Optimization of headspace solid phase microextraction (HS-SPME) for gas chromatography mass spectrometry (GC–MS) analysis of aroma compounds in cooked beef using response surface methodology

Microchemical Journal 111 (2013) 16–24

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Optimization of headspace solid phase microextraction (HS-SPME) for gas chromatography mass spectrometry (GC–MS) analysis of aroma compounds in cooked beef using response surface methodology Q.L. Ma a, N. Hamid a,⁎, A.E.D. Bekhit b, J. Robertson a, T.F. Law a a b

School of Applied Sciences, Faculty of Health and Environment Sciences, Auckland University of Technology, Auckland, New Zealand Department of Food Science, University of Otago, Dunedin, New Zealand

a r t i c l e

i n f o

Article history: Received 30 June 2012 Received in revised form 27 August 2012 Accepted 10 October 2012 Available online 16 October 2012 Keywords: Cooked beef Volatile compounds Optimization Response surface methodology SPME GC–MS

a b s t r a c t The optimization of the main experimental variables, such as equilibrium time (5–10 min), extraction time (10–50 min) and extraction temperature (20–60 °C) of a headspace solid phase microextraction-gas chromatography mass spectrometry (HS-SPME/GC–MS) procedure, for profiling volatile components in cooked beef semimembranosus muscle was evaluated using response surface methodology. A central composite circumscribed design was employed to study the effect of the experimental variables on the extraction of ten representative volatile compounds of beef flavour profile. The parameters of the models were estimated by multiple linear regressions. Results showed that the regression models generated adequately explained the data variation and significantly represented the actual relationships between the reaction parameters and the responses. Regression models of extraction temperature were the most significant factor. The optimum reaction parameters for maximum yield in cooked beef volatiles were identified from their respective contour plots. It was suggested that for optimal cooked beef volatile concentration, HS-SPME should be carried out with for 25 min at 40 °C, with 10 min equilibrium time. © 2012 Elsevier B.V. All rights reserved.

1. Introduction A beef quality survey carried out by Robbins and coworkers reported that tenderness, flavour and juiciness were the most important factors influencing consumer's eating satisfaction of beef [1]. Flavour is an important eating characteristic when meat products are served [2]. A large multiple-city study found flavour to be the most important factor that influenced consumer's meat buying habits and preferences when tenderness was held constant [3]. Meat flavour is thermally derived, because uncooked meats have little or no aroma and only possess what is described as “a blood-like taste” [4]. During cooking, the volatile compounds generated between non-volatile components of lean and fatty tissues of meat through a complex series of thermally induced reactions, contribute to the aroma attributes and characteristic flavours of meat [5]. Volatile compounds formed during cooking determine the aroma attributes that contribute to the characteristic flavour of meat. A large number of volatile compounds have been identified in beef than in other meats. However this is reflected by the larger number of publications for beef compared to pork, sheep meat or poultry [6]. According to Mottram, ⁎ Corresponding author at: School of Applied Sciences, Faculty of Health and Environment Sciences, Auckland University of Technology, Private Bag 92006, New Zealand. Tel.: +64 9 921999x6453; fax: +64 9 9219627. E-mail address: [email protected] (N. Hamid). 0026-265X/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.microc.2012.10.007

over 1000 of the volatile compounds identified in beef, pork, mutton, and chicken can be grouped into chemical groups [5]. These groups include aldehydes, alcohols, ketones, hydrocarbons, phenols, carboxylic acids, esters, lactones, furans, pyrans, pyrroles, pyridines, pyrazines, oxazoles, oxazolines, thiophenes, thiazoles, thiazolines and other nitrogen or sulphur containing compounds. Solid phase microextraction (SPME) is a popular technique used in flavour analysis as it is a simple, low-cost, solvent-free and sensitive technique for the analysis of volatile compounds with a wide boiling point range without artefact formation [7]. SPME involves the extraction of volatile compounds out of liquid samples or out of the headspace of solid or liquid samples onto a fused-silica fibre coated with a polymeric phase. Hence the selection of the fibre and SPME extraction conditions can affect the sensitivity and accuracy of SPME analysis. Headspace SPME has been used in the extraction of volatile compounds from pork [8–10], beef [11–13], chicken [14], lamb [15] and goat [16]. However HS-SPME is a technique that depends upon the equilibrium of experimental conditions such as heating temperature, extraction time, sample volume, concentration of volatiles, and sample matrix and uniformity that necessitates further optimization [17]. As the HS-SPME mechanism is based on the equilibrium of analytes among three phases (fibre coating, headspace and sample), the analysis of headspace volatile compounds by HS-SPME is greatly influenced by the vapour pressure of flavour volatiles in the vial. The main variables that influence the vapour pressure and equilibrium

