Applications of solid-phase microextraction in food analysis

Accepted Manuscript Title: Applications of solid-phase microextraction in food analysis Author: Chang-Hua Xu, Guo-Sheng Chen, Zhen-Hai Xiong, Yu-Xia Fan, XiChang Wang, Yuan Liu PII: DOI: Reference:

S0165-9936(16)30013-9 http://dx.doi.org/doi: 10.1016/j.trac.2016.02.022 TRAC 14685

To appear in:

Trends in Analytical Chemistry

Please cite this article as: Chang-Hua Xu, Guo-Sheng Chen, Zhen-Hai Xiong, Yu-Xia Fan, XiChang Wang, Yuan Liu, Applications of solid-phase microextraction in food analysis, Trends in Analytical Chemistry (2016), http://dx.doi.org/doi: 10.1016/j.trac.2016.02.022. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Applications of solid-phase microextraction in food analysis

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Chang-Hua Xua , Guo-Sheng Chenb‡, Zhen-Hai Xionga, Yu-Xia Fana, Xi-Chang Wanga, Yuan Liua,* a College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, PR China b MOE Key Laboratory of Aquatic Product Safety/KLGHEI of Environment and Energy Chemistry, School of Chemistry and Chemical Engineering, Sun Yat-sen University, Guangzhou 510275, PR China

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‡

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These authors contributed equally to this work.

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Highlights

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 An updated summary of SPME fiber coatings and quantification in is provided.

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 SPME analyses of volatile flavors and off-flavors in diverse food matrices are reviewed.

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 SPME analyses of different categories of non-volatile compounds in foods are expounded.

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 Future perspectives of SPME in food analysis are discussed.

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Abstract

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Solid-phase microextraction (SPME), a solvent-free extraction technique, is an effective, cost-saving, versatile, and easily automated assay for high sample throughput. This paper reviews the application of solid-phase microextraction (SPME) for the analysis of flavors/off-flavors in wine, fruits, meats, cereal products and non-volatile compounds such as pesticides, pharmaceuticals and personal care products, endogenous substances and other contaminants in food samples. The future developments and potential applications of SPME methods in food analysis was looked ahead. Keywords: SPME; Food; Progress; Volatiles; Non-volatiles; Contaminants

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Content

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1. Introduction .................................................................................................................................. 2 2. Solid-phase microextraction ......................................................................................................... 3 2.1. SPME-fiber coating ............................................................................................................. 3 2.2. SPME quantification in food analysis ................................................................................. 4 3. Applications of SPME for food analysis ......................................................................................... 4 3.1 Volatile compounds of food ................................................................................................ 4 3.1.1. Flavors ..................................................................................................................... 4 3.1.2. Off-flavors.............................................................................................................. 13 3.2 Non-volatile compounds of food ...................................................................................... 14 3.2.1. Pesticides and other agrochemicals ...................................................................... 14 3.2.2. Pharmaceuticals and personal care products ....................................................... 18 * Corresponding author. [email protected] 1

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3.2.3. Endogenous substances ........................................................................................ 21 3.2.4. Other contaminants .............................................................................................. 21 4. Conclusions and perspectives ..................................................................................................... 22 Acknowledgements ......................................................................................................................... 23 References....................................................................................................................................... 23

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1. Introduction

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Sample preparation, which is mainly used for analyte enrichment and removal of interfering matrix components, is the critical step in separation science and plays an important role in analytical chemistry. However, sample preparation process is usually tedious and needs to consume large organic solvent. Developing a green sample preparation technique with high efficiency and simple operation process is the most important research and developmental frontier in modern separation science. One of the most significant developments in sample preparation has been, without doubt, solid phase microextraction (SPME), a technique first described by Arthur and Pawliszyn in 1990 [1]. SPME is a solvent-free sample preparation technique and combines sampling, analyte isolation, and enrichment into one step. In this approach, microquantities of the solid sorbent or liquid polymer in appropriate format are exposed to the sample. Quantification is based on the amount of analyte extracted at appropriate conditions [2]. Since its convenience and speed, SPME was implemented by researchers worldwide in food and drugs analysis, clinical chemistry, biochemistry, forensic medicine and other fields. Food analyses are important for the evaluation of nutritional value, the quality control of fresh and processed products, and the monitoring of food additives and other toxic contaminants. For example, flavor, being a combination of taste and olfaction, is a crucial factor in consumer acceptance of foods [3]. However, food samples are very complex, often containing proteins, fat, salts, acids, bases, and numerous food additives with different chemical properties. A large number of analytical tools, especially chromatography, have been used to analyze the constituents of food in order to control their quality. Beyond that, considering the complex constituents in food samples, a novel sample preparation with enhanced efficiency and highly selective extraction is needed to apply in pretreating food matrices. With increasing applications in food samples, SPME plays an important role in food sample pretreatments. Compared to traditional extraction technology such as Head Space technique (HS), Nitrogen Purge and Trap method (NPT), Solid Phase Extraction method (SPE), Continuous Steam Distillation Extraction method (SDE), and Supercritical Fluid Extraction method (SFE), SPME has a serial of aforementioned advantages. Moreover, owing to its unique format and miniature device design, SPME is feasible to couple with gas chromatograph (GC), high performance liquid chromatography (HPLC) and capillary electrophoresis (CE), etc. and capable of full automation. Therefore, it is feasible to realize fast and high-throughput test in food sample. In this article, we review the application of SPME in food analysis, which makes the whole analysis process more selective, more sensitive and more environment friendly. These studies include volatile, semi-volatile and non-volatile organic compounds determination in diverse food samples (wine, juice, fruits, meats, cereal products, other edible plants and animals). Emphasis is placed on brief descriptions of the unique capabilities and advantages of SPME and recently 2

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researches have been focused on using different modern SPME technique to improve absorption and extraction for a variety of analytes. Finally, we look ahead to future developments and potential applications of SPME methods in food analysis.

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2. Solid-phase microextraction

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Solid-phase microextraction is based on the partitioning of the analyte between the extracting phase immobilized on a fused-silica fiber or inner coating and the matrix (air, water, etc.). After equilibrium is reached or a well-defined time, the absorbed compounds are thermally desorbed by exposing the fiber into the injection port of a GC or redissolved in an organic solvent for further HPLC,GC or CE analysis.

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2.1. SPME-fiber coating

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SPME is an advanced sample pretreatment technique integrating sampling, extraction, concentration and sample introduction into a single solvent-free step. The major advantages of SPME are its easy miniaturization, automation of devices, and its convenience in coupling with chromatographic instruments. The facilitation of high-quality analytical methods based on SPME technique requires optimization of the parameters that affect the extraction efficiency, such as extraction-phase chemistry, extraction mode, agitation method, sample modification (pH, ionic strength, organic solvent content), sample temperature, extraction time and desorption conditions [4]. Within these parameters, the fiber coating is one of the most critical factors influencing the performance of SPME methods. In the past, substantial state of the art technology were proposed in the fabrication of the optimal SPME coating/fiber/device for food analysis, such as sol-gel coating [5,6], polypyrrole/sol-gel coating [7], ionic liquids [8], molecularly-imprinted polymer coating [9]. etc. The suitability of the fiber coating for a specific analyte of interest is determined by the polarity of the coating and its selectivity towards the analytes of interest in contrast to other matrix component. Recently, the new SPME coating materials was summarized by Xu et al. [10] Food matrix are very complex, often containing proteins, fat, salts, acids, bases, and numerous food additives with different chemical properties. Among all the coating materials, PDMS, as a liquid coating with a smooth, homogeneous surface, suffers less from the irreversible fouling effect caused by the matrix components than solid coatings [11]. This makes the PDMS coating the most robust option for direct analysis of food sample. However, its sensitivity towards the analytes of interest was a critical problem. It motivated the modification of existing commercial SPME-fiber coatings with a thin layer of PDMS to create a new type of SPME-fiber coating, achieving matrix compatibility while retaining the original coating sensitivity towards the analytes of interest [12]. As shown in Fig.1, The modified SPME-fiber coating, such as PDMS/DVB, DVB/CAR/PDMS, PDMS/DVB/PDMS, was demonstrated to possess extraction efficiency and longevity when directly subjected to a complex matrix [12,13]. Therefore, these PDMS modified coating were the favored tools for SPME in food analysis. Beyond PDMS modified coating, other novel fabricated SPME fiber coating will be discussed in the following section.

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2.2. SPME quantification in food analysis

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The amount extracted by SPME is proportional to the free concentration of the analytes in the samples due to the equilibrium nature of the SPME technique, [12]. This principle often causes misconceptions regarding the quantification capabilities of SPME, especially when dealing with complex matrices, where the absolute recovery of analytes may lie within a small percentage of the total amount. On this occasion, the choice of a proper calibration technique is vital for the achievement of accurate quantification. The most commonly employed calibration approach in food analysis, where complex matrices are present, is matrix matching to the unknown sample. A recent review was summarized the SPME quantification methods in food analysis [14,15], thus, the detail of SPME quantification method was not discussed in this manuscript.

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3. Applications of SPME for food analysis

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3.1 Volatile compounds of food

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3.1.1. Flavors

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SPME has been successfully used in the extraction of many different volatile compounds in various foods for analytical purposes [15-19]. However, there are not standard protocols that can be adopted for the complex target analytes of various foods. Therefore, many researchers devoted to investigating the optimum conditions of SPME to achieve different research purposes.

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3.1.1.1. Wine and alcoholic beverage

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It can be noticed that SPME has been more commonly used for the extraction of volatile organic compounds from wine [20-22], liquor [23], brandy [24] and spirits [25].

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Fan et al. [26] used an automatic headspace sampling system with SPME with a 50/30 m DVB/CAR/PDMS fiber for extraction of volatile compounds of Chinese "Yanghe Daqu" liquors.

