Determination of volatile marker compounds in raw ham using headspace-trap gas chromatography

Determination of volatile marker compounds in raw ham using headspace-trap gas chromatography

Accepted Manuscript Rapid Communication$Analytical Methods$Nutritional and Clinical Methods Determination of Volatile Marker Compounds in Raw Ham usin...

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Accepted Manuscript Rapid Communication$Analytical Methods$Nutritional and Clinical Methods Determination of Volatile Marker Compounds in Raw Ham using HeadspaceTrap Gas Chromatography Ramona Bosse (née Danz), Melanie Wirth, Annette Konstanz, Thomas Becker, Jochen Weiss, Monika Gibis PII: DOI: Reference:

S0308-8146(16)31486-8 http://dx.doi.org/10.1016/j.foodchem.2016.09.094 FOCH 19874

To appear in:

Food Chemistry

Received Date: Revised Date: Accepted Date:

26 February 2016 20 August 2016 14 September 2016

Please cite this article as: Bosse (née Danz), R., Wirth, M., Konstanz, A., Becker, T., Weiss, J., Gibis, M., Determination of Volatile Marker Compounds in Raw Ham using Headspace-Trap Gas Chromatography, Food Chemistry (2016), doi: http://dx.doi.org/10.1016/j.foodchem.2016.09.094

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Determination of Volatile Marker Compounds in Raw Ham using Headspace-Trap Gas Chromatography

Ramona Bosse (née Danz)1, Melanie Wirth1, Annette Konstanz1, Thomas Becker2, Jochen Weiss1 and Monika Gibis1♦

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Department of Food Physics and Meat Science, Institute of Food Science and Biotechnology, University of Hohenheim, 70593 Stuttgart, Germany; 2 Perkin Elmer LAS (Germany) GmbH, 63110 Rodgau, Germany

Submitted to Food Chemistry in February 2016 Revised August 2016

Running Title: HS-Trap GC-FID method

Keywords: Headspace adsorbent trap (HS-Trap); Gas chromatography (GC) - Mass spectrometry (MS); Volatile aroma compounds; North European raw ham; Paramter optimization

Correspondence should be addressed to: [email protected], Tel.: +49 711 459 22293, Fax: +49 711 459 24446 ♦

HIGHLIGHTS •

HS-Trap GC was used to identify volatile aroma compounds in North European raw ham.



13 volatile marker compounds were validated using an optimized HS-Trap GC method.



Repeated extraction cycles of the adsorbent trap reduced LOD into the ppb range.



High method precision and sensitivity were observed.



The developed method is simple, can be automated to complete a run within 55 min.

ABSTRACT A simple, reliable and automated method was developed and optimized for qualification and quantification of aroma-relevant volatile marker compounds of North European raw ham using a headspace (HS)-Trap gas chromatography-mass spectrometry (GC-MS) and GC-flame ionization detector (FID) analysis. A total of 38 volatile compounds were detected with this HS-Trap GC-MS method amongst which the largest groups were ketones (12), alcohols (8), hydrocarbons (7), aldehydes (6) and esters (3). The HSTrap GC-FID method was optimized for the parameters: thermostatting time and temperature, vial and desorption pressure, number of extraction cycles and salt addition. A validation for 13 volatile marker compounds with limits of detection in ng/g was carried out. The optimized method can serve as alternative to conventional headspace and solid phase micro extraction methods and allows users to determine volatile compounds in raw hams making it of interest to industrial and academic meat scientists.

