The German Beer Purity Law of 1516 makes beer one of the best-analyzed food products with the highest standards regarding quality, freshness, appearance, and flavor. According to this law, beer is allowed to contain hops, malt, yeast, and water as ingredients. Of course, beer also contains major B vitamins, bitter substances, as well as minerals and trace elements (such as Ca, Na, Mg, and Zn) that are important for human nutrition. However, undesirable substances such as pesticides and heavy metals (for instance, Cd, Pb, Hg, Sb, and As) can be found in beer as well, mostly as contaminants in brewing water and grains. In particular, the herbicide glyphosate has to be monitored carefully since it is discussed as a possible carcinogen. The chromatography of glyphosate is challenging because of its high polarity. A well-established method including a derivatization step with 9-fluorenylmethyl chloroformate (FMOC) followed by liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis is time-consuming and also susceptible to errors. A sample pretreatment without derivatization is desirable because it is faster and cheaper. The use of a triple-quadrupole mass spectrometer optimizes the analytical procedure and establishes a routine method for the analysis of glyphosate in beer. For the determination of elements present in low concentrations, such as As, Se, Pb, Cd, and Zn, inductively coupled plasma-mass spectrometry (ICP-MS) is applied.

	Glyphosate is currently one of the most common pesticides used worldwide. In spite of its approval by regulatory bodies all over the world, the concern about its harm to humans and the environment persists. In June 2016, the European Commission decided to extend the license for glyphosate by 18 months, after member states failed to achieve a qualified majority in favor or against the executive’s proposal.

	To overcome the challenging chromatography of glyphosate caused by its high polarity, a well-established method can be applied that includes a derivatization step with 9-fluorenylmethyl chloroformate (FMOC) followed by liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis. Unfortunately, this method is time-consuming, expensive, and susceptible to errors. A further drawback is the fact that not all highly polar pesticides are susceptible to derivatization with FMOC-for example, glufosinate´s metabolite 3-(methylphosphinico)propionic acid (MPPA). Therefore, sample pretreatment without derivatization is desirable, because that approach is quicker and more cost-efficient. Furthermore, it will not be limited to detection of glyphosate, but will allow the simultaneous detection of other highly polar pesticides and their metabolites as well.

	In this case study, the quantification of glyphosate, its metabolite aminomethylphosphonic acid (AMPA), glufosinate, and its respective metabolite MPPA based on derivatization are compared to a method without any derivatization. A total of 24 different kinds of beer were tested. The use of high-sensitivity mass spectrometry allowed us to skip a sample concentration step by solid-phase extraction (SPE) for both methods, which additionally reduced time and cost for the analysis.

	First, 1 mL of methanol was added to 1 mL of beer and the mixture was vortexed. The mixture was then centrifuged for 15 min at 12,000 rpm. Next, 500 µL of the supernatant was used as the underivatized sample. For the derivatization sample, 25 µL of EDTA-borate buffer and 75 µL of FMOC were added to another 500 µL of the supernatant. After a 60-min incubation at 50 °C, the reaction was stopped with 30 µL of 0.2% phosphoric acid. Finally, 125 µL of water was added.

	Because derivatized and underivatized samples required different chromatographic conditions, we used an ultrahigh-pressure liquid chromatography (UHPLC) system capable of multiplex analysis (Nexera MX with Dual Stream Technology, Shimadzu) coupled to an MS system (LCMS-8060, Shimadzu) for the application. This approach allowed for the use of a multiplexed method with different columns and LC methods in one batch, thus increasing the throughput and improving the efficiency. The analytical conditions are listed in Table I.

	Two different methods (with and without derivatization) have been established successfully for the quantification of glyphosate and glufosinate in beer, even without the use of internal standards. Glyphosate could be quantified from 5 to 100 ng/mL with both methods while glufosinate could be quantified from 5 to 100 ng/mL with the underivatized method compared to 10–100 ng/mL with the FMOC-derivatization method. With the FMOC-derivatization method, AMPA could be quantified from 5 to 100 ng/mL while MPPA could be quantified from 10 to 100 ng/mL with the underivatized method only. None of these methods are suitable to cope with both metabolites at the same time with sufficient sensitivity.

	The calibration curves obtained for the compounds are shown in Figure 1 and the corresponding chromatograms are shown in Figure 2. The analytical results for glyphosate in 24 different beer samples are listed in Table II. Both methods show comparable results. None of the other compounds could be detected in the samples.

 Calibration curves for glyphosate, glufosinate, AMPA, and MPPA determined in duplicate obtained from beer after sample pretreatment. 

² was greater than 0.99 for all calibration curves.

 Chromatograms of a 15 ng/mL beer sample.

	Both methods allow the quantification of all target compounds at or below 0.01 mg/kg (=≤10 ng/mL), which is below the European Union maximum residue levels (MRL) for all studied compounds. The method without sample derivatization shows comparable sensitivity to the FMOC derivatization, but sample pretreatment is much easier and quicker. Glyphosate could be detected in a concentration above the limit of quantitation (LOQ) in more than 30% of the tested commercially available beers. However, even the positive tested samples contained glyphosate in an amount far below the MRL of the raw material (1).

	Determination of Heavy Metals Using ICP-MS

	The quality standards for beer analysis are defined by the Central European Commission for Brewing Analysis (MEBAK) and the European Brewery Convention (EBC), which is an organization representing the technical and scientific interests of the brewing sector in European countries.

	These regulations include the principles and proceedings for the analysis of raw materials, semifinished goods, by-products and finished products, additives and technical supplies, containers, and packaging materials with the aim of standardization, primarily in the field of breweries and malting industries. The technical analysis methods of MEBAK have been published in several application books, including those for the determination of elements such as copper, zinc, sodium, potassium, calcium, anions such as nitrate and sulfite, and organic components such as ethanol, glycerine, and others (2).

	Nowadays, the health effects of trace elements and the maximum concentration of trace elements in beers are continuously controlled. The determination of trace metals in beers is relevant because they might be essential or toxic in the human body and they also have an influence on the brewing process. The element distribution, however, shows significant differences based on the natural sources of soil, water, cereal, hops, and yeast as well as anthropogenic sources such as environmental pollution and agricultural treatment by fertilizers, pesticides, and fungicides.

	Last but not least, the metal content in beer can be influenced during production, beer processing, conservation, and bottling. This influence is greater than expected because during the beer-making process the raw products and processed products are often in long contact with materials such as stainless steel, copper, glass bottles, and other equipment.

	The determination of copper is important because high concentrations are disadvantageous to the colloidal stability and taste of the beer. The same goes for zinc, which is an essential trace element for yeast that influences metabolic processes such as protein synthesis and nucleic acid metabolism. Typical concentration levels of copper and zinc in beer are 0.2 mg/L (3).

	Furthermore, the determination of arsenic, antimony, cadmium, and lead is important because those elements are toxic when they are present in beer or the brewing water. The source of these elements in beer and other alcoholic beverages could be the contamination of raw material or technological processes.

	Arsenic is released into beer from a filtering material called 

, or diatomaceous earth, which is used to remove yeast, hops, and other particles and give the beer a crystal clear appearance. Diatomaceous earth consists of fossilized remains of 

, a type of hard-shelled algae that lived millions of years ago. Diatomaceous earth finds wide use in filtering beer and wine, and is an ingredient in other products as discussed by Professor Mehmet Coelhan from the Research Center Weihenstephan for Brewing and Food Quality (4).

	One more element of concern is antimony. The annual consumption of antimony trioxide in the United States and Europe is approximately 10,000 and 25,000 tons, respectively. The main application is as a flame retardant synergist in combination with halogenated materials. Furthermore, antimony trioxide is used as a catalyst in the production process for polyethylene terephthalate (PET) bottles.

	Elevated concentrations of Sb have been found in beverages such as cola drinks and orange juices that are stored in PET bottles, because the Sb migrates from the plastic to the liquid and accumulates in the drinks. The migration process is accelerated in alcoholic beverages. Vodka samples from glass and PET bottles have been compared according to their Sb levels, and it was found that the Sb concentration in vodka from a PET bottle can be as high as 20 µg/L in comparison to less than 1 µg/L in a glass bottle. (5).

	The maximum allowable concentration of Sb in drinking water is 5 µg/L. Since the latest development in the beer industry is the introduction of 0.33-, 0.5-, and 1-L PET bottles on supermarket shelves with a variety of beers from European countries, analytical investigations are in process to evaluate the antimony concentrations in beer as well.

	For the simultaneous quantitative determination of the inorganic elements in beer, inductively coupled plasma-mass spectrometry (ICP-MS) is the preferred quality control tool. ICP-MS offers high sensitivity (trace detection), a wide dynamic range, and high sample throughput. In this study, we used an ICP-MS system with an octopole collision cell (ICPMS-2030, Shimadzu). Using helium as a collision gas and running in kinetic energy discrimination (KED) mode, this cell suppressed most of the spectroscopic interferences (polyatomic interferences). The efficiency of interference suppressions and the sensitivity are improved by using a cooled cyclonic chamber and a well-controlled torch positioning.