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Cheng et al. [27] used SPME with a 50/30 m DVB/CAR/PDMS fiber for aroma extraction in Chinese liquors. According to the strong aroma type, chemometric analysis methods, such as partial least squares (PLS) regression and principal component regression (PCR) models developed to predict the quality grade of liquors, and principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and stepwise linear discriminant analysis (SLDA), were used to classify the Chinese liquors from different geographic origins. Another effort

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selected 75 m CAR/PDMS as the fiber coating to perform the Headspace SPME for Chinese liquors analysis was reported by Xiao et al. [28] and 86 aroma compounds were confirmed. Moreover, Wang et al. [29] studied a homemade sol-gel DVB/OH-TSO fiber to conduct the PMSE procedure, which provided the highest analytical responses to the volatile compounds compared with commercial fibers. 57 volatile aroma compounds were identified in Chinese Daohuaxiang liquors. Castro et al. [30] compared rotatory and continuous LLE and a SPME method using a 85

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m CW-DVB fiber to determinate volatile compounds of “fino” sherry wine. Both methodologies showed adequate detection and quantitation limits, and linear ranges for correctly analysing these compounds. Nevertheless, the SPME method showed more advantages. Fiber coating was the core of the SPME technique. Therefore, the kinds of the selected fiber

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could influence the performance of SPME method. Pena et al. [31] found that SPME with a 65 m CW-DVB fiber was better than ones with PDMB fiber for extraction of 22 volatile compounds in 4

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orujo spirits from a defined geographical origin. The results showed that the proposed method was more sensitive (with detection limits between 0.0045 and 0.2399 mg/L), more precise (with coefficients of variation in the range 0.99–8.18%), and possessed wider linear range (over more than 1 order of magnitude). Sagratini et al. [32] used HP-SPME coupled with GC-MS to identify 28 volatile chemicals in red wines from two different regions of Italy. The performances of three different fibers were compared. The results showed that PA fiber and PDMS fiber displayed different sensitivity for some compounds, but DVB/CAR/PDMS fiber showed a lower degree of reproducibility. Burin et al. [33] compared six fibers used for SPME to extract heterocyclic

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compounds in red wines. The 85 m CAR/PDMS fiber was the best option for all heterocyclic compounds. The method allowed the simultaneous determination of 24 heterocyclic compounds in the wine and showed satisfactory repeatability (2.7%–12% of RSD), reproducibility (2.8%–12% of RSD) and accuracy. Slaghenaufi et al. [34] also compared five different fibers for SPME to

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extract five megastigmatrienone isomers in aged wine. However, the 65 m DVB–PDMS fiber resulted in the highest sum of the area of the five isomers and was considered as the most efficient fiber for extraction. The research showed the megastigmatrienone content was dependent on the wine age. Liu et al. [35] reported a homemade SPME syringe with sol–gel-derived OH-TSO-BMA-DVB fiber used to transfer the extracted sample to the GC injector for analysis. They established HS-SPME-GC method to determine the content of the volatile compounds in red wine. The recoveries obtained ranged from 85.87 to 104.2%, and the relative standard deviation values were below 9%, which showed satisfactory linearity, precision, detection limits and accuracy. Fiorini et al. [36] compared three SPME fibers (DVB/CAR/PDMS, 50/30 μm, gray fiber; PDMS 100 μm, red fiber and PDMS/DVB 65 μm, blue fiber) for extraction of the volatile compounds in the red wine Vernaccia di Serrapetrona. The gray fiber was found to be the most efficient fiber for abundant volatiles extraction. The research was in agreement with Riu-Aumatell et al. [37] and the group [38] used SPME to extract volatiles from beers and identified and quantified 59 volatile compounds in beers with DVB/CAR/PDMS fiber. In addition, DVB/CAR/PDMS fiber was also applied to oak compounds analysis in aged red wines and the detection limits and reproducibility of the proposed method were excellent [39]. Rebière et al.[40] investigated volatile compounds within and between vintages of Semillon wines by SPME

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extraction. A 50/30 m DVB/CAR/PDMS fiber was also considered as a better choice. The research identified 21 volatile compounds and 3-methyl-1-butanol was quantified as the most concentrated volatile compound with 83 and 66 mg L−1 for the 2006 and the 1996 wines, respectively. Beyond the DVB/CAR/PDMS fiber, PDMS fiber was another widely used fiber. Li et al. [41] identified a total of 41 volatile compounds in Chardonnay dry white wines. However, in

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this study, a 100 m PDMS was adopted as the best fiber to extract volatile compounds. The results indicated that 13 volatile compounds were considered to be the powerful impact odorants of this wine. The volatiles of German white wine was investigated to verify botanical origin. Moreover, SPME with a PDMS fiber was used for extraction and a partial least-squares discriminant analysis P S-DA) model was validated based on the S-MS data. xternal samples were correctly classified for Silvaner, 3 Riesling, 1 Pinot ris/Blanc and 0 M ller-Thurgau [42]. Several studies about fruit wine have been reported in recent years. For example, Headspace (HS) and immersion (IM) SPME technique for extraction aroma compounds of strawberry wine were compared [43]. The results found that esters were the major compounds and a total of 17 5

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volatile aroma compounds were identified in the strawberry wine, including twelve esters, two acids, two terpenes and one higher alcohol. SPME with a 50/30 µm DVB/CAR/PDMS fiber was employed for aroma extraction in apple ciders [44]. Compared with LLE-SAFE, HS-SPME was more sensitive for esters and highly volatile compounds. Volatile compounds of pineapple wine

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were analyzed and also used SPME method for extraction [45]. In concluded that a 100 m PDMS coating fiber was the good choice for analysis of volatile compounds from several pineapple wine. In this study, eighteen volatiles were identified, including thirteen esters, four alcohols and one acid. Ethyl octanoate, ethyl acetate, 3-methyl-1-butanol and ethyl decanoate were the major constituents. Sun et al.[46] compared the influence of cultivars on aromatic compounds and polyphenols in cherry wines by HS-SPME coupled with GC–MS and HPLC. The results showed that twenty-one aromatic compounds were identified and eleven polyphenols were quantified. The calculated results indicated that cherry cultivars play a decisive role in wine aroma and polyphenol compositions. Xiao et al. [47] had extracted 75 volatiles of cherry wines by HS-SPME with a DVB-CAR-PDMS fiber and analyzed by GC-MS. They have successfully discriminated nine different cherry wines based on their sensory properties and aromatic finger printing. Recently, Xiao et al. [48] used SPME method coupled with GC-MS to confirm and quantify a series of

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volatile compounds in cherry wines. They optimized several parameters, including 50/30 m DVB/CAR/PDMS fiber, 45 min extraction time and 50 ℃ extraction temperature for extraction. The LODs, LOQs and precision of the method were all within the acceptable range. Gallardo-Chacon et al. [49] reported to describe the volatiles retained by lees during second fermentation of sparkling wines. An optimized SPME with 50/30 µm DVB/CAR/PDMS fiber was developed and applied to obtain a wide qualitative profile of lees’ surface volatiles, from a heterogeneous group of sparkling wines. 57 compounds were identified or tentatively identified. Bueno et al.[50] develop an analytical method for the simultaneous determination of free and bonded forms of wine sensory relevant carbonyls. DVB/PDMS was used as a SPME fiber and 14 carbonyls were successfully captured. The use of SPME for extraction of volatile flavor compounds from alcoholic beverage was

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also reported. Khio et al. [51] selected an 85 m CAR/PDMS fiber for SPME extraction due to its high sensitivity and extraction efficacy. Li et al. [52] studied volatile components of camel-naizi (CSCN) by SPME-GC/MS. The extraction performances of three types of SPME fibers (75 µm CAR/PDMS, 65 µm PDMS/DVB, and 50/30 µm DVB/CAR/PDMS) were studied and compared. A total of 45 volatile compounds were identified by using three fibers. Mo et al. [53]compared three types of fibers (PDMS, CAR/PDMS, and DVB/CAR/PDMS) for the analysis of volatile compounds in Chinese rice wine qu. The DVB/CAR/PDMS fiber was found to be the most effective for all of the target molecules, whereas the fewest compounds were extracted by PDMS fiber. Finally, the DVB/CAR/PDMS fiber was selected for the extraction of the aroma compounds in Qu, which was consistent with the previous results [16,54].

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3.1.1.2. Fruits and juices

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Fruit is an important part of plant. It can be used for food directly or applied in liquor production and candy production. The flavor emitted from fruits, including alcohols, aldehydes, carboxylic esters and ketones, is an important attribute of fruits quality. In addition, it influences the quality of relative product such as wines, candy and essential oils. Therefore, study on the volatile compounds profile of the fruits plays guiding roles in agriculture, liquor production, candy 6

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production and essential oil industry. Nowadays, SPME can successfully apply to flavors analysis in fruits sample.

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Ceva-Antunes et al. [54] compared 50/30 m DVB/CAR/PDMS, 65 m CW/DVB, 75 m CAR/PDMS and 100 m PDMS fiber for the volatile composition of ripe siriguela fruits. DVB/CAR/PDMS turned out to be the more efficient qualitatively and semi-quantitatively fiber in

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trapping these compounds. Beaulieu et al. [55] also employed 50/30 m DVB/CAR/PDMS fiber to identify volatile and semi-volatile compounds in five seedless watermelon varieties through coupling with GC-MS. Ong et al. [56] established SPME coupled with gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) method for analysis of volatile

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compounds in five jackfruit. The 50/30 m DVB/CAR/PDMS fiber displayed the largest extraction efficiency. Wang et al. [57] applied HS-SPME to study the characteristic volatiles of

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peaches and nectarines at the germplasm level. They selected 65 m PDMS/DVB fiber for isolation the volatiles and total 84 compounds were identified. The study indicated the amount of total volatiles and certain individual compounds was influenced by years and locations. To investigate the volatile metabolite profile of Madeira island fruit species, Pereira et al.[58]evaluated and compared five different commercialized fibers for HS-SPME procedure,

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including 85 m PA, 100 m PDMS, 65 m PDMS/DVB, 70 m CW/DVB and 85 m CAR/PDMS. The SPME fiber coated with CW/DVB offered the highest extraction efficiency in kiwi and papaya pulps, while the same performance was achieved with PMDS/DVB fiber in lemon and plum. Gebara et al.[59] investigated volatile compounds on fruits and leaves of Mangifera indica var. coquinho. The HS-SPME technique was also evaluated by the comparative study among three fibers: commercial PDMS, NiTi-ZrO2 and NiTi-ZrO2-PDMS. The fiber NiTi-ZrO2-PDMS showed better sensitivity and precision and was adopted for the extraction of volatile components. After long-term natural evolution or artificial cultivation, most plant species contain different varieties. Fruits from different cultivated varieties vary in color, flavor, size and shape. Flavor, as one of the most appreciated characteristics of fruit, can be used to distinguish different types of fruits or cultivars. Moreover, re-harvest environment, harvest maturity, and post-harvest handling or storage also affected overall flavor of fruits. Gokbulut et al. [60] determined the aroma compounds of Malatya apricots using SPME coupled with GC-MS. Volatiles were extracted by

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the 75 m CAR/PDMS SPME fiber. They found volatiles of apricot cultivars composed of mainly of aldehydes, alcohols, acetates, esters, terpenes and acids. The volatile compounds in four

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selected African star apple fruit varieties were isolated by HS-SPME using 50/30 m DVB/CAR/PDMS fiber and identified by GC–MS. A total of 59 compounds were identified. The result showed the relationship between the apple varieties and the key volatile compounds [61].