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INTRODUCTION

Color, texture and aroma are key criteria influencing a customer’s decision to buy a particular food product. In raw hams, complex aroma profiles are generated during the manufacturing and ripening process and reliable, rapid and automated instrumental methods are needed to allow manufacturers to assure quality (Bosse, Müller, Gibis, Weiss, Schmidt, & Weiss, 2016). Many intrinsic and extrinsic factors influence the quality of raw ham and during ripening, proteolytic and lipolytic degradation processes in the raw ham matrix yield typical volatile aroma profiles (Carrapiso & García, 2004; Narváez-Rivas, Gallardo, & LeónCamacho, 2012). Many studies have been carried out to determine the profile of volatile compounds in dry cured ham and fermented sausages from Spain, Italy or France (Narváez-Rivas, et al., 2012; Sabio, Vidal-Aragón, Bernalte, & Gata, 1998; SánchezPeña, Luna, García-González, & Aparicio, 2005). The most relevant volatile compounds for these products were 3-methyl-butanal, hexanal, hexanol, 2-methyl-3-furanthiol, 3methylbutanol, benzaldehyde, 2-heptanone, 2-nonanone, hydrogen sulfide, 1-penten-3one, octanol, 1-octen-3-one, 1-octen-3-ol, 1-pentanol, 2-butanone, 2-methylpropanal, ethyl-2-methylbutyrate, 2-hexenal, limonene and 2-nonenal (Carrapiso, Ventanas, & García, 2002; García-González, Tena, Aparicio-Ruiz, & Morales, 2008; Narváez-Rivas, et al., 2012). However, not much is known about volatile aroma profiles in North European raw ham. Qualification and quantification of volatile compounds can help producers to decide when ripening is completed and consumers’ demands are optimally met. However, the determination of volatile compounds in complex matrices such as

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hams is difficult due to volatile compounds binding to matrix components affecting the degree of their release (Narváez-Rivas, et al., 2012). A key step in the analysis of volatile compounds in raw ham is their isolation and enrichment prior to analysis, taking differences in vapor pressures, chemical structures and functional groups into account. Therefore, a combination of a static headspace (HS) technique with an adsorption trap was used in the present study (Supplemental material 1) (Tipler & Mazza, 2004). The basic principle of the HS-Trap is comparable to that of the static HS sampling; additionally a concentration step of the HS vapor on a cold adsorbent trap is performed. This adsorption step can be repeated several times to increase sensitivity. Finally, the analytes are thermally desorbed in a reverse direction as they are loaded onto the trap and transported by the carrier pressure gas into the GC column for separation and detection (Barani, Dell'Amico, Griffone, Santoro, & Tarabella, 2006; Ingels, Neels, Lambert, & Stove, 2013). The first food applications of the HS-Trap GC included the analysis of volatile compounds in apple juice (Nikfardjam & Maier, 2011), hops (Aberl & Coelhan, 2012) and sprits (Schulz, Dreßler, Sohnius, & Lachenmeier, 2007). To our knowledge, there exists no HS-Trap GC method for a complex solid food matrix such as raw ham. In this study, we present a newly established HS-Trap GC-FID method to determine volatile marker aroma compounds in North European raw ham with minimal sample handling. This is the first time that an HS-Trap in combination with GC-MS and GC-FID analysis has been used to determine qualitative and quantitative volatile compounds in North European raw ham. Marker compounds were to be identified that could later be used to

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investigate the impact of addition of starter cultures to North European raw ham on volatile profiles. 2

MATERIALS AND METHODS

2.1

Chemicals

All reagents were analytical standards or reference materials with the highest purities available. Isovaleraldehyde (3-methyl-butanal; ≥ 97.0 %), nonanal (98.7 %), acetoin (3hydroxy-2-butanone; 99.4 %), hexanal (98.0 %), acetophenone (99.5 %), benzaldehyde (99.5 %), 3-nonanone (≥ 98.0 %), 1-octen-3-ol (≥ 98.0 %), valeraldehyde (n-pentanal; ≥ 97.5 %), 2-butanone (≥ 99.9 %), 2-pentanone (99.9 %), 1-pentanol (≥ 99.8 %) and eugenol (99.6 %; internal standard) were purchased from Sigma-Aldrich (Steinheim, Germany). 2,2,4,6,6-Pentanmethylheptane (99.2 %) and ethanol (99.9 %) were supplied by VWR (Darmstadt, Germany), and sodium chloride (NaCl; ≥ 99.9 %) was delivered by Carl Roth (Karlsruhe, Germany). Ultrapure water (type I) from a PURELAB Classic water purification system (ELGA LabWater, Celle, Germany) was used. 2.2