Q.L. Ma et al. / Microchemical Journal 111 (2013) 16–24

of the volatile components in the headspace have been reported to be extraction temperature, equilibrium time and extraction time [18]. Other parameters, which affect the extraction process include salting, pH, and organic solvent content in water [19]. However although an increase in extraction temperature increases the rate of extraction, it can decrease the distribution constant [20] and conversely cause a decrease in the sensitivity of the extraction process. Hence a well-balanced compromise between sensitivity and extraction rate with regard to the extraction temperature can be obtained by careful optimization of the parameters involved that will reduce the number of experiments to achieve reproducibility [21]. Response surface methodology (RSM) allows an evaluation of the effects of many explanatory variables and their interactions on the response variables [22]. RSM has been used widely in research particularly for the optimization of conditions and processes [23]. The response surface framework has become the standard approach for much of the experimentation [24] and the technique has been used extensively in studying the volatile components of chili peppers [25] and longan [18]. The knowledge of beef production factors that can affect the flavour of cooked beef meat is of significant interest towards achieving a high-quality and differentiated beef product. Hence the development of more specific and efficient methodologies is necessary to analyze cooked meat aroma compounds, which would be used as routine analysis. To date there have been no studies that have examined the primary and secondary interaction effects of SPME variables on the equilibrium headspace concentration of cooked beef volatile compounds. Hence, the main objective of the present study was to optimize HS-SPME conditions for the quantitative analysis of ten target volatile compounds in cooked beef meat. The effects of HS-SPME variables, namely, equilibrium time, extraction time and extraction temperature were investigated using a central composite response surface design. 2. Materials and methods 2.1. Materials and chemicals Hot-boned semimembranosus muscles from Holstein–Friesian cows (>5 years old) were randomly selected on the day of slaughter, approximately 2 to 3 h following slaughter, from Alliance Group Ltd. (Pukeuri Plant, Oamaru). Holstein–Friesian cows were raised on pasture in Central Otago, New Zealand. The samples were vacuum-packed, and stored at 2 °C. Samples for volatile analysis from University of Otago were frozen in liquid nitrogen, vacuum packed and stored at −30 °C until analysis. Frozen samples were air freighted and couriered to the laboratory at AUT University for volatile flavour analysis. 2.2. Extraction of cooked beef volatile compounds by HS-SPME Volatile extraction by HS-SPME was carried out according to the modified method of Machiels and Istasse [12]. Beef samples (2.0±0.1 g) were minced using a coffee grinder (Model CG2B, Breville, Australia) and placed in 10 ml flat bottom headspace vials fitted with a PTFE/ silicone septum and crimp cap (Supleco, USA) that contained 6% (w/w) sodium chloride. 1, 2-dichlorobenzene (2 μl, 1.3 ppm) in a 250 μl flat bottom insert was used as an internal standard and placed in the headspace vial. The headspace vial was heated using a plate heater at 80 °C for 10 min. The SPME fibre was preconditioned prior to analysis at 250 °C for 30 min. After equilibration at a specified temperature (20–60 °C) for a specified time (5–15 min), the volatile components in the samples were adsorbed onto a 50/30 μm layer of divinylbenzene–carboxen–polydimethylsiloxane (Supelco Co., Bellefonte, USA) fibre that was exposed to the sample headspace for a specified time (10–50 min).