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Kraujalyte et al. [62] also used HS-SPME with a 50/30 m DVB/CAR/PDMS fiber to extract volatiles of two berry fruits. Twenty two aroma-active compounds were detected and characterized by the trained panelists in HS-SPME using GC-O detection frequency analysis. HS-SPME with a

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50/30 m DVB/CAR/PDMS fiber was also selected for analysis the volatile aroma compounds in fresh melon fruits by Verzera et al. [63] and for extraction flavor profiles of varieties of muskmelon by Lignou et al. [64]. Beaulieu et al. [65] studied the aroma, astringency, and flavor of rabbiteye blueberry. 53 volatile profiles were extracted by SPME and obtained in five cultivars assayed at four maturities. Steingass et al. [66] reported HS-SPME-GC/MS was used to detect volatiles from pineapple fruits at four ripening stage. And 132 volatiles were identified, which 7

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were extracted using a 65 m DVB/PDMS fiber. Multivariate data analysis was developed to assess the effect of different ripening stage and type-freighted. They also studied SPME as extraction method extracted lactone profiles of pineapple fruits and identified pineapple at different maturity stage. Five volatiles were extracted by HS-SPME for 40 min at 50℃ without

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pre-incubation using a 95 m Carbon WR/PDMS fiber [67]. The changes of the volatiles in different Chinese bayberry fruit in different storage conditions were observed and characterized by

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Cheng et al. [68] reported that HS-SPME with a 50/30 m DVB/CAR/PDMS was used for the extraction and concentration of volatile compounds. 82 volatile compounds (including aldehydes, alcohols, acids, esters, terpenes and others) were identified and there were significant differences in the composition of volatiles among different cultivars. And the volatile profiles at different storage conditions can be used for freshness evaluation during storage. Juice is an important processed goods of fruits. Due to the very complicated matrix in juice sample, a suitable sample preparation method is of great concern. Schmutzer et al. [69] employed HS-SPME-GC-MS to extract and characterize the volatile organic compounds in apple juice. A

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65 m PDMS fiber was used for SPME and more than seventy volatile organic compounds were determined from different chemical families. Llorente et al. [70] also studied volatile compounds in Asturian apple juices by HS-SPME-GC-MS method. Three different fiber coatings have been

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checked (100 m PDMS, 65 m PDMS-DVB and 75 m CAR-PDMS) and PDMS-DVB has been presented to be the most suitable one. Fourteen compounds (esters, aldehydes and alcohols) were determined in approximately 4 min. Wei et al. [71] compared SDE and SPME to isolate volatile compounds in noni fruit juice. SPME was useful to recover low boiling point and low molecular weight compounds; in contrast, SDE possessed higher extraction capacity and higher recovery for polar compounds. SPME and SDE can provide complementary information. Abdullah et al. [72] developed HS-SPME-GS-MS to analyze the volatile compounds in starfruit juice. Different

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experimental parameters were optimized to improve efficiency. A 65 m DVB/PDMS fiber was used for adsorption 30 min at 50℃. Mahattanatawee et al. [73] developed HS-SPME-GS-MS to determine β-damascenone in orange juice and evaluated the effect of thermal processing in orange

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juice. A 50/30 m DVB/CAR/PDMS was used for the extraction. The β-damascenone had been quantified by HS-SPM and they found β-damascenone concentrations increased with increased heat treatment.

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3.1.1.3. Meat and meat products

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Solid phase microextraction (SPME) has been demonstrated to be a useful method to extract volatile compounds from meat and meat products [74, 75]. Moon et al. group [76] detected volatile compounds in simulated beef flavor using HS-SPME method. The four type of SPME

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fibers of 65 m PDMS/DVB, 65 m CW/DVB, 75 m CAR/PDMS and 50/30 m DVB/CAR/PDMS were compared for optimization the SPME condition. The selected extraction

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conditions for SPME were as the following: 50/30 m DVB/CAR/PDMS fiber; 60 min extraction time and 60℃ extraction temperature. Based upon the established method, they applied the SPME technique to investigate the volatile components of simulated beef flavor, boiled beef and roasted beef samples. A total of 70 aroma compounds were identified in the simulated beef favor by combined use of HS-SPME coupled with GC-FID and GC-MS. While the absence of various aldehydes and ketones resulted in the subtle difference between the simulated beef favor and cooked beef [77]. Giuffrida et al. [78] developed the SPME-GC-MS method to quantify low 8

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amounts (g/g range) of hexanal in beef bouillons. Three different fibers were compared, including 50/30 m DVB/CAR/PDMS, 50/30 m DVB/CAR and 65 m PDMS/DVB. The best results were observed for the DVB/CAR/PDMS fiber (37 ℃; 40 min). Watanabe et al. [79] also

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selected a stable-flex SPME fiber coated with 50/30 m DVB/CAR/PDMS for analysis of volatile compounds in beef fat by SPME-GC-MS. Fifty-three compounds were identified from only 0.20 g of rendered beef fat, and 76% of these showed reliable peak size repeatability. Similar to fruit, the flavors emitted from meats were influenced by types, cultivars, slaughter age and storage, etc.. This unique characteristic facilitates the widely applications of SPME on the evaluation of VOCs composition of meats in different cultivars, slaughter stage or during storage to get more economic benefits. Bhattacharjee et al. [80] investigated the volatile compounds produced by Salmonella typhimurium in the repackaged beef samples (aged and fresh) using HS-SPME coupled with GC-MS. A 75 µm CAR-PDMS fiber was used for SPME extraction. The study indicated that Salmonella typhimurium affected several volatile compounds in fresh and aged beef. Santander et al. [81] detected 6 volatile organic compounds in beef, which were extracted by SPME method with a 75 µm CAR-PDMS fiber. These volatiles data was modeled by using PLS and SVM classifiers for recognizing age at slaughter of cattle. Argyri et al. [82] evaluated meat spoilage through the evolution of volatile compounds in the spoilage of minced beef. The volatile compounds of meat were isolated HS-SPM with a 50/30 μm DVB/CAR/PDMS fiber. They found that the HS-SPME-GC/MS analysis provided useful information about a great number of volatile metabolic compounds detected during meat storage. Rivas-Canedo et al. [83] compared dynamic headspace (DHS) and solid-phase microextraction (SPME) as extraction methods for analysis the volatile profile in cooked beef. SPME with a 50/30

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m DVB/CAR/PDMS fiber was more efficient in extracting substances such as 1-alcanols, ethyl esters and acids. They also compared DHE and SPME extraction methods to assess the effect of the effect of high-pressure treatment on the volatile compounds of low-acid fermented sausage ‘‘espetec’’ and sliced cooked pork shoulder. SPM extracted more efficiently a large number of chemical families, especially fatty acids [84]. Watkins et al. [85] used DHE and SPME techniques

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to extract volatile compounds in heated beef and sheep fats. A 50/30 m DVB/CAR/PDMS fiber was used for extraction compounds. Around 100 compounds were characterized in the volatile profiles using SDE and SPME, which were observed differences in the volatiles by each extraction technique. Volatile organic compounds of bovine fresh meat samples were measured by GC/MS–SPM using four SPM fibers. The result revealed that the 65 μm PDMS/DVB and 50/30 μm DVB/CAR/PDMS were the most suitable for extraction of volatile compounds from beef [86]. Some researchers demonstrated that HS-SPME, as a quick, inexpensive, solvent-free technique, coupled with GC/MS analysis, was a method that allows to detect 2-dodecylcyclobutanone (DCB) in order to distinguish irradiated ground beef from nonirradiated one [87] or quantify DCB [88]. They both selected PDMS fiber for SPME extraction. Miks-Krajnik et al. [89] detected chicken breast spoilage based on analysis volatile organic compounds using HS-SPME-GC/MS-FASST. The fibers including 100 µm PDMS, 85 µm PA, 50/30 µm DVB/CAR/PDMS, and 85 µm CAR/PDMS were compared. The largest number of volatile peaks and the largest total peak areas were obtained using DVB/CAR/PDMS fiber and the most promising volatile spoilage markers for chicken breast were EtOH and 3-methyl-1-butanol, followed by acetic acid (C2) and sulfides. Volatile compounds of traditional Chinese Nanjing water-boiled salted duck (NJWSD) during its stages of processing were investigated by HS-SPME 9

