Gas chromatography for food quality evaluation

Gas chromatography for food quality evaluation

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Tao Feng*, Min Sun*, Shiqing Song*, Haining Zhuang†, Lingyun Yao* *School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, People’s Republic of China, †Key Laboratory of Edible Fungi Resources and Utilization (South), Ministry of Agriculture, Division of Edible Fungi Fermentation and Processing, National Engineering Research Center of Edible Fungi, Institute of Edible Fungi, Shanghai Academy of Agricultural Sciences, Shanghai, People’s Republic of China

12.1

Introduction

Food quality is specified in terms of traceable origin, known chemical composition (e.g., fat content, moisture, protein content), adequate physical properties (e.g., texture, color, tenderness), satisfactory sensory evaluation, and safety and health safeguards with respect to microbiological and toxic contamination, and is influenced by the processing and storage of products [1, 2]. Maintaining high food quality is of great importance for food producers, suppliers, and consumers [3]. However, food products show continuous quality changes at every stage of production and food distribution. The increasing demand for food quality requires development and application of highly efficient and reliable detection technologies throughout the food production and distribution process to guarantee high-quality products for consumers. This drives a need for researchers to develop various detection technologies for analyzing, assessing, and certifying product quality. The presence, composition, and content of volatile compounds play important roles in evaluating the quality of many food products. For example, odor sensation, which is triggered by highly complex mixtures of volatile substances, performs a vital role in shaping organoleptic quality and usually occurs in trace-level concentrations [4, 5]. These components may affect health and safety both positively and negatively. Therefore identification and quantitative evaluation of volatile compounds in food will provide important information on the quality of food products. Volatile molecules are present in raw materials and can originate at every production stage from all food components, and they can also be formed during the storage of food products [4]. Until now, more than 7000 volatile molecules have been detected and it has been estimated that up to 10,000 volatiles may be present in food [6]. In addition, new and challenging quality problems have emerged as food supply chains have become increasing global and complex. For example, food fraud and economically motivated adulteration of food are risks gaining increased attention from industry, governments, and standards-setting organizations [7], because adulteration with cheaper ingredients would decrease the quality of food products, mislead consumers, and may imply a Evaluation Technologies for Food Quality. https://doi.org/10.1016/B978-0-12-814217-2.00012-3 © 2019 Elsevier Inc. All rights reserved.

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health risk. In addition, the occurrence and fate of pharmaceutical compounds in food or in the environment may pose a potential threat to the ecosystem and human health and have also been recognized as emerging and prevailing problems [8, 9]. For instance, antibacterials in food constitute a potential risk to human health because the use of antibiotics in feed additives is common [8]. A classical approach to the evaluation of food quality is based on the exploitation of gas chromatography (GC) analysis, which was one of the first chromatographic separation techniques to be developed and has still today lost none of its eminence [10]. Many food components can be analyzed with great accuracy by GC and it has become one of the main techniques in analytical laboratories concerned with food quality evaluation (Fig. 12.1). The popularity of GC is based on a favorable combination of very high selectivity and resolution, good accuracy and precision, wide dynamic concentration range, and high sensitivity. GC remains a healthy and growing measurement technique with expanding influence in innovative applications, including the analysis of emerging organic pollutants, such as polychlorinated alkanes and polybrominated diphenylethers. The vitality of GC is also reflected by on-field analysis and in the development of new technologies, such as high-speed GC and comprehensive multidimensional GC (GC
GC), which greatly increases the separation capability of a chromatographic system. This chapter gives a general introduction to GC. It deals with basic principles of chromatographic methods and the reader is introduced to the chromatographic separation process. The components of a gas chromatograph are described and the application range of GC for food quality evaluation is presented.

Fig. 12.1 Schematic of gas chromatography techniques for food quality evaluation.

Gas chromatography for food quality evaluation

12.2

221

The basic principles of GC

The separating of individual components in complex mixtures by column was first developed in 1903 by Mikhail Tswett, who introduced the term chromatography in 1906 [11, 12]. However, the chromatographic technique was used only by a few researchers in the following decades [12]. Martin and Synge extended the usefulness of chromatography in separation science and technology based on utilization of partition as the basis of the separation process [13], and the important seminal work was awarded the Nobel Prize in Chemistry in 1952. Chromatography separates components in a sample by introducing a small volume of the sample at the start/head of a column, and has become one of the most widely used techniques in modern analytical chemistry. Chromatography achieves separation of mixtures by partition of components between a mobile phase and a stationary phase. When the mobile phase is a gas, the technique is referred to as GC. The stationary phase could be solid and liquid, and the GC technique is called gas–solid chromatography (GSC) or gas–liquid chromatography (GLC) according to the physical state of the stationary phase. Separation occurs mainly according to adsorption and/or partition chromatography. In GSC, separation is obtained when the components have different adsorptivities to a solid stationary phase. In GLC, the stationary phase is a nonvolatile liquid and separation is obtained if the analytes have different distributions between the mobile and stationary phases. The molecules need to be stable at the temperatures in the injector and/or in the column during the analysis process. Components that are not volatile should be made volatile by derivatization for GC analysis.

12.2.1 GC instrumentation In GC, the mobile phase (the carrier gas) flows continuously to push the components in the injected sample through the column so that they can be separated and eluted from the column outlet. After the column, the carrier gas and sample pass through a detector. This device measures the quantity of the sample, and it generates an electrical signal. The output signal of the detector gives rise to a chromatogram (the written record of GC analysis) for sample qualitative/quantitative data collection and analysis. Schematically, a gas chromatographic instrument includes six basic parts (Fig. 12.2) [14]: carrier gas, flow controller, injector, column, detector, and data system.

12.2.1.1 Carrier gas/mobile phase The main purpose of the mobile phase (carrier gas) is to carry the sample through the column. The mobile phase must be an inert gas, and does not interact chemically with the sample components or the stationary phase. Carrier gas is typically provided by high-pressure tanks connected to the sample introduction chamber (injection port) via metal tubing (Fig. 12.2). The gas that is used must be of high purity (99.995% or higher), and, if necessary, can be purified to remove traces of oxygen, water,

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Fig. 12.2 Typical gas chromatograph: (1) gas flask with carrier gas; (2) reduction valve; (3) injection system; (4) column oven; (5) column; and (6) detector. Reprinted with permission from E. Lundanes, L. Reubsaet, T. Greibrokk, Chromatography: Basic Principles, Sample Preparations and Related Methods, first ed., Wiley-VCH Verlag: Weinheim, Germany, 2014 (Copyright, Wiley-VCH 2014).

and hydrocarbons. It is important that the carrier gas be of high purity because impurities such as oxygen and water can chemically attack the stationary phase in the column and destroy it. Adsorbent tubes containing charcoal and molecular sieves are used to remove low molecular mass hydrocarbons and water, respectively. High-purity He, N2, and H2 are the mainly used carrier gases in GC analysis. For the thermal conductivity detector (TCD), helium is the most popular. In some parts of the world (where helium is very expensive), hydrogen is chosen because of its lower price. To provide high safety in use, hydrogen is not recommended because of the potential for fire and explosions. With the flame ionization detector, either nitrogen or helium may be used. Nitrogen provides slightly more sensitivity, but a slower analysis, than helium/hydrogen. For the electron capture detector (ECD), very dry, oxygen-free nitrogen is recommended.

12.2.1.2 Flow controller system The flow rate of the mobile phase may affect the efficiency (plate height) of the column and the retention of the components. Therefore the measurement and control of carrier gas flow is of great importance for both column efficiency and qualitative analysis. It is important to know and record the flow rates of the gas so that the analysis process can be repeated in the future. Regulators on the gas flask help maintain appropriate working pressures and indicate the amount of gas left in the flask. The inlet to the instrument controls the flow rate of gas supplied to the injection port and to the column. For isothermal operation (i.e., constant temperature throughout the separation), a constant flow rate can be obtained by constant column inlet pressure. The pressure of carrier gas is reduced by the reduction valve (with pressure meters) attached to the gas flask; in addition, pressure control is provided at the gas chromatograph.

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In temperature programming, even when the inlet pressure is constant, the flow rate will decrease as the column temperature increases. For temperature gradient separations, where the temperature is increased throughout the separation time, a flow rate controller is used to assure a constant mass flow rate. In modern GC instruments, flow rate and pressure are equipped with control units and these flows are set electronically. In older instruments, the flow is controlled using pressure regulators built into the instrument. For qualitative analysis, it is essential to have a constant and reproducible flow rate so that retention times can be reproduced. Comparison of retention times is the quickest and easiest technique for compound identification. Note that different components may have the same retention time, but no individual molecule may have two different retention times.

12.2.1.3 Injection system There are many different ways of injecting solutes into a column. Most of them involve injecting the sample into the injection-port liner rather than onto the column directly. The sample inlet should handle a wide variety of samples, including gases, liquids, and solids, and permit them to be rapidly and quantitatively introduced into the carrier gas stream. Problems arising in GC separations can often be traced back to the injection process. Thus understanding the injection process is vital to obtain reproducible results and to optimize the performance of the system. The choice of injection system depends on the column type and the sample composition. In packed columns, the sample is injected directly into the column inlet. The temperature of the injection part is usually kept higher than the column temperature, and high enough to allow rapid evaporation of the sample, both solvent and sample components, when the sample is introduced. About 2–10 mL of sample is transferred from the injection syringe, which is equipped with a thin needle having a sharp beveled tip, to the column inlet through the septum, which is made of a synthetic rubber (silicone) (Fig. 12.3). When the liquid evaporates, it occupies a gas volume that is about 1000 times larger than the liquid volume. The septum is kept in place by the metal septum holder and when the syringe needle is withdrawn, the elasticity of the septum closes the puncture hole made by the needle, keeping the septum gas tight. However, after a number of injections, a permanent hole in the septum is formed and the septum needs to be replaced. The injection temperature defines the choice of septum material. In capillary columns, there are four basic types of injection techniques: isothermal (hot) split and splitless, on-column, and programmed temperature vaporization (PTV). Isothermal split and splitless injections are performed in the same inlet called the split/ splitless inlet (Fig. 12.4). This split/splitless inlet is most common because of its simplicity and robustness. The split injection technique allows only a small part of the sample to be transferred to the column, while the largest part is directed to waste through the splitter outlet valve. Injecting too much sample into capillary columns often leads to poor peak shapes and poor resolution. Therefore injections are often conducted in what is referred to as split injection mode. In split injection mode, flow control valves within the instrument divide the total carrier gas flow between the column and the split vent. The ratio of the flow through the split vent relative to that

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Fig. 12.3 Packed column injector. Reprinted with permission from E. Lundanes, L. Reubsaet, T. Greibrokk, Chromatography: Basic Principles, Sample Preparations and Related Methods, first ed., Wiley-VCH Verlag: Weinheim, Germany, 2014 (Copyright, Wiley-VCH 2014).

Fig. 12.4 Split/splitless injector for capillary columns. Reprinted with permission from E. Lundanes, L. Reubsaet, T. Greibrokk, Chromatography: Basic Principles, Sample Preparations and Related Methods, first ed., Wiley-VCH Verlag: Weinheim, Germany, 2014 (Copyright, Wiley-VCH 2014).

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through the column is called the split ratio. It dictates the amount of sample that enters the column. Typical split ratios vary from 2:1 to 100:1 depending on the analysis being conducted and the nature of the sample. The split ratios are achieved by adjusting both the valve that controls the flow through the split vent and the valve that controls total flow into the instrument. While split injections provide improved peak shapes and resolution, the majority of the sample goes undetected and is wasted. In a sense, by using split injection, the challenge of detecting the molecules in the sample has been greatly increased. For relatively concentrated samples, this is not an issue. For trace solutes, however, split injection may not be practical. The purpose of the splitless injection technique is to introduce the entire injected sample into the column and use it for trace determination. In splitless injection, the sample is introduced into the heated liner as in split injection and brought into the gas phase. When splitless injection is carried out, the column inlet temperature is kept at a temperature that is 20–50°C lower than the solvent Bp. Hence when the sample arrives at the column inlet, the solvent condenses as a thick film on the column wall. This film will act as a plug of the stationary phase into which the sample components will be dissolved. Following sample transfer to the column, the column oven temperature is increased. The solvent evaporates first from the column entrance and thereafter the analytes, which will subsequently be separated in the column. The splitter valve is opened when the whole sample has been transferred to the column to wipe out remains of the sample before the next injection. This injection technique is used for trace determinations and can only be carried out in combination with temperature programming. On-column injection is more difficult to perform and is carried out only when the analytes are temperature labile. The liquid sample is introduced at room temperature by a syringe through a valve directly into the column entrance, or more commonly through a retention gap, when the gas flow through the column is stopped. A fused silica needle with a narrow outer diameter (e.g., 200 mm) must be used with a column of 250 mm inner diameter. For 320 mm inner diameter columns, it is possible to use stainless steel needles. For the narrow columns, a large bore retention gap (e.g., 450 mm internal diameter) connected to the inlet of the column can be used for sample introduction.