17

2.3. GC-FID and GC–MS analyses After extraction, the SPME device was removed from the headspace vial and inserted directly into the injection port of the GC. The SPME fibre was immediately thermally desorbed for 3 min at 250 °C in the SPME-specific liner of the injector port of either the GC-FID and GC–MS. The volatile flavour compounds of cooked beef were initially tentatively identified using a GC–MS. Analysis of the volatile flavour compounds of cooked beef for the HS-SPME optimization experiments were analyzed using a GC equipped with a flame ionization detector (FID). 2.3.1. GC-FID The Shimadzu GC-17A was equipped with a FID and a ZB-5 low bleed/ MS fused-silica capillary column (5%-phenyl-95%-dimethylpolysiloxane phase, 30 m × 0.53 mm × 1.50 μm) (Phenomenex, Inc, USA). Nitrogen was the carrier gas. The pressure was set to 43 Pa, flow rate was 7 ml/min, and oven temperature was held for 2 min at 40 °C, increased to 250 °C at 5 °C/min, and held for 3 min at this temperature. 2.3.2. GC–MS The Trace GC Ultra (Thermo Scientific, USA) was equipped with a DSQ series mass spectrometer (Thermo Scientific, USA). The GC–MS was installed with a VF-5 ms low bleed/MS fused-silica capillary column (5%-phenyl-95%-dimethylpolysiloxane phase, 60 m × 0.25 mm× 0.25 μm) (Phenomenex). Helium was the carrier gas with a constant flow rate of 1.5 ml/min in the GC–MS. Chromatographic conditions were as follows: the oven was held for 2 min at 40 °C, heated to 250 °C at 5 °C/min, and held 3 min at this temperature. The mass spectrometer operated in the electron impact mode with a source temperature of 200 °C, an ionizing voltage of 70 eV, and a transfer line temperature of 250 °C. The mass spectrometer scanned masses from 48 to 400 m/z at a rate of 3.41 scan/s. Peak identification was carried out by comparison of the volatile sample mass spectra with spectra in the NIST/EPA/NIH Mass Spectral Database (National Institute of Standards and Technology, Gaithersburg, MD, Version 2.0a, 2002, USA), or NIST web book (http://webbook.nist. gov/chemistry/). To confirm the identity of volatile compounds, the retention index (RI) was calculated for each volatile compound using the retention times of a homologous series of C7 to C30 n-alkanes (1000 μg/ml in hexane from Supelco) and comparing the RI with compounds analyzed under similar conditions in previous literature. The approximate quantities of the volatiles were estimated by comparison of their peak areas with that of the 1, 2-dichlorobenzene internal standard using a response factor of 1. 2.4. Experimental design and data analysis The standard approach to the analysis of experimental design data is to determine a list of main and interaction effects. In the present study, DVB-CAR-PDMS coating fibre was selected to determine the influence factors of the HS-SPME extraction efficiency of flavour compounds from cooked beef meat. A 50/30 um CAR/DVB/PDMS SPME fibre was chosen because of its higher reproducibility, especially in the analysis of flavour compounds with larger levels of higher boiling point compounds with molecular weights between 40 and 275 [12,26,27]. The effect of three SPME variables, namely, equilibrium time (x1, 5–10 min), extraction time (x2, 10–50 min) and extraction temperature (x3, 20–60 °C) were evaluated using response surface methodology (RSM). A total 20 treatments were analyzed for the optimization procedure based on a three-factor central composite design (CCD) (Table 1). Experiments were randomized in order to minimize the effect of unexplained variability in the actual responses due to extraneous factors. The centre point was repeated six times to determine the

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Table 1 The optimization of the HS-SPME experimental conditions.

Table 2 The identified volatile flavour compounds of cooked beef headspace using HS-SPME.

RunOrder

Equilibrium time

Extraction time

Extraction temperature

1a 2 3 4 5a 6 7 8a 9 10 11 12a 13 14 15 16 17 18 19a 20a

7.5 5.0 10.0 10.0 7.5 5.0 10.0 7.5 7.5 7.5 7.5 7.5 5.0 7.5 10.0 5.0 10.0 5.0 7.5 7.5

30 10 10 50 30 50 30 30 30 10 50 30 30 30 10 50 50 10 30 30

40 20 60 20 40 60 40 40 20 40 40 40 40 60 20 20 60 60 40 40

a

: Central point.

No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

repeatability of the method [28]. The response surface model was worked out using the following equation [29]:

20 21 22

2

Y ¼ β0 þ ∑βi X i þ ∑βii X i þ ∑βij X i X j where Y is the response value predicted by the model; β0 is a constant; and βi, βii and βij are the linear, quadratic and interaction coefficients, respectively. In this model, x1, x2 and x3 are the independent variables. The adequacy of the model was determined using model analysis, lack-of-fit tests and coefficients of determination (R2) as outlined by previous studies [29]. The experimental design and data analysis were performed using the Minitab statistical package (Release 16; Minitab Inc., PA, USA). 3. Results and discussion 3.1. Preliminary optimization experiments As shown in Table 2, a total of 24 compounds extracted using DVBCAR-PDMS coating fibres were identified by GC–MS, which have been reported as major volatile compounds of cooked beef [12,13]. These included 11 aldehydes, 2 ketones, 2 furans, 4 nitrogen and sulphur compounds, 1 alkane, 3 alcohols and 1 terpene. 3.1.1. Effect of desorption time In order to determine the optimum desorption time, the fibre was desorbed at different times (30 s, 2 min, 30 min) in the injection port at 250 °C. Peak areas were compared for target compounds and a blank fibre extraction was performed after each analysis to check for remaining analytes. A desorption time of 30 s was sufficient to remove the volatiles completely from the fibre (results not shown). Machiels and Istasse [12] reported that highly volatile compounds were not affected by desorption time, and less volatile compounds needed more time to desorb. Moon and Li-Chan [30] reported desorption conditions for HS-SPME analysis of volatile compounds in simulated beef flavour to be 3 min desorption time, and 250 °C desorption temperature. 3.1.2. Effect of extraction temperature and time High temperature provides enough energy for volatile compounds to overcome energy barriers, which bind them to the matrix, and increases vapour pressure for the mass transfer process [31]. This facilitates the release of volatile compounds into the headspace. The effects

