Microextraction techniques in the analysis of food flavor compounds: A review

Analytica Chimica Acta 738 (2012) 13–26

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Analytica Chimica Acta journal homepage: www.elsevier.com/locate/aca

Review

Microextraction techniques in the analysis of food flavor compounds: A review Henryk H. Jelen´ a,b,∗ , Małgorzata Majcher a , Mariusz Dziadas a a b

Faculty of Food Science, Pozna´ n University of Life Sciences, Wojska Polskiego 31, 60-624 Pozna´ n, Poland Department of Biochemistry and Human Nutrition, Pomeranian Medical University, Szczecin, Poland

h i g h l i g h t s

g r a p h i c a l

a b s t r a c t

 Microextraction methods in food flavors analysis based on 2006–2011 published papers discussed.  SPME, SBSE, LPME methods as dominating summarized in detail.  Potential of other, less popular in this field microextraction methods pronounced.

a r t i c l e

i n f o

Article history: Received 12 February 2012 Received in revised form 5 June 2012 Accepted 6 June 2012 Available online 14 June 2012 Keywords: Microextraction Extraction Food flavors Volatiles

a b s t r a c t Food flavor compounds due to the complexity of food as a matrix, and usually their very low concentrations in a product, as well as their low odor thresholds, create a challenge in their extraction, separation and quantitation. Food flavor volatiles represent compounds of different polarity, volatility and chemical character, which determine method of extraction for their isolation from food. Microextraction techniques, mainly SPME and SBSE have been used for food flavor compounds analysis for two decades. Microextraction methods other than SPME and SBSE are seldom used despite their analytical potential. The review discusses the nature of food flavor compounds, and different approaches to food flavor analysis. It summarizes the use of microextraction methods in food flavor compounds analysis based on papers published in the last 5 years, and discusses the potential of microextraction methods in this field. © 2012 Elsevier B.V. All rights reserved.

Contents 1. 2.

3.

4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Specificity of food flavor compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Approaches in food flavor compounds analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Food as a matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Microextraction techniques for food flavor analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Solid phase microextraction (SPME) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Stir bar sorptive extraction (SBSE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Other microextraction techniques based on sorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Liquid phase microextraction (LPME) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trends in the use of microextraction techniques for flavor analysis. A conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author. Tel.: +48 61 8487273; fax: +48 61 8487314. ´ E-mail address: [email protected] (H.H. Jelen). 0003-2670/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aca.2012.06.006

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H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

´ received his PhD and DSc from the Henryk H. Jelen Faculty of Food Science and Nutrition, Poznan´ Uni´ Poland, where he versity of Life Sciences, Poznan, holds his main position as professor. His scientific interests are focused on food chemistry, mainly flavor chemistry, sample preparation techniques, chromatography and mass spectrometry in volatile/flavor compounds analysis. He is also interested in electronic noses technologies for the assessment of food quality, and also in food key odorants and microbial volatiles analysis.

Małgorzata Majcher is currently working as an assistant professor in the Faculty of Food Science and Nutrition at the Poznan´ University of Life Sciences. In 2006 she has completed a PhD in flavor chemistry and since then her research is focused on food flavors analysis mainly key odorants determination. Recently her interests are particularly on flavors of traditional Polish foods such as dairy products, alcoholic beverages or coffee substitutes.

1. Introduction The common feature of flavor compounds is the interaction with human olfactory system inducing specific odor sensation. The term flavor is assumed to be a sensation induced by food taken in the mouth perceived principally by the senses of taste and smell, however also by general pain, tactile and temperature receptors in the mouth. Although mainly senses of both smell and taste are involved in perception of flavor compounds, the majority of research on flavor has been focused so far on aroma (odoriferous) compounds. In this review only methods related to aroma/volatile compounds will be discussed. The main feature of compounds taken into consideration here is their importance for flavor rather than their volatility. Therefore numerous volatile food contaminants have not been included in this review. In the last decade (since 2001) there have been over 60 review papers focused on the food flavors. Of them vast majority have been devoted to the flavor of specific foods (i.e. wine, cheeses, yoghurt, butter, fruits (apple, strawberry, kiwi)), olive oil, beer, grape juice, hand squeezed orange juice, cocoa, chocolate, tea, breads, rice, herbs and compounds responsible for the formation of off-flavors in different foods. However, only 10 of them were technique, not matrix-oriented. They discussed such extraction techniques as SPME in volatiles/flavor compounds analysis [1–4], sorption techniques used for extraction [5], headspace analysis [6], simultaneous distillation/extraction [7]. Also new trends in the analysis of volatile fraction of vegetable matrices [8] were discussed, as well as the use of electronic noses [9] and gas chromatography–olfactometry [10] in flavor research. There is no current paper summarizing the use of microextraction techniques in the isolation of flavor compounds, which would discuss the most frequently used (SPME), as well as those techniques, which application in the flavor analysis field is limited. Of our special interest were microextraction techniques due to their potential in flavor analysis – fast sample preparation, high sensitivity, high enrichment factor and often possibility of automation. They use a minute amount of solvents, or are solventless – contrary

Mariusz Dziadas is a PhD student at the Faculty of Food Science and Nutrition at the University of Life ´ Sciences in Poznan´ under guidance of professor Jelen. His PhD research work focuses on the use of chromatographic methods in the extraction separation and identification of bound and free volatile compounds in grapes and wine. He works also on new functionalized adsorbents for extraction of food flavor compounds.

to many methods used for flavor isolation and regarded as “classical” such as high vacuum transfer (HVT), solvent assisted flavor evaporation (SAFE), liquid/liquid extraction (L/LE), simultaneous distillation/extraction (SDE). Therefore microextraction techniques should be an attractive tool in the characterization of food flavor compounds. Searching databases for microextraction methods used in food flavor characterization the topic is dominated by papers on solid phase microextraction (SPME). Stir bar sorptive extraction (SBSE) is relatively frequently used, but the remaining sorptive extraction methods are represented only by few papers within last five years (SPE is not included in this review). Liquid microextraction methods are far less popular in the analysis of food flavors, than extraction to solid sorbents. Applications of the mentioned microextraction techniques for flavor research published within last five years will be discussed in this review. 2. Specificity of food flavor compounds To reach the human olfactory receptors odorants need to be volatile, so odorants are generally characterized by relatively high vapor pressures and their molecular weight usually does not exceed 300 Da. The vapor pressure of odorants in a single food product can vary and span several orders of magnitude, which influences, together with their differences in polarity, the choice of extraction techniques for their isolation. Flavor compounds must be distinguished from volatile compounds as the compounds representing the latter group do not need to have a specific odor. Whereas in foods of various types around 12,000 volatile compounds have been identified so far, it is estimated that only around 5% of them play a significant role in the formation of aroma of these products [11]. They can be perceived by human olfactory system if present in concentrations exceeding their odor threshold. Flavor (aroma) compounds are characterized by odor threshold sometimes of very low values in a ng L−1 or ng kg−1 range making it a challenge both to isolate them from food and then identify and quantify. As an example black tea powder/infusion can be given: it contains 89 esters, 81 ketones, 75 aldehydes, 74 acids, 68 alcohols, 64 basic compounds, 52 hydrocarbons, 21 furans, 19 sulfur compounds, 18 lactones, 13 phenols and 17 others, which make a total of 591 compounds [12]. The number of identified volatile compounds in food is dependent on the separation/identification technique used. Therefore the number of identified volatiles in food rapidly increased with the invention of capillary columns, and now similar leap is being observed with the comprehensive gas chromatography–mass spectrometry (GC × GC–MS). As a result the total number of volatiles identified in particular food is abundant, however usefulness of this data especially for flavor studies is sometimes limited.