Preparation of Beer Samples and ICP-MS Setup

	For this study, samples of two commercially available beers were evaluated. The two beer samples were undiluted and were aspirated after degassing using the measurement parameters listed in Table III. An internal standard solution containing 

Tl was added using the automatic internal standard addition kit.

	The concentrations of Ni, Cd, Sb, and Pb in the undiluted beer were determined using the calibration curve method. For each studied element, calibration curves were built using four standards in the concentration range from 2 to 10 µg/L. The standards were prepared using a matrix-matched solution containing 5% ethanol.

	The calibration curves in Figure 3 show that all correlation coefficients are better than 0.999 and low detection limits (LD), which are calculated automatically by the ICP-MS system software (LabSolution-ICPMS) with a 3σ method. Table IV summarizes the results from the study.

	Beer is one of the favorite alcoholic beverages in European countries with a statistical per capita consumption of around 68 L. Therefore, the quality is expected to be on a high level and continuous quality control is essential. Still, beer may contain a variety of heavy metals such as arsenic, lead, and cadmium as well as additional undesirable substances like pesticides. High-sensitivity analytical tools such as LC–MS/MS and ICP-MS are best suited to detect low levels of contaminants to permanently ensure the quality of beer.

http://ec.europa.eu/food/plant/pesticides/eu-pesticides-database/public/?event=pesticide.residue.CurrentMRL&language=DE

 (Band III, Methodensammlung der Mitteleuropäischen Brautechnischen Analysenkommission, 1996). 

. “Widely Used Filtering Material Adds Arsenic to Beers” (2013), 

https://www.acs.org/content/acs/en/pressroom/newsreleases/2013/april/widely-used-filtering-material-adds-arsenic-to-beers.html

Uwe Oppermann, Anja Grüning, Ludivine Fromentoux

 with Shimadzu Europa GmbH, in Duisburg, Germany. Direct correspondence to: 

Articles

The authors compare LC–MS/MS methods for quantification of the pesticide glyphosate with and without sample derivatization, and discuss ICP-MS methods for the determination of heavy metals.

Determination of Contaminants in Beer Using LC–MS/MS and ICP-MS

As a result of the rapid growth of the cannabis industry, many testing laboratories are looking for efficient, reliable, and cost-effective analytical methods to analyze chemical residues, such as pesticides, mycotoxins, solvent residues, terpenes, and heavy metals, as well as cannabinoid concentration in cannabis-infused edibles and beverages. In this article, QuEChERS (quick, easy, cheap, effective, rugged, and safe), a sample preparation technique widely adopted in the food testing industry, is introduced to the discipline of forensic testing as a viable method for the extraction of pesticides and cannabinoids in various complex sample matrices. The claimed amounts of cannabinoids versus the actual amounts are compared, as well as the pesticide residue levels in edible and beverage samples.

	To date, 25 states and the District of Columbia in the United States have legalized the medical use of marijuana, while four states and the District of Columbia have also legalized the recreational use of marijuana (1). Although the federal government still classifies any use or possession of the drug as illegal, all 50 states are starting to see an increase in the number of edible marijuana samples within their borders. As a result, many testing laboratories are looking for fast, reliable, and cost-effective methods to determine cannabis potency and chemical residues in cannabis edibles and beverages. The pros and cons of legalization are still heavily debated throughout the country, but all scientists agree that uniform testing policies and procedures need to be established as soon as possible and that overall sample cleanup is the main issue within these analyses. Many states legalized the use of recreational and medicinal marijuana without establishing any analytical protocols that are commonplace and routine in other scientific industries. Without any sort of regulatory control, laboratories in these states can analyze samples and report results without any fear of repercussion.

	For states where any consumption or possession of marijuana is still illegal, forensic laboratories are saddled with the task of analyzing this contraband. Even though it is extremely common for drug chemistry laboratories to directly test plant material and even oil-based products for the presence of tetrahydrocannabinol (THC) and related compounds, the use of edibles and beverages recreationally has brought along a new set of analytical challenges. Drug chemistry departments are not necessarily equipped to handle this type of analysis. In spite of forensic toxicology laboratories being capable of handling extractions from various biological matrices, baked goods and hard candies have few similarities to their everyday case load.

	One concept that does appear to be readily universal in the edible marijuana community is the establishment that 10 mg of THC is equal to one dose for this drug (2). While this standard works in theory, many edible manufacturers produce products that range from multiple doses in one package to just containing one individual dose. If proper interpretation of dosing instructions is not noted, some consumers may be put at risk for either undesirable effects from consuming too much in one sitting or no relief of symptoms at all for medicinal users. An imperative concept that novice edible users need to keep in mind is that digesting marijuana is not the same as smoking it when discussing the plant’s pharmacology. Those who have prior experience with smoking marijuana may assume that one brownie or one package of gummy bears equals one marijuana cigarette, though that is far from the case. Employees at marijuana shops may not be educated enough on this issue or be aware that edibles do not necessarily contain the THC amount as advertised on their packaging. This fact alone makes it even more critical that effective testing measures are put in place to ultimately protect the end users.

	The development of an extraction method that can be used in a wide variety of laboratory settings is critical to the emerging fields of recreational and medicinal marijuana testing. Within environmental and food testing laboratories, the QuEChERS (quick, easy, cheap, effective, rugged, and safe) sample preparation method has been widely used for the past 13 years. In 2003, Anastassiades and Lehotay published the first QuEChERS application, which discussed the determination of pesticide residues in produce (3). Since then, QuEChERS has become the analytical gold standard for the testing and analysis of a wide variety of edible matrices, including oil, egg, meat, fish, wine, and beverage samples (4–9). Using disposable consumables, hundreds of pesticides can be analyzed in a single extraction with the QuEChERS approach. In addition to pesticide residues, other chemical residues such as antibiotics, veterinary drugs, mycotoxins, polycyclic aromatic hydrocarbons (PAHs), bisphenol A, and phthalates are routinely monitored using this technique (10–14). The solvent waste generated is much less than what is typically associated with complex organic extractions. This technique is a relatively easy analytical method for technicians to learn, allowing for laboratories to effortlessly adopt this system of sample preparation.

	Neither traditional solid-phase extraction (SPE) columns nor liquid–liquid extraction techniques can successfully provide laboratories with the reproducible and fast results needed for cannabis food analysis. Unlike biological matrices, edible products do not easily pass through the porous frits and sorbent of an SPE column. In addition, they do not contain the same endogenous matrix interferences found in biological samples that ultimately need to be removed for accurate quantitation. Lastly, when analyzing the cannabinoid content in edible samples, the final extract often needs to be diluted rather than concentrated before instrumental analysis. This is in stark contrast to forensic samples, which often require concentration of target analytes at trace levels. Liquid–liquid extraction often requires large amounts of undesirable and toxic solvents to be used. The above limiting factors allow for QuEChERS to make a desirable transition to the forensic community.

	High performance liquid chromatography (HPLC)-grade acetonitrile, HPLC-grade methanol, and American Chemical Society (ACS)-grade acetic acid were purchased from Spectrum. Also, 35 neat pesticide standards were purchased from Sigma-Aldrich, Chem Service, or Ultra Scientific. A 2-ppm working solution containing 35 pesticides was prepared in acetonitrile. Three cannabinoids including THC, cannabidiol (CBD), and cannabinol (CBN) were purchased from Cerilliant in 1-mg/mL solutions. A 10-ppm mixture of the three cannabinoids was prepared in acetonitrile. Neat triphenyl phosphate was purchased from Cerilliant and diluted to 10 ppm in acetonitrile.

	Baked goods, chocolate bars, and hard candies were ground into a fine powder using a SPEX 6770 freezer mill before extraction. A hard candy sample before and after grinding is shown in Figures 1a and 1b. Gummy-based candies can be ground into powder with the presence of liquid nitrogen; however, the powder will return to its elastic gel state when the temperature rises. Thus, gummy-based samples were cut into fine pieces instead of using a freezer mill. Carbonated beverages, such as sodas, were degassed for 30 min before analysis, while oil samples were extracted without any sample pretreatment.