Samples and sample preparation

Samples: The studies were carried out using fresh meat (Musculus longissimus dorsi) from a local central market (Mega, Stuttgart, Germany). Moreover, raw hams for the application study were purchased in super markets (EDEKA and Galeria Kaufhof; Stuttgart, Germany) or from a local butcher (Böse, Stuttgart, Germany). Raw hams were produced with and without starter culture (Staphylococcus carnosus LTH 3838) in the pilot plant at the University of Hohenheim using an injection and dry curing step with

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nitrite (further explanation can be found elsewhere (Bosse, Gibis, Schmidt, & Weiss, 2016)). The process included a seven-day curing step (5 °C) and a mild smoking with a drying and ripening time (10 – 15 °C) of 20 days to achieve a weight loss of about 27 % (w/w). For the application study three samples of each raw ham were analyzed. Sample preparation: To reduce the smoking flavor of the raw hams, core samples were taken. Sample cubes were immersed in liquid nitrogen to freeze them rapidly to avoid further enzymatic reactions. The frozen meat cubes were immediately chopped using a blender (Moulinette D56, Moulinex/Krups, Frankfurt am Main, Germany). The cooling step with liquid nitrogen before chopping decreases the particle size, increases the surface area of the sample matrix for a better release of volatile compounds in the HS vial and prevents a temperature rise during chopping. All samples were vacuum-stored at – 20 °C until analysis and defrosted overnight at 1 – 4 °C. For the MS measurements, samples (1.57 ± 0.037 g raw ham or 1.53 ± 0.019 g raw meat) were weighted (Satorius, Göttingen, Germany) in HS vials (22 mL, Perkin Elmer, Rodgau, Germany). Samples for investigations on parameter optimization and for the application study were weighted in vials (1.5012 ± 0.0005 g) and 1.49 mL saturated NaCl solution (36 % in ultrapure water) were added and spiked with 10 µL internal standard working solution (Section 2.3, 1.07 mg/mL). The samples for validation contained 1.5012 ± 0.0005 g raw ham or 1.5011 ± 0.0006 g raw meat with 1.48 mL saturated NaCl solution spiked with 10 µL internal standard working solution and 10 µL respective calibration mixture solution (Section 2.3). The saturated NaCl solution was replaced by the same amount of ultrapure water for the study on the salt effect. All vials containing saturated NaCl solution or ultrapure water were immediately capped (20 mm crimp top aluminum silver caps with

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PTFE/Silicone septa, Perkin Elmer, Rodgau, Germany) and slightly mixed using a vortex. Three replicates were performed for each sample. 2.3

Validation study

Preparation of solutions: Individual stock solutions of all compounds listed below, except acetoin, were prepared by diluting 10 µL – 2.5 mL of the neat agent in 10 mL purified water or ethanol in accordance with the solubility of the analyte to obtain concentrations of stock solution from 0.750 to 266 mg/mL. Regarding acetoin, 4 g of the standard were dissolved in 10 mL purified water. The stock solution of the internal standard (IS) eugenol was prepared by diluting 100 µL of the neat agent in 10 mL ethanol. The IS stock solution was diluted 1:10 in ethanol to obtain a concentration of 1.07 mg/mL (IS working solution). The calibration mixture solutions for validation were prepared as a mixture of all calibration compounds by taking different amounts of stock solutions and filling them up to a final volume of 10 mL with ethanol. Calibration of the method was performed by using four calibration levels in the concentration range of 7.4 – 739.0 µg/mL 2-butanone, 12.1 – 403.1 µg/mL 3-methyl-butanal, 441.2 – 1500.4 µg/mL 1-pentanol, 11.5 – 270.5 µg/mL n-pentanal, 18.0 – 269.3 µg/mL 2-pentanone, 653.3 – 13040.0 µg/mL acetoin, 11.8 – 296.1 µg/mL hexanal, 5.1 – 76.8 µg/mL 2,2,4,6,6pentamethyl-heptane,

52.3 – 667.1 µg/mL

1-octen-3-ol,

34.7 – 1017.9 µg/mL

benzaldehyde, 26.1 – 137.2 µg/mL 3-nonanone, 28.5 – 719.5 µg/mL nonanal and 43.8 – 826.6 µg/mL acetophenone. The calibration was carried out in raw meat or raw ham matrix (section 2.2) with three replications for each level on two days. The validation study was carried out after method optimization of HS-Trap GC-FID method.