23 24

Volatile compounds Aldehydes 3-Methylbutanal 2-Methylbutanal Pentanal Hexanal Heptanal Benzaldehyde Octanal Benzeneacetaldehyde Nonanal (E)-2-Nonenal (E)-2-Decenal Nitrogen and sulphur compounds Methylprazine 2, 5-Dimethylpyrazine 2-Acetylthiazole 2,3-Diethyl-5-methylpyrazine Alcohols 1-Octen-3-ol 2-Ethyl-1-hexanol 1-Octanol Terpenes Limonene Ketones 2,3-Pentanedione 2-Heptanone Alkanes Undecane Furans 2-Ethyl-furan 2-Pentyl-furan

RIa

Identificationb

656 664 694 800 901 965 1003 1049 1104 1162 1263

MS + RI MS + RI MS + RI MS + RI MS 85% MS 85% MS 85% MS 85% MS 85% MS 85% MS 85%

825 920 1023 1171

MS + RI MS + RI MS + RI MS + RI

979 1029 1070

MS + RI MS + RI MS + RI

1033

MS + RI

691 892

MS + RI MS + RI

1098

MS + RI

696 992

MS + RI MS + RI

a RI on a VF-5 ms column, was calculated in relation to the retention time of n-alkane (C7–C30) series. b MS, tentative identification by comparison of mass spectrum with NIST library spectrum (over 85%); MS + RI, mass spectrum identified using NIST mass spectral database and RI agree with literature values (Machiels and Istasses [12]).

of temperature and extraction time were evident from the chromatograms of the extractions performed at 40 and 60 °C for 20 and 40 min (Fig. 1). An increase in the peak chromatographic area was found, especially with the less volatile compounds at higher temperature and longer extraction time. The increase in volatile compounds can be explained by the fact that higher temperature tends to drive the volatiles from the sample matrix to the fibre coating. As seen in Fig. 1 (d), high boiling point compounds such as (E)-2decenal, had higher peak areas at higher temperature and longer extraction time. Headspace sampling was further carried out at 60 °C for 20, 30, 40 and 50 min. Longer extraction times did not have much effect on the low boiling point volatile compounds, such as 3-methylbutanal and methylpyrazine (Fig. 2). 2-acetylthiazole continued to increase after 40 min but (E)-2-nonenal, heptanal and hexanal decreased after 40 min. Hence further HS-SPME optimization was further carried out using extraction time and extraction temperature as variables.

3.2. Optimization of SPME parameters using response surface models Preliminary methods of HS-SPME optimization evaluated the effect of one variable whilst others were kept constant during the experiments. The drawback of this type of experiment is that one variable does not determine what happens if other variables change [32]. The response surface design enables the effects of several variables to be estimated simultaneously. HS-SPME mechanism is based on the equilibrium of analytes among three phases (fibre coating, headspace and sample). Therefore, the analysis of headspace volatile compounds by HS-SPME is greatly influenced by the vapour pressure of flavour sample in the vial. The main factors influencing the vapour pressure and

Q.L. Ma et al. / Microchemical Journal 111 (2013) 16–24

(b) 40 min, 40 oC

4.00E+07

4.00E+07

3.00E+07

3.00E+07

Peak area

Peak area

(a) 20 min, 40 oC

19

2.00E+07

2.00E+07

1.00E+07

1.00E+07

0.00E+00

0.00E+00

(c) 20 min, 60 oC

(d) 40 min, 60 oC

4.00E+07 4.00E+07

(E)-2-Decenal

3.00E+07

Peak area

Peak area

3.00E+07

2.00E+07

2.00E+07

1.00E+07

1.00E+07

0.00E+00

0.00E+00

Fig. 1. Gas chromatography–mass spectrometry chromatograms of the volatiles in cooked beef meat using SPME.