	Homogenized 1-g samples (baked goods, chocolate bars, hard candies, gummy bears, or oil samples) were weighed into a 50-mL centrifuge tube. To each of these samples, 10 mL of reagent water was added. Samples were hydrated for 1 h using a horizontal shaker. For beverage samples, 10 mL of degassed sample was added to 50-mL tubes without the water addition and the 1-h hydration step. Internal standard and 10 mL of acetonitrile containing 1% acetic acid were added to all samples, which were then shaken for 1 min using the SPEX Geno/Grinder homogenizer. A proprietary blend of QuEChERS extraction salts supplied by UCT was added to each tube, and the tubes were shaken vigorously to break up any salt agglomerates. The extraction salts help to facilitate phase separation and partition target analytes from the aqueous layer into the acetonitrile layer. After shaking, the samples were centrifuged for 5 min at 3000 rcf. Three distinct layers are formed after centrifugation as demonstrated in Figure 1c. The top layer is the organic phase (acetonitrile) containing pesticide residues, cannabinoids, and the organic-soluble matrix coextractives; the middle layer is the insoluble matrix components and water containing the water-soluble matrix components, such as sugars; and the bottom layer is the undissolved excess extraction salts.

Photographs of a hard candy (a) before and (b) after freezer mill grinding; (c) after QuEChERS extraction; and (d) the extracts before (left) and after (right) dSPE cleanup.

	For pesticide residue analysis, 1 mL of the supernatant was transferred to a 2-mL dispersive solid-phase extraction (dSPE) tube containing a proprietary blend of sorbents (UCT), and shaken for 1 min using the Geno/Grinder, then centrifuged for 5 min at 3000 rcf. This process removes chlorophyll, sugars, organic acids, and fatty compounds from the sample extracts by retaining them onto the sorbents. The resulting clean extract, illustrated in Figure 1d, is then diluted 2x with reagent water and analyzed by LC–MS/MS.

	For cannabinoid content analysis, dSPE was not necessary because of the high cannabinoid concentration in the acetonitrile extract. Instead, serial dilutions ranging from 200x to 20,000x were carried out to obtain a concentration (a few hundred parts per billion) that is suitable for LC–MS/MS analysis.

	A Thermo Scientific Dionex UltiMate 3000 LC system coupled to a Thermo Scientific TSQ Vantage tandem mass spectrometer was used for pesticide and cannabinoid analysis. Xcalibur (Version: 2.2) software was used for data acquisition and processing. A 100 mm x 2.1 mm, 3-µm 

 Selectra Aqueous C18 HPLC column and 10 mm x 2.1 mm, 3-µm 

 guard column supplied by UCT were used for analyte retention and separation. The aqueous C18 HPLC column was selected because of the high polarity of several pesticides covered in this study, such as methamidophos and acephate. Chromatograms of 35 pesticides and triphenyl phosphate (IS) are shown in Figure 2, with the retention order listed in Table I. The same HPLC column and mobile phases were also used for cannabinoid analysis to provide ease without the need of switching the HPLC column and mobile phases when analyzing the pesticide and cannabinoid samples in succession. The aqueous C18 HPLC column showed great separation of CBD and THC, two compounds that have the same multiple reaction monitoring (MRM) transitions. An example chromatogram of a diluted mint milk chocolate sample spiked with 70 ppb of three cannabinoids using this aqueous C18 column is shown in Figure 3.

 Chromatograms of 35 pesticides and triphenyl phosphate (IS) retained on the UCT Selectra Aqueous C18 HPLC column.

 Chromatogram of a diluted (2000x) mint milk chocolate sample spiked with 70 ppb of three cannabinoids.

	The column oven was maintained at 40 °C, and the samples in the autosampler were kept at 10 °C. The injection volumes were 2 and 5 μL for pesticide and cannabinoid analysis, respectively. Mobile-phase A was 10 mM ammonium acetate in Milli-Q water, and mobile-phase B was methanol with 0.1% formic acid. The mobile-phase flow rate was 300 μL/min. The gradient for pesticides was programmed as follows: 0 min, 0% B; 1–3.5 min, 50% B; 6–9 min, 95% B; and 9.1–14 min, 0% B. For cannabinoid analysis, the gradient program was as follows: 0–0.5 min, 60% B; 3–7 min, 95% B; and 7.1–10 min, 60% B.

	Tandem MS was operated with heated electrospray ionization (HESI) in positive mode. The MS/MS conditions were set as follows: spray voltage at 3500 V; sheath gas of nitrogen at 50 arbitrary units; auxiliary gas of nitrogen at 40 arbitrary units; vaporizer temperature at 450 °C; ion transfer capillary temperature at 350 °C; collision gas of argon at 1.5 mTorr; Q1 peak width of 0.4 Da full width half maximum (FWHM); and Q3 peak width of 0.7 Da FWHM. The optimization of the MS/MS transitions was performed individually for each analyte by infusing 1 μg/mL of standard in acetonitrile at 10 µL/min in a 50:50 A–B mobile phase at a flow rate of 300 µL/min. Scheduled selected reaction monitoring (SRM) with a cycle time of 0.5 s was set for data acquisition. The precursor and product ions, collision energies, and S-Lens RF values of the 35 pesticides, IS, and three cannabinoids are listed in Table I.

Semiquantitative Determination of Pesticide Residues

	Pesticide residues were analyzed semiquantitatively because of the lack of negative control samples for each sample matrix, as well as the large number of pesticides at different concentration levels making the standard addition method impractical. Matrix-matched calibration curves were generated using the post-spiked blank extracts of green tea sample to semiquantify the pesticide residues in edibles and beverages. Appropriate amounts of the pesticide spiking solution were added into the tea extracts to generate six-point matrix-matched calibration curves with concentrations at 5, 10, 25, 50, 100, and 250 ng/mL. The responses were found to be linear (

 > 0.99) over the entire concentration range. Accuracy and precision results at 10-ng/g and 50-ng/g spiking levels are shown in Table II.

	A variety of edibles, including chocolate bars, brownies, hard and gummy candies, CBD oil, and beverage samples, were analyzed for pesticide residues using the QuEChERS extraction and dSPE cleanup method described above, and the results are summarized in Table III. Four products were found to contain bifenazate at concentrations ranging from 10 to 1221 ng/g, although some of them claimed to be “organically grown” products. The highest concentration was found in a CBD oil sample, where the pesticide might have been enriched when manufacturing the concentrated oil product from the raw plant materials. Bifenazate is commonly used to control mites on agricultural products. Though it is not terribly harmful to humans in comparison to other pesticides, there is a lack of research regarding the health risk of constant consumption of this pesticide. Most pesticide research does not take into account the oral dosing over a long period of time, especially in people with compromised immune systems.

Quantitative Determination of Cannabinoid Content

	For cannabinoid analysis, content was quantitated by the standard addition method. Diluted QuEChERS extracts were spiked at +50% and +150% of the stated cannabinoid content. Plotting the peak areas of the diluted sample and the two aforementioned spiked samples allowed for the calculation of cannabinoid concentrations in the diluted samples. Excellent linearity (

 > 0.995) was observed for all samples tested. An example of the standard addition calibration curve is demonstrated in Figure 4. Calculation of the cannabinoid contents in the original samples was based on the dilution factors and unit conversion factors. The results (in milligrams per pack) were then compared to the stated content on the packaging of each product, as summarized in Table IV. For all of the cannabis samples tested in this study, only 31% (four out of 13 samples) had accurately labeled the total cannabinoid content within ±20% of the stated values.

 Standard addition calibration curve of THC in a cookie and cream bar sample (500x dilution of the QuEChERS extract, 70 ppb cannabinoids were added for the 50% spiked sample and 210 ppb were added for the 150% spiked sample).

	CLICK TABLE TO ENLARGE
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	Although the US Food and Drug Administration takes care of monitoring the safe production of the majority of edible products in the United States, marijuana-infused foods do not fall under their jurisdiction because the drug is still considered to be illegal in the eyes of the federal government. Recreational users may be primarily focused on getting their money’s worth from these products, but medicinal users have additional, notable concerns with edibles. Many medicinal consumers do not necessarily want to feel the psychoactive effects of marijuana, but rather just want to combat the symptoms of their specific ailment. If a product is inaccurately labeled, medicinal users run the risk of consuming too much marijuana and thus having undesirable side effects. On the contrary, they also could be unnecessarily suffering from side effects of their illnesses because of an edible product containing less cannabinoids than the suggested dosage amount. These concerns are in addition to the possible presence of unwanted chemical residues, such as pesticides, mycotoxins, and heavy metals.

	A fast, reliable, and cost-effective analytical method has been developed for the determination of pesticide residues and cannabinoid contents in cannabis infused edibles and beverages. This method uses the advantages of QuEChERS products to extract 35 pesticides and three cannabinoids (CBD, CBN, and THC) from complex food and beverage matrices. This extraction is then followed by either serial dilution for cannabinoid content analysis, or a dSPE cleanup for the efficient removal of various matrix coextractives, resulting in extracts for trace-level pesticide residue analysis. This hybrid method allows QuEChERS, which is extensively used in the food testing industry, to be used in a forensic or private cannabis laboratory setting.