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Validation and Quantification: An internal standard calibration was used to maintain the matrix effect (raw meat or raw ham) where the internal standard was used for interanalysis correction by using GC-FID. Validation was carried out with approximately 1.50 g raw meat or raw ham with 1.48 mL saturated NaCl solution spiked with 10 µL internal standard working solution and 10 µL respective calibration mixture solution as described above. A regression analysis was carried out using Statgraphics® for validation of the volatile compounds (Section 2.6). To obtain the concentration of the volatile compound (c , Equation 1), the peak areas (A ) for each compound were normalized to the ratio of the concentration (c ) and area of the internal standard (A ).

c = ∙ A

Equation 1



In order to avoid negative concentrations of the regression lines calculated, the curves were moved to the point of origin by using c  as a moving factor (Equation 2, a slope, b - intercept of the regression line and c as the sample concentration). c  is the value at which the ratio in Equation 1 becomes zero.

∙ A = a ∙ c + c   + b

Equation 2

The limit of detection (LOD) and quantification (LOQ) were carried out without the raw meat or raw ham matrix by using a vial with 1.5 mL saturated NaCl and a 1.502 ± 0.007 g glass bead as a blank sample to get a sample dilution and HS volume comparable to the real samples. This blank sample was necessary, because there exists no raw meat or raw ham matrix that does not contain any of the compounds of interest in very low concentrations. The LOD and LOQ were carried out by using the blank sample

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(n = 3) and measuring the baseline noise at four different times to get the standard deviation of the blank response (s ) and calculating LOD = 3.3 ∙ s /a and LOQ = 10 ∙ s /a, as explained by Shrivastava and Gupta (2011). Recoveries were calculated as mean differences from spiked and unspiked raw meat and raw ham samples over the whole calibration levels. 2.4

Qualitative GC-MS analysis

The qualitative study was carried out with a TurboMatrix 40 Trap Headspace sampler coupled to a Clarus® Gas Chromatograph 680 with Clarus® Mass Spectrometer SQ 8T (both Perkin Elmer, Rodgau, Germany). The measurements for the qualitative study were executed in the Perkin Elmer lab in Rodgau (Germany). The qualitative measurements with GC-MS were conducted to identify key volatile compounds in raw ham that later on should be validated for an optimized HS-Trap GC-FID system for raw ham. The samples were prepared as described above (Section 2.2) and the whole vials were frozen and delivered to Perkin Elmer. Prior to analysis, the vials were defrosted at 1 – 4 °C overnight. The HS-Trap system was controlled by Turbo Matrix software (version 2.5.0), while the GC and MS were controlled by TurboMass software (version 6.1.0). The same capillary column Rtx®-200 (fused silica; 30 m x 0.32 mm ID, 1.00 µm film thickness) coated with trifluoropropyl methyl polysiloxane stationary phase from Restek (Bellefonte, USA) was used in all studies. The trap material used in all experiments was AirToxicTM (Perkin Elmer, Rodgau, Germany). The HS-Trap system was connected directly to the GC-MS system, and the transfer line was maintained at 120 °C to avoid condensation (Ingels, et al., 2013). The HS conditions were: vial oven temperature at 40 °C, needle temperature at 75 °C, trap low temperature at 40 °C, trap high temperature 8

at 280 °C, thermostatting time at 80 min, trap hold time of 5 min, desorption time of 0.4 min, dry purge time of 8 min, vial and desorption pressure at 220 kPa and the outlet split was turned on. Three extraction cycles were used. The injection port of the GC was set at 150 °C and the samples were automatically injected with a split flow of 15 mL/min. The GC oven temperature program was used as follows: initial oven temperature was set at 40 °C, held for 5 min, then increased via ramp of 10 °C/min to 80 °C, held for 3 min and again increased to 180 °C via ramp of 10.0 °C/min, held for 3 min and, finally, increased up to 240 °C via ramp of 15 °C/min and maintained for 5 min. The carrier gas was helium (99.9999 %, He 6.0) with a constant column pressure of 70 kPa. The MS was operated in electron ionization (EI+) and full scan mode with ionization energy of 70 eV. The GC transfer line temperature was set at 150 °C and the source temperature at 240 °C. Mass spectra were collected over the mass to charge ratio (m/z) of 35 – 300 with a scan duration of 0.3 s and an interscan delay of 0.05 s. Data acquisition and analysis were performed with TurboMass software. Identification of the compounds was made after background correction by matching the sample mass spectra with those of National Institute of Standards and Technology (NIST) library mass spectra (NIST2011 version 2.3.0.). The reverse match factor (R match factor), which measures the agreement between the library and search spectra and ignore non-matching peaks in the search spectrum, above 700 was used to select the marker compounds (Hyötyläinen & Wiedmer, 2013). All measurements were carried out in duplicate. 2.5