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2.1. Approaches in food flavor compounds analysis The analysis of flavor compounds in food can be characterized by three types of approaches: (i) sensory guided analysis, (ii) analyzing volatile/flavor compounds to obtain their “profile” in food, often followed by multivariate analysis used for authenticity testing and products classification and comparison mainly, (iii) target analysis aimed at compounds that are either restricted, or known as important for quality, processing and storage. In the sensory guided analysis the main goal is to identify compounds responsible for the specific odor of particular food (key aroma compounds, key odorants). Referring to the cited before example of black tea [12], out of 591 volatile compounds, only 16 were assumed as key, impact odorants. Their odor thresholds ranged from 0.004 ␮g L−1 for (E)-␤-damascenone to 13 ␮g L−1 for (Z)-3-hexenol. The recombination experiment (mixing identified key odorants in proper quantities to obtain the identical aroma with investigated product) is a final confirmation of both qualitative and quantitative analyses results. Use of gas chromatography–olfactometry (GC–O) for odorants detection, together with various GC/MS techniques for their identification, form basic tools for key odorants investigation [13]. As key odorants are often present in a very low concentration and represent various chemical classes of broadly varying polarity, volatility and boiling points, exhaustive extraction techniques have been always a method of choice. To avoid artifacts formation methods based on vacuum distillation, such as SAFE (solvent assisted flavor evaporation) prevail [14]. For foods in which flavor compounds are thermally more stable, simultaneous extraction/distillation (SDE) is used, liquid/liquid extraction is also a method of choice for many analyses [7]. As in most often used GC–O methods, such as AEDA (Aroma Extract Dilution Analysis) [15] and CharmTM [16] from the concentrated flavor compounds extract serial dilutions are prepared, then injected and sniffed at olfactometry port, extraction methods which provide liquid extract are used. Headspace analysis combined with gas chromatography–olfactometry (HS–GC–O) is used far less frequently [17]. To obtain profile of volatile compounds of particular food, SPME is since its invention the predominant method. The reason is that it offers a rapid way to obtain a “profile” of volatile compounds. However it has to be remembered that SPME profile does not reflect the actual composition of volatile compounds in a particular product, as it is a non exhaustive method, but one based on the partition of analytes between phases. However, for many purposes, such as authenticity testing, screening for off-odorants, such profiles provide very useful information. Target analysis in flavor research is usually aimed at quantitation of restricted compounds, or compounds that are known, or suspected to be a cause of quality problems. Taints and off-flavors analysis is an example of such applications, where methods have to provide sufficient enrichment of analyte, selectivity and sensitivity for analysis of compounds often in sub ppb levels. For target analysis microextraction methods are well suited and a great deal of discussed examples refer to this group of analyses. 2.2. Food as a matrix The flavor analysis is determined by the nature and quantity of the aroma active components which is even more multifaceted in food products due to the matrix effect. It is mostly due to the reaction of very often trace quantities of flavor compounds with main food constituents such as lipids, proteins or carbohydrates.

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The release of aroma compounds from foods is determined by the partition coefficient between the air phase and food matrix and type of interaction depends on the physicochemical properties of flavor compounds and food components. The knowledge of flavor compounds–matrix interaction is not only a crucial step in flavor release research, but also important for analytical methods development [18–23]. However, it has been few years back when the flavor interactions in food matrices have been described and named [24–26]. They include covalent bonding (this is irreversible bonding such as the interaction between aldehyde or ketone and amino group of proteins), hydrogen bonding (this occurs between polar or volatile alcohol and heteroatom (N, S, O) of food components), hydrophobic bond (this is weak and reversible bonding, such as van der Waals bond between apolar compounds and fat molecules) and physical binding (for example inclusion complexes, which occurs between flavor compounds and starch or starch derivatives). At the same time Mc Gorrin [24] classified flavor–matrix interation as binding, which means the inclusion, adsorption, absorption and retention of flavor compounds onto nonvolatile substrates; partitioning, as the distribution of flavor compounds between phase such as the oil, water and gas phases and finally release, meaning the availability of flavor compounds from the bulk foods into the gas phase for sensory perception. Concerning the saccharides interactions of aroma compounds mono- and disaccharides usually increase the vapor pressure [27], however polysaccharides mostly decrease aroma compounds volatility [26]. Piraprez et al. studying interaction between lipids and aroma concluded that the structure of the compound strongly influences retention on the lipid matrix and even within the same chemical family exists a linear relationship between lipophilicity index and retention [28]. The effect of hydrocolloids on flavor release may be due to physical entrapment of flavor molecules within food matrix or the interaction with gel components [20], matrix particle size distribution and fat content [21]. As outlined above matrix interactions with volatile flavor compounds is probably one of the most pronounced difficulties in method development process, reflected in quantitation where extreme care must be paid to the choice of calibration methods.

3. Microextraction techniques for food flavor analysis Developments in sample preparation are aimed and find most applications in environmental analysis. The search for improved sample preparation has the following goals: (i) reduction of the number of steps in analytical procedure; (ii) reduction or elimination of solvents required for extraction; (iii) adaptability to field sampling; (iv) automation [29]. Microextraction methods that use a minimal amount of extractant (sorbent or liquid phase) offer these benefits, and are becoming widely used in different fields: environmental, biomedical applications, food and flavor, forensic, to name the most frequently described applications. There are numerous books and review papers devoted entirely to the sample preparation and also to the miniaturization in sampling techniques [30–35]. Extraction techniques can be divided into flow-through and batch equilibrium and pre-equilibrium techniques. The first group includes such exhaustive techniques as purge and trap, sorbent traps, SPE, and non-exhaustive ones such as in-tube SPME. The second group includes exhaustive liquid/liquid extraction, Soxhlet or sorbents extraction, and such non-exhaustive techniques as static headspace, SPME and LLME (liquid–liquid microextraction). There is also a steady state exhaustive and nonexhaustive methods represented by membrane extraction distinguished [31]. Of extraction methods usually discussed, many are prone to miniaturization and solid phase microextraction as well as liquid phase microextraction methods are rapidly evolving in

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3.1. Solid phase microextraction (SPME)

solvent extraction of compounds from absorption tubes, it offers high reproducibility, usually not much different from its automated form. The second advantage of this technique is a choice of fiber coatings. At present absorption fibers are available (PDMS, CW, PA) as well as fiber coatings in which adsorption processes dominate (DVB/PDMS, Carboxen/PDMS). Ionic liquids are also used as SPME fiber coatings [37]. Developments of new SPME coating materials provide new fields of application for this technique and allow, to certain extend, to tailor the extracting phase to type of compounds analyzed. However, when publications are screened for the type of SPME fibers used for extraction a domination of divinylbenzene/carboxene/polydimethylsiloxane fiber coatings can be observed (Table 1). This type of fiber offers high efficiency in extracting food volatiles, and when several fibers are tested in the method development process, it often provides the highest peak areas of extracted compounds. SPME can be used for direct extraction of analytes from liquid phase, can be used for headspace extraction and in case of dirty matrices the fiber can be protected by membrane [38]. Due to the specificity of food matrices – presence of sugars, lipids, proteins, colorants and other non-volatiles, SPME is used almost exclusively as a headspace extraction method (HSSPME). Static headspace extraction (and also HS-SPME) is based on the partition of analytes and is a non exhaustive extraction. However, static headspace can be an exhaustive method, when multiple extractions are performed from the same vial, allowing the sample to re-equilibrate after each extraction. The amount of analyte in the matrix decreases logarithmically. Multiple headspace extraction can be performed for microextraction methods as well and has been discussed for SPME and SDME [39]. MHS-SPME has proved to be a good tool in simultaneous determination of haloanisoles and volatile phenols in wine, allowing to eliminate the matrix effect [40]. However, when searching the modes of SPME extraction in Table 1, MHS-SPME is rarely chosen. Table 1 summarizes the application of SPME for the analysis of volatile/flavor compounds in the most explored food systems. Due to the vast number of papers published on SPME and food flavor/volatiles, the selection of papers for this table was based mainly on the number of citations, however also recent papers were included. Data in Table 1 represent practically all the food categories listed in Fig. 1. It is striking, that out of 52 papers summarized in this table only in 9 of them limits of detection (LOD) or limits of quantitation (LOQ) is provided, few others are quantitative methods but LODs were not provided. It indicates that for the majority of papers in food flavors analyses SPME was used for qualitative rather than quantitative purposes. Several main groups of applications for which SPME is used in food flavor research can be distinguished:

Solid phase microextraction, although still sometimes described as a (relatively) new sample preparation technique is a mature one, nowadays over 20 years after its invention [36]. Based on the absorption–adsorption of analyte into a coating of an optic fiber (recently offered also in a stainless steel version) it quickly became one of the most often used techniques in various fields of analytical chemistry, mainly environmental applications, food and flavor, clinical and toxicological research. When looking into the types of food in which SPME was used for analysis of flavor/volatile compounds, the biggest group was wine, followed by fruits/vegetables, dairy products, beverages, meat, spices and herbs, cereals/bakery, snacks, fats and oils, seafood/fish and honey (Fig. 1B). Certainly SPME is one of the most rapidly developing extraction technique due to its several advantages. The first is its simplicity: it can be easily automated and recent incorporation of SPME modules into XYZ type autosamplers made it available for virtually all GCs. Besides the automated version it exists in a manual form with a cheap, reusable holder in which fibers can be replaced. Contrary to other techniques performed manually, like static headspace or

(i) Comparison studies of different varieties of fruit and vegetables: apricots [41], peppers [42], orange juices [43], olive oils form various countries [44], mandarine, Clementine juices [45], raspberry cultivars [46]. (ii) Profiling particular foods volatiles: beer [47], passion fruit, cashew, tamarind, acerola, guava [48], citrus honey [49], capers [50], pepper [51], different dry-cured hams [52], coffee [53], water melon [54], teas fermented to different extent [55], monovarietal Mencia wine [56], baked bread [57], cocoa [58], smoke-cured bacon [59], Sauvignon blanc wine – to monitor their origin [60], Istrian ham [61]. (iii) Classification of foods using SPME in conjunction with gas chromatography or for direct introduction of volatile compounds into MS-based quasi electronic noses. Either chromatographic profile or obtained “average” mass spectrum is subjected to multivariate analysis. It has been used for Madeira wines [62], raw spirits classification [63], or oils quality and authenticity assessment [64,65]. The use of volatile

Fig. 1. Applications of microextraction methods to food flavors analysis (A) and application of SPME to different food matrices (B). Number of papers based on Web of Knowledge search for years 2006–2011.

all fields of analytical chemistry. Looking into applications of these methods in food flavor analysis some trends in the use of particular methods can be observed. Fig. 1A shows the results of Web of Knowledge search for microextraction methods used in food flavors analysis in years 2006–2011. The results indicate the leading role of SPME in this field. The second method in use frequency was SBSE, followed by SDME and LLME. All other microextraction methods combined were represented by only 23 publications.

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Table 1 Applications of SPME in flavor compounds analysis, based on the 492 publications available in Web of Knowledge in 2006–2011. Matrix

Wine n.d. Madeira Red wines

Red, white, rose wines Synthetic, verdejo, red wines Synthetic, red, white wines Spanish sparkling wines

Synthetic wine Sauvignon blanc

Vegetables Tomato Tomato Cucumber Herbs and spice Spices Pepper Pepper Oils Olive oil Olive oil Olive oil Meat and fish Sausage

Beef

Liver pate Sausage Ham

Bacon

Ham Mackerel

Juices Orange Citrus Fruits Apricot

Tropical

Apple

Pear Citrus

Analytes

Methoda /fiber

Equilibrium/ extraction (min)

LOD

LOQ

Reference

Alcohols, esters, geosmin, haloanisoles, heterocyclic, MIB, phenolic compounds Acids, alcohols, esters, norisoprenoids, terpenes Furanones and furans, ketones, lactones, norisoprenoids, phenolic compounds Haloanisoles, phenolic compounds, Sulfur compounds, Haloanisoles Acids, alcohols, aldehydes, esters, furanones and furans, ketones, lactones, phenolic compounds, terpenes, Acids, alcohols, esters, terpenes, Alcohols, terpenes, isoprenoids, phenoli compounds, thiols, carbonyl compounds

C/D/P

3/60

n.d.

n.d.

[67]

PA

120/120

n.d.

n.d. −1

[62] −1

C/D/P

10/60

2 ␮g L

34 ␮g L

[68]

C/D/P D/PDMS MHS, C/D/P C/D/P

10/60 5/20 30/35 30/30

0.01 ␮g L−1 0.03 ng L−1 7 ng L−1 n.d.

0.23 ␮g L−1 n.d. n.d. n.d.

[40] [70] [149] [94]

PDMS C/D/P

10/60 10/60

n.d. 10 ng L−1

n.d. n.d.

[83] [56]

CAR

30/60

1 ng/g

n.d.

[95]

Alcohols, aldehydes, esters, norisoprenoids, terpenes, Aldehydes, alcohols, ketones, furanones and furans, terpenes Aldehydes

CAR

30/60

n.d.

n.d.

[85]

CAR

n.d./30

n.d.

n.d.

[89]

Terpenes Esters, terpenes, Terpenes

PDMS PDMS D/PDMS

60/10 n.d./44 n.d./20

n.d. n.d. n.d.

n.d. n.d. n.d.

[75] [42] [51]

Acids, esters, ketones, Phenolic compounds Alcohols, aldehydes, ketones,

C/D/P C/D/P C/D/P

15/30 10/30 2/30

0.05 ␮g g−1 0.09 ␮g kg−1 n.d.

n.d. 0.3 ␮g kg−1 n.d.

[69] [74] [44]

Acids, alcohols, aldehydes, esters, ketones, phenolic compounds, sulfur compounds, terpenes Acids, alcohols, aldehydes, esters, furanones and furans, heterocyclic, ketones, phenolic compunds, sulfur compounds, terpenes, Alcohols, alcohols, furanones and furans, Acids, alcohols, aldehydes, esters, ketones, sulfur compounds, Acids, alcohols, aldehydes, furanones and furans, ketones, phenolic compounds, sulfur compounds, Alcohols, aldehydes, ketones, furanones and furans, phenolic compounds, sulfur compounds alcohols, aldehydes, esters, ketones, terpenes Alcohols, aldehydes, esters, furanones and furans, ketones, phenolic compounds, sulfur compounds,

CAR

30/120

n.d.

n.d.

[76]

C/D/P

n.d./60

n.d.

n.d.

[91]

C/D/P

n.d./30

n.d.

n.d.

[78]

MHS, CAR

30/90

n.d.

n.d.

[92]

C/D/P

10/180

n.d.

n.d.

[52]

CAR

15/30

n.d.

n.d.

[59]

C/D/P

n.d./180

n.d.

n.d.

[61]

CAR

n.d./15

n.d.

0.03 ng/g

[73]

Esters, terpenes, Terpenes

CAR C/D/P

n.d./15 120/120

n.d. n.d.

n.d. n.d.

[77] [45]

Acids, alcohols, aldehydes, esters, ketones, lactones, norisoprenoids, phenolic compounds, terpenes Alcohols, aldehydes, esters, futanones and furans, phenolic compounds, terpenes Acids, alcohols, esters, phenolic compounds, sulfur compounds, terpenes, Acids, alcohols, aldehydes, esters, ketones, sulfur compounds, terpenes Alcohols, aldehydes, phenolic compounds, terpenes,

CAR

40/20

n.d.

n.d.

[41]

PDMS

10/25

n.d.

n.d.

[48]

C/D/P

15/30

n.d.

n.d.

[90]

PDMS

n.d./30

n.d.

n.d.

[79]

C/D/P

n.d./30

n.d.

n.d.

[43]

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Table 1 (Continued) Matrix

Analytes

Methoda /fiber

Equilibrium/ extraction (min)

LOD

LOQ

Reference

Apple Watermelon

Alcohols, esters, norisoprenoids, Alcohols, aldehydes, phenolic compounds, terpenes, Alcohols, esters, terpenes, Acids, esters, ketones, phenolic compounds,

C/D/P C/D/P

10/30 10/12.5

n.d. n.d.

n.d. n.d.

[80] [54]

C/D/P PDMS

10/30 n.d./30

n.d. n.d.

n.d. n.d.

[46] [81]

C/D/P

30/30

n.d.

n.d.

[84]

CAR

20/30

n.d.

n.d.

[86]

Acids, alcohols, aldehydes, esters, furanones and furans, heterocyclic, ketones, phenolic compunds, sulfur compounds Aldehydes, esters, furanones and furans, lactones, norisoprenoids, phenolic compounds, sulfur compounds,

CAR

20/30

n.d.

n.d.