	The developed method has been successfully applied to the analysis of 13 real cannabis edible and beverage samples. For pesticide analysis, bifenazate was present in four out of the 13 tested samples at varied concentrations ranging from 10 to 1221 ng/g. For cannabinoid content analysis, only 31% (four out of 13) of the samples had accurately labeled the total cannabinoid content within ±20% of the stated value, while the majority of samples (eight out of 13, or 62%) were overlabeled (more than 20% below the labeled amount). One sample was found underlabeled which actually contained 40% more THC than stated.

	Keith Tucker with SPEX SamplePrep LLC is acknowledged for providing the 6770 Freezer mill and 2010 Geno/Grinder for this study. Erik Swiatkowski with UCT is thanked for his help in handling liquid nitrogen when using the SPEX 6770 freezer mill.

		A.A. Monte, R.D. Zane, and K.J. Heard, 

		State Medical Marijuana Laws, National Conference of State Legislators 18 April 2016.

		M. Anastassiades, S.J. Lehotay, D. Stajnbaher, and F.J. Schenck, 

		S.C. Cunha, S.J. Lehotay, K. Mastovska, J.O. Fernandes, M. Beatriz, and P.P Oliveira, 

		M. Villar-Pulido, B. Gilbert-Lopez, J.F. Garcia-Reyes, N.R. Martos, and A. Molina-Diaz, 

		B. Kinsella, S.J. Lehotay, K. Mastovska, A.R. Lightfield, A. Furey, and M. Danaher, 

		L. Vaclavik, M. Zachariasova, V. Hrbek, and J. Hajslova, 

		T.H. Kao, S. Chen, C.J. Chen, C.W. Huang, and B.H. Chen, 

		S.C. Cunha, C. Cunha, A.R. Ferreira, and J.O. Fernandes, 

Xiaoyan Wang, Danielle Mackowsky, Jody Searfoss

 are with UCT in Bristol, Pennsylvania. Direct correspondence to: 

QuEChERS is introduced to the discipline of forensic testing as a viable method for the extraction of pesticides and cannabinoids in various complex sample matrices.

Determination of Cannabinoid Content and Pesticide Residues in Cannabis Edibles and Beverages

An automated method for determination of water in liquid sweeteners was developed using headspace gas chromatography (GC) and ionic liquid-based capillary GC columns. This method allowed for the rapid determination of water with minimal sample pretreatment. In addition to providing fast analysis time for the samples, the headspace GC method was found to be accurate and precise for the measurement of water in 16 liquid sweeteners. This method was shown to be widely applicable for sugar and sugar-free sweeteners and more accurate than Karl Fischer titration.

	Historically, honey was the primary sweetener used to enhance many foods; however, with advances in technology, sweeteners with high concentrations of fructose or sucrose are now used (1,2). In syrup-form, they provide an economical, easy-to-handle alternative to honey (2). Sweeteners can now be found in most foods, including carbonated beverages, canned goods, jellies, jams, baked goods, and dairy products, and in many pharmaceutical products (1–3). These additives improve the humectancy, color, and flavor of food (1). Sweeteners are found in many foods, and their compositions are monitored and regulated (4,5). One important component, water, must be regulated because it affects both the physical characteristic of the product and consumer safety (1,5). The water content directly affects the viscosity of syrups and sweeteners. When the water content in syrup is low, the sugar may precipitate and the ability to easily handle the product as well as consumer satisfaction will be compromised (6).

	In addition to human consumption, many syrups (such as molasses and corn syrup) are used as additives in animal feed (2,4,5). The water content is monitored, and if the level exceeds the regulated range, both mold and other microbial growth can occur (4–6). This can lead to significant problems because of the toxic nature of some molds, spores, and their by-products (7–10).

	Consumption of the mold and spores leads to a reduction of feed intake, which can cause weakness, weight loss, and decreased production in dairy cattle (7). Furthermore, spores and mold can cause many diseases along with their related symptoms of vomiting, diarrhea, skin lesions, kidney and liver damage, lack of muscle control, and nervous system disorders (7–10). Other effects are an increase in infertility and abortions among exposed cattle (7–10). Mold is known to cause respiratory distress, coughing, and shortness of breath in both humans and livestock (7–10). Consequently, the measurement of water in many products is often required by regulatory bodies worldwide.

	Water content traditionally is measured by refractive index and reported in degrees Brix or by percent by weight of sucrose in water (5,6,11,12). Degrees Brix is used because it is a fast and easy way to measure the moisture in sucrose-based sweeteners (5,11). While it is fast, many sweeteners are fructose based or have a combination of sucrose and other sugars causing it to be inaccurate; therefore, the Brix measurement is actually an “apparent Brix” (5,11). In addition to sugars other than sucrose, salts are known to cause an apparent change in the water content (5,11). When salt is present, the measured degrees Brix can indicate 5–10% less water than is actually contained in the sample (5). Headspace gas chromatography (GC) is another method that has been used for the determination of water in select foods, solvents, and active pharmaceutical ingredients (12–16). Early on, the amount of water in food was measured by the formation of a suspension in methyl glycol and then multiple headspace extractions were used (12). One problem that occurred with this early GC method was that the various supports (for example, diatomaceous earth and molecular sieves) in packed columns led to a nonideal absorption of water; therefore these columns produced broad tailing peaks with poor peak area reproducibility (17–20). In addition, these packed columns tended to have low selectivity and resolution between water and many other common solvents (15–18). In addition, air, water, and some solvents can degrade common liquid stationary phases at the elevated temperatures required for the analyses (14). New GC stationary phases composed of ionic liquids (IL) have been developed that allow GC to be used for the analysis of water (13–16,21–23). The ILs with trifluoromethylsulfonate (TfO

) anions improve the water’s peak shape and peak area reproducibility lowering the limit of detection (14,21–23). Further, these stationary phases are unchanged when exposed long term to water- and oxygen-containing samples.

	In this work, we report a simple, effective, and accurate method for the determination of water content in fructose-, sucrose-, and sucralose-based syrups. This method, unlike previous methods, is not affected by the sugar composition, the presence of solid particles in the sample, or the presence of salts. Also, the method does not entail multiple headspace extractions, additional solvents, or standards as in some of the previous headspace GC methods. This effective approach is easily automated and is made possible by the advent of advanced IL stationary phases for GC coupled with a specific GC system configured for water analysis and containing devices for the stringent reduction of ambient moisture.

	Fructose was obtained from Sigma Aldrich. Blue agave nectar was purchased from C&H Sugar. Grandma’s Molasses was obtained from B&G foods. Karo Light corn syrup was obtained from ACH Food Companies, Inc. Pancake syrup was purchased from Safeway. Hershey’s chocolate syrup and caramel topping were purchased from Hersheys Company. The Nesquik chocolate syrup and strawberry syrup were obtained from Nestle. Strawberry jelly and jam were obtained from Smucker’s. Mrs. Butterworth’s original syrup and Mrs. Butterworth’s sugar-free syrup were from Mrs. Butterworth’s. Coffee creamer was from Kahala Franchising, L.L.C. Sugar Free Butter Flavored Syrup was obtained from Maple Grove Farms. Rose’s Grenadine syrup was purchased from Mott’s LLP. Dimethyl sulfoxide (DMSO) was purchased from Sigma Aldrich.

	Screw-thread vials (22 x 75 mm) and magnetic screw-thread covers for the autosampler were purchased from Restek. The GC columns were 30 m x 0.25 mm, 0.20-μm 

 Watercol 1460 and Watercol 1900 columns along with a 60 m x 0.25 mm, 0.20-µm 

 Watercol 1910 column and were obtained from Sigma Aldrich.

	Samples with <40% water were prepared by adding 500 mg of sample to a clean vial using a pipette. Samples that contained >40% water were prepared by adding 0.125 g of sample and 0.375 g of DMSO to a clean vial. After the sample was prepared it was immediately capped. The vial was pressurized to 200 kPa for 2 min at room temperature using a Shimadzu HS-20 headspace autosampler. The headspace was then loaded or extracted for 1 min. After the purging process was complete the vial was heated for 5 min at 100 °C. The sample was pressurized to 100 kPa and the headspace vapor was loaded for 2 min into a 0.2-mL sample loop. A 0.5-min injection was then made into the GC system. Two external calibration curves were produced: one for the lower water content (<40% water) and a second calibration curve for samples with higher water content (>40%). The first was used for samples with lower water content, by combining 0.4, 0.5, 0.6, and 0.8 g of water with 2.6, 2.0, 1.9, and 1.8 g of fructose, respectively. Samples were made in quadruplicate by adding successive 500-mg aliquots of sample to clean vials. Then the vials were purged, heated, and analyzed the same as the samples. The second calibration curve for higher water contents was produced by making samples with 5%, 10%, 15%, 20%, and 25% water in a DMSO matrix. This was achieved by combining 0.125, 0.250, 0.375, 0.500, and 0.625 g of water with 2.375, 2.250, 2.125, 2.000, and 1.875 g of DMSO, respectively. The solutions were then divided into 500-mg aliquots and treated in the same manner as the samples.