12.2.1.4 GC columns and partitioning The chromatographic column contains the stationary phase and is the place where the separation process occurs. Therefore the column is often called the heart of the chromatograph. The choice of column type, dimensions, and stationary phase determines the feasibility, quality, and duration of the analysis. GC separations can be carried out on packed or capillary columns. The column is connected directly to the injector and the detector by nuts and ferrules. Packed columns feature an inner diameter greater than 1 mm and are completely packed with the stationary phase. The packing material causes a resistance against the flow of the mobile phase through the column. Stainless steel is used most often, primarily because of its strength. Glass columns are more inert, and they are often used

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for trace pesticide and biomedical samples that might react with the more active stainless steel tubing. Packed columns are easy to make and easy to use. A large variety of liquid phases is available. Because the columns are tightly packed with small particles, this flow resistivity restricts the maximum length of packed columns to about 10 m, but mostly up to 4 m long columns are in use. Capillary columns have a much smaller inner diameter than packed columns, but the stationary phase is only located as a thin film or layer on the inner wall of the column. This leaves an open longitudinal channel in the middle of the column through which the mobile phase flows. Flow resistivity (backpressure) is only determined by column length and inner diameter. With capillary columns, the length of columns can reach 50 m and longer are possible. In GC analysis, the sample is injected at one end of the column. A carrier gas such as H2 or He serves as the mobile phase and is continuously pumped through the column. The gas is chosen so as not to interact or react with the solutes in the gas phase and is thus chemically inert. It is there simply to push the solutes down the column. When a molecule partitions into the stationary phase, it does not move down the column. However, when the molecule leaves the stationary phase and enters the gas phase, it is swept down the column by the flowing carrier gas. By being swept to a new part of the column, the molecules are in contact with a new portion of the stationary phase and reestablish an equilibrium between the stationary and mobile phases. Thus the solutes reenter the stationary phase some distance down the column. Solutes that are strongly attracted to the stationary phase spend a relatively long time in the stationary phase compared to the time they spend in the mobile phase. In this way, a complete separation of components of a mixture can be achieved.

12.2.1.5 Detectors The detector must be heated to avoid condensation of components eluted from the column, and generally the detector temperature is kept at least 20°C above the highest column temperature. There are a variety of detectors available for gas chromatographs, each with their own advantages and limitations. GC detectors can be classified as mass- or concentration-sensitive detectors. The chromatographic peak area using a mass-sensitive detector is independent of the flow rate used, while the peak area using a concentration-sensitive detector depends on the flow rate. The most common modes of detection for GC are flame ionization, thermal conductivity (TC), electron capture, and mass spectrometry (MS), although other methods also exist. Table 12.1 summarizes the detection limits, selectivity, and linear ranges of these detectors.

Flame ionization detector The flame ionization detector (FID) is one of the most widely used detectors due to its low detection limits, wide dynamic range, affordability, and reliability [15]. In an FID, solutes are swept through a detector component (FID jet) as they elute from the end of the column. At the tip of the jet, the solutes pass through a flame created by the combustion of a hydrogen/air mixture. Thus this detector requires that both H2 and compressed air be supplied via external high-pressure tanks. As organic solutes burn in the

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Table 12.1 Characteristics of common gas chromatography detectors

Flame ionization detector Thermal conductivity detector Electron capture detector Mass spectrometry

Type

Detection limit

Mass sensitive

1 pg C/s

Concentration sensitive

1 ng/mL

Concentration sensitive

10 fg/s

Concentration sensitive

10 pg–10 ng

Selectivity

Linear range

Nonselective: responds to nearly all organic compounds Nonselective: responds if thermal conductivity differs from carrier gas Halogenated compounds

107

Tunable for any species

105

105

104

flame, they create ions. These ions are collected at electrodes called collector plates, creating a current in the detector circuitry. The column effluent is burned in a small oxy-hydrogen flame producing ions in the process. These ions are collected and form a small current that becomes the signal. When a hydrocarbon compound from the column enters the flame, the following happens in the reducing zone: CH radicals are formed from hydrocarbons : (CH) ! CH + O. Formyl cations are formed from CH radicals : CH  ! CHO+ + e–. A potential (300 V) is applied between the jet tip (flame) and the collector. The generated ions in the flame will produce a small current, which is proportional to the amount of compound combusted. The current (signal) is amplified in an electrometer. The FID can detect all organic compounds containing C and H, with the exception of formic acid and methane. It is a mass-sensitive detector. The minimum detectable (MD) mass is about 0.01–0.1 ng. Thus the FID is a specific property-type detector with characteristic high sensitivity.

TC detector One of the first GC detectors developed was the TCD [16]. The TCD consists of a heated metal block with two channels. Each channel is equipped with a filament (metal wire), and the filaments are connected to a Wheatstone bridge. The carrier gas going into the injector/column is led through one of the channels, while the carrier gas from the column is led through the other channel. The filament temperature depends on the heat conductivity of the passing gas. The TCD responds to changes in TC when analytes are eluted from the column. Because the carrier gas is set as a reference, analytes with thermal conductivities similar to the carrier gas will provide small responses, while analytes with thermal conductivities that differ more from the

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carrier gas will provide higher sensitivities. The carrier gas used with the TCD must have a TC that is very different from the samples to be analyzed, so the most commonly used gases are helium and hydrogen, which have the highest TC values [17]. When a compound eluted from the column passes the filament, the conductivity of the gas is decreased and the filament temperature increases. This increase in temperature results in a change in the electrical resistance of the filament, and this change is registered by the Wheatstone bridge system and a change in detector signal is observed. TCDs have remained popular, particularly for packed columns and inorganic compositions like H2O, CO, CO2, and H2. The TCD is nondestructive, and may be used for preparative separations. This detector responds to all compounds regardless of their structure and elemental make-up. The advantages of the TCD are its simplicity and reproducibility; however, this detector is not very sensitive.

Electron capture detector The ECD was developed by Lovelock in 1958 [18] and, similar to the FID, is also an ionization detector. The ECD is a selective detector for organic compounds containing an electron capturing group, for example, a halogen, a nitro group, or a conjugated carbonyl group. These compounds include halogenated materials like pesticides and, consequently, one of its primary uses is in pesticide residue analysis. The detector consists of a heated metal block with a detection channel. The carrier gas from the column enters the detection compartment and is mixed with a reagent gas if the carrier gas itself cannot be ionized. The detection compartment contains a positively charged anode, a cathode, and a β-radiation source. The β-radiation source may be 3H (0.018 MeV) or 63Ni (0.067 MeV). The 63Ni source has some practical advantages and can be used at higher temperatures. The high-energy electrons emitted from radioactive nuclide collide with the molecules or atoms of the carrier gas and the make-up gas and ionize them, thereby liberating thermal electrons of a lower energy. Several hundred thermal electrons can arise as the result of one disintegration event. These electrons are attracted by an anode in the center of the detector cavity, giving rise to a constant baseline current. When a compound with high electron affinity enters the negative zone, it can capture low-energy electrons and form negatively charged ions. Because the negative ions can be more rapidly neutralized than the electrons, the current will be reduced. The decrease in current is registered as the detector signal for the compound. The ECD is a sensitive detector and the MD mass is about 1 pg. For the right compounds, the ECD displays extremely low detection limits in the lower fg/s range. The numbers of halogens in an analyte and the substituent positions have a significant effect on the MD. Unfortunately, it is also very sensitive toward contamination and cannot be used for samples dissolved in chlorinated solvents. One drawback of the ECD is the necessity to use a radioactive source, which may require a license or at least regular radiological testing. A newer type of ECD is operated with a pulsed discharge detector so that it does not require a radioactive source [19].

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Olfactometric detector GC with olfactometric detection is based on sensory evaluation of the eluate from the chromatographic column aimed at discovering the active odor compounds [20]. The role of the detector is played by a specialist or a team of evaluating personnel. Qualitative and quantitative evaluation of the odor is carried out for each analyte leaving the chromatographic column. This establishes whether a given compound is sensory active at a given concentration (i.e., whether it appears in the sample at a level higher than the threshold of sensory detection) and what its smell is, as well as the determination of the time of sensory activity and the intensity of the odor. Determination of the analyte’s odor is possible thanks to the presence of a special attachment, a so-called olfactometric port, connected in parallel to conventional detectors, such as an FID or a mass spectrometer. The flow of the eluate is split in such a way that the analytes reach both detectors simultaneously, and because of this both signals can be compared. A combination of the olfactometric detector with a mass spectrometer is particularly advantageous, because it makes the identification of odor-active analytes possible. However, since the mass spectrometer works under vacuum conditions, while the olfactometric detector works under atmospheric pressure conditions, the retention times of the analytes might differ for the two detectors (typically shorter for the mass spectrometer). This difficulty can be overcome by installing a restrictor (in the form of a narrow bore capillary) before the mass spectrometer to increase the pressure drop between the interface and the flow splitter, as well as through careful selection of the flows of the carrier and auxiliary gases [21].

Mass spectrometry The mass spectrometer has become a very important detector in GC. Combined gas chromatography-mass spectrometry (GC-MS) is probably the most comprehensive instrumental analytical technique available to the scientist in food analysis at present. The technique is well established in food science, and a predominant area of application is in food safety, where reliable information on food contaminants, e.g., pesticides, mycotoxins, and veterinary drug residues, is of vital consequence. Information to be obtained can be both the unequivocal identification or confirmation of the contaminant and the quantification. The mass spectrometer basically consists of an ionization unit (ion source), a mass/ charge (m/z) separation unit (analyzer), and an ion detector. The mass spectrometer is a mass-sensitive detector, where the signal (S) depends on the concentration (C), the mobile-phase flow rate (F), and the split ratio in the chromatographic system (R), if a split is used: S ¼ dm=dt ¼ C  F  R The mass spectrometer can provide structural information, which can be used for identification of the compounds in addition to quantification. In GC, the most common ionization technique is electron ionization (EI). Electrons formed in a filament are sent as an electron beam with energy 70 eV through the

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relatively open ion source. The molecules (analytes) that are in gas phase at low pressures are ionized, and positive monoisotopic molecular ions (M+) are formed. Since the ionization energy of most organic compounds is 7–10 eV, the molecular ion possesses surplus energy causing fragmentation, which is compound specific. The resulting mass spectra have been shown to be reproducible, allowing reference mass spectra in a mass spectrum library to be used for identification of a compound. When molecular mass information is sought, an ionization technique giving little fragmentation, such as chemical ionization (CI), is preferred. CI is a softer ionization technique than EI. In CI, the molecules are ionized by ion/neutral reactions between the molecule and the ions formed in a reagent gas. The reagent gas ions are formed at relatively high pressures (0.1–2 Torr) in a more closed ion source, where the reagent gas is ionized by 200–500 eV electrons and ion/neutral reactions. Common reagent gases are methane, isobutane, and ammonia. Mostly protonated molecules, MH+, are formed, while the fragment ions formed are small in number. In some cases, adduct formation will occur, for example, the formation of (M + NH4)+ when ammonia is used as a reagent gas. Negative ions can be formed at conditions used for CI, that is, when using an ion source that is relatively closed and with a reagent gas (or moderating gas) of high pressure. A moderating gas does not provide negative ions, but due to its presence generates electrons of low energy (thermal electrons) by slowing down 200–500 eV electrons coming from a filament. Thermal electrons can be captured by the analyte and a negative ion is formed. When reagent gases are used, the formation of negative ions is due to ion–molecule reactions between the analyte and the negative ions from the reagent gas. The combination of negative ionization and chromatography has so far not been widely used. Negative MS is, however, especially useful for molecules with high electron affinity as in the case of the ECD. Using MS as a detector in GC and especially in capillary GC is relatively simple. The most common mobile phases do not interfere, and the analytes are volatile and already in gas phase so that EI and CI can be used. The only problem is the pressure difference between the GC and MS units. The outlet of the column is commonly at atmospheric pressure (760 Torr), while a pressure of 106–107 Torr is required in the ion source with EI. A modern mass spectrometer can usually receive 1–2 mL/min of gas and still maintain a low pressure, and this compares with the mobile-phase flow rates used in capillary GC. However, if the end of the column is placed directly into the ion source, this can lead to varying retention times because of varying pressure. Therefore a split interface is often preferred. The analytes are transferred to the mass spectrometer without loss if the carrier gas flow rate at the column outlet is equal to the flow rate to the ion source. If the inlet flow rate is lower, less of the analyte is transferred, and if the carrier gas flow rate is lower, dilution of the analyte occurs. For packed columns, different types of interfaces have been used, but the most common is the jet separator. GC-MS, especially capillary GC-MS, has become a widely used method, and is becoming very important also in routine analyses. Quadrupole mass spectrometers are most common in GC-MS. The quadrupole mass spectrometer has a mass range that covers the molecular masses of compounds, which can be chromatographed by GC.