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coupled with GC-MS [90]. A 75 µm CAR-PDMS SPME fiber was selected for extraction according to the previous research [91]. The results showed that the major volatiles identified were degradation products of fatty acids, which were considered to account for the typical flavor of duck meat. Moreover, three different extraction techniques were compared for determining the flavor profiles of traditional Chinese Nanjing marinated duck (NJMD), which were solid phase microextraction (SPME) with a Carb/PDMS fiber, purge and trap (P&T) using Tenax-TA absorbent and simultaneous distillation–extraction (SDE) in 2007 [92]. Results indicated that SPME method was better than P&T method, and SPME with SDE method may well complement each other. Processed meats, such as hams and salami, are widely consumed around the world. To evaluate the flavors emitted from processed meats was an important application of SPME. A 75 µm CAR-PDMS SPME fiber was also selected for extraction of volatile flavor compounds from Jinhua ham. They studied the changes of volatile flavor and compounds were studied during the traditional ageing process of Jinhua ham [93]. Del Pulgar et al. [94] used the SPME technique with a CAR/DVB/PDMS fiber to extract volatile compounds and the most odor-active compounds of dry-cured Iberian hams. Jerkovic et al. [95] developed a HS-SPME-GC-MS method for the analysis of 54 volatile compounds in Istrian dry-cured hams. PDMS/DVB fiber was used to extract volatiles. Wagner et al. [96] reported the extraction of volatile compounds in salami by SPME. The optimal conditions were determined to be an extraction period of 45 min at 50 °C for the extraction of volatile compounds by HS-SPME with a CAR/PDMS fiber. Lorenzo et al.[97] studied the effect of fiber coating and extraction time on the volatile profile of dry-cured loin analyzed by SPME in order to determine the most suitable conditions for extraction. Two SPM fibers of 5 μm CAR/PDMS and 50/30 μm DVB/CAR/PDMS and three extraction time (15, 30 and 45 min) were compared. Two fibers provide a similar volatile compound profile for dry-cured foal loin and the extraction time significantly affected DVB/CAR/PDMS fiber. Benet et al. [98] also used SPM with a 50/30 μm DVB/CAR/PDMS fiber to extract volatile compounds from cooked cured pork ham and analyzed the influence of the IMF content and the fatty acid saturation profile on cooked cured pork ham volatiles. Some researchers reported SPME methods applied to determining volatile compounds in fish and seafood. The volatile compounds were evaluated during storage for different sample. Edirisinghe et al. [99] developed a SPME-GC-MS method to study the changes of volatiles in fresh yellowfin tuna during storage. SPME was used for extraction the volatiles coated with a 100 μm PDMS fiber. Xu et al. [100] also developed HS-SPME-GC-MS method for the study of the volatile profile characteristics of turbot during refrigerated storage at 4 ℃ for 20 days in order to find possible markers of freshness or spoilage. Four fibers of 100 μm PDMS, 5 μm CAR/PDMS, 65 μm PDMS/DVB and 50/30 μm DVB/CAR/PDMS were compared. DVB/CAR/PDMS fiber was found to give a good result in terms of relatively high total peak area in GC-MS chromatogram and extract 61 volatile compounds. The volatile profile characteristics of turbot were changed at different storage periods. Tuckey et al. [101] reported on monitoring the changes of volatile organic compounds in reenshell™ mussels during chilled storage using HS-SPME-GC-MS. 65 μm PDMS/DVB fiber was used to extract target volatiles and volatile compounds were found to change in relative concentration in homogenised mussel meat. Duflos et al. [102] also monitored the changes of volatile compounds in whiting (Merlangius merlangus), 10

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cod (Gadus morhua) and mackerel (Scomber scombrus) and related to spoilage by HS-SPME-GC-MS. They selected a 5 μm CAR/PDMS fiber for SPM extraction and SPME/GC/MS identified 86 compounds, 20 of which could perhaps be used to characterize freshness. Soncin et al. [103] also selected a 5 μm CAR/PDMS fiber for SPM extraction volatile compounds of precooked prawn (Penaeus vannamei) and cultured gilthead sea bream (Sparus aurata) stored in ice to monitor fish freshness. Chan et al. [104] developed a HS-SPME-GC-MS method for monitoring the change of the alkylamines in two chilled and frozen fish species and dimethylamine (DMA) and trimethylamine (TMA) were opined to be effective chemical indicators for monitoring the freshness of fish. Analogously, both qualitative and quantitative information are desired in order to monitor flavor quality and provide quality control for fresh and processed sea food. SPME also shows prominent superiority in this field. Iglesias et al. [105] used a 50/30 μm DVB/CAR/PDMS fiber for the extraction of volatile compounds by HS-SPME and analyzed volatile compounds by GC-MS, which were characterized the fresh and frozen-thawed Italian and Spanish cultured gilthead sea bream fish. Iglesias et al. [106] determined carbonyl compounds in fish by HS-SPME-GC-MS, but selected a 65 μm PDMS-DVB fiber for extraction because linear aldehydes PDMS-DVB produced higher responses than CAR-PDMS-DVB. They applied the HS-SPME-GC-MS method to the determination of volatile compounds associated with oxidation of fish muscle. The different fibers were also compared and a 5 μm CAR/PDMS fiber was selected for extracting the volatiles. Analysis of volatile compounds could be successfully applied to indicate the oxidative deterioration in fish muscle [107]. O'Dwyer et al. [108] also used SPME-GC/MS to determinate volatile compound in order to evaluate the oxidative stability of tuna fat. Souza et al. [109] established a HS−SPM − C−MS method to quantify the volatile lipid oxidation products V OPs) in shrimp during the salting and drying process. A 50/30 μm DVB/CAR/PDMS fiber was the most adequate for the extraction of the VLOPs after evaluation four fibers. The salting and drying negatively affected shrimp quality, reducing the fatty acid content and increasing the VLOPs, especially hexanal. In addition, HS-SPME was applied to the extraction volatile compounds in seafood, such as smoked fish [110], sardine [111], Chinese mitten crab [112], Alaska Pollock [113], puffer [114] and shrimp head [115]. Different fibers were always compared for optimization of the extraction condition and the selection was different because of the sample and the target analytes.

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3.1.1.4. Cereal products

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More than 500 wheat bread volatile compounds have been reported in the literature, which belong to different chemical classes such as alcohols, aldehydes, ketones, pyrazines and other N-heterocycles, acids, furans, esters, sulphides and others [116, 117]. Wheat bread volatile compounds have been determined and extracted with SPME. However, these reports neglected several important bread odorants or a poor precision in the determination of some important odorants has been observed [118-123] . An improved method was developed for the analysis of wheat bread volatile compounds to

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provide a more complete volatile profiles and give more precise information. A 50/30 m DVB/CAR/PDMS fiber was used for HP-SPME to extract volatiles from the headspace of a bread powdered sample. The research concluded that 134 kinds of volatiles were identified [124]. SPME as a fast, solvent-free technique was also used for analyzing cereal or flour volatile composition, 11

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such as oat [125], barley flour [126], pea flour [127], kama flour [128], noodle [129] and bread oils [121, 125]. Most researchers were focused on volatile compounds in oils sample. Tu et al. [130]used HS-SPME technique to extract volatile compounds and analyzed with GC-MS. Based on the data with multivariate analysis techniques, Edible Oils and Waste Cooking Oil were classified on the basis of different volatile compounds. Wei et al. [131] developed a HS-SPME method with a 50/30 μm DVB/CAR/PDMS fiber combined with C-MS to identify aroma-active compounds in flaxseed oils. A total of 60 compounds were tentatively identified and six aroma-active compounds were considered major contributors to the characteristic flaxseed oils odor. Cecchi et al. [132] applied HS-SPME-GC-MS to identifying volatile profiles of Italian monovarietal extra virgin olive oils. They also selected a 50/30 μm DVB/CAR/PDMS fiber for SPM extraction and forty-eight compounds were characterized by GC-MS. Kwon et al. [133] established a HS-SPME-GC-MS method for the simultaneous characterization and quantitation of pyrazines in perilla seed oils. For the optimal extraction of pyrazines, a HS-SPME conditions was set for the absorption time of 20 min at 70 ℃ with a CAR/PDMS fiber. Fourteen pyrazine compounds were isolated, identified, and quantitated in perilla seed oils. Petersen et al. [134] reported that HS-SPME-GC-MS was used to identify in total 74 volatile lipid oxidation compounds altogether in thermally stressed conventional and high-oleic sunflower oil samples. A 50/30 μm DVB/CAR/PDMS fiber was used for volatile extraction. Sanchez-Cabrera et al. [135] analyzed volatile compounds in nine spices by HS-SPME combined with GC-MS and GC-FID. Four fibers were compared and a 100 μm PDMS fiber was used because of its stability. They found the evaluation of the analytical parameters indicating that the method had a high precision for the analysis of the spices volatile compounds in dry flavoring. Park et al. [136] analyzed volatiles using SPM with a 65 μm DVB /PDMS fiber in sesame oils at different roasting conditions. Pyrazines were major volatiles in sesame oils and furans, thiazoles, aldehydes, and alcohols were also detected. Koprivnjak et al. [137] used HS-SPME with DVB/CAR/PDMS fiber to extract volatile compounds determined by GC-FID in virgin olive oils. Influence of free fatty acids, sterols and phospholipids on volatile compounds were evaluated, which did not significantly influence the determination of virgin olive oils volatiles in concentration ranges considered. Aroma compounds in olive oil were determined by HS-SPME-GC and two fibers of 100 μm PDMS and 5 μm PA were compared. They observed that PDMS fiber was capable of extracting the olive oil aroma compounds faster than PA fiber, but PA fiber was found to be the adequate fiber to perform relative quantification of aroma compounds in a non-equilibriumstate in a non-aqueous sample like olive oil [138]. Volatile compounds in virgin olive oils from five new cultivars were also analyzed by SPM with a 100 μm PDMS fiber. Forty five compounds were isolated and characterized by GC-MS and the results indicating the profiles of oleaster oils were distinctly different from those of European and Tunisian oil [139]. Kalua et al. [140] developed a HS-SPME-GC method to monitor volatile compounds in extended time-course experiments of olive oil. A 50/30 μm DVB/CAR/PDMS fiber was used for extraction volatile compounds. The results demonstrated that the method could applied to monitor the change in concentration of selected C6 volatile compound. HS-SPME technique was also reported for analysis and characterization of volatile lipid oxidation products present in oil-in-water emulsions [141]and fish oil [142].