	Loss on drying was measured by weighing four clean empty vials. A sample, ~500 mg, was added to each vial and the new mass was recorded. Samples were heated for 12 h at 60 °C and then cooled and weighted. A second 12-h evaporation step was performed at 60 °C. The process was repeated until a constant mass was obtained.

	The Karl Fischer titration (KFT) analyses were performed by Robertson Microlit Laboratories. The atmospheric moisture was measured by adding 3–10 mg of sulfosalicylic acid dehydrate to the Hydranal Coulomat AG in the titration cell. The standard was titrated coulometrically to the electrometic endpoint and used to determine the response of residual moisture. The sample, 10 mg, was then added to the titration cell and titrated. The atmospheric moisture was subtracted for the reported value to obtain the moisture in the sweetener sample.

	The analyses were performed using a Tracera 2010 equipped with barrier discharge ionization detection (BID) and thermal conductivity detection (TCD) (Shimadzu Scientific Instruments). Labsolutions 5.82 software was used for all peak integration. A Shimadzu HS-20 headspace autosampler was used to purge, heat, and inject all samples. The transfer line and sample line were kept at 170 °C. The oven in the autosampler was kept at room temperature (25 °C) when purging the vials and at 100 °C for all analyses. A 60 m x 0.25 mm, 0.2-µm 

 Watercol 1910 fused-silica capillary column coated with IL synthesized as previously reported or commercially acquired from Supelco/Sigma-Aldrich (22). The GC system oven temperature was held isothermally at 170 °C with a run time of 5 min. The carrier gas for all runs was helium at a flow rate of 1.5 mL/min (26 cm/s). The helium was dried with a high-capacity gas purifier and an OMI purifier tube (Supelco). The injection port was set at 280 °C and the TCD system was set at 200 °C with a current of 80 mA. A split ratio of 100:1 was used for all analyses of the sweeteners. Selected analyses were performed using a 6890N gas chromatograph with TCD (Agilent Technologies Inc.) and Chemstation plus software (Rev.B.01.03). A 1-mL gastight syringe (Hamilton) was used for all injections.

	The GC oven temperature, split ratio, and GC column were evaluated, and the optimized conditions are specified in the “Experimental” section. It was determined that a temperature of 170 °C and a split ratio of 100:1 were optimal for these analyses. The Watercol 1910 GC column gave the best peak symmetry for water compared to the Watercol 1460 and Watercol 1900 columns (see “Experimental” section). The Watercol 1900 column gave the lowest retention time, but the peak shape was slightly less symmetrical than that obtained using the Watercol 1910 column. The improved peak shape of the water when analyzed on the Watercol 1910 column in turn, provided more precise water determinations (

). It was found that the water concentrations were not in the linear range of the sensitive BID, but they were well within the linear range of TCD. One of the virtues of a GC system specifically configured for water analysis is that it has both of these detectors and therefore the flexibility to handle samples containing trace levels to higher levels of water. In the case of these 16 sweeteners, the higher water content in the samples allowed TCD to give a response 4x10

	The headspace analysis of samples for water requires the optimization of a few parameters. These include the purging conditions, sample loop size, and the length of time the sealed samples are heated (equilibrium time). It should be noted that the headspace autosampler used in this study has a unique configuration that is advantageous for water analysis (16). The equilibrium temperature was set at 100 °C to reduce side reactions (such as the Maillard reaction), which produce water as a by-product. The equilibrium time was also optimized as seen in Figure 1. The sample required 5 min at 100 °C to reach equilibrium. Various sample purge conditions were evaluated using the autosampler. For example, the vials were pressurized in a range of 25–200 kPa and the headspace was then removed for 6–120 s. It was found that a using a pressure of 200 kPa and then extracting 30 s of headspace was optimal and provided the lowest residual moisture in the vials. Two different sample loop sizes, 0.2 and 1.0 mL, were compared. When the larger sample loop was used with samples that contained high water amounts, the GC column was overloaded, and the peaks were asymmetrical because of increased tailing.

 The amount of water in the headspace of sealed samples at 100 ºC was evaluated every 5 min for 20 min. It can be seen that the maximum response is at 
					5 min and after that point the response plateaus.

Quantitative Analysis of Residual Water in Samples

	Two calibration curves for water were developed in order to quantify its content in 115 syrup samples (see “Experimental” section). Figure 2 illustrates the linear relationship between the peak area and the percent water for different concentrations of water in fructose. The correlation (

) was found to be 0.99. A second calibration curve produced in DMSO was also found to have a correlation of 0.99. The water in 16 syrups and sweeteners was analyzed and the percent water therein is presented in Table I (they ranged from ~20% to 90%). The water content was also analyzed with the loss on drying method, which gave comparable values but required much longer analysis times (Table I) and by KFT.

 Plots of the linear relationship between TCD response and the water content in fructose–water solutions and DMSO–water solutions. Both had a correlation of 0.99. The equation for the line produced by the fructose–water solutions is 

 = 429,000x and the equation of the line produced by the DMSO–water solutions is 

	The precision of the headspace GC method was evaluated by analyzing all of the samples in quadruplicate. The relative standard deviation (RSD) for loss on drying, headspace GC and KFT methods were similar in most cases. When the average precision of the headspace GC method was compared to the average RSD produced by loss on drying, there were a few values with more than 8% RSD for the latter approach (that is, Nesquik chocolate syrup and Hershey’s caramel topping). It should be noted that while loss on drying usually produced similar RSDs, the procedure took 4–7 days to complete whereas the headspace GC method took 10 min. As has been noted previously, KFT often provides good precision while producing inaccurate results (16). This tendency will be discussed in the next section.

	The National Institute of Standards and Technology (NIST) does not currently provide standard reference materials for moisture in sugar solutions; therefore, accuracy of the headspace GC method was estimated by comparing it to results obtained by two other methods, KFT and loss on drying. The three methods gave similar results, but it was determined that KFT often appeared to overestimate the water content compared to the other two methods. When KFT and headspace GC were compared with a T-test it was found that they were only similar in the case of five samples, and KFT was similar to three of the loss on drying samples. When loss on drying and headspace GC were compared, it was found that most of the samples were similar. When the french vanilla coffee creamer was analyzed with headspace GC and loss on drying, a similar result of ~30% water was found. In contrast, KFT gave a significantly higher water content (46% water). On average, KFT yielded ~5% higher water contents than the other two methods. It appears likely that the KFT reagent reacted with some of the nonaqueous components or constituents of many of the samples. Results with high bias have been previously noted for KFT for samples that contain large amounts of sugar (24). Loss on drying usually had the lowest measured water content of the three methods; however, it has been known to underestimate water when the viscosity of the sample increased substantially after heating, which, in turn, decreases the diffusion rate of water (25). This effect would also apply to a few of the samples (that is, Nesquik chocolate syrup and Hershey’s caramel topping), which still had small decreases in mass after being heated for seven days. In addition, when the incubation temperature was further increased for a few hours it led to sample degradation. Since the mass did not completely stabilize it can be assumed that there was still some moisture present.

	The effect of different instrumentation can affect the GC conditions used as well as peak shape, split ratios, and resolution. This is particularly true when comparing new state of the art instruments with analogous types that are 10 or more years old. It was found that the older TCD system had poorer sensitivity and therefore required a lower split ratio, 5:1. As shown in Figure 3, the decrease in split ratio caused the water peak to lose symmetry via increased tailing. The lower split ratio also led to broader peaks and therefore a lower resolution between the air and water peaks. In addition, when samples were analyzed with the older, less sensitive TCD systems, the analysis temperature had to be kept slightly lower, 150 °C versus 170 °C, to allow for baseline separation between the water and air because of peak broadening and increased tailing.

 Typical chromatograms obtained for the analysis of water in agave nectar 
					(a) when analyzed with the Shimadzu Tracera 2010 TCD system at 170 °C with a split ratio of 100:1 on a 60-m Watercol 1910 column, and (b) using an older, less sensitive TCD system at 150 °C and a split ratio of 5:1 on a 60 m Watercol 1910 column.

	The water content of 16 liquid sweeteners were determined using headspace GC. This method was rapid, accurate, and precise. It was shown to be broadly applicable to a variety of sugar and sugarless sweeteners. The method does not require long heating periods (4–7 days) in an oven as with the loss on drying method, so the water content can be rapidly determined in the syrups. KFT was shown to overestimate the water content in most of the samples. The ease, accuracy, and robustness of the headspace GC analyses are greatly enhanced when using an ionic liquid-based column and a GC instrument that is specifically designed and configured for the analysis of water.

	This work was also supported by the Robert A. Welch Foundation (Y0026). We would like to thank Shimadzu Scientific Instruments for the use of the Tracera 2010 GC.

		L.R. Richardson and J.V. Halick, “Bulletin 754,” Texas Agricultural Experiment Station: College Station, Texas (1952).