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In addition to the type of mass spectrometer, the MDs obtainable depend on both the mode of ionization and the mode of operation. Typical values for MD amounts in full scan and selected ion monitoring (SIM) mode may be 10 and 1 pg, respectively, with EI.

12.2.1.6 Data system The major requirement of a good data system is the ability to measure the GC signal with rapid sampling rates. Currently, there is an array of hardware, made possible by advances in computer technology, which can easily perform this function. In general, there are two types of systems in common use: integrators and computers. Microprocessor-based integrators are simply hard-wired, dedicated microprocessors that use an analog-to-digital (A-to-D) converter to produce both the chromatogram (analog signal) and a digital report for quantitative analysis. They basically need to calculate the start, apex, end, and area of each peak. Algorithms to perform these functions have been available for some time. Most integrators perform area percent, height percent, internal standard, external standard, and normalization calculations. For nonlinear detectors, multiple standards can be injected, covering the peak area of interest, and software can perform a multilevel calibration. The operator then chooses an integrator calibration routine suitable for that particular detector output. Many integrators provide BASIC programming, digital control of instrument parameters, and automated analysis, from injection to cleaning of the column and injection of the next sample. Almost all integrators provide an RS-232-C interface so the GC output is compatible with “in-house” digital networks. Personal computer-based systems have now successfully migrated to the chromatography laboratory. They provide easy means to handle single or multiple chromatographic systems and provide output to both local and remote terminals. Computers have greater flexibility in acquiring data, instrument control, data reduction, display, and transfer to other devices. The increased memory, processing speed, and flexible user interfaces make them more popular than dedicated integrators. Current computerbased systems rely primarily on an A-to-D card, which plugs into the PC mainframe. Earlier versions used a separate stand-alone A-to-D box or were interfaced to stand-alone integrators. Because costs for PCs have decreased, their popularity and use have increased.

12.2.2 Theory of GC separations 12.2.2.1 Distribution constant (K) In chromatography, different theories and models have evolved that are applicable and valid under a number of given assumptions. These models are not only useful to explain the chromatographic process from a theoretical point of view, but they also offer valuable input for the practical application of GC. The separation mechanism of GC involves the equilibration of analytes between the stationary phase and the

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mobile phase. The distribution constant for the process may be expressed as a ratio between the concentration of analyte interacting with the stationary phase and the concentration of analyte in the mobile phase. The separation is caused by distinct migration rates of the components due to different strong interactions with the stationary phase. This separation is superimposed with mixing processes (dispersion) during transport through the column, which cause a broadening of the substance bands and counteract the separation since broad bands/peaks impede the resolution of closely eluting peaks. Consequently, we aim to sufficiently maximize the differences in migration rates and minimize dispersion of the components by choosing appropriate column dimensions and operating parameters. The migration rate of a compound is the sum of the transport rate through the column and retention in the stationary phase. The time spent in the mobile phase is the same for all sample components, but the retention is compound specific. It is based on the distribution of an analyte between stationary and mobile phase and is expressed by the distribution constant K. Large distribution constants mean high solubility in the stationary phase and long retention on the column. The distribution constant is defined as K ¼ cs =cm where cs is the concentration of a component in the stationary phase and cm is the concentration of a component in the mobile phase. A separation is only successful if the distribution constants of the sample components are different. The distribution constant can be graphically described with a distribution isotherm with the concentration of the solute in the mobile and stationary phases as x-axis and y-axis, respectively (Fig. 12.5) [22]. The distribution constant is either independent of the concentration of the component (linear isotherm) or changes with the concentration (nonlinear isotherm). In the latter case, the effective migration rate depends on the concentration, which results in unsymmetrical solute bands. A linear isotherm delivers a symmetric solute band (peaks) and the peak maximum is independent of the solute amount. A nonlinear isotherm results in unsymmetrical solute bands and the location of peak maximum depends on the solute amount. A nonlinear isotherm can be formed either convex or concave. In the case of a concave isotherm, K increases with increasing concentrations resulting in a shallow frontal edge and a sharp rear edge of the peak. This is called fronting. As a consequence, the peak maximum moves to higher retention times. In the opposite case, the convex isotherm, K, decreases with increasing concentrations resulting in a sharp frontal edge and a shallow rear edge of the peak. This is called tailing. The peak maximum moves to lower retention times. In practice, linear distribution isotherms are only found if the solute and stationary phase are structurally similar. However, as Fig. 12.5 shows, even for nonlinear distribution isotherms, a quasilinear range exists at low concentration, which delivers symmetric peaks with retention times that are independent of the solute amount. Depending on the shape of the distribution isotherm, GC can be distinguished between linear and nonlinear chromatography for the description of chromatographic processes. The processes further divide into ideal and nonideal chromatography. Ideal chromatography implies a reversible exchange between the two phases with the

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Fig. 12.5 Correlation between the shape of the distribution isotherm and peak form. Reprinted with permission from K. Dettmer-Wilde, W. Engewald, Practical Gas Chromatography, Springer Berlin Heidelberg, 2014 (Copyright, Springer-Verlag Berlin Heidelberg 2014).

equilibrium being established rapidly due to a fast mass transfer. Diffusion processes that result in band broadening are assumed to be small and are ignored. In ideal chromatography the concentration profiles of the separated solute should have a rectangle profile. The Gaussian profile obtained in practice demonstrates that these assumptions are not valid. In case of nonideal chromatography these assumption are not made. With these two types of classification the following four models are obtained to mathematically describe the process of chromatographic separation: l

l

l

l

Linear, ideal chromatography; Linear, nonideal chromatography; Nonlinear, ideal chromatography; Nonlinear, nonideal chromatography.

In GC, the mostly used partition chromatography can be classified as linear nonideal chromatography. In that case, almost symmetric peaks are obtained and band broadening is explained by kinetic theory according to Deemter [23].

12.2.2.2 Retention factor (k) In GC, retention (most commonly measured in units of time) is related to the distribution constant through the phase volume ratio (Vm/Vs), the mobile-phase volumetric flow rate (corrected for gas compressibility), and the unitless retention (or capacity) factor, k: k ¼ ðtR  t0 Þ=t0

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where tR is the retention time for a given analyte and t0 is the time it takes for an unretained compound to transit the entire length of column, also known as the dead time. The retention factor is important because it describes the total amount of interaction between the stationary phase and a given analyte during a separation. Further thermodynamic information about the analytes’ interaction with the stationary phase can be obtained from these relationships [24], but is not of primary interest here. For relative comparison of retention of two analytes on a stationary phase, the selectivity, α, is defined as α ¼ k1 =k2 where k1 is the retention factor of the analyte of interest and k2 is the retention factor of the other analyte. Favorable separation of two analytes is expressed in larger selectivity values and increased chromatographic space between the two peaks. The efficiency of the separation (N) is conventionally given by N ¼ 16ðtR =Wb Þ2 ¼ L=H with the analyte retention time, tR, and peak width at the base, Wb, in units of time. L is the length of the column and H is the theoretical plate height, both in units of length.

12.2.2.3 Separation number and peak capacity A number of additional parameters can be used to characterize column performance. A useful concept for multicomponent analysis is to evaluate the number of peaks that can be separated with a defined resolution in a given range of the chromatogram or the whole chromatogram. The effective peak number (EPN), the separation number (SN), and the peak capacity (nc) can be used. Resolution (Rs) is the absolute physical separation of two adjacent peaks (analytes or interferents) and is expressed as Rs ¼ ðt2  t1 Þ=W b where t2 and t1 are the retention times of the respective analytes and W b is the average width of the analyte peaks. Because Rs is specific to two analytes it is often used as a local metric for determining the suitability of a routine targeted analysis (i.e., the resolution between two standards in a calibration sample or a targeted analyte and a known interferent). Another metric often applied is SN, which is the number of peaks with an Rs of 1.18 that fit between two reference peaks [25]. By definition this only applies to the portion of the chromatogram between the reference peaks and thus represents a metric of more regional scale. While these separation terms and metrics cover the local and regional scale of a chromatogram they are insufficient for evaluating global separation performance. For that purpose, Giddings introduced peak capacity as a metric to give

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“information on the total number of resolvable components” in a separation [26]. More specifically, for a given resolution (Rs ¼ 1, herein) the theoretical peak capacity for a 1D-GC separation, nc, is given by nc ¼ ðtR, f  t1 Þ=W b where tR,f is the separation run time (and could be viewed as the last retained peak at the end of the separation), t0 is the dead time, and W b is the average peak width throughout the chromatogram. Requiring higher resolution (e.g., 1.5–2) will decrease the peak capacity proportionally. From the relationship in the equation, it is clear that with all else being equal, longer separation run times result in higher peak capacities. However, peak capacity as well as SN/EPN are theoretical values. The peak capacity assumes that the peaks are evenly distributed across the chromatogram, which unfortunately never happens in reality. Davis and Giddings demonstrated that peak resolution is already affected if the number of solutes exceeds 37% of the peak capacity [27].

12.3

Procedures for GC

12.3.1 Sample preparation Even though GC is a very powerful separation method, some GC analyses require sample preparation prior to injection. While sample preparation may be as simple as diluting the analyte(s) in an appropriate solvent or loading into a vial, or as complex as multistep extractions, the eventual quality of the method may be more dependent on the sample preparation than on the chromatography. Most sample preparation approaches for GC involve moving the analyte(s) into a solvent phase (usually organic) appropriate for liquid injection using a syringe or into the vapor phase for introduction as headspace, with a sample loop or a gas-tight syringe. In gas chromatographic method development, sample preparation should be considered in concert with the injection technique and the required detection limits of the method. Sample preparation for GC analysis involves techniques that preferentially isolate volatile and semivolatile substances and prevent the presence of ionic or high molecular weight species in the mixture to be injected into the GC. These techniques can be divided roughly into three major groups: distillation, extraction, and headspace methods. The basic goal of sample preparation is to ensure that the foregoing conditions are met, with additional goals that the preparation be reproducible to meet quantitative analysis requirements and straightforward to perform, if the analysis is to be performed routinely, as in quality assurance and in other routine testing laboratories. Nearly all sample preparation methods involve the transition of analyte(s) between phases, commonly either solid or solution to gas, or solid, liquid, or gas to liquid. In any event, gases and liquids are by far the most commonly injected sample phases. Our ability to accomplish this phase transfer is driven first by chemical equilibrium, which determines the amount of analyte that may be transferred from the original

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phase to the final phase, determining recovery, or the amount that is extracted. Second, the kinetics involved in reaching that equilibrium often determine the reproducibility of the method and may affect the recovery if equilibrium in the extraction process is not reached. There are few comprehensive treatments of sample preparation in the literature; however, there are many books and articles describing specific techniques, which are referenced throughout this chapter [28, 29]. There are several implications for all sample preparation methods. 1. Quantitative extraction (100% transfer of the analyte to the extracted phase) cannot happen, although a high partition coefficient and/or multiple extraction steps may nearly achieve it. Extraction phases should generally be chosen to maximize the partitioning into the extract phase. 2. Some amount of analyte (or interference) is always extracted, no matter how low the partition coefficient. 3. Multiple extraction steps will result in a more efficient extraction and will magnify the positive effect of small differences between analyte and interference partition coefficients. 4. Kinetics must be considered to ensure that the extraction reaches equilibrium. If equilibrium is not reached, reproducibility may suffer.