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3.1.2. Off-flavors

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Jelen et al. [143] reported the SPME applied to analysis of food taints and off-flavors in a review. He introduced compounds causing the taints and off-flavors in food and the application of SPME. Recently, López et al. [144] isolated and evaluated the volatile sulfur off-flavor compounds in wine by HS-SPM with a 5 μm CAR/PDMS fiber combined with C-PFPD. Gomez-Ariza et al. [145] developed multiple headspace solid-phase microextraction (MHS-SPME) coupled with GC/MS to determine off-flavors in wine. 100 μm PDMS fiber and 50/30 μm DVB/CAR/PDMS fiber were compared and better results were obtained with the latter for haloanisoles determination. Fan et al. [146] developed a SPME-GC-MS method to quantify 2-aminoacetophenone (2-AAP) in white wines, which causes an ‘‘atypical aging” or ‘‘untypical aging” UTA) off-flavor. A 50/30 μm DVB/CAR/PDMS fiber was used for the extraction of 2-AAP and the distinct off-flavor associated with 2-AAP could be detected when the concentration of 2-AAP reaches 0.5 μg/ . HS-SPME-GC-MS applied to determinate (E)-2-nonenal in beer was reported by Scherer et al. [147]. The extractions were carried out in 5 μm CAR-PDMS fiber and showed a good response to (E)-2-Nonenal. The method proved to be simple to carry out and could be used in routine analysis for (E)-2-nonenal for quality control of beer. Campillo et al. [148] reported that HS-SPM with a 5 μm CAR-PDMS fiber was used for the determination of volatile organic sulphur and selenium compounds in beers, wines and spirits. Shim et al. [149] developed method to identified and quantified trimethylamine (TMA) in spinach, cabbage, and lettuce at alkaline pH by HS-SPME. Six fiber were compared for a good extraction efficiency and a 65 μm PDMS/DVB fiber was selected. The results showed that the amount of TMA formed was dependent on pH. The amount of TMA formed increased dramatically at a pH greater than 9 and was not formed at a pH lower than 7. Tian et al. [150] developed HS-SPME-GC-MS method for determination of volatile off-flavor compounds in citral emulsion. Three types of SPME fibers (65 μm PDMS/DVB, 100 μm PDMS and 5 μm CAR/PDMS) were compared and 65 μm PDMS/DVB was chosen as the optimum fiber to obtain the highest extraction efficiency for seven off-flavor compounds. Bai et al. [151] reported an in vivo SPME method applied to monitoring the concentration of off-flavor compounds (geosmin and 2-methylisoborneol (2-MIB)) in living fish. The detection limit of in vivo SPME in fish muscle was 0.12 ng/g for geosmin and 0.21 ng/g for 2-MIB, which are both below the human sensory thresholds. The HS-SPME-GC-MS technique was applied to the analysis of the off-flavor compounds in milk. Vazquez-Landaverd et al. [152] used a 50/30 μm DVB/CAR/PDMS fiber for extraction the volatile compound. The results concluded that 2, 3-butanedione, 2-heptanone, 2-nonanone, 2-methylpropanal, 3-methylbutanal, nonanal, decanal, and dimethyl sulfide could be important contributors to the off-flavor of UHT milk. Vazquez-Landaverd et al. [153] also determined the volatile sulfur compounds in Milk, which were extracted by HS-SPM with a 5 μm CAR/PDMS fiber, and analyzed by GC. Seven sulfur compounds were accurately quantified and Jimenez-Alvarez et al. [154] characterized and quantified volatile compounds in a food matrix supplemented with fish oil. The primary oxidation products of long-chain polyunsaturated fatty acids in fish oil degraded and promoted some volatile compounds. HS-SPME-GC/MS could monitor lipid oxidation in early stage and c-4-heptenal as a possible oxidation marker gave rise to off-flavors in a milk.

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3.2 Non-volatile compounds of food

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3.2.1. Pesticides and other agrochemicals

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Pesticides, mainly including organochlorine pesticides (OCP), organophosphorous pesticides (OPP), carbamate pesticides (CP), phenyl urea pesticides (PUP) and pyrethroid pesticides (PP) have been used effectively to control pests, fungi and weeds. Use of pesticides plays a beneficial role in providing large quantities of a low-cost supply of fruits, vegetables and etc. [155, 156], but also be along with side effects. Pesticides and other agrochemicals may penetrate the tissues of fruits, vegetables, etc., where they remain as residues, result in the contamination of foods, and pose both acute and chronic health effects to human health due to their toxicity. Therefore, there is a need to strike a balance between their expected benefits and possible risks [157]. Hence, their concentration must always be minimal in fruits and vegetables and must be below the maximum residue limits. Today, the monitoring of pesticide residues in food is an objective of high priority in agrochemical research in order to allow extensive evaluation of food quality and contamination. Therefore, the analysis of pesticide and other agrochemical residues in food is essential for monitoring and safety purposes. The sample preparation step is commonly believed to be a most critical step in the qualitative and quantitative analysis of pesticide and other agrochemical residues in complex food matrices. The SPME extraction technique has also been adequately applied for the extraction of pesticides and other contaminants from food matrices with numerous of advantages, including no toxic solvents involved, short sample preparation time, compatibility with analyte separation and detection with chromatographic instruments and amenable to automation, feasibility for the extraction of diverse pesticides and other food contaminants from sample matrices in solid, liquid, or gaseous state, and linear results for a wide range of analytes, better consistency and highly quantifiable results from very low analyte concentrations, small volumes of sample required, relatively low cost and ruggedness, a small size viable for designing portable field-sampling devices. The technique is frequently chosen for the qualitative and quantitative sample preparation method for chromatographic (GC, LC) and hyphenated chromatographic-mass spectrometry analysis (GC-MS, LC-MS, GC-MS/MS, LC-MS/MS) (Table 1). Beverages, generally divided into alcoholic beverages and soft drinks, are very popular with consumers all over the world. Therefore, to control the quality in beverage sample is vital. Cortes et al. [158] developed a vanguard-rearguard SPME analytical method coupled to GC-MS and GC-MS/MS for determining 54 pesticide residues in natural and commercial orange, peach and pineapple juices. A fast screening (vanguard) method was firstly implemented for detecting juicy samples containing pesticides at concentrations above a pre-established cut-off value. The samples were secondly re-analyzed by a conventional pesticide residue (rearguard) method to confirm and quantify the pre-detected pesticides. The extraction process was very simple, fast and semiautomatic and required only 1 ml of juice sample. The screening step only required 10 min of SPME extraction and the confirming/quantifying step required 55 min of SPME extraction. The combination of single solvent based on SPME extractions and GC-MS/MS provided an excellent selectivity and sensitivity with a proven reduction of false positive and negative cases. Using vanguard-rearguard strategy reduced 50% of the total time required for determining common juices in a laboratory by a conventional analytical approach. A simple and environmentally friendly HS-SPME-GC-MS/MS method using a fiber of polyacrylate (PA) has been proposed by 14

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Robles-Molina et al. [159] for the simultaneous quantification of 32 pesticides in fruit-based soft-drinks. The proposed method applied a triple quadrupole analyzer to the multiple reaction monitoring (MRM) acquisition mode in MS/MS analysis and was successfully applied to the analysis of 26 market purchased fruit-based soft drink samples from Spain and some other countries. The data presented indicated that the method yielded good recoveries in the range 75-113% with RSD (%) along with LODs varied in the ranges of 0.1-180 ng/L for spiked samples and 1.5-320.8 ng/L for commercial samples. SPME using PDMS/DVB fibers in combination with sample stacking micellar electrokinetic chromatography (MEKC) was proposed by Ravelo-Pérez and coworkers [160] for the simultaneous determination of 11 multi-class pesticides residues (pyrimethanil, procyrniclone, pirimicarb, metalaxyl, nuarimol, tebufenozide, fenarimol, azoxystrobin, benalaxyl, penconazole and tetradifon) in red wines. The combination of two preconcentration procedures (SPME and reversed-electrode polarity stacking mode (REPSM)) allowed the determination of 10 pesticides in red wines at concentrations between 0.049 and 1.69 mg/L (except for pirimicarb) with recovery values in the range of 90-107%. Multiple homemade red wine samples from the Canary Islands and two commercial samples were used to demonstrate the promising potential of the proposed method. Martins et al. [161, 162] reported a SPME-GC-MS/MS method to quantify multi-class pesticides in fortified white wine and fortified red wine. The proposed method showed good

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linearity with R2 ≥0. for all pesticides, and good limits of detection (LOD, 0.05-72.35 g/L) and quantitation (LOQ, 0.16-219.23 g/L), much lower than the maximum residue levels (MRL) set by European Regulation for grapes. Wang et al. [163] applied a home-made sol-gel-derived co-poly (hydroxy-terminated silicone divinylbenzene) (OH-TSO/DVB) coating fiber for HS-SPME coupled with GC-NPD to determine 5 organophosphorus pesticides (OPPs) in pakchoi samples. Compared with commercial available fibers and OH-TSO SPME fiber, OH-TSO/DVB fiber showed statistically better enrichment capability for the 5 pesticides. The developed HS-SPME-GC method offers the limits of detection (LOD) ranging from 0.007 to 0.07 ng/g with recoveries of spiked pakchoi samples ranged from 80.74 to 101.47% for every pesticide at each investigated concentration. Analytical methods (SPME-GC-mu-ECD and SPME-GC-NPD) for the residues of fungicide residues (boscalid, cyprodinil and fludioxonil) in blueberries were developed by Munitz [164, 165]. The effect of pH

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values and fiber coatings were studied. The SPME fiber coating selected was 100 m PDMS. Degradation of boscalid, cyprodinil and fludioxonil were studied in a blueberry field located in Concordia, Argentina, with fruits from Emerald and Jewel varieties. The degradation of these fungicides in both blueberry varieties studied followed first-order rate kinetics for all fungicides, and the half-life for boscalid was 5.3 and 6.3 d for Emerald and Jewel cultivars, respectively, for cyprodinil was 2.2 and 3.4 d, respectively, and for fludioxonil was 12.7 and 16.3 d, respectively. Saraji et al. [166] prepared a SPME fiber coated with polypyrrole/sol-gel composite through electrochemical deposition. Organophosphorus pesticides (OPPs) in cucumber and lettuce were analyzed to evaluate the SPME composite coating, having porous surface structure, stable performance in high temperature and good preparation reproducibility, followed by GC-NPD detection. The coating exhibited better extraction efficiency than polypyrrole and commercial SPME fibers, and had LODs of ppb level and excellent precision and recoveries (80-109%). Wang et al. [167] applied a sol-gel technique for preparing water-compatible molecularly imprinted polymer (MIP) for SPME using diazinon as template and polyethylene glycol as functional 15

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monomer. The MIP-coated fiber demonstrated much larger extraction capability than the non-imprinted polymer and commercial fibers, and excellent thermal and chemical stability due to its specific adsorption to diazinon, rough and porous surface. Excellent capability (LODs,

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0.017-0.77 g/kg; recoveries, 81.2-113.5%) for evaluating OPPs in spiked cucumber, green pepper, Chinese cabbage, eggplant and lettuce samples had been proved by developing a MIP-SPME-GC-NPD approach. As water and soil pollution have become a global environmental issues, the vegetation, which could directly contact with polluted water and soil, may threat human health through the food chain. Recently, SPME was widely used for contamination monitor in edible vegetation sample.