		R.S. Applebaum, R.E. Brackett, D.W. Wiseman, and E.H. Marth, 

		J. Pleadin, M. Zadravec, N. Perši, A. VuliÄ, V. Jake, and M. Mitak, 

		D.A. Jayawardhana, R.M. Woods, Y. Zhang, C. Wang, and D.W. Armstrong, 

		L.A. Frink, C.A. Weatherly, and D.W. Armstrong, 

		W.K. O’Keefe, F.T.T. Ng, and G.L. Rempel, 

		H.G. Streim, E.A. Boyce, and J.R. Smith, 

		D.W. Armstrong, T. Payagala, and L.M. Sidisky, 

		K. Huang, X. Han, X. Zhang, and D.W. Armstrong, 

		C.A. Weatherly, R.M. Woods, and D.W. Armstrong, 

		P. Bruttel and R. Schlink, “Water Determination by Karl Fischer Titration,” Metrohm Monograph 4-1 (2003). 

		H.-D. Isengard, D. Schultheiß, B. Radovic´, and E. Anklam, 

This fast, automated method was shown to be accurate and precise for 16 liquid sweeteners, and is likely more accurate than Karl Fischer titration.

Using Headspace Gas Chromatography for the Measurement of Water in Sugar and Sugar-Free Sweeteners and Products

Speciation analysis of elemental contaminants in food and beverages has received a lot of attention in recent years. Recent regulations limit inorganic arsenic, taking into account that arsenic toxicity is dependent on the species present. Thus, the analysis procedure needs to be able to differentiate inorganic from organic arsenic forms. Liquid chromatography–inductively coupled plasma-mass spectrometry (LC–ICP-MS) is commonly used for the separation and detection of arsenic species, with the most widely used implementation based on ion exchange and characterized by relatively long run times. Testing of increasing sample numbers means that analysis speed becomes a focal point for potential improvements. We developed a method based on ion interaction chromatography, allowing a reduction in run times to <3 min. The method was applied to a range of food and beverages samples. Here we discuss the results of these analyses and associated method validation tests.

	With the expanding knowledge of element species and their distribution in foods, elemental speciation analysis has received increasingly wider attention by the food industry. The relevance of speciation analysis for the elements As, Se, Cr, and Hg has long been established based on the significant toxicity differences between the species of these elements. For arsenic, the number of identified species found in food is still growing, as evidenced by new research findings into arsenolipids (1); therefore, our knowledge of the biochemistry and toxicity of arsenic-containing biomolecules is also still expanding. It is a very active research field, and most new findings have been made in aquatic species and seafood. For terrestrially grown food, the number of arsenic species is more limited. For this report we investigated rice and juice, which have been the target of recent regulatory oversight that singles out and limits the toxic inorganic arsenic forms.

	The increased demand for testing requires methods that are fast, sensitive, and sufficiently robust to cope with the matrix changes associated with various food products being subjected to extraction and analysis. Various methods exist to analyze for inorganic arsenic, including hydride generation coupled to spectrometric detection (2) and the development of field kits (3). The gold standard for this analysis, however, is liquid chromatography–inductively coupled plasma-mass spectrometry (LC–ICP-MS). It is the most widely used method for arsenic speciation (4) and is investigated in this study. The methodology to separate and quantitate common arsenic species by LC–ICP-MS is mature and well established. However, one disadvantage of current LC–ICP-MS methods is their relatively long run times, even for food matrices where the speciation is not complex.

	Ion-Interaction Chromatography or Ion Pairing: Differences and Novelties

	For the food examined in this paper, the number of arsenic compounds quantitated is typically restricted to four species: As3, As5, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA). These are ionizable compounds, and the LC separation techniques are therefore based on ion-exchange or ion-pair chromatography. The latter is also referred to as 

 to more correctly denote the wider scope of the interactions encountered beyond formation of ion pairs (5). Nevertheless, Cecchi still titled her book “Ion Pair Chromatography” because of the widespread recognition of the term (5). The term 

 is emphasized in this article to better highlight the difference in this approach compared to conventional ion-pair chromatography. Some of the pros and cons of ion-exchange and ion-pair chromatography have been summarized earlier (6). Among other factors, ion interaction approaches may use less-expensive columns with well-characterized stationary phases, while methods based on ion exchange may suffer less from matrix interferences.

	Ion-interaction chromatography gives great flexibility in tailoring the separation to the speciation analysis in terms of ion-pairing reagents to use for the separation. Whereas ion-exchange separations are based mainly on electrostatic interactions, the retention behavior of analytes in ion-interaction mode may be more complex and involve more than one retention mechanism (5). In addition to electrostatic interaction of analyte ions with the electrical charge imparted by the ion-pairing reagent to the stationary phase, retention may also occur through interaction of uncharged analytes with the nonpolar component of the stationary phase or interaction with residual silanol groups.

	Both traditional anion-exchange and anion-pairing methods for the separation of As3, As5, MMA, and DMA use circumneutral or alkaline conditions to ionize most of the target analytes, resulting in run times typically ranging from 9–15 min. Reducing the run time required by anion exchange is still a pressing issue and the subject of recent research (7). The traditional ion-pairing approach for this problem involves anion-pairing reagents, such as tetrabutylammonium hydroxide (8). Our approach investigated here differs in that we use a cation-pairing reagent in a mobile phase at acidic conditions. The purpose of the cation-pairing reagent is not to interact with cations, but rather to repel like charged anions.

	It has previously been noted that when working with cation-pairing reagents the separation of early eluted anions or neutral molecules, such as those studied here, can be achieved (9). The problem was, however, that the cationic analytes eluted at long retention times, leading to attempts of combining two ion-pairing reagents in the same solution to shorten the elution times of the analyte cations while trying to maintain the separation of the early eluted species (9). Similarly, Miyashita used a mixture of ion-pairing reagents, with a less effective, shorter-chain cation-pairing reagent to decrease the retention of cations (10). The resulting compromise was, however, not ideal in those cases and was characterized by loss of baseline resolution for some of the early eluted peaks. Reproducibility problems ensued when implementation was attempted in different laboratories, and these techniques did not catch on. The aim of those analyses was to also determine cationic species such as AsC. They, therefore, did not focus on a dedicated optimization for the separation of the early eluted species for situations where cationic species are absent as target analytes. The benefit of the fast run times of the approach explored here was yet untapped.

	Ion-Interaction Chromatography: Method Development

	To make the output from the column amenable to introduction to the ICP-MS system, we considered in our optimization both peak separation and minimizing the dissolved solids content of the mobile phase. Using the conditions in the study by Miyashita and colleagues (10) as a starting point, we changed the cation-pairing reagent to octane sulfonate (OSA), omitted the anion pairing reagent, retained malonic acid as a buffer, and used the same column. However, the pH, OSA concentration, and malonic acid concentration were reoptimized to separate the four species As3, As5, MMA, and DMA. Furthermore, arsenobetaine was included in the study on the sideline to possibly serve as an internal standard and explore the potential to expand the technique to seafood analysis. Accurate species quantitation in seafood was hindered by the early elution of large amounts of AsB in anion exchange techniques, prompting the development of fast techniques that aim to only quantitate inorganic As in LC runs (11). The late elution of AsB after the other analyte peaks may be an attractive feature here. Proper pH selection is crucial as it is in other ion-pairing or ion-exchange applications. At the experimentally determined optimum pH 4.0, As5 is anionic (p

 = 6.2) are neutral (acidity constants taken from reference 12). Thus, the anions arsenate (As5) and MMA are eluted first as a result of electrostatic repulsion from OSA adsorbed onto the C18 surface. The neutral species arsenous acid (As3) and DMA are retained stronger and are eluted later. Retention of those species is likely based on weak partitioning. AsB is zwitterionic at this pH (p

 = 2.2) and is eluted last. Its stronger retention may be influenced by electrostatic attraction between its cationic moiety with the negatively charged stationary phase. In summary, a variety of interaction mechanisms, both attractive and repulsive, take part in the separation. Overall, the limited interaction by attractive forces results in desirable short run times while maintaining baseline separation of the species. Understanding the separation mechanism may be aided by the illustration provided in Figure 1.

 Ion interaction chromatography mechanism. Repulsive forces between anions and a negatively charged surface lead to their early elution and separation from neutral molecules, which are weakly retained by partitioning. The diagram includes the four most abundant arsenic species in apple juice and rice.

	The regulatory bodies initially focused on the need for testing apple juice, therefore, we first applied our method to the analysis of apple juice.

	The analysis was carried out on an Altus-10 HPLC system coupled to a NexION 350D ICP-MS system (both from PerkinElmer). The mobile phase for the apple juice analysis consisted of 2 mM octanesulfonate, 2 mM malonic acid, adjusted to pH 4.0 and blended with 1% methanol. The separation was carried out on a C18 column, monitoring As75 in standard mode. The injection volume was 20 µL. Complete operational details are given elsewhere (13).