[47]

C/D/P

10/40

0.03 ␮g L−1

0.02–4.7 ␮g L−1

[71]

Alcohols, aldehydes, esters, furanones and furans, heterocyclics, ketones, norisoprenoids, phenolic compounds, terpenes, Acids, aldehydes, esters, ketones, lactones, norisoprenoids, phenolic compounds Terpenes Acids, alcohols, aldehydes, ketones, furanones and furans, Acids, alcohols, aldehydes, esters, ketones, phenolic compounds, sulfur compounds, Acids, alcohols, ketones, aldehydes, heterocyclics Alcohols, aldehydes, furanones and furans, ketones phenolic compounds, sulfur compounds, Aldehydes, esters, heterocyclics, phenolic compunds, sulfur compounds, Acids, alcohols, aldehydes, ketones, terpenes

CAR

n.d./30

n.d.

n.d.

[55]

C/D/P

30/60

n.d.

n.d.

[49]

CAR C/D/P

10/30 20/20

n.d. n.d.

n.d. n.d.

[88] [96]

C/D/P

30/40

n.d.

n.d.

[50]

CAR

5/60

n.d.

n.d.

[57]

C/D/P

30/30

n.d.

n.d.

[82]

C/D/P

10/40

n.d.

n.d.

[53]

CAR

10/15

n.d.

n.d.

[58]

Raspberry Bananas Cheese Spanish soft cheese Manchego cheese Beer Different types

Different types

Miscellaneous Tea

Honey

Flavorings Fermented milk Capers

Bread Concentrates

Coffee Cocoa

Acids, alcohols, aldehydes, esters, ketones, phenolic compounds, Acid, alcohols, ketones,

a Methods – in all papers headspace SPME was used except those marked as MHS, where multiple headspace solid phase microextraction was used. Abbreviations of fiber coatings used: P – polydimethylsiloxane (PDMS); CAR – carboxen/PDMS; C/D/P – carboxen/divinylbenzene/PDMS, PA – polyacrylate; D/PDMS – divinylbenzene/PDMS, CW/D – carbowax/divinylobenzene.

compounds profiling in the authenticity and traceability testing has been recently summarized [66]. (iv) Analysis of selected compounds important for food quality: offodorants in wine [67], compounds extracted from oak into wine [68], olive oil volatile oxidation products [69], 2-methyl3-furanthiol and 3-mercaptohexyl acetate in wines with onfiber derivatization to achieve limits of detection similar to odor thresholds [70], compounds determining flavor stability of beer, carbonyls in beer [71,72], compounds associated with oxidation of fish muscle (1-pentene-3-ol, 2,3-pentanedione, 1-octene-3-ol [73], volatile phenolic compounds in olive oil [74]). (v) Monitoring the influence of technological processes on flavor compounds: encapsulation of oregano, citronella and marjoram flavors [75], sausage fermentation [76], flavor of cloud orange emulsions [77], monitoring antioxidant properties of essential oils in liver pate based on measurement of aldehydes resulting from lipid oxidation [78], changes in volatiles of Yali pear during storage [79], effects of supercritical CO2 and N2 O pasteurization on the quality of fresh apple juice [80], different drying systems for banana powder [81], agglomeration and storage of whey protein isolates/concentrates [82], influence of yeast strains on the profile of produced sulfur compounds

[83], soft cheese ripening [84], high pressure processing of cherry tomato puree [85], stability of irradiated cheese [86], maturation of raw goat milk cheese [87]. (vi) Monitoring chemical, biochemical and biotechnological processes such as biotransformations of terpenes [88], degradation of flavors [89]. (vii) Application of SPME for gas chromatography–olfactometry (GC–O) where sniffing compounds after desorption of SPME fiber can provide a useful data on the characteristic odor notes: apricots [41], apple cider [90], simulated beef flavor [91], dry fermented sausages [92], odor active compounds in grapes [93]. Methods comparison was performed for several techniques and matrices. In sparkling wines SDE, CLSA (closed loop stripping analysis), HS-SPME were compared, and SPME provided comparable results for the main volatiles, compared to lengthy procedures of CLSA and SDE [94]. Comparison of SPME and purge and trap was performed for tomato aroma [95]. Fermented camel milk was investigated using SAFE, SDE and HS-SPME [96]. Simultaneous distillation extraction in the Likens-Nickerson apparatus (120 ◦ C, CH2 Cl2 , 3 h, 200 g of milk) provided the highest number of identified compounds, followed by SAFE and then by HS-SPME (40 ◦ C,

H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

20 min, 5 g of milk). In this case probably the main differences in number of identified compounds by examined methods was the prolonged heating of a milk sample. Horak et al. [97] compared the suitability of SPE, SPME and SBSE for the analysis of free fatty acids in beer. The disadvantage of SPME compared to other methods was the ability to extract only C4:0 (caproic) to C12:0 (lauric) acid, whereas both SPE and SBSE were able to extract fatty acids up to C18:3 (linolenic). However, the sampling time using SPME was comparable to SPE (30 min) and three times shorter than for SBSE. 3.2. Stir bar sorptive extraction (SBSE) Stir bar sorptive extraction (SBSE) is a microextraction method introduced in 1999 by Baltussen et al. [98]. In SBSE a coated stir bar can be added to the sample for stirring and extraction (direct SBSE) or exposed to the headspace (HS-SBSE). The amount of coating (PDMS) in SBSE is usually 50–250 times larger than in SPME, which increases the preconcentration efficiency [99], however increases equilibrium time due to the diffusion into the large volume of coating. Therefore the extraction times described in literature for SBSE are usually longer than that for SPME (Table 2). The sampling time in case of solvent reextraction of volatiles from the stir bar make the process even longer [97]. In the optimization of SBSE parameters for Sherry brandy volatiles extraction was performed for 100 min [100,101], in case of beer volatiles for 60 min [102] and for blackberries – 120 min [103]. Stir bar sorptive extraction found numerous applications in food flavors/volatiles analyses the main being wine analysis, beverages, detection of off-flavors, monitoring metabolism of flavor compounds. Due to the high volume of phase in SBSE stirrer, which results in low detection limits, it is a good tool for the analysis of offflavor. It has been used for the multi residue profiling of wine, allowing quantitation of volatile phenols, haloanisoles, geosmin and 2-isobutyl-3-methoxypyrazine with detection limits <1 ␮g L−1 for all except geosmine and recoveries >92%. For geosmin extraction by SBSE pH adjustment to pH 10 was useful to avoid coextraction of free fatty acids [104]. Chloro-, bromoanisoles and phenols were detectable by SBSE in a concentration ranging from 0.01 to 0.71 ng L−1 [105]. These authors compared immersion SPME with SBSE using the same phase (PDMS) to notice that compared to LODs achieved by SBSE, those for SPME were generally approximately 20 times higher. SBSE can be used with thermal desorption, which is more common, but also using reextraction. Combining this with large volume injection allowed an effective extraction of esters, monoterpenes, sesquiterpenes and C13 norisoprenoids from sparkling wines [106]. Method parameters of SBSE-LD/LVIGC–qMS were optimized for compounds representing different flavor groups [107]. SBSE was used for monitoring of wine volatiles dependence on agronomical conditions [108], Saccharomyces cerevisiae strains used for fermentation [109], composition of volatiles in grapes transferred to wine and their influence on wine flavor [110]. SBSE is sometimes used in a manner similar to SPME “profiling” for qualitative analysis. However, it was used also for the multicompound (68) quantitative analysis of volatiles in blackberries [103]. Despite the SBSE affinity to compounds of different polarity and volatility some of the polar compounds, such as furaneol, mesifurane, ethyl maltol have to be quantified using solid phase extraction and microvial insert thermal desorption [103]. SBSE proved to be a very good tool for monitoring biogenesis and metabolism of volatile flavor compounds in plants. It allowed extraction of linalool, nerolidol and pinene enantiomers using multidimensional gas chromatography mass spectrometry (SBSE–TD-Enantio-MDGC–MS) [111], monitoring monoterpenes and norisoprenoids in raspberry fruits [112]. It was also used to monitor profiles of volatiles in transgenic raspberries [113]. A very interesting from the flavor point of view, application of SBSE is the