Optimization of quantitative HS-Trap GC-FID settings

After identification of the most important volatile compounds using the MS analysis, the optimization of the parameters of the HS-Trap GC-FID system was carried out, using a 9

TurboMatrix 40 Trap Headspace sampler directly coupled to a Clarus® GC 580 with a flame ionization detector (FID; Perkin Elmer, Rodgau, Germany) and the transfer line was maintained at 120 °C to avoid condensation (Ingels, et al., 2013). The GC was controlled by the TotalChrom Workstation (version 6.3.2). All settings for the optimization study of the HS-Trap parameters are given in parentheses and the final settings in bold. The HS conditions were: vial oven temperature at (40 °C, 50 °C, 60 °C), needle temperature was adjusted 5 °C above the thermostatting temperature to avoid condensation (45 °C, 55 °C, 65 °C), trap low temperature at 40 °C, trap high temperature at 280 °C, thermostatting time at (10 min, 20 min, 40 min, 80 min), trap hold time of 5 min, desorption time of 0.5 min, dry purge time of 5 min, vial and desorption pressure (70 kPa, 140 kPa, 220 kPa) and the outlet split and the dry purge mode were turned on. The settings (1, 2, 3 cycles) were used with a pressurization time of 2 min for the study of the number of cycles. The decay time used for the different vial pressure settings was changed as follows: 70 kPa (vial pressure) and 0.6 min (decay time); 140 kPa and 1.2 min and 220 kPa and 1.8 min because this time is dependent on the vial pressure and flow resistance of the trap (Røen, Unneberg, Tørnes, & Lundanes, 2010b). The GC parameters were the same as described for the MS analysis (Section 2.4). Data acquisition and analysis was performed by TotalChrom Workstation. 2.6

Statistical Analysis

Statistical analysis was conducted with Statgraphics® (Centurion XV, version 15.2.11, StatPoint Technologies, Inc.) using the Shapiro-Wilkes test, Levene’s test and Grubbs’ test. Multiple-sample analysis (ANOVA, Multiple-Range test with Fisher’s Least Significant Difference (LSD)) was used for normal distributed data to compare more than 10

two data sets (Tab. 2 and Fig. 2) and non-parametric tests (Kruskal-Wallis test, MannWhitney (-Wilcoxon) test) were used for not normal distributed data sets. Multiple nonnormal distributed data sets were compared with Kruskal-Wallis test for significant differences and paired comparison over median comparison (Mann-Whitney (-Wilcoxon) test) was carried out to found significant data pairs taking Bonferroni correction into account (Granato, de Araújo Calado, & Jarvis, 2014). Moreover, a linear regression to calculate the calibration curves was carried out. A confidence level of α = 0.05 was used for all statistical calculation. 3

RESULTS AND DISCUSSION

3.1

Qualitative analysis: identification of volatile compounds in raw ham

More than 35 potential volatile aroma compounds of North European raw hams were identified in the qualitative study using the HS-Trap GC-MS method (Table 1). A typical chromatogram is shown in Figure 1a. The largest volatile groups of all investigated raw hams were of different chemical origins: ketones (12), alcohols (8), hydrocarbons (7), aldehydes (6) and esters (3) (Table 1). Some important aroma active compounds detected, were 2-butanone, 2,3-butandione and acetophenone. The formation of methyl ketones by the autoxidation of unsaturated free fatty acids, by β-keto acid decarboxylation or by fatty acid β-oxidation was described (Narváez-Rivas, et al., 2012). In addition, compounds, such as diacetyl or acetoin, are produced using the microbial carbohydrate metabolism (Montel, Reitz, Talon, Berdagué, & Rousset-Akrim, 1996). Volatile compounds with sweet, fruity or onion and mushroom-like odors belong to the group of alcohols and eight compounds were identified (Tab. 1). Compounds such as 1-