	Standards were prepared in mobile phase, and the apple juice samples were injected directly without further dilution. The only sample treatment was filtration, if required. Figure 2 shows the peaks are well resolved. Not only is the run time very short, but also DMA is well resolved from As3, whose adequate separation is typically challenging in anion-exchange chromatography. Furthermore, AsB, which is not present in the samples, is eluted well after the analyte peaks and may be used as an internal standard.

 Sample chromatogram of an apple juice sample (20 µL injection) with and without AsB spike. AsB may be used as an internal standard.

	Several store bought apple juice samples were analyzed, and the results (Figure 3) show that both inorganic arsenic forms dominate. Levels of inorganic arsenic are well below the action limit of 10 ppb proposed by the United States Food and Drug Administration (US FDA). The check standards analyzed periodically throughout the run showed 6% maximum deviation over an 8 h period, thus obviating the need for an internal standard.

	Arsenic Speciation in Rice: Method Optimization

	Arsenic speciation in rice is receiving a lot of attention because of legislation being implemented in Europe and China limiting the content of permissible inorganic arsenic. The most stringent limit of 100 ppb inorganic arsenic applies to rice for production of food for infants and young children.

	We investigated arsenic speciation in rice after extraction with 0.28 M nitric acid according to the method published by Huang and colleagues (14). This extraction method preserves species identity and has been thoroughly validated (15). Initial tests with direct injection of the acidic extract impacted the chromatography: The DMA peak broadens and shifts to a longer retention time, while the As5 peak shape deteriorated. There is also a very strong effect on AsB retention time and peak shape. Those effects were less pronounced upon dilution, but not eliminated (Figure 4a).

 Effect of acidity: Analysis of diluted rice extracts without (a) and with (b) neutralization. Neutralization eliminates adverse effects on DMA and AsB. Solutions were spiked with 5 ppb for all As species. 20-µL injections.

	Neutralizing the sample extract restored peak shape and retention times for DMA and also allowed AsB to be used as internal standard (Figure 4b), indicating that the adverse effect on those peaks was caused by the introduced acidity. However, the As5 peak shape remained poor (Figure 4b), suggesting this effect is related to ionic strength. In a subsequent optimization of the mobile phase, we aimed to reduce the difference between sample matrix and mobile phase to improve the As5 peak shape. We obtained both optimum separation and peak shape for all four analyte peaks with the addition of 50 mM ammonium nitrate to the mobile phase. Those experiments were carried out with two-fold diluted, neutralized extract matrix at 10 and 20 µL injection volumes.

	The results achieved with neutralization allow for lower detection limits (because of limited sample dilution) and display good method robustness. The benefits of a neutralization step led to its incorporation in the arsenic speciation protocol used by the FDA (16). However, the addition of a neutralization step also increases the analysis complexity and needs more user awareness than a direct analysis of acidic extracts. We therefore tested the possibility of analyzing extracts simply diluted with deionized water without further neutralization. The results show that the improvement to As5 peak shape brought about by the ammonium nitrate addition to the mobile phase persisted, corroborating the earlier indication that the As5 peak shape had been affected by ionic strength differences between samples and mobile phase. However, at low dilutions (twofold), the DMA peak broadened and even split. The effect was seen in both rice extract and extract matrix and persisted when the DMA solution was prepared fresh from the solid chemical, eliminating the possibility that the peak split would be attributable to aging of solutions. Increasing the dilution ratio with deionized water alleviated the issue, and 10-fold diluted extracts were successfully analyzed at 10- and 20-µL injection volumes (Figure 5).

 Extract matrix, 10-fold diluted with deionized water, and spiked with 1 ppb As species.

	The results of the optimization experiment show that a mobile phase modified by the addition of 50 mM ammonium nitrate provides both good peak separation and peak shape of all four analyte peaks for twofold diluted neutralized extracts and 10-fold diluted extracts without neutralization, allowing flexibility in the sample preparation protocol to accommodate both approaches. If dilution with deionized water is selected as the sole analysis approach, a lower ammonium nitrate concentration in the mobile phase may also be used.

	Using the mobile phase composition of the apple juice analysis with the modification of 50 mM ammonium nitrate addition, we injected 10 µL of 1:10 diluted sample extracts. National Institute of Standards and Technology (NIST) 1568b rice flour reference material was digested in duplicate and analyzed to test the applicability of the method for rice analysis. The results agreed well with certified values with recoveries averaging 99% for MMA and DMA, and 97% for inorganic arsenic, thus validating the method.

	We analyzed two rice samples intended for baby food production and five additional rice-derived products aimed at babies that are 4 or 7 months old. The results are displayed in Figure 6. Inorganic arsenic is given as the sum of As3 and As5. Both species are plotted as adjacent bar segments so inorganic As can be easily read off the graph (Figure 6). The white rice sample (R1) was far below the relevant EU limit of 100 ppb inorganic arsenic, while the brown rice sample (R2) was above the limit. The rice cereal (R3) and porridge samples (R4, R5) range from 67 to 117 ppb, and the two rice cake samples (R6, R7) are 142 and 116 ppb, respectively, both below the total inorganic arsenic limit of 300 ppb set by the EU legislation. Inorganic arsenic was the dominant arsenic form. DMA is the major organic arsenic species, and MMA is a minor constituent of some samples.

 Distribution of arsenic species in rice and rice derived products for baby food.

	The mobile phase worked as a calibration matrix with species remaining stable during the run. Reanalyzing standards prepared in mobile phase in the range 0.05–5 ppb one day after preparation confirmed the species are stable.

	Detection limits expressed as parts per billion in solid were 2.5 µg/kg for As5 and As3 and 2.0 µg/kg for MMA and DMA (expressed on elemental As basis), demonstrating adequate sensitivity of the analysis. Detection limits were calculated based on 3*SD of analysis of seven replicates of a 0.05 ppb As standard. Detection limits may be further lowered by increasing the injection volume from 10 to 20 µL if desired, or by neutralizing samples before injection to utilize lower dilution ratios.

	Spike recoveries (1 ppb spike level) ranged from 94–115% for all samples and all species, with averages for all samples being 102%, 104%, 102%, and 102% for As5, MMA, As3, and DMA, respectively.

	An analysis method for arsenic in apple juice and rice by ion-interaction chromatography has been developed that uses electrostatic repulsion of analyte anions from a negatively charged stationary phase in addition to partitioning of neutral analytes. The limited role of attractive forces results in very short run times, substantially shorter than what is currently used for ion-exchange techniques. We adapted the technique for the analysis of apple juice and rice extracts and demonstrated accurate results and method robustness to cope with variations in sample type. Early elution of analyte peaks leads to tall and narrow peaks, which allow lower levels to be measured and increases quantitation accuracy. This approach provides advantages compared to anion-exchange methodology, which not only has longer run times, but also reverses elution order with As5 eluted as the last peak. With substantially shortened run times, recalibrations are much less time consuming (12 min for four standards). Also check standards and quality control solutions can be analyzed more frequently, improving data quality. Furthermore, higher sample throughput is desirable to meet the increased testing needs generated by the introduction of recent legislation for arsenic speciation in food.

		K.O. Amayo, A. Raab, E.M. Krupp, and J. Feldmann, 

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Spectrochim. Acta Part B-Atomic Spectrosc.

Ion-Pair Chromatography and Related Techniques

		S. Afton, K. Kubachka, B. Catron, and J.A. Caruso, 

		J.J. Sloth, E.H. Larsen, and Y. Julshamn, 

		H. Ernstberger and K. Neubauer, “Accurate and Rapid Determination of Arsenic Speciation in Apple Juice,” PerkinElmer application note (2015).

		J.H. Huang, P. Fecher, G. Ilgen, K.N. Hu, and J. Yang, 

		K.M. Kubachka, N.V. Shockey, T.A. Hanley, S.D. Conklin, and D.T. Heitkemper. US Food and Drug Administration, “Elemental Analysis Manual for Food and Related Products,” Section 4.11 (FDA, Rockville, Maryland, 2012).

 is with PerkinElmer in Shelton, Connecticut. Direct correspondence to: 

This speciation method based on ion-interaction chromatography has a run time of 

Ensuring the Safety of the Food Supply: Speeding Up Arsenic Speciation Analysis

Using a liquid chromatography–mass spectrometry (LC–MS) method in conjunction with two complementary types of chromatographic retention modes-reversed phase and aqueous normal phase-various compounds present in mesquite flour extracts were identified. Because of the diverse types of chemical constituents found in such natural product extracts, a single chromatographic mode may not be sufficient for a comprehensive characterization. However, the combination of reversed-phase and aqueous normal phase LC can encompass a wide range of analyte polarity. This characterization of the composition of mesquite flour could be used in future studies to elucidate the beneficial health effects of its consumption.