12.3.1.1 Liquid–liquid extraction Liquid–liquid extraction (LLE) usually involves extraction of analytes from a dilute aqueous phase into an organic phase, often with a concentration step to improve sensitivity. LLEs are either macroextractions or microextractions, depending on the volume of extraction solvent used, with the dividing line about 1 mL of extraction solvent. Macroextraction is performed using a separatory funnel, test tubes, or a continuous extraction device. There are a number of techniques and considerations that can affect recovery in LLE and other extractions. These include agitation, salting out, pH, temperature, washing or back extraction, and solvent choice. Extraction requires intimate contact between the two phases, most often with agitation by shaking, stirring, or vortex mixing. Generally, higher agitation speed results in more rapid equilibration, and longer agitation time ensures that equilibrium has been reached. Agitation devices (shaking speed, vortex mixer rpm, stirrer velocity, etc.) should be operated as reproducibly as possible. It is important to adjust extraction timing to reach a plateau. This ensures that small variations in mixing speed, solvent viscosity, or matrix effects should not adversely affect the extraction. Adding a high concentration of a salt such as sodium chloride often enhances extraction recovery of organic compounds extracted from water into organic phases. Increasing the ionic strength often reduces solubility of organic compounds in water, thus increasing the value of Kc and therefore the amount extracted. However, it is difficult to make general statements about whether recovery will be improved for a specific extraction scheme and analytes without testing this experimentally. Many common analytes and interferences are weak organic acids and bases. Since solution pH for these compounds can drastically affect their solubility in an aqueous phase, knowledge of their pKa and control of the solution pH can be used to effect the

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extraction. The aqueous solubility of acidic compounds will be enhanced in basic solution, while the solubility of bases will be enhanced in acid. In both cases, Kc is reduced, thereby reducing extraction recovery. To improve extraction recovery of acids, the aqueous phase can be adjusted to lower the pH, ideally to at least 2 pH units lower than the pKa of the desired analyte. Likewise, for bases, the pH can be raised. If there are multiple ionizable analytes and/or interferences, it may be necessary to adjust the aqueous solution pH by buffering to provide more reproducible control of the original solution pH. The equilibrium position of all chemical processes is affected by the temperature. Generally, to ensure extraction reproducibility, temperature should be controlled as carefully as practicable. This may be as simple as ensuring that all solutions and samples have equilibrated at the laboratory room temperature, or as complex as performing the extraction within an oven or heating block. An increase in temperature will decrease the distribution constant, Kc, thereby reducing the amount extracted. However, at elevated temperature, kinetics is often faster, so extraction speed may be increased. Often, adjusting temperature provides a trade-off between lowered recovery and faster kinetics. Careful temperature control may be required for reproducibility and is especially critical in liquid–vapor (headspace) extraction. The ideal extraction solvent would show very high solubility for analytes of interest and very low solubility for interferences, generating a large difference in the partition coefficients. If the solubilities of analytes and interferences in the original phase and in the extraction phase can be estimated or are known, Kc can be estimated as a ratio of these solubilities. Furthermore, the extraction phase must not be miscible or significantly soluble in the original phase.

12.3.1.2 Single-drop microextraction The concept of single-drop microextraction (SDME), introduced in 1996, is simple: A single drop of organic solvent is suspended from a syringe needle into the aqueous phase, and the system is agitated to drive organic compounds into the drop. The organic drop can then be transferred to the gas chromatograph using the syringe. The equilibrium theory of SDME is similar to that seen in LLE, with the equilibrium concentration of analyte in the organic phase at equilibrium given by ½A2 ¼ Kc ½A1 =ðV1 + Kc V2 Þ where the subscripts 1 and 2 refer to the aqueous and organic phases, respectively. If V2 ≪ V1 and Kc is small, this reduces to ½A2 ¼ Kc ½A1 In other LLE methods, “salting out” increases the amount extracted; however, the opposite has been observed with SDME, due to the higher ionic strength of the aqueous phase decreasing the analyte diffusion rate, thus requiring longer extraction time to reach equilibrium.

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12.3.1.3 Solid–liquid extraction: Soxhlet extraction and accelerated solvent extraction Extractions involving transfer of analytes into an organic solvent are not limited to liquid samples or solutions. In Soxhlet extraction, the solid sample is placed in a porous thimble above a solvent reservoir. As the solvent is heated, distilled solvent drips into the porous thimble, immersing the solid sample. When the thimble is full, solvent is siphoned back into the solvent reservoir and redistilled. Soxhlet extraction is generally used for semi- or nonvolatile analytes because volatiles may be lost through the condenser. Soxhlet extraction is usually slow, often requiring hours. Glassware for Soxhlet extraction is available from many chemical glassware supply houses. In the 1980s and 1990s, supercritical fluid extraction (SFE) was proposed as a useful alternative to Soxhlet extraction and is still used for a few applications; however, difficulties with instrumentation handling of supercritical fluids and reproducibility limited its routine use as an analytical technique. SFE is still commonly used in many industrial applications requiring extraction. Accelerated solvent extraction (ASE) provides an instrumental alternative to both SFE and Soxhlet extraction. As in SFE, in ASE the solid to be extracted is placed in a high-pressure vial and heated. It is then extracted with a traditional solvent that is heated and pressurized, but not to its critical point. High pressure forces solvent into the pores of the solid facilitating extraction, and elevated temperature increases extraction kinetics. The solvent is then vented and the resulting solution is collected for analysis. Traditional solvents are pumped into the extraction cell using a highperformance liquid chromatography (HPLC) pump. The cell is cleaned with a purge of nitrogen. Back pressure is maintained using a valve at the outlet.

12.3.1.4 Liquid–solid extraction: Solid-phase extraction When the sample phase is liquid and the extracting phase is solid, the family of techniques is called solid-phase extraction (SPE). Most commonly, SPE is performed by passing the liquid phase through a column, cartridge, or filter disk, selectively collecting analytes on the surface of the solid phase, while the remaining liquid phase is passed through. Analytes can then be collected by passing a strong eluting solvent over the solid. Thorough reviews of SPE techniques and methods are provided by the vendors of SPE materials. First, the stationary phase must be wetted and equilibrated with an appropriate solvent. Next, the sample is added and passed through. Usually, this is accomplished by slowly decanting the sample into the cartridge and then pulling it through using a vacuum. Because a phase transition from the liquid phase to the solid surface is involved, flow through the cartridge should be slow; to effectively transfer analyte(s) to the surface, often several minutes are needed. Following transfer, the vacuum remains on, thereby allowing the phase to dry. It may then be washed using aliquots of the original sample solvent or a weak additional solvent to remove unwanted interferences. Finally, the analytes are eluted using a strong solvent in which they are highly soluble. SPE is one of the most flexible of all extraction methods.

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There are numerous stationary phases available, allowing extraction of nearly any analyte or class of analytes. A summary of commonly used SPE phases and applications is shown in Table 12.2. When extraction involves gas chromatographic analysis of a vapor phase, usually in equilibrium with a liquid or solid phase, the technique is termed headspace extraction. If the vapor phase is stationary (usually contained within a vial or other container), it is termed static headspace extraction. If the vapor phase is moving (usually bubbled through the liquid phase and collected later), it is termed dynamic headspace extraction, also commonly called “purge and trap.” Static headspace extraction generally requires that analyte partitioning between the liquid and vapor phases reaches equilibrium, so as in LLE, analytes are not exhaustively extracted. The same extraction theory described earlier applies, except that one phase is vapor. Dynamic headspace extraction depends on continuous renewal of the extracting vapor to exhaustively drive analytes from the liquid into the vapor, allowing exhaustive extraction. The myriad applications of solid-phase microextraction (SPME) are described in several texts [30, 31]. Stir-bar sorptive extraction (SBSE) resulted from an SPME application that exhibited low analyte recovery. It was discovered that the analytes had adsorbed on the stir bar that had been added to the sample for agitation. A stir bar is coated with a sorbent material (usually polydimethylsiloxane [PDMS]), placed into the sample and stirred. Following equilibration, the stir bar is removed and placed into a PTV inlet and the analytes are desorbed into the column. SBSE has similar applications to SPME, with the main advantage being higher analyte recovery due to the larger

Table 12.2 Overview of sample preparation techniques by sample type Sample type: Solid Dissolving followed by liquid technique Supercritical fluid extraction Headspace extraction Accelerated solvent extraction Pyrolysis Thermal desorption Microwaveassisted extraction

Sample type: Liquid

Sample type: Gas

Direct “neat” injection

Direct “neat” injection (syringe or sample valve) Membrane extraction

Liquid–liquid extraction Solid-phase extraction (includes solidphase microextraction [SPME], sorbent-based extractions) Headspace extraction (includes SPME, sorbent-based extractions) Membrane extraction Trapping on a solid followed by solid technique

Trapping on a solid followed by solid technique Trapping in a liquid followed by liquid technique

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volume of extraction phase, and the main disadvantage being slower extraction and desorption kinetics also due to the larger extraction phase volume.

12.3.1.5 Solid-phase microextraction SPME was developed in 1989 as a simplified solvent-free extraction method for volatile contaminants from water. An SPME device employs a coated fused silica fiber that is attached to the end of a microsyringe plunger and can be stored within the syringe barrel. Recently, instrumentation for fully automated SPME has become available through the major instrument vendors. Nonpolar PDMS is by far the most commonly employed fiber coating (extraction phase), with about 80% of applications. Other materials include polyacrylate (PA, polar) and several combinations of solid-phase sorbents. Since PDMS and PA are both fundamentally liquids (they are so viscous that they appear to be solids, thus the colloquial description of this as a solid-phase technique) and the fiber coatings are very low volume (1 μL or less). Also, the fiber device is inserted directly into a liquid sample, the advantage of unlimited sample volume, as seen in purge and trap extraction, for analytes with low Kc applies. In SPME analysis, the fiber is first exposed either directly to a liquid sample or to the headspace. All conditions described earlier for LLE apply to these extractions as well. Following exposure, which may range in time from a few minutes to hours, depending on kinetics within the sample phase, the fiber is retracted into the syringe needle and transferred to GC for desorption under splitless inlet conditions. The splitless time, inlet temperature, and initial column conditions must be optimized to ensure complete analyte desorption from the fiber and to assist in chromatographic peak focusing. Depending on sample characteristics and extraction mode, fibers can last for as few as 10 or as many as 100 analyses.

12.3.2 Derivatization Modern capillary GC offers high chromatographic resolution, making it an excellent tool for the analysis of complex mixtures. However, an analyte must have sufficient vapor pressure that allows its transfer into the gas phase without thermal decomposition. Vapor pressure decreases with increasing molecular weight and polarity of a compound until vaporization without decomposition is no longer possible. If the low volatility is caused by strong intermolecular interactions such as hydrogen bonding, a derivatization step can mask the polar groups, which significantly increases volatility. Overall, the range of analytes suitable for GC analysis can be substantially extended by derivatization. Derivatization describes the chemical modification of an analyte into an analog that is amenable to GC analysis. Derivatization does not only aim at increasing the volatility and thermal stability of an analyte, it can also improve the gas chromatographic properties of a compound because interactions with active sites or adsorption is reduced, resulting in a more symmetric peak shape. In addition, the derivatized form of an analyte may provide a better separation from interfering compounds because it elutes in a different part of the chromatogram with potentially fewer coeluting

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compounds. Moreover, derivatization can be performed to transform the analyte into a derivative that allows a more sensitive or selective detection. For example, a halogenated derivatization reagent can be used with subsequent detection of the derivatives carried out by ECD. Derivatization reactions for ECD detection have been recently reviewed [32]. Derivatization can also aid in the identification of unknown analytes. A peak shift in the chromatogram after application of a derivatization reaction typical for a specific functional group aids in the identification of the functional group, and mass spectral detection can reveal the number of functional groups based on the mass shift. Derivatization can also produce more distinct mass spectra, e.g., typical fragment formation, which helps in the identification of unknowns. Finally, derivatization with a chiral reagent can be employed to transform enantiomers into diastereoisomers to facilitate their separation on nonchiral columns. An ideal derivatization reaction should fulfill the following requirements: l

l

l

l

l

l

l

l

l

The reaction should be fast. The reaction must be reproducible. Ideally, a single distinctive derivative is formed (not always the case, e.g., silylation of amino acids, oximation, or hydrazone formation of carbonyl compounds). The derivative must be thermally stable and exhibit good chromatographic performance. The reaction should give a quantitative yield, because an incomplete derivatization with a low derivative yield will negatively affect detection limits and can potentially increase the chromatographic background. However, as long as the derivatization yield is reproducible, the reaction may be used. The analyte composition of the sample should be mirrored in the derivatized sample without discrimination or decomposition of analytes. Formation of derivatization by-products should be minimal and they should not interfere with the analysis. This also applies to reagent excess, which should also not damage the column; otherwise it must be removed before analysis. The reaction should be easy and safe to perform. The derivatization reagent should have adequate chemical stability to allow for a convenient shelf life.