19

buccal odor screening system (BOS) [114]. This approach is based on the use of PDMS stir bar closed in a glass capsule for intraoral sampling of volatile compounds, which normally are perceived by human olfactory system retronasally (from the oral cavity). The authors found out that even the short extraction time of 5 min provides sufficient extraction degree and sensitivity to monitor after-odors which occur after consumption of food. They checked the usefulness of the system with GC–O detection and GC–MS, and also noted that there are no hazards related to metal ions or nonvolatiles migrating from PDMS into saliva. They pointed out the potential application of SBSE used for intraoral in vivo sampling for the characterization of after-odors, as well as investigation of the matrix effect of food on the release of volatiles during food mastication. SBSE was also employed as extraction mode for the gas chromatography–olfactometry (GC–O) in single dimensional or two-dimensional (heart cutting) systems [115]. The same authors used SBSE in 1D and 2D GC/MS systems with preparative fraction collector to analyze wine off-odorants (TCA, geosmin and 2-isobutyl-3-methoxy pyrazine) in a low ng L−1 levels [116]. SBSE can be used for both direct extraction and the extraction from headspace. The latter approach called HSSE [117–119] eliminates interfering nonvolatile compounds that can be adsorbed by SBSE, although PDMS used for absorption on the stir bar has no affinity for pigments or organic acids. The advantage of SBSE is a particularly high sensitivity for the semi volatiles. Buettner analyzed the volatile odor active compounds in small samples of human milk (5 mL) using both headspace SBSE and direct extraction of milk performed for one hour. The headspace profile milk (HS-SBSE) consisted of 22 compounds, whereas in direct extraction additional 25 less volatile compounds were detected [119]. Contrary to SPME, where the number of fiber coating flourished since its invention from PDMS and PA to numerous coatings involving adsorption and absorption mechanisms, SBSE suffered for a long time a flaw of offering only one coating: PDMS. This, to certain extent limited the selectivity of SBSE i.e. for very volatile compounds (C1–C4), for extraction of which SPME Carboxen–PDMS fibers were developed, or for extraction of polar analytes for which SPME CW or PA perform better than PDMS. Analysis of ultratraces of polar compounds using PDMS is difficult, therefore derivatization is sometimes used when feasible to increase log P values. Dual phase twisters for SBSE, which used Carbopack B, Carbopack C, Carbosieve G and Carboxen 1000 packed inside a PDMS tube were used by Bicchi et al. [120]. They observed the higher concentration factors in dual phase twisters when Carbopack B was used as the adsorbent. The differences were less pronounced when stir bar with higher thickness of PDMS was compared. Remaining tested carbons were generally inferior in performance compared to both Carbopack B, but also to PDMS conventional twisters of 0.5 and 1 mm thickness. 3.3. Other microextraction techniques based on sorbents Both SPME and SBSE use sorbent material on the outer surface of optical fiber, steel rod (SPME) or a magnet (SBSE). In recent years there have been several techniques developed that use sorbent material placed in flow-through devices, such as inside needle capillary adsorption trapping (INCAT), open tubular trapping (OTT), in-tube SPME. Solvent free microextraction techniques used in gas chromatography have been summarized recently in a review [32]. Authors discuss apart from SPME and SBSE also HSSE (high capacity headspace sorptive extraction), which is in its most popular form synonymous with headspace SBSE (HS-SBSE) and enables headspace extraction of volatiles using either stir bars, or coated glass rods. They discuss also rod extraction where a rod made of PDMS several cm long is used to extract analytes from a liquid phase. Other two techniques (SPDE and ITEX) are similar in mode of operation: SPDE (solid phase dynamic extraction) uses a

20

Table 2 Microextraction methods other than SPME used in flavor compounds analysis based on 77 publications on LLME, SBSE, MEPS and related techniques in Web of Knowledge published in 2006–2011. Method

Analytes

Extraction time (min)

LOD

LOQ

Reference

wine Red wines

HS-SBSE

60

n.d.

n.d.

[109]

African different wines

SBSE

Acids, esters, carbonyls, phenols, alcohols, terpenes, lactones Acids, esters, phenols, alcohols, aldehydes, terpenes, lactones

(ng L−1 ): acids: 1.25–44.3; esters: 0.19–128, phenols: 1.2–25.6; alcohols: 1.75–98; aldehydes: 0.18–1.36; terpenes: 36.2; lactones: 33.6–47.1

[152]

Different wines

SBSE

Esters, alcohols, terpenes, norisoprenoids

60

SBSE

Esters, alcohols, terpenes, norisoprenoids

60

Pinot noir

SBSE

Esters, phenolic compounds, terpenes, alcohols, norisoprenoids

720

Merlot

SBSE

120

n.d.

Red wines Bordeaux

DLLME SBSE

Esters, alcohols, terpenes, lactones, norisoprenoids Phenolic compounds Phenolic compounds, haloanisoles, geosmin, 2-methylisoborneol

(␮g L−1 ): esters: 2.11; alcohols: 7.36–537; terpenes: 0.27–30.3; norisoprenoids: 6.02 (␮g L−1 ): esters: 0.2–0.7; alcohols: 24.9–1388.2; terpenes: 0.6–44.8; norisoprenoids: 10.8–10.9 (␮g L−1 ): esters: 0.8–5.14; phenols: 0.88; terpenes: 0.84–1.06; alcohols: 146–174, norisoprenoids: 0.1–1.04 n.d.

[107]

Sparkling wines

(ng L−1 ): acids: 0.38–13.3; esters: 0.06–38.2; phenols: 0.36–7.68; alcohols: 0.53–281; aldehydes: 0.05–0.41; terpenes: 10.9; lactones: 10.1–14.1 (␮g L−1 ): esters: 0.63; alcohols: 2.21–161; terpenes: 0.05–9.09; norisoprenoids: 1.81 (␮g L−1 ): esters: 0.05–0.2; alcohols: 7.5–416.5; terpenes: 0.2–13.4; norisoprenoids: 3.2–3.3 n.d.

nc 60

DLLME DLLME DLLME IL-SDME MEPS HS-SDME HS-SDME SBSE USAEME SBSE

Phenolic compounds, haloanisoles Haloanisoles, phenolic compounds Haloanisoles Haloanisoles Haloanisoles Haloanisoles Haloanisoles Haloanisoles Haloanisoles Acids, esters, aldehydes, alcohols, ketones, terpenes, sulfur compounds, norisoprenoids

nc nc nc 30 5 25 35 60 5 120

95–147 ␮g L−1 0.9–1.1 ␮g L−1 (phenols) 0.4–0.9 ng L−1 (haloanisoles) geosmin: 11 ng L−1 ; MIB: 2.5 ng L−1 n.d. 7.3–17.7 ng L−1 n.d. 0.66 ng L−1 n.d. n.d. n.d. Quanta n.d. n.d.

[144] [104]

Red wines Red wines Red, white wines Different wines Red wines Synthetic, red wine Different wines Different wine Different wine Model wine

Chardonnay Different wine Fruits and vegetables Blackberry

USAEME USADLLME

Sulfur compounds Geosmin, MIB

1 3

28–44 ␮g L−1 0.3 ␮g L−1 (phenols) 0.1–0.3 ng L−1 (haloanisoles) geosmin: 3.3 ng L−1 ; MIB: 0.8 ng L−1 0.004–0.108 ng mL−1 2.2–5.3 ng L−1 0.005–0.075 ␮g L−1 0.2 ng L−1 0.22–0.75 ng L−1 6.1–8.1 ng L−1 0.01 ng L−1 – 0.6–0.7 ng L−1 (␮g L−1 ): acids: 0.017–275; ester: 0.008–8.5; aldehydes: 0.07–17; alcohols: 0.066–136, ketones: 0.26–1.1; terpenes: 0.009–0.54, sulfur compounds: 0.5; norisoprenoids: 0.016–0.017 0.36–1.67 ng mL−1 Geosmin: 2 ng L−1 ; MIB: 9 ng L−1

0.63–3.02 ng mL−1 n.d.

[158] [157]

SBSE

120

n.d.

Quanta

[103]

Grapes

SBSE

60

n.d.

n.d.

[110]

Grapes

SBSE

Acids, esters, ketones, alcohols, aldehydes, terpenes, lactones, norisoprenoids, furanones and furans Acids, esters, terpenes, sulfur compounds, furanones, carbonyls, alcohols Terpenes

30

n.d.

n.d.

[163]

[106]

[153]

[108]

[155] [145] [156] [134] [162] [133] [135] [116] [160] [154]

H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

Matrix

Table 2 (Continued) Method

Analytes

Extraction time (min)

LOD

LOQ

Reference

Fruits Melon

SDME LLME

20 60

0.6–164 ng mL−1 n.d.

n.d. n.d.

[165] [166]

Apricot

LLME

60

n.d.

n.d.

