Variations in Cannabinoid Reporting: Part Four
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!
Sampling is the process of of taking a representative sample of a product for chemical testing. In environmental laboratories, sampling is frequently performed by a certified third party sampling service, trained in the methodology of proper sample collection. These samples can be used for the detection of lead in drinking water or a mold outbreak in a residential property.
However, in the cannabis industry, the process varies by state jurisdiction. In Colorado, Massachusetts, and formerly California, cultivators or dispensaries drop off cannabis samples at the lab without any formal training. In Nevada and now California, the lab must go to the cultivation or manufacturing site and sample from their final cured product. Although no state has yet mandated third party sampling services, it would greatly aid in the precision and alignment of results between laboratories in that jurisdiction as it has in environmental, food, and drug testing.
The best sampling method can be determined by a statistician; many international shipping and large scale manufacturing companies employ them. One of the most practical approaches is random sampling, where samples are taken randomly from within the batch. This guarantees that while variation may occur from sample to sample, statistically the overall results are very close to the actual batch average. When intentional manipulation is afoot, selective sampling is often employed. This occurs when the sample is carefully selected from the whole of the batch to influence certain values in the lab report, such as maximizing cannabinoid potency or minimizing mold spore counts or pesticide levels. Below I will illustrate some of the different ways in which a sample may be biased.
Cannabis plants naturally have a gradient within them, with increasing THCA concentrations near the top of the plant. Figure 5 illustrates the cannabis plant’s potency gradient and distribution. As these buds are combined together into large batches, the differences should mix randomly and evenly. If buds from the top of each plant are placed into a separate container from other buds, it could be easily used to maximize the lab’s reported potency. This can be done with samples that are sent to the lab or the lab’s sampling technician fails to properly collect the samples.
Another critical issue is sample size. In Nevada, a 12 gram cannabis flower sample size has been written into the adopted regulations governing the medical cannabis businesses. In other less-regulated states, the sample size submitted is determined by the laboratory. Although labs can produce results with as little as 0.5 grams of cannabis flower, a larger sample size generally produces more precise and accurate results by assuring that the results are averaged across a large-enough amount of cannabis. A larger sample also allows for re-testing of the same sampled batch, should the need arise.
Sampling is not just performed in the field. When a 10 gram sample is sent to an analysis lab, technicians and chemists use smaller samples for each test. These samples should be also be randomly selected from the available product, weighed, and prepared for analysis. However, there is potential for a lab to influence the result via sampling. Labs can process cannabis flower to different degrees before testing for potency. This will influence or change the lab results and will inflate the reported lab’s values away from a true representation of the batch of flower in question.
Figure 6 shows a diagram comparing three different cannabis sample processing techniques, and how they influence the final number reported by the laboratory. This also illustrates why it is better for a third party or laboratory to collect samples, rather than rely on material sent by cultivators.
The first, and most accurate method, is testing the sample as received from the cultivator. Processing the sample before testing and removing things like stems at the laboratory will increase the final potency, but will push the reported result away from an accurate representation of the batch of cannabis flower in question. Further processing, as seen in Cannabis Sample Prep 3, involves grinding the product and filtering it through a sieve or kief screen, as discussed in the AHP guide. This removes large amounts of plant material with low THC content and causes the final reported number to be significantly higher, but moves the reported results very far away from what is representative of what the end consumer will receive.
HIV/AIDS and Medical CannabisJanuary 17, 2018
Ask DryGair: Ventilation vs. DehumidificationJanuary 16, 2018
Variations in Cannabinoid Reporting: Part FourJanuary 12, 2018
The Basics of Plant Spectral ResponseJanuary 11, 2018
Do you want to receive the next Grower’s Spotlight as soon as it’s available? Sign up below!
- Want to learn more about subjects touched upon in this article? Check out our articles on subjects such as:
- Inside Look at Leading AZ Extraction Company
- Variations in Cannabinoid Reporting Part One
- Treatise on Decarboxylation: Part One
- Treatise on Decarboxylation: Part Two
- Smoking vs Eating Cannabis: The Effects on Patient Health: Part One
- Smoking vs Eating Cannabis: The Effects on Patient Health: Part Two
- Smoking vs Eating Cannabis: The Effects on Patient Health: Part Three
- Variations in Cannabinoid Reporting: Part One
- Variations in Cannabinoid Reporting: Part Two
- Want to get in touch with Savino? He can be reached via the following methods:
Do you have any questions or comments?
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.