Are There Limits to the Range of Possible Cannabinoid Ratios in Plants?: Page 4 of 6

March 12, 2020
Figure 6 (click to enlarge)
Abstract / Synopsis: 

Strikingly similar results have been reported from a wide range of studies on the ratio of tetrahydrocannabinol (THC) to cannabidiol (CBD) concentrations in strains of cannabis. Whether the source has been legalized markets in the west, medical markets in the U.S. and Canada, or collections from law enforcement and researchers, three easily distinguishable types of plant have consistently been found: THC-dominant strains (with less than 1% CBD); CBD-dominant strains (less than 1% THC); and balanced strains with comparable concentrations of both substances. Another consistent finding of these studies, carried out in a variety of laboratory settings, is a positive correlation between THC and CBD levels in those plants that can make substantial quantities (>1%) of each. The correlation between THC and CBD quantities in these varied populations suggests that there is a fundamental property of the plant that makes some combinations impossible, for instance, >15% THC and also >5% CBD. Such results have never shown up in published data sets of carefully, consistently tested samples, but those were all relatively small collections. A much larger data set has been released by the state of Washington (140,000 flower samples), and this has been scrutinized for evidence of consistently propagated strains with higher than a 2-to-1 ratio.

Are Strains with >15% THC and >5% CBD Possible?

To search for cannabis strains that posses a rare combination of THC and CBD, that have not been reported in small collections, a thorough re-examination has been made of the full database of test results made available by the Washington State Liquor and Cannabis Board. This collection was produced for the study by Jikomes and Zoorob (9) and they have made it available for others to query. The in-between data points, those that are not easily assigned to the three identified clusters, were investigated to look for reliable evidence for certain cannabinoid profiles that have not been documented in small collections. It may be that if enough plants are tested, any combination of THC and CBD concentrations might be found. An alternative view is that such results are simply “noise” in a very large data set, one that has been generated by many different laboratories and protocols.

Searching for results that do not fit the mold, which may either be exceptions to the rule or noise, must be done while bearing in mind important caveats. One of the conclusions of the Jikomes and Zoorob study of this collection is that there was evidence of “cannabinoid inflation” by some laboratories. Their finding of “systematic differences in the cannabinoid content reported by different laboratories” has to be considered as one possible source of unexpected results. Identifying anomalies and getting a handle on the scope of unreliable results, though, should not ruin the credibility and usefulness of the data set as a whole. 

The goal of the investigation of the state of Washington data collection was to get an indication whether the test results that lie between the typical clusters are:

  • simply anomalous test results (noise in the testing and reporting system);
  • anomalous plants (test results are accurate but the phenotype is not reliably cultivated); or
  • reliable results (a consistent property of a strain or grower).

The Washington test results were generated between June 2014 and May 2017, and the full data set totals 215,286 entries (10). Each entry, with a unique identification number, includes strain name, the name of the grower and the testing laboratory, the test date, and reported values for total THC and total CBD concentrations. Each entry is also identified by the type of product tested (flower, extract, wax, edible); thus the data set can be culled to just flower product, and the number of entries is reduced to 146,768. That quantity of entries still presents a challenge for common data analysis methods; in preparing their scatter plots of cannabinoid concentrations, Jikomes and Zoorob subsampled the data to allow visualization. 

To further reduce the data set, and to focus on the strains that fall between the clusters on plots of THC and CBD, the set of all flower results was cut-off to only those entries that have a CBD value greater than 1%. With that restriction, the data set reduced to 6818 entries, and the scatter plot shown in Figure 6 can be generated with standard plotting tools.  The three expected clusters are evident, as they are in scatter plots of smaller collections, but many more entries lie between the most concentrated clusters, leaving some uncertainty about  which cluster they belong to. (See upper right for Figure 6, click to enlarge.)

  1. A. Schwabe and M. McGlaughlin, J. Cannabis Res. 1, 3 (2019).
  2. J. Sawler, J. Stout, K. Gardner, D. Hudson, J. Vidmar, L. Butler, J. Page, and S. Myles, PLoS One 10(8), (2015).
  3. E.M. Mudge, S.J. Murch, and P.N. Brown, Scientific Reports 8, 13090 (2018).
  4. U. Reimann-Philipp, M. Speck, C. Orser, S. Johnson, A. Hilyard, H. Turner, A. Stokes, and A. Small-Howard, Cannabis and Cannabinoid Research (2019).
  6. E. de Meijer, M. Bagatta, A. Carboni,  P. Crucitti, V. Moliterni, P. Ranalli, and G. Mandolin, Genetics 163, 335–346 (2003).
  7. K. Hillig and P. Mahlberg, Amer. J. Bot. 91, 966–75 (2004).
  8. T. Coogan, J. Cannabis Res. 1, 11 (2019).
  9. N. Jikomes and M. Zoorob, Sci. Rep. 8, 4519 (2018).


About the Author

Thomas A. Coogan, PhD, is an Academic and Research Liaison with the New Jersey Cannabis Industry Association. Direct correspondence to: [email protected]


How to Cite this Article

T.A. Coogan, Cannabis Science and Technology 3(2), 32–39 (2020).