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Chai et al. [168] reported a HS-SPME-GC-ECD method using 100 m PDMS fiber for the determination of pesticide residues in fruits (strawberry, star fruit and guava) and vegetables (cucumber, tomato and pakchoi). The developed HS-SPME procedure gave a good linear range, accuracy, precision, detection and quantification limits and was adequate for analysing pesticide

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residues in fruits and vegetables. Specifically, the LOD (0.01-1 g/L) and the limits of quantification (LOQ, 0.05-5 g/L) of these pesticides were far below the maximum residue levels (MRL) regulated in Malaysia. The obtained recoveries for each pesticide ranged from 71% to 98% at three fortification levels with the RSD less than 5%. Chai et al. [169] also applied the developed HS-SPME-GC-ECD method to examining the organophosphorus (diazinon, malathion, chloropyrifos, quinalphos, profenofos) and organochlorine (chlorothalonil, alpha-endosulfan and beta-endosulfan) pesticide residues in cucumber and strawberry before and after being washed by different solutions. Compared to sodium carbonate, sodium chloride and tap water, the results demonstrated that acetic acid was the most effective solution in removing the residues of the investigated pesticides from cucumber and strawberry. The effectiveness of pesticides removal by solution washing was related to water solubility and vapor pressure properties of pesticides as well.

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A DI-SPME-GC-ECD method using a 100 m PDMS fiber was developed by Mariani [170] for trace determination of 19 chlorinated pesticides in tomato samples. The LODs ranged from 0.5 to

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8 g/kg, and the LOQs from 5 to 30 g/kg with good linearity ranging from 0.97 to 0.9985. Organochlorine pesticides (lindane, heptachlor, aldrin, dieldrin and endrin) from milk samples were investigated by Merib [171] using HS-SPME-GC-ECD. A fiber coating DVB/Car/PDMS exhibited the best extraction efficiency towards the target pesticides. A Doehlert design was used to condition optimization, and an extraction temperature of 80 °C and an extraction time of 90 min

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were found to be the best conditions to afford satisfactory LODs (0.5 to 1.2 g/L) and recoveries (>75%). The fiber was tough as a single fiber was used throughout the study and no damage on coating was observed. A headspace solid-phase microextraction/gas chromatography-isotope dilution mass spectrometry (HS-SPME/GC-IDMS) method was developed by Feng et al. [172] for determination of 8 pesticides in tea samples. The isotopic labels spiked in incurred samples were

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equilibrated for 15 min followed by HS-SPME, and analytes were absorbed by a 100 m PDMS fiber for 70 min at 70 °C. Compared with the conventional sample preparation methods, the proposed method has the advantage of being quick, easy to operate, highly sensitive and also solvent saving. Compared to the traditional external standard method, the optimized HS-SPME/GC-IDMS method offered improve RSD, good recoveries (86.7-112.8%) and LODs (1.2-22.1 ng/g), demonstrating its applicability for qualitative and quantitative analysis of pesticides in tea. 16

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SPME methods coupled to HPLC-DAD were increasingly applied to determining pesticides in fruits and vegetables. Melo et al. [173] developed a SPME method coupled to HPLC-DAD for the determination of 10 pesticides frequently used in lettuce production (acetamiprid, azoxystrobin, cyprodinil, fenhexamid, fludioxonil, folpet, iprodione, metalaxyl, pirimicarb, and tolyfluanid). CW/TPR fiber was selected and response surface methodology based on central composite design was applied to investigating interactions between three key variables (pH, NaCl% and extraction time) and their optimal levels. The method was applicable for the quantification of fludioxonil, folpet, iprodione, azoxystrobin, cyprodinil, fenehexamid, and tolyfluanid in lettuce at concentrations from 0.8 to 25.6 mg/kg. The dissipation behavior during days to harvest of folpet and fenehexamid were investigated after Lettuce samples suffered treatments of the two pesticides. It was found that concentration of the two pesticides was reducing continuously till not detected at 64 days. A carbon nanotubes (CNTs)-reinforced hollow fiber (HF) was prepared and applied in SPME-HPLC-DAD approach for determining five carbamate pesticides in apples [174]. Through adding surfactant, the CNTs were dispersed in water and then were held in the HF pores supported by capillary forces and sonication. The SPME device was incubated with 1-octanol before being immersed in a stirred apple samples to extract pesticides. The results obtained under the optimized extraction conditions demonstrated that the described method was efficient for the determination of trace carbamate pesticides in apples. Obuseng et al. [175] developed dispersive solid phase extraction in the form of the quick, easy, cheap, effective, rugged and safe (QuEChERS) method and solid phase microextraction (SPME) for the cleanup of pesticides in plant samples from the Okavango Delta (Botswana). Concentration levels of aldrin, 1,1-dichloro-2,4-bis[chlorophenyl]ethane (DDD), 1,1-dichloro-2,2-bis[p-chlorophenyl]-ethylene(DDE),1,1-trichloro-2,2-bis[p-chlorophenyl]ethane (DDT), dieldrin, endosulfan and endrin were investigated using GC-ECD and confirmed with GC-TOFMS. Recoveries for both QuEChERS and SPME were in the range 61-95 %. The calibration plots were reproducible and linear (R2> 0.995) with LODs between 0.102 and 1.693

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g/L for all the pesticides. The optimized QuEChERS and SPME method were successfully applied to the extraction of pesticides residues from the edible parts (leaves, roots and/or stems) of Asparagus africanus, Cleome hirta and Nymphaea nouchali plants. A new hybrid material of a copper-based metal-organic framework (MOF-199) and graphite oxide (GO) was used as SPME coating [176]. The MOF-199/GO fibers with 10% (wt%) GO contents showed enhanced adsorption affinity to organochlorine pesticides (OCPs) compared to MOF or GO individually and commercial PDMS and PDMS/DVB fibers. The new fiber was used for HS-SPME-GC-ECD analysis of eight OCPs in water convolvulus and longan rendering satisfactory results. A new SPME fiber, polypyrrole/montmorillonite nanocomposite, was prepared and coupled with gas chromatography corona discharge ion mobility spectrometry (GC-CD-IMS) for the determination of diazinon and fenthion (as model compounds) in cucumber, lettuce and apple [177]. The fiber exhibited a rather porous and homogenous surface, and good thermal stability. The satisfactory LODs of low ppb level and recoveries demonstrated the capability of the two-dimensional separation technique (retention time in GC and drift time in IMS) for the analysis of complex matrices based on SPME extraction. A HS-SPME-GC-MS method was developed for eleven dedicated OPs assessment in turnip, green cabbage, French beans, eggplant, apple, nectarine and grapes [178]. Based on range-specific evaluation, each OP in extracts was characterized by sub-ppb level sensitivity with a wide 17

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0.01-2.5 mg/L dynamic range. Effective sample clean-up afforded precise quantification (0.5-10.9% RSD) within a 70-120% recovery range and the developed method could be a promising way to deliver international standards in OP screening routines. Abdulra'uf et al. [179] applied multivariate strategy to determining the significance of the factors affecting HS-SPME of pesticide residues (fenobucarb, diazinon, chlorothalonil and chlorpyrifos) in apples using a

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randomized factorial design (23 factorial designs). Analytes were extracted with 100 m PDMS fibers according to the factorial design matrix and desorbed into a GC-MS detector. The

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developed method offered LODs between 0.01 and 0.2 g/kg and RSD between 0.1% and 13.37% with average recoveries of 80-105%. Chlorpyrifos, fenitrothion, endosulfan I, and endosulfan II pesticide residues in cocoa powder were analyzed by Abdulra'uf [180] using HS-SPME-GC-MS based on multivariate strategy and central composite design and the applied analytical methodology exhibited good figures of merit. A new chemometric approach (Plackett-Burman (P-B) design combined with central composite design (CCD) was employed for the optimization of HS-SPME-GC-MS for the determination of multiclass pesticide residues in apple, tomatoes, cucumber and cabbage [181]. P-B design was used to estimate/identify the significance of each factor and CCD was applied to optimizing the significant factors, for the identification of significant factors. Compared to the conventional HS-SPME-GC-MS method, the chemometric approach helped to reduce optimization time and improved analytical throughput. Since the in vivo sampling-rate calibration was proposed by Ouyang et al. [182], the in vivo SPME technique was demonstrated and considered to be an efficient method for contaminants detection and monitoring in biota [183]. Recently, in vivo SPME was proposed for contaminants analysis in fish and vegetable samples. In a recent study, in vivo SPME with 44 PDMS fiber was applied to studying the impact of nanoparticle on the accumulation/depuration behaviors of contaminants in crop, mustard (Brassica juncea) (Fig. 2). The uptake and depuration kinetics of 8 contaminants, including organochlorine pesticides, organophosphorus pesticides, pyrethroid insecticides, pharmaceuticals, and personal care products (PPCPs), were long-time traced the living mustard. The results showed that an enhancement of contaminant accumulation in living plants exposed to nanoparticle was observed. Combination with a series of characterizations, they concluded that nanoparticle can act as contaminant carriers and be transported to the edible parts of mustard [184]. Meanwhile, Xu et al. introduced in vivo SPME with PDMS fiber to trace the uptake and elimination processes of pesticides in living fish. Moreover, the metabolism of fenthion was also traced with in vivo SPME. Importantly, the method was time-efficient and laborsaving. Much fewer experimental animals were sacrificed during the tracing [185].