Commonly used derivatization reactions are silylation, alkylation, acylation, oximation/hydrazone formation, and to a lesser extent, cyclization. Despite the huge potential of derivatization, many analysts hesitate to use it because it is an additional step during sample preparation that can be tedious and time consuming and may introduce both qualitative and quantitative errors if not validated rigorously. Furthermore, many derivatization reagents are hazardous because of their usually required high reactivity.

12.3.3 Process optimization GC, as the separation method of choice for separation and quantification of volatile and semivolatile compounds, has been and continues to be evolving to improve the speed and quality of the data and information produced by the separation. Since the valuable information produced in a GC analysis is described by the retention time, width, and shape of the analyte peak, peak capacity is the most often used metric for

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comparing and evaluating the resolving power or information-producing ability of a GC instrument. The random nature of analyte peak distribution within a chromatogram means that the theoretical peak capacity generated during analysis must be much larger (up to an order of magnitude) than the number of peaks to be separated [27, 33]. This reality requires continued improvement to GC separation power available to analysts. One analytical strategy to optimize the information content of a separation could be to hold constant the separation time, while reducing the average peak width, resulting in an overall increase in total peak capacity. Alternatively, another analytical strategy could be to maintain the total peak capacity constant, by concurrently reducing the average peak width and the separation run time. This second strategy provides for higher throughput analyses, while maintaining the information content in a given chromatogram. The inverse relationship between peak capacity production and peak width means that to determine the upper bounds for peak capacity production for a column of given dimensions, it is necessary to further understand the sources contributing to a detected peak’s width. Peak widths can be viewed as due to two different types of contributions: on-column contributions (due to the separation processes) and off-column contributions (due to nonseparation processes such as injection, detection, electronics, dead volumes, etc.). Typically, off-column peak broadening is addressed via instrumental improvements, while on-column broadening is minimized by applying GC theory to determine optimal experimental conditions for a given analysis. The most direct approach to improving peak capacity production is to minimize on-column band broadening by optimizing separation conditions such as column dimensions, carrier gas flow program, and temperature program. In addition, common sources of off-column band broadening can include injection, nonuniform column temperatures, and dead volumes at column connections and/or within the detector, while careful implementation of GC components can minimize many of the sources of broadening (especially dead volumes). There is a large body of work in this area, with Gidding’s text being particularly relevant and useful [34].

12.3.4 Qualitative analysis GC can be used for both qualitative and quantitative analysis. Because it is more useful for quantitative analysis, most of this chapter is devoted to that topic. However, it begins with a brief look at qualitative analysis. Qualitative analysis is often the first step in the examination of a chromatographic separation. We want to know either: “What is in the sample?” or “Are certain compounds present in the sample?” Both approaches intend to identify individual components of a sample. Qualitative analysis can have different aims. It can focus on the recognition of selected analytes in the sample, which is called targeted analysis. Instead of searching for a limited number of analytes, the goal can also be the identification of all components in a sample in a nontargeted approach. One can also compare peak patterns of different samples without knowing the identity of each individual signal. This so-called fingerprinting approach classifies the samples based on the overall signal pattern. This is often used

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in metabolomics, petrochemical analysis, food, flavor, the fragrance industry, or in forensics. Furthermore, qualitative analysis can aim at the identification of biologically active substances by coupling GC to a biosensor, which acts as a detector. An example is the use of the human nose to recognize odorous compounds by means of a sniffing port. Another approach to identify biologically active substances is electroantennographic detection. The starting point for qualitative analysis is the chromatogram as a plot of detector signal over time. The qualitative information gained can be generally divided into two parts. On the one hand, the retention time on a given stationary phase is characteristic for an analyte and, on the other hand, the detection principle can deliver information on the nature of the analyte. Nowadays, MS, in most cases with EI and a quadrupole mass analyzer in combination with a mass spectral library, is often used as an identification tool. However, one should keep in mind that the comparison of the acquired spectrum with library spectra delivers a hit list that does not necessarily contain the correct compound. The match quality, potential isomers, and the overall plausibility of the respective structures must be evaluated carefully. Retention values, structure– retention relationships, and other selective detectors are valuable tools to be employed. Furthermore, selective derivatization or degradation reactions can aid in the identification of unknown signals.

12.3.5 Quantitative analysis GC is an excellent tool to separate complex mixtures to identify the components of the sample. After the question “What is in the mixture?” is answered, we almost always want to know how much of a specific compound or several compounds is in the sample. This second question is answered by quantitative analysis, which aims at the determination of the concentration or mass of an analyte in a given sample. A basic requirement for a reliable quantification is the development of an optimized analytical method, including sampling, sample preparation, and analysis of the target analytes. With regard to the chromatographic method, the injection method, injection parameters, column selection, temperature program, and detection method have to be optimized resulting ideally in baseline-separated, symmetric peaks of the target analytes that can be detected with sufficient sensitivity. It must be ensured that sampling, sample preparation, and the chromatographic process proceed with acceptable accuracy and precision. In chromatographic analysis the detector signal increases, in most cases linearly, with the analyte concentration or mass. This correlation forms the basis for quantitative analysis. To quantify an analyte, the relationship between the extent of the detector signal and the analyte concentration or analyte mass must be established, which in most cases is done by analysis of reference compounds in known concentrations. In elution chromatography, the magnitude of a chromatographic peak is expressed in two ways using either the peak height or the peak area (Fig. 12.6). In frontal chromatography, the step height is a measure for the analyte concentration. However, quantification is mostly performed using elution chromatography. With today’s electronic integrators and computers, peak area is the preferred method,

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Figure 12.6 Peak height and peak area as input data for quantification. Reprinted with permission from K. Dettmer-Wilde, W. Engewald, Practical Gas Chromatography, Springer Berlin Heidelberg, 2014 (Copyright, Springer-Verlag Berlin Heidelberg 2014).

especially if there may be changes in chromatographic conditions during the run, such as column temperature, flow rate, or sample injection reproducibility. However, peak height measurements are less affected by overlapping peaks, noise, and sloping baselines. In the discussions that follow, all data will be presented as peak areas. Gas chromatographic separation should be carried out following the advice given in this and other chromatographic treatises; some objectives are: good resolution of all peaks, symmetrical peaks, low noise levels, short analysis times, sample sizes in the linear range of the detector, and so on. Five methods of quantitative analysis will be discussed briefly, proceeding from the most simple and least accurate to those capable of higher accuracy.

12.3.5.1 Area normalization As the name implies, area normalization is really a calculation of area percent, which is assumed to be equal to weight percent. If X is the unknown analyte, then we obtain Area%X ¼ Ax =

X

! Ai
100%

i

where Ax is the area of X and the denominator is the sum of all the areas. For this method to be accurate, the following criteria must be met: l

l

l

All analytes must be eluted. All analytes must be detected. All analytes must have the same sensitivity (response/mass).

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These three conditions are rarely met, but this method is simple and is often useful if a semiquantitative analysis is sufficient or if some analytes have not been identified or are not available in pure form (for use in preparing standards).

12.3.5.2 Area normalization with response factors If standards are available, the third limitation can be removed by running the standards to obtain relative response factors, f. One substance (it can be an analyte in the sample) is chosen as the standard, and its response factor f is given an arbitrary value like 1.00. Mixtures, by weight, are made of the standard and the other analytes, and they are chromatographed. The areas of the two peaks—As and Ax for the standard and the unknown, respectively—are measured, and the relative response factor of the unknown, fx, is calculated: fx ¼ fs
ðAs =Ax Þ
ðwx =ws Þ where wx/ws is the weight ratio of the unknown to the standard. Relative response factors of some common compounds have been published for the most common GC detectors. For the highest accuracy, one should determine his/her own factors. When the unknown sample is run, each area is measured and multiplied by its factor. Then, the percentage is calculated as before:

Weight%X ¼ Ax fx =

X

! Ai fi
100%

i

12.3.5.3 External standard This method is usually performed graphically and may be included in the software of the data system. Known amounts of the analyte of interest are chromatographed, the areas are measured, and a calibration curve is plotted. If the standard solutions vary in concentration, a constant volume must be introduced to the column for all samples and standards. Manual injection is usually unsatisfactory and limits the value of this method. Better results are obtained from autosamplers that inject at least one microliter. If a calibration curve is not made and a data system is used to make the calculations, a slightly different procedure is followed. A calibration mixture prepared from pure standards is made by weight and chromatographed. An absolute calibration factor, equal to the grams per area produced, is stored in the data system for each analyte. When the unknown mixture is run, these factors are multiplied by the respective areas of each analyte in the unknown resulting in a value for the mass of each analyte. This procedure is a one-point calibration, as compared to the multipoint curve described

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before, and is somewhat less precise. Note also that these calibration factors are not the same as the relative response factors used in the area normalization method.

12.3.5.4 Internal standard This method and the next are particularly useful for techniques that are not too reproducible, and for situations where one does not (or cannot) recalibrate often. The internal standard method does not require exact or consistent sample volumes or response factors since the latter are built into the method; hence it is good for manual injections. The standard chosen for this method can never be a component in a sample and it cannot overlap any sample peaks. A known amount of this standard is added to each sample—hence the name internal standard. The internal standard must meet several criteria: l

l

l

l

It should elute near the peaks of interest. But it must be well resolved from them. It should be chemically similar to the analytes of interest and not react with any sample components. Like any standard, it must be available in high purity.

The standard is added to the sample in about the same concentration as the analyte(s) of interest and prior to any chemical derivatization or other reactions. If many analytes are to be determined, several internal standards may be used to meet the preceding criteria. Three or more calibration mixtures are made from pure samples of the analyte(s). A known amount of internal standard is added to each calibration mixture and to the unknown. Usually, the same amount of standard is added volumetrically (e.g., 1.00 mL). All areas are measured and referenced to the area of the internal standard, either by the data system or by hand. If multiple standards are used, a calibration graph is plotted where both axes are relative to the standard. If the same amount of internal standard is added to each calibration mixture and unknown, the abscissa can simply represent concentration, not relative concentration. The unknown is determined from the calibration curve or from the calibration data in the data station. In either case, any variations in conditions from one run to the next are canceled out by referencing all data to the internal standard. This method normally produces better accuracy, but it does require more steps and takes more time. Some EPA methods refer to spiking with a standard referred to as a surrogate. The requirements of the surrogate and the reasons for using it are very similar to those of an internal standard. However, a surrogate is not used for quantitative analysis so the two terms are not the same and should not be confused with each other. In general, spiking standards are used to evaluate losses and recoveries during sample workup.

12.3.5.5 Standard addition In this method the standard is also added to the sample, but the chemical chosen as the standard is the same as the analyte of interest. It requires a highly reproducible sample volume, a limitation with manual syringe injection.

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The principle of this method is that the additional, incremental signal produced by adding the standard is proportional to the amount of standard added, and this proportionality can be used to determine the concentration of analyte in the original sample. Equations can be used to make the necessary calculations, but the principle is more easily seen graphically. As increasing amounts of standard are added to the sample, the signal increases, producing a straight-line calibration. To find the original “unknown” amount, the straight line is extrapolated until it crosses the abscissa; the absolute value on the abscissa is the original concentration. In actual practice, the preparation of samples and the calculation of results can be performed in several different ways.

12.4

Advantages and limitations of GC

12.4.1 Advantages of GC The basic components of a GC instrument have remained remarkably unchanged since the first commercial instrument was introduced in 1955. Every GC instrument still is composed of a sample introduction/injection system, a device to regulate the flow of the mobile phase, an oven containing the separation column, and a detector. GC is a technique for separating individual components of chemical mixtures via differences in partitioning between a gas mobile phase and a stationary phase. The gaseous state of the mobile phase means the technique is amenable to the analytical separation of mixtures containing semivolatile and volatile analytes. In practice this leads to GC being an important analysis tool in a wide range of applications, including environmental chemistry, the food and flavor industry, the energy and petroleum industries, and the chemical manufacturing industry [35–37]. Its widespread use in both research and industrial settings has made GC a foundational analytical chemistry technique with persistent demand for improved information production via decreased analysis time or increased sensitivity or selectivity. GC has several important advantages: l

l

l

l

l

l

l

Fast analysis, typically minutes; Efficient, providing high resolution; Sensitive, easily detecting ppm and often ppb; Nondestructive, making possible online coupling; e.g., to a mass spectrometer; Highly accurate quantitative analysis, typical relative standard deviations of 1%–5%; Requires small samples, typically μL; Reliable and relatively simple.

