Table 2.

Common pitfalls in quantitative and qualitative interpretation of data from botanical extracts

1.	Assuming that relative peak intensities in a chromatogram represent relative concentrations in the sample.
	Do not assume that a large peak means a high concentration of analyte in an LC-MS or LC-UV chromatogram. Instead, recognize that they reflect the responsiveness of the analyte to the detector, i.e. its ionization efficiency (for MS) or its molar absorptivity (UV). One approach to circumvent this problem is to use an evaporative light scattering detector (ELSD) or charged aerosol detector (CAD) 153, 154. The response of these detectors closely reflects relative abundance of analytes in the sample, but they are less sensitive than MS or UV.
2.	Attempting to quantify analytes without reference standards.
	Because response of the detector (mass spectrometer or spectrophotometer) depends on structure, an authentic standard should be used to quantify the unknown of interest.
3.	Assuming that the absence of a constituent in the data means an absence of the compound in the sample.
	Failure to observe a compound in the data means only that it was not detectable by the technique used above a specific stated limit of detection. It does not mean that the analyte was absent from the sample. Including a positive control can help address this problem. If the analyte of interest is detectable in the positive control but not in the sample, the analyte likely is absent from the sample (above the limit of detection).
4.	Overstating the accuracy to which a concentration is known.
	Absolute quantitation (knowledge of the true amount of a given compound in a botanical sample) is difficult to achieve. Factors such as inefficient extraction, lack of purity in the standard, and drift in instrument response make knowledge of true absolute concentration extremely difficult to assess. Avoid chasing perfect and absolute quantitation when relative or approximate quantitation will be sufficient. On the other hand, knowing that most quantitative measures are not as absolute as the reports may imply, avoid the pitfall of comparing samples from different runs or different laboratories when the results may be different due to factors inherent in the analysis. Include appropriate replicates, references and controls in each experiment such that comparison among experiments is possible. Report the concentration of a given analyte with its associated uncertainty and to the correct significant figures.
5.	Assuming confirmation of identity with MS data.
	Even if appropriate standards are used to match retention time and fragmentation patterns of unknown compounds in a sample, mass spectrometry data does not confirm configuration of stereoisomers. NMR is needed for such confirmations. However, depending on the needs of the study, knowledge of configuration of stereoisomers may not be necessary, and MS data may be sufficient.
6.	Extrapolating results beyond the linear range of the calibration curve.
	Always dilute samples so that the analyte of interest falls within the linear range of the calibration curve. Failure to do so may result in serious underestimation of analyte concentration. Errors also result from attempting to quantify analytes present at too low of a concentration, i.e. below the limit of quantification for the analytical method.
7.	Failing to account for matrix interference.
	Matrix interference occurs when the matrix (everything but the analyte in the sample) alters the response of the analyte. This issue can be particularly pronounced with mass spectrometry as an analytical method. The best strategy for avoiding matrix interference is to dilute the sample as much as possible and subject it to chromatographic separation prior to analysis. A validation check that involves spiking the sample with a standard and comparing its response in matrix and solvent is necessary to check for matrix interference.95
8.	Assuming a sample is “pure” based on LC-UV data.
	When interpreting LC-UV data, it is important to remember that contaminants will not be detectable unless they absorb light in the region used for the analysis. Quantitative NMR represents an alternate method to determine purity.155
9.	Assuming that each peak in an LC-UV chromatogram represents a single compound.
	Multiple compounds in a complex sample may coelute in what appear as a single peak. Thus, one peak does not necessarily mean one compound. MS detection can be used to identify coeluting compounds if they differ in mass. Examination of UV spectra at multiple retention times across a single chromatographic peak can also aid in detecting coeluting compounds.
10.	Assuming that each peak in the mass spectrum represents a different ion.
	Clustering and in-source fragmentation in mass spectrometric analysis often lead to multiple masses that represent a single ion. Identifying the true “molecular ion” can be difficult. Software packages such as RamClust156 and IntelliXtract157 can help assign identities of clusters and fragments and group associated ions.