5.00E+07 4.50E+07 4.00E+07

Peak area

3.50E+07 3.00E+07 2.50E+07 2.00E+07 1.50E+07 1.00E+07 5.00E+06 0.00E+00

0

10

20

30

40

50

60

Extraction time (min) 2-Acetylthiazole

(E)-2-Nonenal

Heptanal

6.00E+06

Peak area

5.00E+06 4.00E+06 3.00E+06 2.00E+06 1.00E+06 0.00E+00 0

10

20

30

40

50

60

Extraction time (min) methylpyrazine

3-Methylbutanal

2,5-Dimethylpyrazine

Hexanal

Fig. 2. The peak area of key volatile compounds at different extraction times (20, 30, 40 and 50 min).

equilibrium of the volatile components in the headspace are equilibrium time, extraction time and extraction temperature [27]. Response surface plots (Figs. 3–6) showed how the target cooked meat volatiles (response variables) related to extraction time, extraction temperature and equilibrium time used in the SPME method using a model equation. Contour plots show how response variables relate to two continuous design variables whilst holding the rest of the variables in a model at certain settings and are useful for establishing operating conditions that produce desirable response values [33]. In this study, an overlaid contour plot (Fig. 7) of the response variables in the controllable factors space resulted in the area, which gives the best possible yield for each of the target cooked meat volatiles [28]. The results showed that the estimated regression coefficients for the response variables, along with the corresponding R 2 as well as F- and p-values for lack of fit, are given in Table 3. Each response (Y) was assessed as a function of main, quadratic and interaction effects of the equilibrium time (x1), extraction time (x2) and extraction temperature (x3). The results indicated that the final reduced models were significantly (p b 0.05) fitted for ten of the response variables studied with relatively high R 2, ranging from 0.8455 to 0.9740, and there was an insignificant (p > 0.05) lack of fit for the regression models fitted for the total response of ten individual response variables (Table 3). The closer the value of R 2 to unity, the better the empirical models fitted to the actual data. On the other hand, the smaller the value of R 2, the less relevance the dependent variables in the model have in explaining the behavior of variations [34]. Thus, all response variables could be accurately explained by the response-surface model as a function of three SPME variables (equilibrium time, extraction time and extraction temperature). In general, the single effect of extraction temperature played the most significant (p b 0.05) role in the total response of cooked beef flavour compounds (Table 3). The quadratic effect of extraction temperature and interaction effects between three factors were also significant (p b 0.05).

55

15 0 5.0

40 25 x2 7.5 x1

10.0

10

3 2 55

1 5.0

40 25 x2 7.5 x1

10.0

10

55

0

40 25 x2

5.0

7.5 x1

10.0

10

1.5 1.0 0.5

55

0.0

40 25 x2

5.0

10

2,3-Pentanedione

30

20

2-Pentyl-furan

45

Methylpyrazine

2-Ethyl-furan

2-Methylbutanal

Q.L. Ma et al. / Microchemical Journal 111 (2013) 16–24

3-Methylbutanal

20

7.5 x1

10.0

4 3 2

55 40 25 x2

1 5.0

7.5 x1

10.0

10

1.25 1.00 0.75

55 40 25 x2

0.50 5.0

10

7.5 x1

10.0

10

Fig. 3. Response surface plots of significant (p b 0.05) interaction effects of equilibrium time and extraction time on the 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione, 2-ethyl-furan, methylpyrazine and 2-pentyl-furan.

20

60

0

40 x3

5.0

7.5 x1

10.0

20

30 20 10

60

0

40 x3

5.0

4.5 3.0 1.5 0.0 5.0

60 40 x3 7.5 x1

10.0

20

2,3-Pentanedione

40

the linear effect of equilibrium time (p b 0.05). The yields were also linearly related to the interaction between equilibrium time, extraction time, and interaction between equilibrium time and

7.5 x1

10.0

20

Methylpyrazine

2-Methylbutanal

60

2-Ethyl-furan

3-Methylbutanal

3.2.1. Effect of equilibrium time The extraction yields of 3-methylbutanal, 2-methylbutanal, 2, 3pentanedione, and methylpyrazine were found to be a function of

4.5 3.0 1.5

60

0.0

40 x3

5.0

7.5 x1

10.0

20

1.2 0.9 0.6

60

0.3 5.0

40 x3 7.5 x1

10.0

20

Fig. 4. Response surface plots of significant (p b 0.05) interaction effects of equilibrium time and extraction temperature on the 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione, 2-ethyl-furan and methylpyrazine.