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octen-3-ol and 1-penten-3-ol have low odor threshold values and influence the volatile aroma profile in comparison to other alcohols identified (Narváez-Rivas, et al., 2012). Linear alcohols are produced by the oxidative decomposition of fatty acids and are related to long-ripened hams (Garcia, Berdagué, Antequera, López-Bote, Córdoba, & Ventanas, 1991; Martín, Córdoba, Aranda, Córdoba, & Asensio, 2006; Narváez-Rivas, et al., 2012; Sánchez-Peña, et al., 2005). 3-methyl-1-butanol is a branched alcohol and can be produced either by a reduction of branched aldehydes or by catabolism of amino acids by means of Strecker degradation (Garcia, et al., 1991; Martín, et al., 2006). The production of branched alcohols can be increased by the activity of microorganisms due to their formation of precursors (branched aldehydes) (Narváez-Rivas, et al., 2012; Sabio, et al., 1998). Seven

hydrocarbons

were

detected

(Tab. 1),

including

3-methylene-heptane,

methylbenzene and 2,2,4,6,6-pentamethyl-heptane. Hydrocarbons are a portion of cured meat (Berdagué, Denoyer, Le Quere, & Semon, 1991; Narváez-Rivas, et al., 2012) and fresh meat flavor (Narváez-Rivas, et al., 2012; Shahidi, Rubin, D'Souza, Teranishi, & Buttery, 1986) but have no sensory impact. Most of the hydrocarbons are produced by the oxidative decomposition of lipids (Garcia, et al., 1991; López, de la Hoz, Cambero, Gallardo, Reglero, & Ordóñez, 1992; Narváez-Rivas, et al., 2012). Low odor threshold values have aldehydes an important group of volatile aroma compounds (Narváez-Rivas, et al., 2012). High impact volatile compounds in raw ham identified were 3-methyl-1-butanal, hexanal, benzaldehyde and nonanal (Tab. 1). The linear aldehydes are produced mainly by autoxidation of unsaturated fatty acids and by oxidative deamination-decarboxylation, probably via Strecker degradation (Frankel, Neff,

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& Selke, 1981; Narváez-Rivas, et al., 2012). The aroma-relevant branched aldehydes 2methyl-propanal, 2-methyl-butanal and 3-methyl-butanal are produced by the conversion of the branched-chain amino acids valine, isoleucine and leucine (Ardö, 2006). Staphylococci are particularly involved in the production of branched aldehydes, and therefore enhance the cured aroma (Ardö, 2006; Sabio, et al., 1998). In the study, three esters were identified (Tab. 1). Esters are produced by a reaction of an alcohol and a carboxylic acid (or acyl-coenzyme A) or microbial esterase activity (Narváez-Rivas, et al., 2012). The antioxidant butylated hydroxytoluene (E 321) is used in sausage mixtures or could be added to pig feed (Ansorena, Gimeno, Astiasarán, & Bello, 2001; Berdagué, et al., 1991). The antioxidant activity of butylated hydroxytoluene and other compounds can influence the formation of volatile compounds especially those that originate from lipid oxidation. The smoking of raw ham can produce compounds such as methylbenzene or cyclopentanone. In addition, aldehydes (formaldehyde), phenolic compounds (phenol, cresol), furans, pyridines and pyrazines are typical volatiles that originate from wood smoke and contribute to the characteristic smoky odor and taste of smoked products (Berdagué, et al., 1991; Hierro, de la Hoz, & Ordóñez, 2004). In this study, core samples of slightly smoked hams were used and it is known that volatiles from smoke can diffuse from the surface into the center of the ham (Hierro, de la Hoz, & Ordóñez, 2004). Nevertheless, the smoke odor and taste was low but detectable. 3.2