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3.2.2. Pharmaceuticals and personal care products

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Pharmaceuticals and personal care products (PPCPs) are compounds with special physical and chemical properties that address the care of animal and human health. Interest in these emerging contaminants as environmental pollutants has increased rapidly. Milk, including its related commercial products, is one of the most popular foods in daily life but sometimes polluted by chemical contaminants, such as PPCPs. For example, antibiotics have been widely used in animal rearing and veterinary practice for therapeutic and prophylactic purposes [186], which have induced their contamination of milk products. Tylosin in different milk samples was determined by functionalized TiO2 hollow fiber solid/liquid-phase microextraction method [187]. The absorbent phase was functionalized with TiO2 nanoparticles dispersed in organic solvent and 18

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held in the pores and lumen of a porous polypropylene hollow fiber membrane. Compared with conventional hollow fiber liquid-phase microextraction, the extraction method showed excellent extraction efficiency and a high enrichment factor (540.2) for the isolation and determination of tylosin in milk samples with good linearity (0.51-7000 mg/L (R2 = 0.991) and LOD (0.21 mg/L). Zhao, T. et al. [188] recently reported a new SPME technique based on a new temperature sensitive molecularly imprinted polymer (MIP) with ofloxacin (OFL) as template. OFL in milk was effiectively extracted and determined by the proposed SPME coated with the MIP fiber coupled with HPLC. A new SPME method using crosslinked polymeric ionic liquid (PIL)-based sorbent coatings was applied to the extraction of 21 polychlorinated biphenyls (PCBs) from bovine milk. Due to the incorporation of benzyl moieties of PCBs into the PIL structures, PIL-based fibers showed higher sensitivities for PCBS than a commercial 7 mm PDMS fiber using GC-ECD and GC-MS as detectors. A nanocomposite composed of graphene, cetyl trimethylammonium bromide (CTAB), and polyaniline was prepared and applied by Abedi [189] to HS-SPME of three tricyclic antidepressant drugs (TCAs), imipramine, desipramine and clomipramine. The nanocomposite coating had large specific surface resulting in good mechanical and thermal stability and high extraction efficiency. The develop SPME-GC method was successfully applied to the extraction and determination of TCAs in milk samples. PPCPs and their metabolites are typically introduced to the environment through wastewater treatment plant (WWTP) effluent. As a result, PPCPs and their metabolites have been measured in surface waters, sediments, and groundwater at ng/ to μg/ levels. Inevitably, aquatic products and vegetation have been threaten by these pollutants. In the last decade, application of SPME for PPCPs determination in aquatic products and vegetation has increased rapidly. Wu et al. [190] used one-step microwave-assisted headspace solid-phase microextraction (MA-HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to analyze synthetic polycyclic musks, galaxolide (HHCB) and tonalide (AHTN), in oyster samples. The good precision and accuracy of the developed method for analyzing trace level of AHTN in oyster samples was demonstrated as well. Wu et al. [191] also applied MA-HS-SPME-GC-MS to successfully analyzing synthetic polycyclic and nitro-aromatic musks with the total concentrations ranged from 2.1 to 23.1 ng/g in various fish samples. Xu et al. [192] reported a SPME technique using graphitic carbon nitride (g-C3N4) as a coating material for the extraction of amphetamine, deltamethrin, nerolidol, dodecane, ametryn and acrylamide. By GC analysis, g-C3N4 coating showed superior extraction ability and durability than commercial fibers (100 mm PDMS and 85 mm CAR/PDMS) due to its loose structure and unique physicochemical properties. Acrylamide in potato chips was effectively analyzed by the g-C3N4 SPME fiber coated SPME coupled to GC-ECD. Some researchers developed in vivo SPME for PPCPs monitoring in living fishes [193]. For example, Zhang et al [194]. summarized recent challenges and solutions associated with the application of in vivo SPME in freely moving fish, including questions of invasiveness, sequential sampling of individual fish, calibration methods, and interpretation of data and their ecotoxicological relevance. They also examined spatial and temporal resolution and associated technical parameters, such as sampling time and dimensions of the SPME probe. Finally, the application of in vivo SPME for PPCPs monitoring in living fish was evaluated. Relative to other in vivo sampling techniques, such as microdialysis, in vivo tissue collection or biosensors. SPME has distinct advantages in its simplicity and its ability to sample simultaneously various tissues 19

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and locations in a single fish in a relatively non-invasive, timely and cost-effective manner. In a study by Togunde et al.[195], a new thin film microextraction (TFME) configuration based on C18 thin film was optimized to improve SPME sensitivity and extraction kinetics for in vivo determinations of trace pharmaceuticals in fish tissue, and C18 TFME phase successfully quantified fluoxetine, venlafaxine, sertraline, paroxetine, and carbamazapine in muscle of living fish at concentrations ranging from 1.7 to 259 ng/g. Reproducibility of the method in spiked fish muscle was 9–18% RSD with limits of detection and quantification ranging from 0.08 to 0.21 ng/g and 0.09 to 0.64 ng/g (respectively) for the analytes examined. The complexity of matrix effects (ME) in food sample, such as fish tissues, is an issue needing to be considered. An isotopic internal standard (IIS) method was developed, with the strengths and limitations of the approach discussed. This study provides a framework for applying SPME within complex sample systems where the influences of ME are inevitable, thus ensuring more accurate quantitation of PPCPs during fish tissues samples [196]. Moreover, Space-Resolved SPME (SR-SPME) technique utilized miniaturized segmented fibers was proposed by Zhang et al., and then was simultaneously applied to PPCPs analysis [197] and relative bioaccumulations [198] in adipose and muscle tissue of fish. Systematic testing over increasing levels of in vitro and in vivo complexity demonstrated the feasibility, accuracy, and efficiency of this approach. The segmented design of the SPME fibers and stepwise successive esorption procedure offer not only high spatial and temporal resolution but also increased capability for high-throughput parallel sampling with a single probe, which suggests the potential for depth-profiling studies in complicated biological systems. Very recently, direct detection of fluoxetine and its metabolite norfluoxetine in living fish brains was also realized for the first time by using a novel solid-phase microextraction fiber, which was prepared by mixing the polyelectrolyte in the oligomer of silicone rubber and followed by in-mold heat-curing [199]. The polyelectrolyte was finally encased in microcapsules dispersed in the cured silicone rubber (Fig. 3). The fiber exhibited excellent interfiber reproducibility (5.4-7.1%, n = 6), intrafiber reproducibility (3.7-4.6%, n = 6), and matrix effect-resistant capacity. Due to the capacity of simultaneously extracting the neutral and the protonated species of the analytes at physiological pH, the fiber exhibited high extraction efficiencies to fluoxetine and norfluoxetine. Beside the fish sample, in vivo SPME was recently expanded for PPCPs evaluation in vegetable samples. Chen et al, [200] used in vivo SPME with PDMS fiber to investigate the environmental fates of synthetic musks in fish and aloes. The validation of the proposed SPME was demonstrated through comparing the extraction results with liquid extraction method. In this work, the uptake and elimination behaviors, as well as the transferable capacities, of SMs in living fish and aloe were revealed. Fish muscle was approximately 100–2000 times more efficient in accumulating SMs than was aloe leaf, and nitro musks showed a higher bioaccumulation potential than did polycyclic musks in biota. In addition, the transferable capabilities of SMs by root uptake in aloe were poor. This investigation also showed that both nitro musks and polycyclic musks that accumulated in biota exhibited excellent elimination rates in clean water.

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3.2.3. Endogenous substances Except for contaminants analysis, endogenous substances of food sample, mainly focused on edible plant, were successfully detected by SPME recently, but the relative studies were few. For instance, a multilayer interparticle linking hybrid MOF-199 SPME fiber was prepared for plant hormone ethylene analysis in grapes, wampees, blueberries and durian husks [201]. Furthermore, a new poly(acrylamide-co-ethylene glycol dimethacrylate) (poly(AM-co-EGDMA)) coating was prepared for the preconcentration of 24-epibrassinolide (24-epiBL), which represents a new sixth class of plant hormones with wide occurrence in plant samples, from pollen samples [202]. Importantly, the novel SPME probe based on phenylboronic acid functionalized carbon nanotubes was proposed or ultrasensitive carbohydrate determination in living aloe leaf without any expensive enzymes or tedious pretreatment procedure [203] (Fig. 4). The coating of the proposed probe possessed a 3D interconnected porous architecture formed by the stacking of CNTs. As a result, the binding capacity toward carbohydrates was excellent. The proposed approach was demonstrated to be much superior for most carbohydrate sensors, including higher sensitivity, wider linear range, and excellent qualitative ability in multi-carbohydrate systems. Thus, this approach opens up new avenues for the facile and efficient recognition of carbohydrates in food sample as well as for important applications such as glycomics.

3.2.4. Other contaminants Foods can sometimes be contaminated with other pollutants mainly originating from two aspects: naturally occurring and man-made hazardous chemicals [186].These contaminants cause threats to human health in diverse extent, hence it is essential to monitor them in foods to reduce human health risks. Polycyclic aromatic hydrocarbons (PAHs), carcinogenic to humans, can be produced from food processing, packaging materials and other environmental sources. Robles-Molina et al.[159] applied HS-SPME method to extracting PAHs in fruit-based soft-drinks. Thirteen PAHs, extracted in polyacrylate (PA) fiber, were selectively identified and quantified low to ng/L level by GC-MS/MS) using a triple quadrupole analyzer in the multiple reaction monitoring (MRM) acquisition mode. Recently, Menezes et al. [204] developed a cold fiber (CF) SPME sampling method with GC/MS to identify 16 PAHs in artisanal cachaca. Compared with conventional approaches, the proposed method extracted higher amounts of PAHs in a single extraction procedure. PAHs in 29 artisanal cachaca samples collected in Brazil were analyzed by this method and the health risks associated with PAR exposure were assessed by the benzo[a]pyrene equivalent (BaPeq) value calculation. Finally, different sources of contamination in cachaca were rapidly discriminated by Principal component analysis (PCA). Banned dyes have been attracting much attention from food scientists and other related communities due to increasing food safety occurrences caused. Banned dyes in food samples can arise from environmental pollutants or illegal adulteration. Tian et al. [205] developed a two-step SPME technique using a coacervation phase of the anionic surfactant sodium dodecyl benzene sulfonate and diatomite bonded Fe3O4 magnetic nanoparticles (DBMNPs) for preconcentration and extraction of trace amounts of malachite green (MG) in flesh of fish. The extracted surfactant-rich phase could be readily separated in a magnetic field and then was diluted with 21

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ethanol before being measuring its absorbance by spectrophotometer at 624 nm with a linear range from 2 ng/mL to 180 ng/mL. A new SPME coating with carboxy graphene (G-COOH) on a stainless steel wire was prepared by Wang et al. [206] for the determination of methylene blue (MB). This SPME was coupled to electrochemiluminescence detection of MB to offer a low LOD of around 45 pM in original samples. Wang et al. [207] designed a method, ionic liquid-based matrix solid-phase dispersion homogeneous liquid-liquid microextraction (IL-based MSPD-HLLME), specifically for the extraction of four banned dyes (safranine O, auramine O, chrysoidin and rhodamine B) in condiment samples. HPLC was applied to separating and selectively determining the four analytes with LODs between 6.7 and 26.8 mg/kg and LOQs between 15.99 and 58.48 mg/kg. Recently, Wang et al. [208] used new monolithic fibers based on dual functional monomers (octadecyl methacrylate and vinylimidazole copolymerized with DVB) for the SPME extraction and determination of sudan dyes (I, II, III and IV) in tomato sauce and egg yolk samples by coupling with HPLC.

