Chemical Fingerprinting of Cannabis as a Means of Source Identification

  • Mahmoud A. ElSohly
  • Donald F. Stanford
  • Timothy P. Murphy
Part of the Forensic Science And Medicine book series (FSM)


Marijuana is the most widely abused and readily available illicit drug in the United States, with an estimated 11.5 million current users annually purchasing more than $10 billion of the drug (1). Drug enforcement agencies are therefore keenly interested in trafficking routes of both foreign and domestically grown supplies of marijuana. From confidential sources to satellites, these agencies employ a multitude of methods to gather intelligence to direct resources, plan control operations, and develop policies. A practical means to recognize the source of seized marijuana would be a valuable tool for those purposes. Based on findings from 1990 to 1992 and described here, one way to determine origin is by using a chemical fingerprint system, a method that has shown promise as an effective intelligence tool to ascertain the geographic origin of confiscated marijuana samples. Of the many factors that affect the chemical constituents of marijuana, it is apparent that environmental factors consistently induce profiles unique to each environ. An “environ of origin” as broad as a continent or as small as an indoor garden may be differentiated based on the chemical fingerprint, or “signature,” of marijuana cultivated there—if a statistically significant number of samples grown in that environ are available for comparison. However, because all environs are not unique, the chemical fingerprint of cannabis is not considered to be an ultimate tool for forensic applications, although the technique may effectively support other types of evidence and is certainly of particular value in intelligence operations.


Cannabis Sativa Chemical Fingerprint Cannabis Plant Drug Enforcement Administration Daughter Plant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Humana Press Inc., Totowa, New Jersey 2007

Authors and Affiliations

  • Mahmoud A. ElSohly
    • 1
  • Donald F. Stanford
    • 2
  • Timothy P. Murphy
    • 3
  1. 1.The School of PharmacyThe University of MississippiOxford
  2. 2.National Center for Natural Products Research, Research Institute of Pharmaceutical Sciences, School of PharmacyThe University of MississippiOxford
  3. 3.ElSohly Laboratories Inc.Oxford

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