50 25

60

0

40 x3 25 x2

40

20

40 20 60 0 10

55

2-Ethyl-furan

10

40 x3 25 40 x2

55

3.0 60

0.0 10

40 x3 25 40 x2

55

4.5 3.0 1.5

60

0.0

40 x3

10

20

4.5

1.5

21

2,3-Pentanedione

75

Methylpyrazine

2-Methylbutanal

3-Methylbutanal

Q.L. Ma et al. / Microchemical Journal 111 (2013) 16–24

20 55

1.5 1.0 60

0.5

40 x3 10

20

25 40 x2

25 40 x2

55

20

Fig. 5. Response surface plots of significant (p b 0.05) interaction effects of extraction time and extraction temperature on the 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione, 2-ethyl-furan and methylpyrazine.

1.5 60

0.5 25 x2

40

55

0.3

0.9 0.6

60

0.3 10

20

Diethyl-5-methylpyrazine

10

40 x3

1.2

40 x3 25 x2

40

55

0.2 0.1

60

0.0

40 x3

10

20

25 x2

40

55

20

0.45

0.3 0.2 0.1

60

0.0

40 x3

10

25 x2

40

55

20

(E)-2-Decenal

1.0

25 min and 30 °C, respectively. In order to obtain a high level of response areas, an equilibrium time of 10 min was found to be sufficient in this study.

(E)-2-Nonenal

Benzeneacet aldehyde

2-Pentyl-furan

extraction temperature (p b 0.05) (Table 3). Figs. 3 and 4 showed that the high level of these response areas tended to increase with decreasing extraction time and extraction temperature of less than

0.30 0.15 0.00 10

60 40 x3 25 x2

40

55

20

Fig. 6. Response surface plots of significant interaction effects of extraction time and extraction temperature on 2-pentyl-furan, benzeneacetaldehyde, (E)-2-nonenal, 2,3-diethyl-5-methylpyrazine and (E)-2-decenal.

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60

Predicted Responsesa 3-Methylbutanal

27.4954

0.936919

2-Methylbutanal

14.4028

0.978404

2,3-Pentanedione

2.1501

0.999984

2-Ethyl-furan

2.1000

0.964934

Methylpyrazine

0.379

0.933822

2-Pentyl-furan

1.0948

0.975085

Benzeneacetaldehyde

1.0547

0.993752

(E)-2-Nonenal

0.1743

0.878729

2,3-Diethyl-5-methylpyrazine

0.1563

0.842212

(E)-2-Decenal

0.1190

0.951960

50

Extraction Temperature

Desirability

40

30

Composite desirability

20 10

a

20

30

40

50

b

0.944320

predicted response is the ratio of peak areas of individual volatile compound to internal standard

Extraction Time b

Composite desirability=average of each response desirability

Fig. 7. Overlaid contour plots showing the effect of extraction time and temperature on variable responses (equilibrium time hold value 10 min).

in roast beef [35] was significantly (p b 0.05) affected by the quadratic effect of extraction time. Figs. 3 and 5 clearly showed a non-linear relationship between the significant (pb 0.05) interaction effect of the SPME variables on cooked beef volatile compounds. It can be observed that the peak area

3.2.2. Effect of extraction time The results indicated that extraction time had a significant effect (p b 0.05) on most of the targeted flavour compounds, except for 2-pentyl-furan, benzeneacetaldehyde and (E)-2-nonenal. In addition 2,3-diethyl-5-methylpyrazine, which was reported to be important

Table 3 The significance probability (p-value, F-ratio) of regression coefficients, R2, and lack of fit in the final reduced models. No

Volatile compounds

1

3-Methylbutanal

2

2-Methylbutanal

3

2,3-Pentanedione

4

2-Ethyl-furan

5

Methylpyrazine

6

2-Pentyl-furan

7

Benzeneacetaldehyde

8

(E)-2-Nonenal

9

2,3-Diethyl-5-methylpyrazine

10

(E)-2-Decenal Total

Main effects

p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value F-value p-value p-value

Quadratic effects

x1

x2

x3

(x1)

0.005a 15.09 0.004a 15.55 0.007a 12.62 – – 0.012a 10.33 – – 0.045a 5.63 – – – – – – – –

0.000a 38.06 0.001a 31.25 0.000a 36.66 0.019a 8.58 0.004a 16.39 – – – – – – 0.018a 8.72 0.045a 5.64 – –