[167]

Raspberry

SBSE

60

n.d.

n.d.

[113]

Raspberry Apples Peaches

SBSE SBSE SBSE

30 60 60

n.d. n.d. n.d.

n.d. n.d. n.d.

[112] [164] [153]

Strawberries Cucumber

SBSE SDME

Acids Esters, ketones, alcohols, aldehydes, terpenes, sulfur compounds, lactones Esters, ketones, alcohols, aldehydes, terpenes, lactones Esters, alcohols, aldehydes, terpenes, ketones, lactones, norisoprenoids Terpenes Esters, alcohols, aldehydes Alcohols, aldehydes, lactones, norisoprenoids Terpenes Aldehydes

30 20

n.d. 0.02 mg kg−1 (2-nonenal); 0.01 mg kg−1 (2,6-nonadienal)

n.d. n.d.

[111] [136]

HD–SME HD-HSME HD–HSME SFME-HSSDME HS-SDME

Alcohols, aldehydes, terpenes Terpenes Terpenes Terpenes

9 3.5 2.5 7

n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d.

[168] [169] [170] [171]

Terpenes

7

n.d.

n.d.

[172]

SBSE

Acids, esters, ketones, phenolic compounds, alcohols, aldehydes, terpenes, sulfur compounds, norisoprenoides Acids, esters, ketones, alcohols, aldehydes, terpenes, sulfur compounds, norisoprenoides Acids, alcohols, terpenes

120

n.d.

n.d.

[183]

120

0.035–286 ␮g L−1

n.d.

[154]

30

n.d.

n.d.

[184]

HSME UNE–HS-SDME UNE-HGFT-HSSDME HSSE-dual phase MD–HS-SDME HD-SHLPME SHD-SHLPME SDME HD-HSME UNE-HS-SDME HS-HD-LPME

Alcohols, terpenes Alcohols, aldehydes, terpenes Terpenes

20 5 10

n.d. 6.67–14.8 pL L−1 n.d.

n.d. n.d. n.d.

[179] [176] [178]

Sage leaf volatiles

60

n.d.

n.d.

[182]

Acids, alcohols, aldehydes, terpenes Ketones, alcohols, heterocyclic, terpenes Terpenes Terpenes Terpenes Terpenes

4 4

n.d. n.d.

n.d. n.d.

[175] [173]

5 5 10 60

n.d. 0.23–1.87 mg L−1 n.d. 1.5–3.2 ng

n.d. n.d. n.d. n.d.

[180] [174] [177] [138]

SBSE SBSE

Acids Acids, esters, alcohols, aldehydes, heterocyclic, terpenes, furanones and furans Sulfur compounds

60 60

n.d. n.d.

n.d. n.d.

[97] [102]

5

0.2–1.9 ng mL−1 (HS) 10.7–57.1 ng mL−1 (direct)

n.d.

[181]

Essential oils Artemisia Anise Foeniculum Eugenia caryophyllata Cuminum and syzygium Juices Grape

Model

SBSE

Orange Spices and herbs Curcuma Cuminum Zanthoxylum

HSME

Coffee, sage leaves Chinese herbs Artemisia Cinnamon, thyme, oregano Artemisia Cuminum Clove buds Beer

HS-SDME Direct SDME

H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

Matrix

21

22

Table 2 (Continued) Matrix

Method

Analytes

Extraction time (min)

LOD

LOQ

Reference

SBSE

Acids, esters, alcohols, aldehydes, terpenes, norisoprenoids

100

[100]

SBSE

Acids, esters, alcohols, aldehydes, terpenes, norisoprenoides

100

SDME SBSE HSSE

Aldehydes Phenolic compounds, haloanisoles

5 60 (SBSE) 25 (HSSE)

(␮g L−1 ): acids: 24.7–166; esters: 0.335–720; alcohols: 6.75–821; aldehydes: 64.5; terpenes: 2–68.7; norisoprenoides: 2.39 (␮g L−1 ): acids: 24.7–166; esters: 0.335–720; alcohols: 6.75–821; aldehydes: 64.5; terpenes: 2–68.7; norisoprenoides: 2.39 0.58–330 ␮g L−1 n.d.

[185] [186]

n.d.

[187]

Spirits

Geosmin, MIB

10

Miscellaneous Soy sauce

SBSE

90

n.d.

n.d.

[188]

Plants Liquid matrix Lemon oil Lamb ham

UAE–DLLME SBSE SBSE HSSE

10 60 60 60

0.2–29 ng mL−1 0.01–0.71 ng L−1 n.d. n.d.

1–285 ng mL−1 0.01–1.27 ng L−1 n.d. n.d.

[161] [105] [115] [189]

Human milk

SBSE, HS-SBSE

60

n.d.

n.d.

[119]

Buckwheat Coffee

HSSE HSSE-dual phase HS-SDME

Acids, esters, ketones, phenolic compounds, alcohols, aldehydes, heterocyclic, sulfur compounds, furanones Terpenes Terpenes Terpenes Acids, esters, ketones, alcohols, aldehydes, terpenes Acids, carbonyls, phenols, heterocycles, terpenes, sulfur compounds, lactones, norisoprenoids Aldehydes Acids, phenols, alcohols, aldehydes, heterocyclic compounds Aldehydes

30 60

n.d. n.d.

n.d. n.d.

[191] [182]

7

4–20 ng mL−1

12–59 ng mL−1

[190]

Oils a

Quant – quantitative method, LOD or LOQ not provided.

[101]

H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

HS-LPME

(␮g L−1 ): acids: 7.41–49.8; esters: 0.101–216; alcohols: 2.02–246; aldehydes: 19.9; terpenes: 0.6–20.6; norisoprenoides: 0.71 (␮g L−1 ): acids: 7.41–49.8; esters: 0.101–216; alcohols: 2.02–246; aldehydes: 19.3; terpenes: 0.6–20.6; norisoprenoides: 0.71 0.29–160 ␮g L−1 SBSE (␮g L−1 ): phenols: 0.002–0.065; haloanisoles: 0.002–0.016 HSSE (␮g L−1 ): phenols: 0.003–0.174; haloanisoles: 0.005–0.026 (ng L−1 ): geosmin: 1.1; MIB: 1.0

H.H. Jele´ n et al. / Analytica Chimica Acta 738 (2012) 13–26

coating inside the needle, whereas ITEX (in tube extraction device) has a sorbent material packing (usual Tenax) inside a wider part of needle [121]. This part has its own heating coil, so desorption is not made using injection port heater, but using this outer device. Extraction in both methods is performed by multiple pumping of the headspace from a vial through sorbent. Both techniques are automated. Another technique that starts to be used in food flavor analysis is MEPS (microextraction by packed sorbent) where MEPS cartridges were designed as a miniature SPE devices capable of handling small sample volumes of 10–250 ␮L [122]. Extraction using needle traps can be exhaustive technique, and thus complements non exhaustive techniques such as SPME. A theory and applications of needle trap devices has been recently summarized by Lord et al. [123]. 3.4. Liquid phase microextraction (LPME) Extraction of analytes from aqueous matrices and headspace with a minimal amount of solvent started with a work of Liu and Dasgupta [124], Jeannot and Cantwell [125] and He and Lee [126]. They noticed that single droplet of solvent can be used for effective extraction of compounds form matrix. After initial use of polymer rod to which the solvent drop adhered, GC syringe became a tool which enabled withdrawal of the droplet into syringe needle and subsequent injection into GC. Liquid phase microextraction (solvent microextraction, SME) term describes LLE with a minimized solvent volume (acceptor phase – water immiscible solvent) used to extract analytes from aqueous solution (donor phase). LPME is usually divided into three approaches: (i) single drop microextraction (SDME), (ii) hollow fiber protected microextraction (HF-LPME) and, (iii) dispersive liquid–liquid microextraction (DLLME) [127]. Since its invention liquid phase microextraction in its various forms has been a subject of about 800 papers and an excellent starting point into these methods is a recent monography by Kokosa, Przyjazny and Jeannot, which provides theoretical fundamentals, method development hints as well as an overview of applications [29] There are also several recent review papers referring to various approaches in liquid phase microextraction: principles [127], single drop microextraction [128], hollow fiber membrane liquid phase microextraction [129]. There are similarities between solvent microextraction and solid phase microextraction where the solvent drop acts similarly to SPME absorbent covering a fiber. Single drop microextraction (SDME) usually uses a drop of 1–3 ␮L of organic solvent at the tip of a syringe needle, so it can be withdrawn inside the barrel after the extraction process and injected into a GC injection port. Similarly to SPME, SDME is used for direct extraction (DI-SDME, direct immersion SDME) and extraction from headspace (HS-SDME). For direct immersion usually an immiscible organic solvent is used to extract relatively nonpolar or completely nonpolar compounds from aqueous phase, for HS-SDME solvents of different polarities can be used. The advantage of both methods is their simplicity. For DI-SDME the main disadvantage is related to the instability of solvent droplet at the tip of the syringe, especially during stirring at high speeds. Extraction using a single drop from headspace is more suitable for volatile/aroma compounds isolation from food. In recent years an increased interest among researchers was the application of ionic liquids as extractants for SDME (and also for SPME). The negligible volatility of ionic liquids make them incompatible for direct coupling with GC in SDME applications, however by developing special interfaces, or retracting ionic liquid droplet after desorption make such analyses possible [130]. HS-SDME was introduced in