Optimization of the headspace-trap parameters

The compounds selected for optimization and validation of the HS-Trap GC-FID method (Tab. 2 and 3) represent the whole spectra of chemical classes (ketones, aldehydes, alcohols, hydrocarbons), their different chemical or microbial origin (lipid oxidation, 13

amino acid degradation, carbohydrate fermentation) and the different chemical structures (linear, branched) that influence the aroma of North European raw ham. In addition, raw meat as a reservoir for volatile precursors and enzymes was analyzed additionally to identify potential effects of variations in the raw material that later influence quality and volatiles in raw hams. 3.2.1

Thermostatting temperature and time

The equilibrium in the HS vial depends on the sample volume, the matrix, the physical properties of the volatile compounds and the thermostatting temperature and time (Barani, et al., 2006; Kolb & Ettre, 2006). Thermostatting temperature: The extraction profiles of selected volatile compounds changed over the investigated thermostatting temperatures (Tab. 2). The two volatiles 2pentanone and nonanal decreased with increasing temperature from 10.1 mVs (40 °C) to 7.5 mVs (60 °C) and 7.7 mVs (40 °C) to 6.5 mVs (60 °C), respectively. Most volatiles such as 3-methyl-butanal or benzaldehyde increased with increasing temperature. In between, some compounds, such as 2-butanone and 1-octen-3-ol, decreased at temperatures above 50 °C. The decrease of the two volatiles 2-pentanone and nonanal could be due to a thermal or chemical decomposition, by different chemical and physical properties that led to different transitions into the gas phase or due to a loss of volatiles during loading and desorption of the trap (Kolb, et al., 2006). Ruiz et al. (1998) analyzed Iberian hams by headspace solid phase micro extraction (SPME) and detected some compounds such as 1-pentanol, 1-octanol, decanal, methanethiol, furanone and branched pentane that decreased in peak area when temperature was increased from 40 °C to 60 °C. Nevertheless, most compounds increased with rising temperature and time. Another

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volatile analysis working with adsorption of volatiles is SPME, and in studies for raw ham samples common extraction temperatures were around 40 °C (Andrade, Córdoba, Sánchez, Casado, & Rodríguez, 2009; Jurado, Carrapiso, Ventanasa, & García, 2009). In general, SPME fibers have lower sorbent volumes than the trap used in the current study, so higher extraction yields can be achieved at lower temperatures in less time due to greater adsorption volume and repeatable extraction cycles (Section 3.2.3) (Ruiz, Cava, Ventanas, & Jensen, 1998; Schulz, Dreßler, Sohnius, & Lachenmeier, 2007). In addition, the meat proteins changed over the investigated temperature range of 40 to 60 °C during thermostatting. At 40 – 45 °C, the heat denaturation of meat proteins started and showed high impact at 50 and 60 °C (Hamm & Iwata, 1962; Martens, Stabursvik, & Martens, 1982). The samples thermostatted at 60 °C were fully denaturized, pale and hard, whereas the samples thermostatted at 40 °C kept their red color and texture as typical for cured raw ham products. Although temperatures up to 50 °C gave higher peak areas for several compounds (e.g. 2-butanone, 3-methyl-butanal), a 40 °C thermostatting temperature was chosen as optimum, because the raw ham character was maintained and the two volatiles 2-pentanone and nonanal could be detected with highest peak areas. In addition, to facilitate a further correlation of volatile data with results from an olfactometry sensory panel, a low thermostatting temperature is preferred to maintain the cured raw ham character as much as possible. Thermostatting time: The next step included the optimization of the equilibrium time for the selected thermostatting temperature of 40 °C (Fig. 2a). For all compounds, except for benzaldehyde, an increase in peak area over the first 20 min was detected. Further heating longer than 20 min decreased analytes such as hexanal or acetophenone, without reaching

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equilibrium due to chemical or thermal degradation of the analytes over time. Therefore, the thermostatting time was set at 20 min (at 40 °C) to reach equilibrium for the analytes and to avoid chemical or thermal decomposition of sensitive analytes. 3.2.2