0.000a 111.36 0.000a 105.73 0.000a 118.88 0.000a 67.27 0.028a 7.19 0.001a 25.43 0.005a 14.77 0.000a 63.53 0.006a 14.18 0.000a 32.27 0.014a 9.93

– – – – – – – – – – – – – – – – – – – – – –

2

(x2)

2

– – – – – – – – – – – – – – – – 0.022a 8.04 – – – –

Interaction effects (x3)

2

0.034a 6.52 – – – – – – 0.030a 6.96 – – – – – – – – – – 0.028a 7.13

x1 x2

x1 x3

x2 x3

0.009a 11.65 0.010a 11.05 0.011a 10.93 0.013a 10.27 0.000a 123.33 0.042a 5.88 – – – – – – – – 0.005a 15.03

0.003a 16.88 0.004a 15.84 0.003a 18.22 0.035a 6.42 0.000a 33.87 – – – – – – – – – – 0.003a 18.32

0.000a 35.14 0.001a 26.28 0.003a 17.72 0.018a 8.80 0.000a 38.61 – – – – – – – – – – 0.000a 33.54

Regression

Lack of fit

R2

0.000 27.18 0.000 24.36 0.000 25.94 0.001 12.05 0.000 29.79 0.013 5.46 0.028 4.18 0.003 8.97 0.020 4.72 0.010 5.94 0.000 29.77

0.052b 8.81 0.066b 7.35 0.998b 0.04 0.958b 0.17 0.293b 2.06 0.346b 1.73 0.358b 1.66 0.885b 0.30 0.065b 7.45 0.480b 1.16 0.079b 6.37

0.9708 0.9677 0.9681 0.9369 0.9740 0.8911 0.8455 0.9176 0.8547 0.8724 0.9734

x1, x2 and x3: the main effect of equilibrium time, extraction time and extraction temperature, respectively. (x1)2, (x2)2 and (x3)2: quadratic effect of equilibrium time, extraction time and extraction temperature, respectively. x1 x2,: interaction effect of equilibrium time and extraction time, x1 x3: interaction effect of equilibrium time and extraction temperature, x2 x3: interaction effect of extraction time and extraction temperature. a Significant p b 0.05. b Insignificant p > 0.05.

Q.L. Ma et al. / Microchemical Journal 111 (2013) 16–24

of 3-methylbutanal, 2-methylbutanal, 2, 3-pentanedione 2-ethyl-furan and 2-pentyl-furan increased in a quadratic manner with the increase in equilibrium time and decrease in extraction time (Fig. 3). However the peak area of methylpyrazine reached the lowest response area at 5.2 min equilibrium time and 48 min extraction time. In addition, Fig. 5 indicated that the peak areas of 3-methylbutanal, 2-methylbutanal, 2, 3-pentanedione and 2-ethyl-furan increased in a quadratic manner with the decrease in equilibrium time and extraction time. The highest levels of methylpyrazine were obtained with an extraction temperature of 55 °C and extraction time of 15 min (Fig. 5). It was identified in pork arising from a Maillard-type reaction between amino acids and sugars and demonstrated the requirement for formation of this compound at high temperature [36]. A longer extraction time favoured the occupation of more sites on the fibre by analyte molecules, but prolonged time when all sites are occupied does not affect the pre-concentration efficiency and sometimes can cause desorption [21]. 3.2.3. Effect of extraction temperature Generally, the optimal extraction temperature depends on matrix composition, its components and the stationary phase used. In this study, the effect of extraction temperature (20–60 °C) was determined to establish the effect of matrix interference on the cooked beef volatile compounds. The results indicated that extraction temperature had a significant (pb 0.05) effect on all the targeted flavour compounds (Table 3). 3-methylbutanal, 2-methylbutanal and 2,3pentanedione were the most significantly (pb 0.05) affected by extraction temperature as indicated by the high F-values. The variation in 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione, 2-ethyl-furan and methylpyrazine could also be explained by a non-linear function, given by significant (p b 0.05) interaction effect of the SPME variables namely between extraction temperature and equilibrium time, and between extraction temperature and extraction time (Figs. 4 and 5). In general, heating provides energy for analyte molecules to overcome energy barriers that tie them to the matrix [37]. This will enhance the mass transfer process, increase the vapour pressure of the analytes [27], and thereby facilitate the release of analytes into the headspace [31]. However, the concentration of 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione and 2-ethyl-furan decreased with increasing extraction temperature (Figs. 4 and 5). Although high temperature is good for the release of analytes from their matrix, it can adversely affect the adsorption of analytes by the coating due to decrease in the partition coefficients. Therefore a smaller amount of volatile is extracted at equilibrium when the temperature is raised [31]. In addition, an increase in extraction temperature increased the rate of extraction that results in a decrease in the distribution constant [20]. This conversely causes a decrease in the sensitivity of the extraction process. A well-balanced compromise between sensitivity and extraction rate with regard to the extraction temperature can be obtained by careful optimization. 3.2.4. Optimization of extraction conditions Time and temperature are parameters closely related to each other [38]. An increase in temperature enables shorter exposure time, and thus accelerates the analysis time. Hence, it is important to evaluate the relationship between extraction time and temperature. Fig. 5 indicated that the lower boiling points volatile compounds, such as 3-methylbutanal, 2-methylbutanal, 2,3-pentanedione and 2-ethyl-furan, had high response areas at short extraction time and lower extraction temperature. In contrast, the higher boiling point volatiles, such as, (E)-2-nonenal and (E)-2-decenal, had high response areas at longer extraction time and higher extraction temperature (Fig. 6). The dramatic change with extraction time is due to the fact that an increase in temperature results in an increase of the analyte's Henry's