23

2001 by Jeannot and co-workers [131]. Mass transfer in headspace is a rapid process due to the large diffusion coefficients in the gas phase compared to condensed phase, which can be as much as several thousand times. With the aid of stirring the sample and thus improving kinetics of extraction the thermodynamic equilibrium between aqueous and vapor phases can be reached rapidly. The additional benefit of HS-SDME is elimination of the nonvolatile compounds, which could be co-extracted using direct extraction mode. This is of crucial importance in flavor compounds isolation from such matrices as food. An interesting variation of extraction of analytes using a drop of solvent is an approach presented by He and Lee (dynamic LPME) who proposed extraction of analytes from aqueous solution by the thin film of organic solvent present in the syringe barrel walls during plunger movement [126]. With the similar amount of solvent used, dynamic LPME offers better enrichment than the static method. In HS-SDME the choice of solvents that can be used somehow provides the selectivity of extraction, however solvents must have a low vapor pressure and the properties of matrix, especially at elevated temperatures, has to be considered. The example can be water that causes swelling of the droplet of polar solvent used for extraction. Solvent microextraction based on microdroplets can be also performed as directly suspended droplet microextraction (DSDME) [132], which is based on the extraction of compounds into a water immiscible solvent droplet added to the surface of aqueous solution. Most applications of single drop microextraction for food volatiles/flavor compounds refer to headspace extraction. However, contrary to SPME the number of publications utilizing this method is not impressive (Table 2). One of the most explored area in the analysis of off-flavors and taints is the analysis of haloanisoles, mainly 2,4,6-trichloroanisole in wine. The one reason is the frequency of occurrence of “cork taint” in wines, which is the predominant wine flavor defect. The other reason is the low odor threshold of this (and related compounds) in wine (in low ng L−1 ) which makes the quantification of TCA at these levels a challenging task from the analytical point of view. Single drop microextraction using 1-octanol was used for determination of TCA and TBA in wine by Martendal et al. [133] obtaining a detection limit of 8.1 and 6.1 ng L−1 , respectively (GC–ECD). Impressive detection limits for TCA were obtained by Valcarcel and co-workers, who used ionic liquids as extracting solvents for SDE and combining this extraction method with ion mobility spectrometry. Ionic liquid 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [Hmim][NTf2 ] used as HS-SDME extractant after wine sample precleaning using Lichrolut EN SPE allowed to achieve LOD of 0.1 ng L−1 . Portable ion mobility mass spectrometer was used for detection [134]. Using the same ionic liquid for extraction of TCA from wine and multicapillary column as a pre-separation tool for ion mobility portable spectrometer the authors achieved LOD for TCA of 0.01 ng L−1 , comparable only to SBSE–GC–MS–MS [135]. Single drop microextraction (1-pentanol) was used also for the analysis of volatile aldehydes responsible for cucumber aroma ((E)-2-nonenal, (E,Z)-2,6-nonadienal) [136], for linalool in evening primrose flowers (hexadecane as extractant) [137], or flavors from clove buds (1-octanol) [138]. It was also used for the determination of alcohols in beer using octanol and ethylene glycols as extractants [139,140]. Apart from directly suspended droplet microextraction, dispertive liquid–liquid microextraction (DLLME) has been described by Rezaee et al. [141]. In his method acceptor to donor phase is greatly reduced. Small volume (microliters) of extraction solvent (extractant, high density) mixed with water miscible dispersive solvent (usually acetonitrile, acetone, methanol) form tiny droplets (cloud) in aqueous sample, which provides a vast interphase contact and accelerates the mass transfer of analytes. As extractants usually carbon tetrachloride, tetrachloroethylene, 1-dodecanol and hexadecane are used. Extractant represents only 1–3% of the

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extraction mixture. Centrifugation provides separation of phases for subsequent analysis. Methods based on a droplet extraction have been used in relatively simple aqueous matrices [142], which limits their use in the analysis of food flavors. DLLME has been used mainly for the determination of metal ions, phthalates, PAHs, drug residues, chlorophenols. It offers high enrichment factors within short extraction times (∼600–1000 for PAH in water, [141]). The combination of solid phase extraction followed by DLLME was described for the isolation of trace amounts of chlorophenols from aqueous samples. Such approach can lead to extremely high enrichment factor (∼18,000) and can be used for relatively complex aqueous samples [143]. The basic benefits of DLLME for eventual use in aroma compounds analysis are very low LODs (in ng L−1 ), as well as short extraction times (few minutes). It makes perspectives for its use in aqueous foods with the careful estimation of matrix effects. DLLME was used also to extract volatile phenols from wine contaminated by Brettanomyces yeasts, where the extraction was completed in 6 min. To avoid coextraction of phenolic acids pH of wine was adjusted to basic (pH 8) [144]. DLLME was also used for the extraction of halophenols and haloanisoles in wine and detected using ECD. The extraction was made into carbon tetrachloride, acetone as a disperser and acetic anhydride as a derivatization agent [145]. Another mode of liquid phase microextraction was developed by Pedersen-Bjergaard and Rasmussen – hollow fiber (HF) LPME [146]. To overcome the fragility of droplet of organic solvent used in single drop microextraction they used a hollow membrane (HF) to stabilize the extracting phase. Organic solvent immobilized in the wall pores of HF provides a supported liquid membrane (SLM). For extraction of analyte from aqueous solutions porous hollow fiber is first immersed in organic solvent immiscible with water, to immobilize it in the pores of HF and then the lumen of the hollow fiber is filled either with the same organic solvent (two phase systems) or with aqueous acceptor phase (three phase systems). The latter mode is limited to analytes with ionizable functionalities. Solvent impregnation of the fiber is essential as the extraction occurs on the surface of the immobilized solvent and the extractant should be similar in polarity to the fiber to facilitate easy immobilization within hollow fiber pores. To improve the ease of operation fully automated HF-LPME using CTC autosampler was described [147]. The application fields of HF-LPME are mainly bioanalytical and environmental ones [129], whereas in the field of food analysis there are only few applications related mainly to the contaminants/pesticides analysis. Mainly due to the nature of volatile/flavor compounds HF-LPME did not find much interest in this field, despite one paper targeted at monitoring essential oils in active food packagings that were analyzed using automated, dynamic two phase HF-LPME [148].