Chromatographers have always been interested in fast analyses, and GC has been the fastest of them all, with current commercial instrumentation permitting analyses in seconds. The high efficiency of GC was evident because capillary columns typically have plate numbers of several hundred thousand. Furthermore, there have been many advances in column technology, detectors, injectors, and data-handling techniques, and the suitability of GC for automated analysis has increased its attraction to analysts. Many food components can be analyzed with great accuracy by GC and it has become

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one of the main techniques in analytical laboratories concerned with food analysis. For example, GC has replaced distillation as the preferred method for separating volatile materials. In both techniques, temperature is a major variable, but gas chromatographic separations are also dependent on the chemical nature (polarity) of the stationary phase. This additional variable makes GC more powerful.

12.4.2 Limitations of GC GC is limited to volatile samples. A practical upper temperature limit for GC operation is about 380°C, so samples need to have an appreciable vapor pressure (60 Torr or greater) at that temperature. Solutes usually do not exceed boiling points of 500°C and molecular weights of 1000 Da. This major limitation of GC is listed here along with other disadvantages of GC: l

l

l

l

Limited to volatile samples; Not suitable for thermally labile samples; Fairly difficult for large, preparative samples; Requires spectroscopy, usually MS, for confirmation of peak identity.

In summary: For the separation of volatile materials, GC is usually the method of choice due to its speed, high-resolution capability, and ease of use.

12.5

Recent technology development of GC

12.5.1 Sample preparation development The analysis of food composition present at very low concentrations in complex matrices (e.g., residues and contaminants in food samples) usually requires a complex analytical approach, involving sampling, sample preparation, analyte isolation, and qualitative and quantitative determination. From the sampling procedure up to final data processing, every step might introduce errors compromising the quality of the final analytical result. Sample preparation is usually time consuming, environmentally unfriendly, and is more difficult to automate than other steps. In spite of the tremendous evolution of the analytical instrumentation that has occurred in recent decades, especially in chromatography and MS, complex sample analysis still cannot achieve the desired results if the samples are introduced directly into the analytical instrument without a sample pretreatment step [38]. As a result, more extended methods have been developed to fulfill regulatory and analytical requirements, resulting in methodologies that involve several independent, complex steps. Most of microextraction techniques are based on sorption processes, making the development of novel sorptive materials one of the most active research areas in this field [38]. Nowadays, commercial SPME fibers are available to improve the extraction of nonpolar and polar analytes for sample preparation. However, there are still some drawbacks, such as low thermal stability, poor extraction sensitivity, swelling in organic solvent, extraction variability, and short lifetime due to fiber coating selectivity [39]. Sol–gel technology is a versatile way to overcome these limitations and

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sol–gel-based materials have been widely used as sorbents for sample preparation techniques (SPE and SPME) and chromatography stationary phases. Sol–gel chemistry is based on the hydrolysis and condensation reactions of metal alkoxides (M[OR]x) in the presence of a catalyst (acid or base) and a solvent (water and/or alcohol) prior to forming the polymer network. Much research employing sol–gel coatings in SPME has been published, which uses various precursor and organic additives during hybrid fiber synthesis to modify coating polarity and selectivity [40]. For example, Shu et al. [41] developed a novel SPME coating based on the sol–gel process; the fibers showed good thermal stability at 400°C, chemical resistance to polar organic solvent, and a wide range of pH stabilities. The use of graphene and other graphitized derived materials in sample preparation has also significantly increased in recent years since using graphene as an adsorbent for chlorophenol extraction in SPE in 2011 [42]. Graphene has a large adsorption capability thanks to the morphology of nanosheets that is accessible for molecular adsorption in both surfaces and to the large surface area. This morphology can be an advantage in comparison to carbon nanotubes and fullerenes because steric hindrance may exist when molecules access their inner walls [42]. In SPME, graphene was used for the first time by Chen et al. [43]. SPME performance was evaluated through a mixture containing six pyrethroid pesticides, the results being compared with those obtained utilizing extraction on PDMS and PDMS/divinylbenzene SPME fibers. Ponnusamy and Jen [44] also used graphene SPME fibers in the headspace mode to determine organochlorine pesticides in water samples. There are other ways to prepare SPME fibers containing graphene, such as sol–gel coating [45] and sulfonated graphene sheets [46]. Utilization of greener analytical methods stimulated the development of microextraction techniques [47]. The applications of ionic liquids (ILs) and supported IL phases in extraction and separation techniques have attracted great interest due to their hydrophobic or hydrophilic abilities for improving extraction efficiencies and selectivity [48]. In addition, the QuEChERS (quick, easy, cheap, effective, rugged, and safe) sample preparation approach, which involves liquid–liquid partitioning using acetonitrile and purifying the extract using dispersive solid-phase extraction (d-SPE), is gaining significant popularity in the analysis of food and pharmaceutical products due to its flexibility and cost-effective character [49].

12.5.2 Instrumentation development The essential elements of instruments were developed by the early 1960s, with further developments occurring in short bursts of innovation and advances in technology followed by longer periods of evolutionary changes and consolidation. Many advances were catalyzed by advances in column technology or electronics. With the introduction of robotic autosamplers at about the same time, the gas chromatograph could now operate without human intervention, 24 h operation became standard practice for routine analysis in high sample throughput environments, and gas chromatographs were deployed to remote locations and monitored electronically with only occasional visits for service and routine maintenance [50].

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The ability to identify the analytes separated by GC and deconvolute the analytical data depends on the characteristics of the detector. GC detectors can be concentration sensitive or mass sensitive. TC and ECDs are examples of concentration-sensitive detectors. In mass-sensitive detectors, the signal is related to the rate at which solute molecules enter the detector. Moreover, GC detectors can be classified as destructive, where the eluent is transformed by, for example, combustion in the FID, or nondestructive, where the analytes are detected without being significantly chemically altered. Some detectors such as the FID are not able to provide qualitative information directly, but rather rely on the reproducibility of an analyte’s retention time under consistent method parameters. Other detectors (e.g., ECD) provide unique selectivity in the detection of specific compound classes. Yet, this characteristic may be a compromise between specificity and the application range of the detector. MS is currently the most broadly applicable detector that can provide both qualitative and quantitative information. The vacuum ultraviolet (VUV) spectrophotometer was developed recently as an alternative chromatography detector. Using this detector, qualitative and quantitative information can be obtained. Additionally, the deconvolution of coeluting analytes and pseudo-absolute quantitation can be performed [51]. Additionally, the VUV detector can be used in combination with GC-MS (GC-VUV-MS) as a complementary technique to give dual qualitative information, which could be useful in food analysis. Another increasingly used type of GC detector is the atomic spectrometric detector. Atomic spectrometry is one of the oldest, most prominent, and widely used methods for elemental analysis. Different types of atomic spectrometry, including atomic absorption spectrometry, atomic fluorescence spectrometry, and plasma atomic emission spectrometry/mass spectrometry, have been coupled to GC as detectors. These detectors are able to determine the speciation of an element and chemical forms of analytes, which are usually more meaningful than merely total element contents [52]. Analytical samples are often at risk for sample contamination, decomposition, degradation, and loss during storage and transport from the collection site to the laboratory for analysis. This has resulted in a growing trend toward efforts to bring the lab to the sample when possible. Significant efforts have been invested to develop and test portable instrumentation. A new commercially available portable GC with detection provided by a toroidal ion trap mass spectrometer has been developed and described by researchers at Brigham Young University and Torion Technologies (www.torion. com) [53]. In addition, there have been several advances in the area of microfabricated and miniaturized GC detectors, including mass analyzers, ion mobility spectrometers, optical sensors, and microcantilever arrays [54].

12.5.3 Multidimensional GC GC is one of the highest resolution separation methods available to food quality evaluation. Many gas chromatographic systems are capable of achieving hundreds of thousands of theoretical plates and hundreds of peaks in a single chromatogram. Even with this great separation power, there are still many analytical samples that are even more complex. Complete separation of such samples by traditional GC is not practical. Multidimensional separations involving GC can employ two gas chromatographic

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columns or may employ HPLC followed by GC. Multidimensional gas chromatography (MDGC) is generally employed for the separation and isolation of target analytes of complex samples where linear GC has proven to be unsuccessful [55]. The aim of a typical MDGC system is to either increase the peak capacity of a separation system or increase the speed of analysis. The increase in speed of analysis is very important in industrial applications where the routine analysis of complex samples is common but it is the increase in peak capacity that is imperative. To increase the peak capacity using linear GC the analyst can choose to lengthen and/or decrease the internal diameter of a column; however, these gains in peak capacity are very limited due to practical/technical problems. MDGC offers excellent separation efficiency that serves advanced characterization of volatiles and semivolatiles in food samples [37]. An early application of MDGC in the area of food flavor was reported in 1978 [56]. Dimandja et al. [57] reported applying GC
GC to the analysis of essential oils in 2000, which was followed by further foodrelated analysis by GC
GC. In general, MDGC applies high-resolution approaches for the analysis of complex samples by providing improved separation of volatile analytes [58]. Most often, MDGC will be hyphenated with FID or MS, although other detectors (e.g., ECD) may offer specific compound analysis as required [59, 60]. For example, MDGC can be hyphenated with olfactometry for odorant analysis [20]. Due to the complexity of food samples, where aroma-active compounds are to be distinguished from other components by using olfactometry, high-resolution techniques such as MDGC are required. This is to minimize background interference prior to odor detection and to narrow down a range of possible odorants in olfactometric analysis, especially for parallel MS detection. Poorly resolved compounds will make attribution of the sensed odor to a specific compound recorded by MS difficult. Different MDGC-olfactometry-based methodologies have been developed and reviewed for analysis of complex food samples to distinguish individual odor compounds, and then their contribution to global aroma and odor characteristics of a sample was assessed [61]. Characterization of chemical constituents in food (qualitative or quantitative) by MDGC approaches is essential for the improved assessment of food safety and quality. This enables enhanced analysis and differentiation of food products with more complete descriptive and informative parameters for evaluation of food compared to conventional analytical approaches, according to bulk factors such as smell, texture, flavor, or color. High-resolution GC techniques play an important role in food analysis. Approaches that provide greater separation power than 1D-GC, such as a range of MDGC methodologies, should be increasingly attractive to provide various desirable goals for analysis of volatile and semivolatile compounds, particularly for identification with high confidence.

12.6

Recent application progress in different types of foods

From the multitude of methods applied in food analysis, GC has a key function. Presently, besides the appearance of the product, the products’ internal nutritional and health properties are becoming more and more important for consumers, especially

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in the case of beneficial compounds related to well-being as well as residues and neoformed compounds related to safety issues. There are defined prescriptive limits and maximum residual levels for residues and contaminants. However, even these aspects are the result of a scientific and political negotiation process in which economic interests with food safety aspects are weighed. This is shown by the variation of maximum residual levels (e.g., for pesticides) in different countries. For beneficial compounds, no regulations exist up to now. Food analysis is the major tool not only for ensuring food quality but also for supporting the development of new food products or technologies. From the multitude of methods applied in food analysis, GC has a key function. Although it provides the best chromatographic resolution, it was used for many decades only for the determination of more or less complex volatile compound mixtures with simple detectors such as the FID. However, at that time, use of MS in GC was limited. Parallel to the modern developments in MS (electrospray ionization, atmospheric pressure CI), which are coupled primarily to liquid chromatography, MS detection became affordable and ubiquitous for GC too. In this subsection several examples for the application of GC, including specific detection systems or sample preparation techniques, are reviewed. These examples cover major topics (sensory properties, food safety, authenticity, and health benefits) necessary for evaluating food quality.

