Variations in Cannabinoid Reporting: Part Two

In this series of contributor articles, Savino Sguera of Digamma Consulting explores the reasons that laboratories may report different cannabinoid and terpene profiles for similar samples. There are many steps in sample testing and collection that can go wrong or can be intentionally manipulated, and Savino is here to guide us through the process.

Want to read the first article? Click here.

The following is an article produced by a contributing author. Growers Network does not endorse nor evaluate the claims of our contributors, nor do they influence our editorial process. We thank our contributors for their time and effort so we can continue our exclusive Growers Spotlight service.

Variations in Cannabinoid Reporting: Part Two

Based on a presentation to the American Chemical Society Fall Conference, 2016

by Savino Sguera


Savino Sguera of Digamma consulting continues his analysis on the reasons why cannabinoid and contaminant reporting can vary heavily in the cannabis industry. Click here to see part one!

Calibration and Reference Standards

Instrument calibration is the process of generating what is called a calibration curve. A calibration curve is a slope that relates the instruments response to established values.

When an instrument is first installed, its response to chemicals needs calibration. The instrument is calibrated by running a series of standards, chemicals with a precisely known concentration. These series of standards produce a slope that sets the instruments’ response to known amounts of the chemical being analyzed. At this point, an unknown concentration can be run through the instrument and can compared against the slope to pinpoint the precise concentration of chemicals in the unknown sample. This is how all client samples are run by an analytical lab, as all client samples are treated as a sample of unknown concentration until the laboratory releases their report on them.

If calibration is performed properly, a laboratory’s reporting of an unknown sample will be very accurate. But if the calibration is slightly off, the potential to report incorrect values for unknown solutions becomes very high.

The main source of erroneous calibrations are the standards. If a lab has an accurate standard, it will generate an accurate curve. If this standard is higher in concentration than the label value of the standard, it will generate a curve that skews unknowns to lower values. If the standard is lower in concentration than the label value of the standard, it will generate a curve that skews unknowns to higher values.

Figure 2: A graph illustrates how a 25% degradation of the calibration standard produces a 33% increase in final results reported. The black line represents a calibration curve generated with a proper standard of 1000 ug/ml, the red line represents a calibration curve generated with a degraded standard of 750 ug/ml. The properly calibrated machine measures the unknown sample correctly as 800 ug/ml, and the improperly calibrated machine measures 1067 ug/ml.

An example is illustrated in Figure 2. The black line represents a calibration curve created with no errors. The black curve is generated off a standard labeled at 1000 ug/ml and with a true value of 1000 ug/ml. When an “unknown” standard with a true value of 800 ug/ml is tested against the black curve, it generates a value of 800 ug/ml.

Next look at the red calibration curve. This curve was generated using a standard which was labeled at 1000 ug/ml but with a true value of 750 ug/ml. This results in an erroneous calibration curve, and when an “unknown” sample with a true value of 800 ug/ml is run against it, it reports a value of 1067 ug/ml. That’s a 33% increase when compared to the black calibration curve. The red curve’s standard was 25% lower than the label value of 1000 ug, and caused a 33% increase over the value reported by the black calibration curve.

Standards can be lower than their label value for a variety of reasons, but the source of problem can be determined. A retailer of reference standards typically has certificates of precision for their products, and they can trace the sample back to the manufacturer with ease by lot and batch number. Most discrepancies between the true value and label value of a standard occur after the standard has been shipped from the manufacturer to the client laboratory. It is up to the laboratory to ensure that the standard is correct and consistent with previous standards in addition to being consistent with the same standard from a second manufacturer.

The most common reason that a standard would be at a lower concentration than the label value is due to degradation. THCA degrades above room temperature to THC easily. Labs can prevent this degradation by ensuring that standards are delivered to laboratories on on dry ice to prevent heat based degradation, and stored in a -20 C freezer.

Editor’s Note: Standards may eventually degrade even when used under appropriate conditions! Make sure that the standard is replaced and tested against on a regular basis.

Other sources of standard manipulation may be intentional. By adding excess solvent, even a drop, to a certified reference standard, a dishonest person can lower the concentration of chemicals in the standard through dilution. This increases the reported results and is very difficult to detect. Some labs may attempt to manipulate their standards and then attempt to use standard manufacturers’ certificates of precision as a legal defense. Though this manipulation can be very difficult to detect, a skilled administrator can discern when manipulation is present by cross-checking the manufacturer’s certificates against the laboratories result and as well by cross-checking the results of one lab with those of others for the same sample.

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About the Author

Savino Sguera is founder and CSO of Digamma Consulting. Since 2010 he has been an analytical chemist and researcher in the cannabis industry, working with both private and public interests to bring scientific integrity to the business. Savino holds a B.Sci. in Biomedical Engineering from Columbia University.