4. Trends in the use of microextraction techniques for flavor analysis. A conclusion Microextraction methods available to analytical chemist find their applications in the field of flavor analysis in a varying proportions. Table 1, which summarizes the most cited and the newest publications on SPME in flavor analysis, reflects main fields of application of this technique. It shows the versatility of SPME for different matrices sampling, however the vast majority of applications utilize SPME as a quantitative or semi-quantative methods. It is caused by the use of SPME for monitoring technological processes using volatiles, where peak areas comparison is often sufficient to detect changes. Headspace SPME, because of matrix complexity is almost exclusively used in flavor research. Relatively seldom multiple extraction headspace SPME (MHS-SPME) is used usually for compounds present in trace concentrations [92,149]. An important

group of applications are off-flavors. The character of compounds causing taints and off-flavors, variety of sources and matrices they are present [150] predestine them for SPME sampling. Reviews [151,152] summarize the use of SPME and also other techniques in this field of applications. SPME proved its suitability as a quantitative method providing satisfactory limits of detection and method parameters for the most demanding applications in detection of off-flavors. Contrary to Table 1 where only a small part of selected applications on SPME could be presented, in Table 2, majority of published papers using microextraction methods other than SPME have been included. When food matrices are examined it can be seen that wine attracts the highest interest (as in SPME). Dominating method is SBSE, which is used for esters, alcohols, terpenes, norisoprenoids analysis [106,107,152,153], and also sulfur compounds [154] volatile phenols, haloanisoles causing off-flavors in wine [104]. Haloanisoles and phenolic compounds causing “corky” and “Brett” taints in wine are probably the most thoroughly explored group of food off-flavors. Other microextraction methods are used for these purposes less frequently. Dispersive liquid–liquid microextraction (DLLME) was used for volatile phenols from wines [144] or for phenols and chloroanisoles [145,155,156]. Taking into account the character of phenols, chlorophenols and chloroanisols DLLME seems to be a very good method for their analysis in beverages. Due to the lack of automated versions of SDME and LLME, and also due to their lower popularity in the scientific community (compared to SPME and SBSE) their use in flavor analysis is not enough explored. Also more sophisticated methods have been developed: ultrasound assisted dispersive liquid microextraction (USADLLM) was also used for analysis of other trace off-odorants in wine – geosmin and 2-methylisoborneol [157]. A very interesting application of ultrasound assisted emulsification DLLM (USADLLM) was elaborated for the quantification of sulfur compounds (methyltioesters, alcohols and ketones) which have extremely low odor thresholds, in Chardonnay wines [158]. The method can be competitive to the traditional detrmination of thiols in wine using SPE or binding thiols using hydroxymercuribenzoate (pHMB) [159]. Similarly low detection limits were attained using USAEME for haloanisoles and terpenes [160,161]. The only application of MEPS in this review was also used for haloanisoles in wine [162]. Apart from wine microextraction methods other than SPME have been used in the analysis of fruits and vegetables. Also in this group SBSE dominates [103,110–113,153,163,164], although single drop microextraction (SDME) [165]/liquid–liquid microextraction (LLME) is used [166,167]. Profiling volatiles is the most frequently use of these methods in fruit. Methods described in Table 2 were developed for the analysis of terpenes in essential oils [168–172] and spices and herbs, where they form the most important group of compounds. For the analysis of herbs and spices authors develop usually a hyphenated approach that would provide a profile of volatile compounds similar to profile after hydrodistillation, regarded as standard in essential oil analyses. These methods combine simultaneous hydrodistillation with (static headspace) liquid phase microextraction (SHD-SHLPME), where compounds obtained in the hydrodistillation process are adsorbed in a solvent drop [173,174] or microwave distillation with single drop microextraction (MDHSSDME) [175]. Another example of a multitechnique approach for analysis of terpenes is the use of ultrasonic nebulization in conjunction with single drop microextraction [176–178]. Also headspace solvent microextraction (HSME) [179], single drop microextraction [180,181], and headspace hanging drop liquid phase microextraction (HS-HD-LPME) [138] methods are used for the analysis of mostly terpenes in spices and herbs. Concluding above applications liquid phase microextraction methods are foremost methods

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used for this type of analyses providing profiles more resembling hydrodistillates, although SBSE or related methods are also used [182]. Microextraction methods (SBSE and LPME) were also used for the analysis of flavor compounds in juices [154,183,184] and spirits [100,101,185–187]. SBSE and LLME have been used in analysis of flavor compounds in soy sauce [188], lamb ham [189], coffee [182], oils [190] and buckwheat [191]. The diversity of matrices for which microextraction methods other than SPME are used proves that these methods await broader applications in flavor analysis. To summarize current status of microextraction methods in flavor compounds analysis, the leading position of SPME is undisputable, however more impact on quantitative analysis would exploit all the advantages of this technique. Together with SBSE solid phase microextraction methods are the most popular ones, mainly due to their simplicity and possibilities of automation. Operational problems related to other microextraction methods, especially single drop microextraction, lack of automation possibilities result in far less applications in the field of flavor analysis. However, taking into account the potential of methods, especially those discussed in the last paragraph, they should be far more popular in the analysis of flavor compounds, especially in target analysis of off-odors and taints and analysis of essential oils. Acknowledgement Polish Ministry of Science and Higher Education is acknowledge for financial support within a project N N312 215538. References [1] M.C. Boyce, E.E. Spickett, Food Aust. 54 (2002) 350–356. [2] E.E. Stashenko, J.R. Martinez, J. Biochem. Biophys. Meth. 70 (2007) 235–242. [3] A. Verzera, C. Condurso, in: J.K. Lang (Ed.), Handbook on Mass Spectrometry: Instrumentation, Data and Analysis, and Application, Nova Science Publishers, Inc., Hauppauge, NY, USA, 2009, pp. 345–370. [4] W. Wardencki, M. Michulec, J. Curylo, Int. J. Food Sci. Technol. 39 (2004) 703–717. [5] A. Nongonierma, P. Cayot, J.L. Le Quere, M. Springett, A. Voilley, Food Rev. Int. 22 (2006) 51–94. [6] N.H. Snow, Trends Anal. Chem. 21 (2002) 608–617. [7] A. Chaintreau, Flavour Fragr. J. 16 (2001) 136–148. [8] C. Bicchi, C. Cagliero, P. Rubiolo, Flavour Fragr. J. 26 (2011) 321–325. [9] S. Ampuero, J.O. Bosset, Sensor Actuator 94 (2003) 1–12. [10] B.D. Zellner, P. Dugo, G. Dugo, L. Mondello, J. Chromatogr. A 1186 (2008) 123–143. [11] W. Grosch, Chem. Senses 26 (2001) 533–545. [12] P. Schieberle, T. Hofmann, in: H. Jelen´ (Ed.), Food Flavors. Chemical, Sensory and Technological Properties, CRC Press, Boca Raton, FL, 2012, pp. 413–436. [13] S.M. van Ruth, Biomol. Eng. 17 (2001) 121–128. [14] W. Engel, W. Bahr, P. Schieberle, Eur. Food Res. Technol. 209 (1999) 237–241. [15] W. Grosch, Trends Food Sci. Technol. 4 (1993) 68–73. [16] T. Acree, J. Barnard, D.G. Cunningham, Food Chem. 14 (1984) 273–286. [17] P. Schieberle, M. Steinhaus, Gas chromatography–olfactometry, in: J.V. Leland, P. Schieberle, A. Buettner, T.E. Acree (Eds.), The State of Art. ACS Symposium Series 782, American Chemical Society, Washington, DC, 2001, pp. 23–33. [18] D.D. Roberts, A.J. Taylor, Flavor release, in: ACS Symposium Series 763, American Chemical Society, Washington, DC, 1999. [19] E. Guichard, Food Rev. Int. 18 (2002) 49–70. [20] P. Naknean, M. Meenune, Int. Food Res. J. 17 (2010) 23–34. [21] E.O. Afoakwa, A. Paterson, M. Fowler, A. Ryan, Food Chem. 113 (2009) 208–215. [22] C. Arancibia, L. Jublot, E. Costell, S. Bayarri, Food Res. Int. 44 (2011) 1632–1641. [23] Y. Merabtine, S. Lubbers, I. Andriot, A. Tromelina, E. Guichard, J. Sci. Food Agric. 90 (2010) 1403–1409. [24] R.J. McGorrin, in: R.J. McGorrin, J.V. Leland (Eds.), ACS Symposium Series 633, American Chemical Society, Washington, DC, 1996, pp. IX–XII. [25] J. Solms, F. Osman-Isamail, M. Beyeler, J. Can. Inst. Food Sci. Technol. 6 (1973) A10–A16. [26] M. Le Thanh, P. Thibeaudeau, M.A. Thibaut, A. Voilley, Food Chem. 43 (1992) 129–135. [27] J. Bakker, in: A.G. Gaonkar (Ed.), Ingredients Interactions: Effects on Food Quality, Dekker, New York, 1995, pp. 411–439. [28] G. Piraprez, M.-F. Hérent, S. Collin, Food Chem. 61 (1998) 119–125. [29] J.M. Kokosa, A. Przyjazny, M.A. Jeannot, Solvent Microextraction. Theory and Practice, John Wiley & Sons, Hoboken, NJ, 2009.

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