate height by model.
- To convert height into concentration, add calibration slope/intercept and dilution.
- Click Calculate. Results appear above the form.
- Use Download CSV or Download PDF to export the report.
Baseline selection and drift control
A stable baseline is the foundation of any peak-height report. For short windows, a constant baseline near the peak is often adequate. For drifting traces, use the linear option and enter b0, slope m, and the apex position x. A practical check is baseline drift per minute: values above 2% of expected peak height can bias quantitation. If drift is present, shorten integration windows or improve equilibration fully.
Peak apex integrity checks
Peak height assumes the apex is correctly captured and not clipped by detector range. Review raw data for flat tops, spikes, or missing points around the maximum. A simple sanity metric is the “apex neighborhood” ratio: average of the two adjacent points divided by y_max. Ratios below 0.90 may indicate noise-driven maxima; smoothing or higher sampling rates can help. In chromatography, confirm retention time is within your suitability window before comparisons.
Area-to-height model guidance
When area and FWHM are available, the calculator estimates height using Gaussian or Lorentzian relations. Gaussian fits many chromatographic peaks, while Lorentzian is common for resonance-dominated spectral lines. Compare the model height with the direct height; differences within ±5% typically indicate consistent integration and shape. Larger differences suggest tailing, fronting, or incorrect width measurement. If peaks overlap, rely on deconvolution or report model choice explicitly.
Signal-to-noise for method suitability
SNR links peak visibility to method performance. Using RMS noise from a quiet region, SNR = Height/Noise_RMS. Many laboratories target SNR ≥ 3 for detection and ≥ 10 for quantitation, though requirements vary by SOP. Track SNR; a 20% drop can signal lamp aging, column fouling, or injection issues. Use the absolute-height option for inverted or negative peaks. Keep the noise window length consistent to avoid SNR changes.
Reporting and comparability across runs
For trending, keep units, baseline mode, and scaling consistent across batches. If dilution is applied, report both the measured height and the final concentration estimate so audits can reproduce calculations. Record the selected shape model and FWHM source (software or manual). Exporting CSV helps build control charts for height, SNR, and percent difference, supporting routine suitability checks. Add batch IDs and sample IDs to your exported files.
FAQs
1) What is peak height in this calculator?
Peak height is the apex signal minus the baseline at the apex. You can use a constant baseline or a linear baseline b(x)=b0+m·x to account for drift, then apply an optional scale factor.
2) When should I choose constant vs linear baseline?
Use constant when the baseline is flat around the peak. Choose linear when the trace drifts over time or position, and you can estimate an intercept, slope, and the apex x-value.
3) Why is my area-based height different from the direct height?
Area-to-height assumes an ideal peak shape and an accurate FWHM. Tailing, fronting, overlap, or incorrect width selection can shift the estimate. The percent difference helps you spot integration or model mismatches.
4) How do I compute SNR here?
Enter Noise RMS from a quiet region near the peak. The calculator reports SNR as Height/Noise_RMS. Keep the noise window consistent between runs so the ratio reflects real performance changes.
5) How does concentration estimation work?
If you provide a linear calibration, concentration is computed as (Height − intercept)/slope, then multiplied by the dilution factor. Ensure slope units match your chosen signal and concentration units.
6) Can I use this for negative or inverted peaks?
Yes. Enable the Absolute height option to report magnitude. Leave it off if the sign is meaningful for your method, such as differential signals or baseline-corrected spectroscopy.