12.6.1 Determination of volatile flavor compounds Aroma, a complex mixture of volatile compounds, plays a critical role in the perception and acceptability of fruits and vegetables. For example, durian, a kind of tropic fruit, has a unique sweet taste and strong stinky aroma. The special aroma of durian makes this fruit favored only by limited consumers. The volatiles profiles of durians have been investigated. In the study of aroma, GC analysis is the most frequently used. Li et al. [62] detected 46 odor-active compounds from Thai durian “Monthong” using aroma extract dilution analysis and GC-olfactometry. Among them, 24 were never reported to be found in durian before. The authors conducted further research, which disclosed that durian pulp overall odor can be mimicked by only two compounds: ethyl (2S)-2methylbutanoate and 1-(ethylsulfanyl) ethanethiol [63]. To get new opportunities for a wider durian marketplace, plant breeders are currently attempting to develop new cultivars of durian that have milder aromas and flesh with no seeds but a sweet taste and attractive color. Studies on characterization and identification of volatiles are important for new cultivar development. Belgis et al. [64] analyzed volatiles of six lai and four durian cultivars grown in Indonesia using SPME/GC-MS. According to their results, lai cultivars have less diverse sulfurs and esters as compared to durian, which were most probably the key reason for the different aroma characteristics of lai and durian. Lai was characterized by a less intense sulfury, fruity, and sweet aroma since it contained fewer sulfur and ester compounds than durian. Lower sulfur in lai cultivar increases its potency to be induced into new durian cultivar expansions. GC-MS with headspace solid-phase microextraction (HS-SPME) was used for the quantification of the different volatile components of bananas. Typical banana-related aroma components such as hexanal, 2-pentanone, 2-pentanol, 3-methyl-1-butanol,

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3-methylbutyl acetate (isoamyl acetate), and eugenol were detected, and differences in flavor profile were observed between ethylene and nonethylene-treated bananas at the same color stage and between bananas from different origins [65]. Nearly 250 volatile constituents have been identified for several fresh and processed banana products; however, only some of them have been recognized as banana flavor contributors. It is important to identify the trace compounds contributing significantly to banana aroma. For this purpose, it is necessary to achieve proper isolation (using adequate solvent and solventless methods) and identification of odor-contributing constituents in combination with sensory evaluation of the fruit and its individual components. SPME, simultaneous distillation–extraction, and LLE, combined with GC-FID, GC-MS, aroma extract dilution analysis, and odor activity value were used to analyze volatile compounds from banana fruit cv. Giant Cavendish and to estimate the most odor-active compounds. The analyses led to the identification of 146 compounds, and 124 of them were positively identified. Thirty-one odorants were considered as odor-active compounds and contributed to the typical banana aroma; 11 of them were reported for the first time as odor-active compounds [66]. GC-MS has been used to characterize tomato pericarp composition in transgenic plants, to assess metabolic diversity of tomato species, to measure metabolic changes associated with tomato fruit development, and to characterize biochemical changes during the development, ripening, and postharvest shelf life of tomato fruit. Mannose, citramalic, gluconic, and keto-l-gulonic acids were shown to be strongly correlated to final postharvest stages. During on-vine ripening, an increase was observed for the major hexoses, glucose and fructose, cell wall components such as galacturonic acid, and for amino acids such as aspartic acid, glutamic acid, and methionine. Major changes were also observed at the level of the tricarboxylic acid cycle, showing a decrease in malic and fumaric acids, and accumulation of citric acid [67]. Wang et al. [68] investigated the differences in volatile profile between pericarp tissue and locular gel in tomato fruit. Based on headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME-GC-MS) analysis, a total of 42 volatile compounds were detected in FL 47 and Tasti-Lee tomato fruits. Regardless of cultivars, a substantially higher concentration of total volatile compounds was observed in pericarp than in locular gel, associated with higher levels of aldehydes, hydrocarbons, and nitrogen compounds. Pericarp tissue possessed higher levels of cis-3-hexenal, hexanal, heptanal, octanal, nonanal, cymene, terpinolene, undecane, dodecane, 2phenylethanol, 6-methyl-5-hepten-2-one, 2-methylbutyl acetate, 1-nitro-pentane, and 1-nitro-2-phenylethane, while the abundances of 2-methylpropanal, butanal, 2-methylbutanal, 2-methyl-2-butenal, 2-methylpropanol, 3-methylbutanol, 2-methylbutanol, and 2-butanone were higher in locular gel.

12.6.2 Determination of pesticides, toxins, and pathogenic fungal disease Pesticides are a numerous and diverse group of chemical compounds, which are used to eliminate pests in agriculture and households. They enable the quantities and the quality of crops and food to be controlled, and help to limit many human diseases

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transmitted by insect or rodent vectors. However, despite their many merits, pesticides are some of the most toxic, environmentally stable, and mobile substances in the environment [69]. They are particularly dangerous in fruit and vegetables, by which people are exposed to them. Especially, the presence of pesticide residues in baby food ingredients implies a potential risk to this vulnerable consumer group, since their metabolic pathways are still immature and food consumption rates per body weight are higher when compared to adults. Evidence suggests that early exposure to pesticides and other environmental toxicants increases the risk of developing chronic diseases, including certain cancers and neurodegenerative diseases, as well as dysfunctions in the endocrine and reproductive systems. It is therefore crucial to monitor pesticide residues in fruits and vegetables using all available analytical methods. GC can be used to determine the residues of all classes of pesticides. The choice of chromatographic column is extremely important for separating analyses and for their qualitative and quantitative determination. The chromatographic column should be highly efficient and resistant to changes in the parameters of the separation process. The solid (stationary) phase should be thermally stable and highly selective with respect to the constituents of the mixture being analyzed. The multiresidue determination of pesticides in fruits and vegetables is generally carried out by GC-MS, due to its excellent characteristics of efficient chromatographic separation, sensitivity, and confirmation power based on electron-impact ionization mass spectra. Prior to GC-MS detection, the samples of fruits and vegetables were prepared according to the material under investigation. Usually, the fruits and vegetables need to be homogenized and then different methods used to extract pesticide residues effectively. The usual techniques for fruit and vegetable extracts are: (1) (2) (3) (4)

SPE; LLE; SPME; liquid-phase microextraction (LPME).

Although SPE and LLE methods yield accurate results, they are expensive, time consuming, tedious, and hazardous for the environment and health due to the use of the relatively high volumes of organic solvents. Therefore SPME and LPME methods have been developed as replacements for LLE and SPE. SPME is a solvent-free method in which the pesticide residues are simultaneously extracted from aqueous samples or the headspace of the samples on a fiber. However, SPME is a relatively expensive technique, its fiber is fragile, and sample carryover can be a problem. In recent years, LPME has attracted increasing attention as a new technique for sample preparation. In LPME a few microliters of a water-immiscible solvent are used as an acceptor phase for the analytes and generally an aqueous solution is used as a donor phase. The LPME method, after introduction in 1996, was performed in different modes, including SDME, hollow fiber–liquid-phase microextraction, dispersive liquid–liquid microextraction (DLLME), air-assisted liquid–liquid microextraction, solidification of floating organic droplets liquid-phase microextraction, and homogeneous liquid–liquid microextraction (HLLME). The HLLME method is an extraction method in which the selected analytes are extracted from a homogeneous solution into

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a water-immiscible extraction solvent by performing a phase separation phenomenon such as using a change in temperature, ionic strength, or pH. In HLLME, the initial state is a homogeneous solution and there is no interface between the aqueous phase and the extraction solvent. Therefore it has the advantage of extremely fast extraction speed due to the absence of obstacles from the surface contact between the aqueous phase and the organic phase during the extraction procedure. Torbati et al. [70] developed a new microextraction method called salt and pH-induced HLLME in a home-made extraction device for the extraction and preconcentration of pyrethroid insecticides from different fruit juice samples prior to GC-MS. Namely, an extraction device made from two parallel glass tubes with different lengths and diameters was used in the microextraction procedure. In their method, a homogeneous solution of a sample solution and an extraction solvent (pivalic acid) was broken by performing an acid–base reaction and the extraction solvent was produced in whole in the solution. The produced droplets of the extraction solvent went up through the solution and solidified using an ice bath. They were collected without a centrifugation step. With the aim of developing a new GC-MS method to analyze 24 pesticide residues in baby foods at the level imposed by established regulation, two simple, rapid, and environmentally friendly sample preparation techniques were compared based on QuEChERS with DLLME and QuEChERS with d-SPE by Petrarca et al. [71]. Both sample preparation techniques achieved suitable performance criteria, including selectivity, linearity, acceptable recovery (70%–20%), and precision (20%). A higher enrichment factor was observed for DLLME and consequently better limits of detection and quantification were obtained. Nevertheless, d-SPE provided a more effective removal of matrix coextractives from extracts than DLLME, which contributed to lower matrix effects. Bakirci et al. investigated pesticide residues in fruits and vegetables from the Aegean region of Turkey. A total of 1423 samples of fresh fruits and vegetables collected from 2010 to 2012 were analyzed to determine the concentrations of 186 pesticide residues, among which 43 pesticide residues were detected by GC-MS. As for GC detection, the instruments and apparatus were as follows: GC analysis was conducted using a GC-ECD, and the detected pesticides were confirmed by GC-MS. The GC-ECD analyses were performed on an Agilent 6890N equipped with a split/splitless injector and a 7683B autoinjector (Agilent, Santa Clara, CA, USA). GC-MS analysis was performed on an Agilent 7890A Turbo MSD 5975C equipped with a PTV inlet and a 7683B autoinjector (Agilent, Santa Clara, CA, USA). Helium was used as the carrier gas at a flow rate of 1.0 mL/min. Argon was used as the collision gas. Separations were conducted using an HP 5-MS 30 m
0.25 mm
0.25 μL column for GC-ECD and an HP 5-MS Ultra Inert 30 m
0.25 mm
0.25 μL column (Agilent, Santa Clara, CA, USA) for GC-MS. The injection volume was 25 μL and the injector temperature was held at 280°C. Samples were analyzed as follows: the temperature program was set for an initial temperature of 70°C (held for 2 min), increased to 150°C at 25°C/min (held for 1 min), raised to 200°C at 3°C/min (held for 1 min), and finally increased to 280°C at 8°C/min (held for 15 min) for GC-ECD and GC-MS analyses [72].

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Estrogenic chemicals, including bisphenol A, alkylphenols, and natural estrogens, have attracted public attention due to their negative effects on human and environmental health, and wide occurrence in various environments and foodstuffs like vegetables and fruits. Lu et al. [73] developed a simple, reliable, and sensitive analytical method for the analysis of estrogenic contaminants in vegetables and fruits by using an isotope dilution technique coupled with GC. The isotopically labeled standards of related environmental estrogens were used as the isotope dilution standards to form the following analyte/surrogate pairings: octylphenol/13C6-4-n-nonylphenol, 4-n-nonylphenol/13C6-4-n-nonylphenol, 4-nonylphenol/13C6-4-n-nonylphenol, bisphenol A/13C12-bisphenol A, estrone/13C6-estrone, 17-α-estradiol/13C6-β-estradiol, 17-αestradiol/13C6-β-estradiol, 17-α-ethynylestradiol/13C2-17-α-ethynylestradiol, and estriol/D4-estriol. Plant samples were homogenized and extracted ultrasonically with acetone. Acid pretreatment greatly increased peak intensities for the analytes. Acid hydrolysis pretreatment was important for liberating conjugates of estrogenic contaminants in plant materials. Recoveries of the spiked analytes were greater than 90%. Method limits of detection ranged from 0.01 to 0.20 g/kg, while limits of quantification ranged from 0.04 to 0.60 g/kg. Bisphenol, nonylphenol, and natural estrogens were detected in vegetable and fruit samples obtained from local markets, illustrating the feasibility of this method for determining trace estrogenic contaminants in vegetables and fruits. The method has significant environmental implications in terms of the simultaneous analysis of estrogenic contaminants in vegetables and fruits. Aspergillus, Penicillium, Mucor, and Fusarium are responsible for the rotting of fruits like apples, pears, and cherries, and they can produce a kind of mycotoxin patulin (4-hydroxy-4H-furo[3,2-c] pyran-2(6H)-one). Although no general consensus has been reached about the degree of toxicity of patulin, government agencies in the European Union have regulated the following maximum patulin concentrations in food products intended for infants and young children: 50 μg/kg in juices; 25 μg/kg in solid apple products; and 10 μg/kg in apple products. 5-Hydroxymethylfurfural (HMF) is one of the main products of the Maillard reaction, which may occur during food processing and storage, particularly at high temperatures in carbohydrate-rich products. Moreover, HMF can also be produced during the acid-catalyzed dehydration of hexoses via 1,2 enolization or by glucosamine hydrolysis. It is present naturally in products in which water coexists with monosaccharides in acid medium, such as balsamic vinegar and fruit juice. Patulin and 5-HMF can be considered as markers of the quality of a fruit-derived product. Simultaneous GC analyses of patulin and HMF in apple and pear juice were reported by Marsol-Vall et al. [74]. The GC-MS and GC-MS/MS analyses were performed with an Agilent 7890 GC (Agilent Technologies, Palo Alto, CA, USA) with a multimode injector and a splitless liner containing a piece of glass wool. A fused silica high-temperature capillary column J&W DB–5MS (30 m
0.25 mm internal diameter; 0.25 μm film thickness) from Agilent was used at constant flow. The detector was an Agilent 7000B triple quadrupole mass spectrometer with inert EI ion source. The mass spectrometer worked in SIM or multiple reaction monitoring mode with EI ionization source at 70 eV. Helium with a purity of 99.9999% was used as carrier gas and quenching gas, and nitrogen with a

