Up in Smoke: The Naked Truth for LC–MS/MS and GC–MS/MS Technologies for the Analysis of Certain Pesticides in Cannabis Flower: Page 5 of 6

October 25, 2019
Volume: 
2
Issue: 
5
Abstract / Synopsis: 

In U.S. states, Canada, and other countries where medicinal or adult recreational cannabis has been legalized, regulatory entities require a panel of chemical and biological tests to assure quality and safety of the products prior to retail sales. Of the required assays, residual pesticide identification and quantification is arguably the most challenging. The reason for this is the complexity of the cannabis genome that synthesizes phytocannabinoids, terpenes, polyphenols, lipids, and a host of other endogenous chemicals. It is not unusual for today’s selectively bred and cloned cannabis to contain 20–30% ∆9-tetrahydrocannabinol (THC) and other cannabinoids such as cannabidiol (CBD), and 1–3% terpenoids by dry weight. These chemicals alone constitute hundreds of milligrams per gram of sample. In contrast, residual pesticides are typically measured in the 10–1000 ng/g (ppb) range. Pesticide analysis in this matrix requires tandem quadrupole mass spectrometry (MS/MS) because of its mitigation of chemical noise through MS/MS processes. Notwithstanding the power of MS/MS, there are many cases where isobaric interferences effect quantitative results and therefore selectivity becomes as important as sensitivity. In this study, we used liquid chromatography and gas chromatography quadrupole time-of-flight mass spectrometry (LC-qTOF and GC-qTOF, respectively), and gas chromatography tandem mass spectrometry (GC–MS/MS) to evaluate the selectivity of a model pesticide commonly found in regulatory target lists. The LC-qTOF system used negative ion-atmospheric pressure chemical ionization (NI-APCI), and the GC–MS systems used electron ionization (EI). Through this work, we demonstrated that the GC–MS precursor ion and product ion pairs are highly specific derivatives of the parent molecule while the NI-APCI precursor ion is a nonspecific chemical species created in situ through a complex ionization mechanism. In this latter case, all precursor ion and product ion pairs are not selective for the intact analyte molecule.

GC–MS/MS

Table I identifies the precursor ion species used for GC–MS/MS MRM data acquisition. Figure 4 illustrates the ion species of the primary ion fragments. In Figure 5, the EI HRAM MS/MS spectra are shown for three precursor ions. Figure 6 illustrates the GC–MS/MS multiple-reaction monitoring (MRM) chromatogram for the PCNB quantifier and qualifying ions at 8 ppb in 20–30% cannabis flower extract matrix, and the linear calibration curve over the range of 8 ppb through 250 ppb in vial. Table II defines the MRM transitions used for the GC–MS/MS work and Table III illustrates the summary statistics over the same calibration range.

Figure 4

Figure 5

Figure 6

Table 2

Table 3

References: 
  1. D. Tran, et al. Document number: RUO-MKT-02-7607-A. 2018, AB Sciex, Framingham, MA.
  2. C.N. McEwena and B.S. Larsen, J .Am. Soc. Mass Spectrom. 20, 1518–1521 (2009).
  3. I. Dzidic, D.I. Carroll, R.N. Stillwell, and E.C. Horning, Anal. Chem. 47(8), 1308–1312 (1975).

Matthew Curtis, Eric Fausett, Wendi A. Hale, Ron Honnold, Jessica Westland, Peter J. Stone, and Jeffery S. Hollis are with Agilent Technologies in Santa Clara, California. Anthony Macherone is with Agilent Technologies and The Johns Hopkins University School of Medicine in Baltimore, Maryland. Direct correspondence to: [email protected]

How to Cite This Article

M. Curtis, E. Fausett, W.A. Hale, R. Honnold, J. Westland, P.J. Stone, J.S. Hollis, and A. Macherone, Cannabis Science and Technology 2(5), 56-60, 70 (2019).