23

Constant, an increase in the diffusion coefficient, and a decrease in the amount extracted at equilibrium. This decrease is associated with the fact that the distribution constant decreases when the temperature increases. It is important to carefully optimize the extraction temperature for the shortest extraction times and for acceptable sensitivities [39]. Areas of optimum performance of cooked beef volatile compounds analysis were located by overlaid contour graphs for extraction time and extraction temperature, with equilibrium time value held at 10 min (Fig. 7). Since the optimum condition variables for each response did not fall exactly in the same area in the two-dimensional space formed by the different condition levels, it was surmised that the optimization range between 10–35 min, 30–55 °C and 35–50 min, 20–30 °C was acceptable. Superimposing the individual contour plots for the response variables resulted in the identification of a region (shown by the white coloured area), which satisfied all constraints (Fig. 7). However, it may not be advisable to set the experimental conditions very rigidly and therefore a moderation level was given to each response with a composite desirability of 0.944320. Hence, the final optimum conditions predicted to result in the most desirable equilibrium headspace concentrations for target cooked beef volatile compounds were found to be 10 min equilibrium time, 25 min extraction time and 40 °C extraction temperature using a CAR/DVB/PDMS fibre. A study by Moon and Li-Chan [30] reported a sensitive and reproducible HS-SPME method for simulated beef flavour made from a blend based on vegetable proteins with other vegetable origin materials, and the beef character derived from Maillard reaction during roasting of the protein fractions. The conditions reported in that study: adsorption at 60 °C for 60 min on 50/30 lm DVB/CAR/PDMS, followed by desorption of extracted volatiles at 250 °C for 3 min were quite different to that reported in this study on cooked meat volatiles that could be attributed to the different food matrix used in these two studies. 4. Conclusion A total of 24 compounds extracted using a CAR/DVB/PDMS fibre was successfully identified using GC–MS. The optimum HS-SPME conditions for the extraction of 10 target flavour compounds in cooked beef that significantly contributed to the regression models using a comprehensive experimental design were determined in order to study the effect of SPME variables, namely, equilibrium time, extraction time and extraction temperature. The response-surface analysis showed significant (pb 0.05) relationships between the SPME variables and the component headspace concentrations, with regression equations of relatively high R2 values, ranging from 0.8455 (benzeneacetaldehyde) to 0.9740 (methylpyrazine). In general, the results showed that the main effect of extraction temperature was considered the most critical factor when studying the equilibrium headspace concentration of cooked beef volatile flavour compounds. The extraction using 10 min equilibrium time, 25 min extraction time and 40 °C extraction temperature was predicted to result in the most desirable equilibrium headspace concentrations for all target cooked beef volatile compounds in this study. Acknowledgement We acknowledge funding support from Meat and Livestock Australia and the AUT Contestable Fund grant (CGH 30/11). References [1] K. Robbins, J. Jensen, K.J. Ryan, C. Homco-Ryan, F.K. McKeith, M.S. Brewer, Consumer attitudes towards beef and acceptability of enhanced beef, Meat Sci. 65 (2003) 721–729. [2] J.M. Behrends, K.J. Goodson, M. Koohmaraie, S.D. Shackelford, T.L. Wheeler, W.W. Morgan, J.O. Reagan, B.L. Gwartney, J.W. Wise, J.W. Savell, Beef customer

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