	Mesquite flour is made from the seed pods of shrubs belonging to the 

 genus, indigenous to various arid and semiarid ecosystems throughout the Americas, Africa, and Asia. In comparison to wheat-based flour, its consumption has numerous health advantages. Wheat contains a mixture of proteins known as gluten, which imparts chewy, elastic properties to foodstuffs derived from wheat (for example, bread, muffins, cakes, and so forth) However, gluten has little nutritional value and can even be detrimental to certain individuals, such as those with celiac disease. In this case, ingesting even trace amounts of gluten can induce a serious systemic autoimmune response, necessitating strict adherence to a lifelong gluten-free diet (1). As a legume-derived food, however, mesquite flour is naturally gluten-free. Hence, it offers a viable dietary alternative for gluten-intolerant individuals who still wish to eat flour-based foodstuffs. For diabetics, its low glycemic index makes it a good source of carbohydrates that can help keep blood sugar levels stable (2). In general, it is high in nutritious proteins as well as in dietary fiber (3,4), the latter of which may be difficult to obtain in some gluten-free diets. Another advantage pertains to the climate of a given area; in certain desert regions where cultivation of wheat or maize crops is difficult, mesquite is often considered to be a staple food.

	Consumption of mesquite-derived foods has been linked to antibacterial (5), cardioprotective (6), and anti-inflammatory (7) health effects. Various small molecules that are known to be present in mesquite are thought to play a role in some or all of these properties, including flavonol glycosides, glycosyl flavones, anthocyanins, and ellagic acid derivatives. Hence, to better study these health effects, there is a need for reliable analytical methods for the characterization of compounds found in mesquite flour-based foodstuffs.

	This is a nascent topic of food research today and several recent studies have begun to report such characterizations. For example, in their liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis of Chilean 

 mesocarp flour, Schmeda-Hirschmann and colleagues identified eight anthocyanins and 13 different phenolic compounds (8). Quantitative analysis showed that their antioxidant activity was determined to be 0.82–2.57 g gallic acid equivalents/100 g fresh flour weight. In another recent work, Pérez and colleagues used both LC–MS/MS and high performance liquid chromatography–ultraviolet spectroscopy (HPLC–UV) based methodologies for determining the content of phenolics, flavonoids, anthocyanins, and alkaloids in 

	In terms of a total characterization of the constituents of mesquite flour, the primary challenge facing chromatographers is how to retain compounds encompassing the whole range of polarity that may be encountered in a given sample extract. While conventional reversed-phase chromatography may be well-suited to retention of some of the more hydrophobic analytes such as anthocyanins or polyphenols, others that have hydrophilic glycosidic moieties may be more problematic. In this case, aqueous normal phase chromatography may be able to offer a viable solution for adequate retention.

	In recent years, aqueous normal phase chromatography has been shown to be a valuable tool in the characterization of food samples. Suited to retention of polar compounds, it can be thought of as a complementary or orthogonal technique to reversed-phase chromatography (10). Hence, both polar and nonpolar compounds can be retained in a complex sample, leading to a more complete characterization of its components. Recent examples of aqueous normal phase chromatography used to retain polar compounds in foodstuffs include histamine in cheese and tuna (11) and sugars in beverages (12).

	Along these lines, we performed a qualitative investigation of the chemical constituents of mesquite flour samples using a LC–MS method in conjunction with both reversed-phase and aqueous normal phase retention modes.

 (white mesquite) flour samples were obtained from Argentina. Formic acid was from Sigma–Aldrich. Acetonitrile, methanol, and deionized water (HPLC grades) were obtained from GFS Chemicals, Inc.

	An Agilent 1100 Series LC system, including degasser, binary pump, temperature-controlled autosampler, and temperature-controlled column compartment, was used. The mass spectrometer system was an Agilent Model 6210 MSD time-of-flight (TOF) system with a dual sprayer electrospray ionization (ESI) source. The analytical columns were packed with either a 50 mm x 2.1 mm Phenyl Hydride or a 100 mm x 2.1 mm Bidentate C18 (BDC18) stationary phase, which had a particle diameter of 4 µm and a pore size of 100 Å in either case (MicroSolv Tech. Corp.). The final mobile phase obtained after method development used a gradient: Solvent A was deionized water–0.1% formic acid (v/v) and solvent B was methanol–0.1% formic acid (v/v) for reversed-phase mode or acetonitrile–0.1% formic acid for aqueous normal phase mode. The gradient programs are shown in Table I. The flow rate was 0.4 mL/min and the injection volume was 1.0 µL. In the positive and negative ionization modes, the extracted ion chromatogram was obtained for each analyte as the [M + H]

Sample Preparation: Mesquite Flour Extracts

	First, 1.00 g of mesquite flour was weighed on a Mettler Toledo ME204E toploader balance and transferred to a 250-mL beaker. In a graduated cylinder, 15.0 mL of deionized water was measured and transferred to the beaker as well. The mixture was then stirred with a magnetic stir bar on a stir plate for 15 min. Subsequently, it was transferred to a centrifuge tube and centrifuged for 5 min with an International Clinical Centrifuge Model CL centrifuge. The supernatant was collected with a pipet and transferred to a new container. The whole procedure was repeated two more times to obtain a total of 45.0 mL of water-based sample extracts.

	The remaining flour in the centrifuge tube was used for additional extractions with 70:30 methanol–deionized water. In a 250 mL beaker, 1.00 g of the wet flour and 15.0 mL 70:30 methanol–deionized water were added. The mixture was then stirred with a magnetic stir bar on a stir plate for 15 min. Subsequently, it was transferred to a centrifuge tube and centrifuged for 5 min. The supernatant was collected with a pipet and transferred to a new container. The whole procedure was repeated two more times to obtain a total of 45.0 mL of methanol–water-based sample extracts.

	Both 45.0-mL extracts were then vacuum filtered through a 0.45-μm nylon membrane filter (MicroSolv Tech. Corp.) and transferred to round-bottom flasks. The filtrates were then evaporated using a rubber tube connected to the vacuum line. The filtrates were kept at room temperature until all of the solvent (water or methanol–water) was removed. Aliquots of these filtrates were then used for the LC–MS injections.

	A summary of the retention times observed for the different analyte ions using both reversed-phase and aqueous normal phase gradients and both column types is shown in Table II. The table values show that reversed-phase mode was found to be suitable for most of the analytes that were observed in the mesquite flour extracts. In addition to the specificity afforded by the extracted ion chromatograms (EICs) themselves, chromatographic selectivity between the different peaks spanned a wide distribution of retention times across the chromatograms. With most of the studied compounds, the bidentate C18 column produced slightly greater retention than the phenyl column because of its greater hydrophobicity. However, quercetin 3-O-rutinoside was actually retained slightly longer on the phenyl column. Since the primary difference between the two stationary phases is the ability of the phenyl to participate in π–π interactions, this difference in retention among the two columns seems to suggest that such interactions played a more prominent chromatographic role in the case of quercetin 3-O-rutinoside’s π system.

	Peak shapes were generally very sharp for all the studied analytes, and no significant tailing was observed. Figure 1 shows representative EICs for two analytes from the mesquite flour extracts in reversed-phase mode using the bidentate column, illustrating the high efficiency of the peaks. In addition to the chromatographic separation itself, the use of mass spectrometry allowed for excellent specificity in isolating individual peaks via the EICs.

LC–MS EICs for two compounds observed in the mesquite flour extracts in the reversed phase mode: (a) vitexin and (b) Q-hexoside.

	However, some analytes could not be adequately retained using either column in reversed phase, such as the 

 505.176 sugar compound. In these cases, aqueous normal phase approaches were investigated and often found to be able to retain such compounds. For instance, the same sugar compound that was eluted at the solvent front in reversed-phase mode was found to be eluted at 2.449 min under aqueous normal phase conditions (refer again to Table II). Cyanidine-3-hexoside and luteolin 7-O-glucoside were also observed to be retained strongly in the aqueous normal phase gradient (see Figure 2). Conversely, malvidin dihexoside was well-retained in reversed-phase mode using the phenyl column but was eluted at the solvent front in the aqueous normal phase mode (Figure 3). This behavior highlights the complementary nature of the two retention modes: If a compound cannot be retained by one mode, the other may be a viable option for its retention instead. In the comprehensive analysis of complex samples such as mesquite flour extracts-in which many kinds of compounds with disparate structural characteristics may be present-the use of a single chromatographic mode may not be sufficient.

 LC–MS EICs for two compounds observed in the mesquite flour extracts in the aqueous normal phase mode: (a) cyanidine-3-hexoside and (b) luteolin 7-O-glucoside.

Given the wide range in polarity of the components of mesquite flour, it is advantageous to study the health benefits of this flour using methods that combine the complementary approaches of reversed-phase and aqueous normal phase LC.

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Ensuring the Safety of the Food Supply: Speeding Up Arsenic Speciation Analysis

LC–MS Characterization of Mesquite Flour Constituents

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