4. Conclusions and perspectives Solid-phase microextraction, combines sampling, isolation, concentration, and enrichment in one step, is a simple and effective sample preparation technique. It possessed advantages over conventional procedures, such as simple operation, low cost, low solvent consumption, speed, high enrichment and ease to realize automation. Owing to the high flexibility, SPME is widely used in the analysis of volatile/no-volatile compounds in complex matrix, especially in food sample. As microextraction is one of the most important research and development frontiers in modern sample pretreatment, it could expect that the applications of SPME technique on food analysis will be extended to more and more endogenous as well as exogenous substances in the further. As well known, the researches on SPME technique are mainly focused on two aspects. One is the fabrication of novel SPME coating. Coating material is the core of SPME technique and could directly determine the sensitivity and selectivity of the method. Novel sorbent materials such as carbon materials, mesoporous nanomaterials, nano inorganic oxides, ionic liquids, molecular imprinting polymers, and mesoporous organicinorganic hybrid materials are usually possessed of larger specific surface area or controllable pore size, and there are some interesting nanoscale materials being explored for applications in fabricating SPME coating. We concluded that the use of new types of materials or new strategies with novel sorbents for coating preparation will still be the research hotspot in the further. Another aspect is expanding the application of SPME technique. As mentioned above, volatile flavor compounds and some contaminants are the main analysis objects in food sample. However, the applications of SPME technique on endogenous non-volatile substances analysis are relatively rare and less works on the deep analysis of contaminants behaviors in food sample were reported. It is remarkable that the sensitivity, selectivity and accuracy of SPME are the always important tasks to extend the application for endogenous non-volatile substances, especially for the high polar compounds. The sensitivity and selectivity may be improved by the novel extraction phase, while the accuracy should be determined by calibration method. With the increasing concern on food safety as well as the successful applications of SPME in vitro or in vivo sampling technique on animal studies, it could be expected that the applications of SPME technique on food analysis will be extended to the research on the real-time monitoring the 22

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accumulation, transportation and metabolism of contaminants.

Acknowledgements This work was funded by National Natural Science Foundation of China (Grant No. 30901125, 31540087, 31401571), uropean Union project “Sustaining thical Aquaculture Trade” rant agreement No. 222889), Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation (Project No. 11DZ2280300).

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Fig. 1. (A) Micrograph of the commercial PDMS/DVB coating before extractions. (B) Micrograph of the PDMS/DVB/PDMS coating before extractions. (C) SEM images of the PDMS/DVB coating after 20 extractions cycles in grape. (D) PDMS/DVB/PDMS coating after over 130 extractions cycles in grape. (SEM surface morphology using 580× magnification). Reprinted with permission from ref 13. Copyright 2010 American Chemical Society

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Figure 2. The schematic diagram of in vivo SPME in mustard plant leaf. a) The petiole of mustard plants was pierced with a 26 gauge hypodermic needle to a depth of approximately 1.4 cm, b) two parallel samplings in both sides of the petiole were conducted at each sampling point, c) the custom-made 44 µm PDMS fiber. Reprinted with permission from ref 184. Copyright 2015 Nature Publish Group.

Figure 3. Analysis of fluoxetine and its metabolite norfluoxetine in fish by using a novel solid-phase microextraction fiber. Reprinted with permission from ref 199. Copyright 2015 American Chemical Society

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Figure. 4 (A) The in vivo sampling procedure in plant tissues with the probe based on phenylboronic acid functionalized carbon nanotubes; (B) biological macromolecules analysis in the eluent with MALDI-TOF MS; (C) carbohydrate assay in the stem of Malabar spinach and leaf of aloe; (D) in vivo continuous carbohydrate monitoring in aloe leaf using the proposed probe. Reprinted with permission from ref 203. Copyright 2016 Royal Society of Chemistry.

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Table 1 Typical application of SPME to determination of pesticides in food samples Pesticide class

Food matrix

Apple, 14 pesticides tomatoes, cucumber (multi-class） and cabbage Bovine OCPs milk

Fiber type

Mode of application type

LOD

LOQ

Linearit y

Re f

0.35-8.33 g/kg

1.15-27.7 6 g/kg

1 to 500 g/kg （ >0.99 ）

[81 1]

34

62

GC-MS

DVB/CAR/PDMS

HS-SPME

90

80

GC-ECD

Polypyrrole/montmorill onite nanocomposite

DI-SPME

4 OCPs

Cocoa powder

100 lam polydimethylsiloxane fibers

HS-SPME

CPs

Chromatograp hic

HS-SPME

Cucumber , lettuce, apple

OPPs

Extractio n temp/°C

PDMS, 100 um

2 OPPs (diazinon and fenthion)

8 OCPs

Extracti on time/min

Water convolvul MOF-199/GO fibers us and longan Cucumber , green pepper, Sol–gel molecularly Chinese imprinted polymer cabbage, eggplant， lettuce Carbon Apple nanotubes-reinforced

30

45

GC–CD–IMS

0.5 to 1.2g/L

[17 1] 0.05–10 and 0.08–10 g/ L 2.5 to 500 g/kg

0.020 and 0.035 g/L

GC-MS

[17 7] [18 0]

HS-SPME

40

80

GC-ECD

2.3–6.9 ng/L

[17 6]

HS-SPME

30

70

GC-NPD

0.017–0.77 μg/kg

[16 7]

DI-SPME

40-60

HPLC-DAD

0.09-6.00 ng/g

0.2511.00

[17 4]

40

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hollow fibre OPPs

OPPs

OCPs

19 chlorinated pesticides 4 pesticides (Fenobucarb, diazinon, chlorothaloni l and chlorpyrifos) 10 pesticides (multi-class) 8 pesticides

Cucumber and lettuce Turnip, green cabbage, French beans, eggplant, apple, nectarine and grapes Asparagu s africanus, Cleome hirta and Nymphae a nouchali

ng/g

Polypyrrole/sol–gel composite

DI-SPME

30

45

GC-NPD

1.5-10 ng/L

[16 6]

PDMS, 100 um

HS-SPME

45

70

GC–MS

0.01-2.5 g/L

[17 8]

100 μm PDMS

QuEChERS/HS-SP ME

20

60

GC-ECD GC-TOF-MS

0.102 -1.693 /L

Tomatoes

PDMS, 100 um

DI-SPME

GC-ECD

0.5-8 g/kg

5-30 g/kg

Apple

PDMS, 100 um

HS-SPME

30

60

GC-MS

0.01-0.2 g/kg

0.05-1 g/kg

DI-SPME

30

22 ± 3

HPLC-DAD

HS-SPME

70

70

GC-IDMS

Lettuce Tea

Carbowax/ templated resin (CW/TPR) PDMS, 100 um

0.8-25.6 g/kg 1.2-19.6

[17 5]

g

[17 0]

0.5-50 g/kg

[17 9]

[17 3] [17

41

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(Multi-class) 32 pesticides (Multi-class)

31 pesticides (Multi-class)

OPPs OCPs

and

OPPs OCPs

and

Fruit-base d soft drinks Fortified white wine and fortified red wine Cucumber and strawberr y Strawberr y, star fruit and guava; cucumber, tomato and pakchoi

PA

DI-SPME

ng/g

2]

GC-MS/MS

0.1-180 ng/L

[15 9] 0.16-219. 23 g/L

[16 1, 16 2]

PDMS, 100 um

DI-SPME

60

35

GC-MS/MS

0.05-72.35 g/L

PDMS, 100 um

HS-SPME

30

60

GC-ECD

0.01–1 g/L

0.05–5 g/L

[16 9]

PDMS, 100 um

HS-SPME

30

60

GC-ECD

0.01–1 g/L

0.05-5 g/L

[16 8]

HS-SPME

50

75

GC-NPD

0.007- 0.07 ng /g

[16 3]

DI-SPME

143

ambient temperatu re

MEKC

0.049-1.69 g/L

[16 0]

DI-SPME

10

ambient temperatu re

GC-MS/MS

0.6-19.6g /L

[15 8]

OPPs

Pakchoi

OH-TSO/DVB (Co-poly (hydroxy-terminated silicone divinylbenzene) coating)

11 pesticides (multi-class)

Red wine

PDMS/DVB

54 pesticides (Multi-class)

Orange, peach and DVB pineapple juices

Note: 42

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OCP, organochlorine pesticides; OPP, organophosphorous pesticides; CP, carbamate pesticides; phenyl urea pesticides (PUP) and pyrethroid pesticides (PP)； PDMS, polydimethylsiloxane; PA, polyacrylate; CAR, Carboxen; CW, Carbowax; DVB, divinylbenzene；MOF：Metal-organic framework；GO：graphite oxide； HS, headspace; DI, direct immersion； GC：gas chromatography; MS: mass spectrometry; ECD: electron capture detection; TOF: time-of-flight；NPD: nitrogen-phosphorus detector; IDMS: isotope dilution mass spectrometry; MEKC: micellar electrokinetic chromatography

43

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