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purity of 99.999% as collision gas, both supplied by Air Liquide (Madrid, Spain). A quantity of 5 g of the homogenized sample was placed into a 50-mL centrifugation tube. Subsequently, 10 mL of EtOAc was added. The mixture was vigorously shaken for 1 min by hand. Next, the tube was centrifuged for 5 min at 5000 rpm (Multi Reax; Heidolph, Schwabach, Germany). A volume of 1.5 mL of the upper layer was transferred into a 2-mL Eppendorf vial containing 100 mg of anhydrous sodium sulfate. The vial was manually shaken for 1 min and centrifuged for 3 min at 12,000 rpm (Hettich Eppendorf Centrifuge MIKRO 22 R; Germany). Finally, the organic phase was transferred to a crimp-cap vial for injection into the gas chromatograph. Optimal conditions for injection-port derivatization were 270°C, 0.5 min purge-off, and a 1:2 sample:derivatization reagent ratio (v/v). Strawberry is one of the most currently consumed berries and the fifth most preferred fresh fruit in the United States after bananas, apples, oranges, and grapes. New information on the health benefits of strawberries, because of their high nutritional values (which include high contents of folate, potassium, vitamin C, and fiber), has stimulated domestic consumption rates. However, strawberry fruits are highly perishable and vulnerable to tissue damage during harvest and postharvest handling and storage. The ripe fruits usually have a short postharvest life, estimated to be less than 5 days due to rapid dehydration, physiological disorders, bruising, mechanical injuries, and infections caused by a wide range of phytopathogenic fungi, bacteria, and viruses. Strawberry fruit decay caused by fungal infection usually results in considerable losses during postharvest storage; thus discerning the decay and infection type at an early stage is necessary and helpful for reducing losses. Fruits infected by pathogenic microorganisms produce a different array of volatile compounds, and the compounds characteristic to a specific infection may be assessed by GC-MS. In the study of Pan et al. [75], three common pathogenic fungi belonging to Botrytis sp., Penicillium sp., and Rhizopus sp. were individually inoculated into ripe strawberry fruits; noninoculated fruits were used as controls. The strawberry fruits were stored at 5  1°C for 10 days. During storage, inoculated fruits began rotting on day 2, while control fruits began rotting on day 4. The volatile compounds emitted by the fruits were analyzed by GC-MS. The volatile compounds of strawberry fruits were collected and analyzed by HS-SPME-GC-MS. The strawberry fruits in each of the three replicates were cut up and blended for volatile gas identification and quantification. The volatiles in the sample headspace were extracted and concentrated using an SPME fiber (PDMS, 100 μm, Supelco, USA), separated and identified by GC-MS (7890A/ 5975C, Agilent, USA). SPME fiber was aged in the GC inlet port at 250°C for 30 min at 1 mL/min to remove the residual gas. Approximately 10 g of strawberry fruits from one sample were weighed and placed in a 20-mL vial. The volatile was equilibrated at 40°C for 40 min in the vial sealed with a polytetrafluoroethylene (PTFE)/butyl septum and absorbed by the extraction head of SPME from the vial. Following equilibration, the extraction head was injected into the GC inlet port in a splitless mode. Subsequently, the volatile compounds absorbed in the SPME fiber were thermally desorbed at 250°C for 3 min and transferred to the GC system. The volatile compounds were then separated by a capillary column (30 m
0.25 mm
0.25 μm of film thickness) (HP-5MS, Agilent, USA). The GC

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parameters were as follows: initial oven temperature (50°C) was held for 5 min, the oven was subsequently programmed from 50 to 200°C at a rate of 2°C min/L and the temperature was maintained for 10 min after temperature programming the helium flow to 1 mL/min. The compounds were analyzed by MS using the following parameters: electron-impact mass spectra were recorded at 70 eV ionization energy by scanning MS from m/z 30 to 450; the temperatures of the ion source and the quadrupole were 230 and 150°C, respectively. The peaks were identified by comparing their mass spectra with the spectra of the NIST library (NIST, 2008), and compounds with an N80% match were used. The relative content was represented by the peak area, which accounts for the total peak area of all the acquired compounds. There were 20 major volatile compounds acquired by HS-SPME for the four strawberry fruit groups and analyzed by GC-MS for the three replicates on day 2. On the basis of their chemical and biological properties, all volatile compounds were divided into even broader categories as esters (11), aldehydes (1), alcohols (1), acids (2), phenols (1), and olefins (4). A multiple comparison test of the relative contents of the major aromas was used to find the difference in volatiles emitted from strawberry fruits of the four groups. The key compounds can be selected and confirmed. This resulted in six volatiles (ethyl hexanoate, hexanoic acid hexyl ester, hexyl isovalerate, 2-propen-1-ol, 3-phenyl acetate, styrene, limonene) being included. The six compounds showed a significant difference in relative contents between uninfected samples (CK) and infected samples (BO, PE, and RH). GC-MS results of the four strawberry fruit groups on day 2 identified several key characteristic volatile compounds for each infection treatment compared with the control. This could be used to detect pathogenic fungal disease at an early stage.

12.6.3 Determination of nitrosamines in vegetable and meat products Inorganic nitrates are ubiquitous in the environment and can occur in foodstuff as additives (E252) or contaminants. The major contribution of nitrate to human diet is due to vegetables, where NO 3 an easily reach the part-per-thousand level. Despite nitrate being relatively nontoxic for humans, attention should be given to nitrite, which is its main metabolic by-product. In this regard, NO3  reduced to NO2  by enzymatic reactions occurring in saliva, and the resulting nitrite may react with secondary and tertiary amino compounds to form highly carcinogenic N-nitroso compounds. Furthermore, NO2  inactivates hemoglobin by converting the oxyHb (Fe2 + ) into metHg (Fe3 + ). This last effect can have severe consequences for infants and may lead to a deadly condition known as methemoglobinemia. Campanella et al. [76] present a novel isotope dilution GC method for the determination of nitrate in vegetables. The analyte was extracted in water at 70°C and mixed with isotopically enriched 15 NO3  internal standard. The sample was centrifuged and the supernatant reacted with sulfamic acid for removal of nitrite, and with triethyloxonium tetrafluoroborate for converting NO3  into volatile EtONO2. This simple aqueous chemistry allowed for separation of analyte from the sample matrix

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in the form of a gaseous derivative, which could be sampled in the headspace before GC-MS analysis. This key feature of the method made possible the collection of clean chromatograms within an elution time of only 1.8 min. Detection of EtONO2 could be performed using electron-impact ionization with a standard GC-MS setup. The method was optimized and validated for the analysis of nitrate in fresh vegetables in the 10–10,000 μg/g range with a detection limit of 2 μg/g. Due to the use of primary isotope dilution quantitation, high-precision traceable results were attained. Meat products are substrates for diverse microorganisms, some of which have the potential to lead to harmful infectious diseases. To prevent this risk, several decades ago the application of nitrate and nitrite to meat products was invented. These additives especially act on Clostridium botulinum, known as the organism forming one of the most potent toxins in nature. Further advantages of adding nitrate are the stabilization of the product color, texture, and flavor formation. Unfortunately, the major disadvantage is the ability of these compounds to react with amino groups and amides to N-nitrosamines, some of which are highly carcinogenic. For the analysis of nitrogen compounds, the use of an element-specific detector seems to be highly recommended because conventional universal detectors such as the FID or even MS in full scan mode often are not sensitive enough to detect organic nitrogen compounds at low concentrations. More specificity and sensitivity are achieved by applying chemiluminescent detection. To analyze several N-nitrosoamines, Ozel et al. [77] developed a comprehensive 2D-GC coupled to a fast-responding nitrogen chemiluminescent detector, because the nature of GC
GC approaches requires detectors that have high-speed responses. With this method they were able to determine six N-nitrosamines in various Turkish meat products [77]. This methodology might also be used for other products such as fish products or water.

12.6.4 Determination of lipophilic compounds GC is generally the technique of choice when analyzing lipophilic compounds, such as fatty acids, fatty alcohols, phytosterols, and triterpenes. Free steroidal compounds in vegetable oils were determined by Maesol-Vall et al. The GC-MS analyses were performed on an Agilent 7890 GC (Agilent Technologies, Palo Alto, CA, USA) with a multimode injector and a splitless liner containing a piece of glass wool. A fused silica high-temperature capillary column J–5MS (30 m
0.25 mm internal diameter; 0.25 μm film thickness) from Agilent was used at constant flow. The detector was an Agilent 7000B triple quadrupole mass spectrometer with inert EI ion source. The mass spectrometer worked in SIM mode with EI ionization source at 70 eV. Helium with a purity of 99.9999% was used as carrier and quenching gas, and nitrogen with a purity of 99.999% as collision gas, both supplied by Air Liquide (Madrid, Spain). The gas chromatograph temperature was programmed as follows: 150°C (held for 1 min) to 220°C at 20°C/min and to 320°C at 5°C/min (held for 1 min) at a constant flow regime of 2 mL/min. The cap of the vial containing the derivatization reagent was PTFE/silicone/PTFE, which allowed repeated injections [78]. Xu et al. [79] developed a new method that was based on comprehensive 2D-GC coupled to time-of-flight MS to analyze steroidal compounds in vegetable oils, which

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could provide better separation and higher sensitivity than conventional 1D-GC, and allowed determination of 31 sterols and triterpene alcohols in one injection. With this method, more elaborate and complete information regarding the distributions and concentrations of free phytosterols and triterpene alcohols in safflower seed oil, soybean oil, rapeseed oil, sunflower seed oil, and peanut oil were obtained. The proposed method could potentially open a new opportunity for more in-depth knowledge of the steroidal compounds of vegetable oils.

12.6.5 Determination of the authenticity of foods using GC Prerequisite analytes for the determination of authenticity are compound classes such as aroma compounds, secondary plant metabolites, or fatty acids. Due to their high numbers and diverse chemical structures, as well as varying concentrations, a unique profile of substances is present. Furthermore, the possibility is given that singlecompound (sub)classes or even single compounds are specific for a raw material (e.g., plant species) or geographical origin. The class of substances that is most unique in food products comprises the volatile compounds. These several thousand substances are responsible for the flavor of foods and their raw products. Due to their high number and different formation pathways, they provide high specificity and their volatility makes them perfect analytes for gas chromatographic determination. A prominent example for isotope analysis is the determination of the kind of sugar (beet, corn, or cane) added to products that originally contain only their endogenous sugars (e.g., honey, wine, fruits). Due to biosynthesis, sugar beets and sugarcane develop different 13C ratios in their isotope pattern. As a result an adulteration can be detected because of an unusual isotope ratio [80]. To analyze mixtures of vegetable oils and the determination of their geographical as well as their botanical source, GC directly coupled to isotope ratio MS via a combustion interface can be used. In the combustion interface the fatty acids are oxidized to carbon dioxide of which amounts of 12CO2 and 13CO2 will then be analyzed [81, 82].

12.7

Summary and outlook

Food analysis is the major tool not only for ensuring food quality but also for supporting the development of new food products or technologies. The association of GC separation and various detection techniques is a key that opens up a rich and multidimensional analytical space for the investigation of complex mixtures with high sensitivity, selectivity, and specificity. GC techniques play an important role in food quality evaluation. While GC technologies will not be available in all laboratories, deciding to use a GC system and approach clearly depends on a compromise between user aims (e.g., analysis quality and level of compound detail required) and expense of time, system complexity, and analysis cost. Clearly, adoption of more advanced methods in a routine laboratory will require a significant investment in time, cost, education, and commitment.

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Approaches that provide greater separation power than 1D-GC, such as a range of MDGC methodologies, should be increasingly attractive to provide various desirable goals for the analysis of volatile and semivolatile compounds, particularly for identification with high confidence. However, the full capabilities of these techniques are expected to be more widely applied in the future following the growing need to characterize food samples more completely, the introduction of new types of food, to monitor foods for toxicity or adulteration, as well as the increasing demand for chemical information to meet more stringent new regulations, or discovery of benefits of chemical species. The recent commercial interest in MDGC and the introduction of related devices for MDGC augurs well for increasingly sophisticated gas-phase separations. This is now deliverable through GC
GC and MDGC developments, such as those described in this chapter. It is likely that the distinction between conventional MDGC and GC
GC will become increasingly blurred into a continuum of multicolumn methods suited to volatile chemical analysis, with hybrid systems incorporating facets of both technologies.

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