Vial and desorption pressure

The vial and desorption pressure affects the transport of analytes onto the adsorbent material, but too high pressures could lead to leakages (Ingels, et al., 2013; Røen, et al., 2010b). The peak areas of all compounds increased with increasing vial and desorption pressure from 70 to 220 kPa (Tab. 2), except for 1-pentanol (data not shown), which decreased by about 30 %. The highest pressure effect was observed for 2-butanone: it was not detected at 70 kPa, while highest areas were observed at 220 kPa (Tab. 2). Therefore, the vial and desorption pressure were set to the optimum at 220 kPa with a decay time of 1.8 min. 3.2.3

Number of extraction cycles

The pressurization of the HS vial and the trap loading can be repeated several times to achieve higher trap enrichments and, therefore, get higher extraction yields (Supplemental material 1) (Ingels, et al., 2013; Schulz, et al., 2007). Figure 2b summarizes the results for the repetition of the trap extraction up to three times over the peak area (log scale). The results showed that the repetition of the extractions of the HS vapor increased the peak area of the analytes by a factor of about 150 for penta-methylheptane and a factor of about 1120 for acetophenone. Due to the higher yields of three extraction cycles for the analyzed compounds, the three-extraction cycle mode was used in the optimized method. In contrast to SPME and solid-phase dynamic extraction, which use small fibers or coated capillaries with low sorbent volumes (0.94 or 5.99 mm³) to 16

collect analytes, the traps used in this study consist of tubes packed with a solid sorbent (e.g. carbon or Tenax®) having a greater volume (160 mm³) (Schulz, et al., 2007). The water was removed successfully from the trap by using a dry purge time of 5 min and a complete desorption of the trap at temperatures of 280 °C with a hold time of 5 min prevented carry-over effects between samples. 3.2.4

Effect of salt addition

The addition of water or saturated salt solution to a solid matrix can lead to a higher reproducibility by achieving a more homogenous sample distribution, a better heat transfer and less inhomogeneities in water and salt content (Copolovici & Niinemets, 2007; Røen, et al., 2010b). As a result, two equilibrium states occurred in the HS vial due to the addition of water or saturated salt solution; on the one hand the solubility of the compounds from the meat or ham matrix with the water or saturated salt solution changed, and on the other hand the transfer of volatiles from the water or saturated salt solution to the HS vapor phase increased. The addition of salt solution to raw meat samples showed an increase in peak area for most analytes (Fig. 2c), such as 2-butanone, 2-pentanone, hexanal and benzaldehyde. The other compounds, such as 3-methylbutanal, 1-octen-3-ol and acetophenone decreased not significantly in peak area after the addition of saturated NaCl. In raw ham, substances such as 2-butanone, 3-methyl-butanal and 2-pentanone increased or stayed constant, whereas hexanal, acetophenone and benzaldehyde decreased after the addition of NaCl. The matrix of raw meat and raw ham differed in the addition of curing agents (sodium chloride, nitrite). The effect of saltingout to increase the peak area is higher for a matrix that does not contain salt in comparison to a matrix with a low salt level (Copolovici, et al., 2007). Besides that, a

17

decreasing effect of NaCl on the peak area due to a change in protein surface polarity, which affects the binding activity of volatile compounds to the matrix, has been described by different authors (Guichard & Langourieux, 2000; Pérez-Juan, Flores, & Toldrá, 2007). Furthermore, the effect of protein binding and salting-out on volatile compounds in meat products was studied using SPME by Pérez-Juan et al. (2008). They found that sarcoplasmatic proteins limited the release of the volatile 3-methylbutnal but supported the volatile 2-pentanone. The addition of sodium chloride to sarcoplasmatic proteins increased the release of all volatiles (Pérez-Juan, Flores, & Toldrá, 2008). In addition, a study of apple juice demonstrated that the increase in peak areas after salt addition varies over chemical classes (esters, aldehydes and alcohols) (Poll & Flink, 1984). Nevertheless, all the samples in the present study were prepared with the same amount of saturated salt solution to compensate differences between the samples in salt and water content. 3.3

Quantitative analysis: analytical performance

The results of the validation of the optimized HS-Trap GC-FID method for the 13 selected compounds in raw meat and raw ham are summarized in Table 3. A typical chromatogram of North European raw ham is illustrated in Figure 1b. The chromatographic separation of the volatile compounds was well established, except for the double peak compounds 1-pentanol and n-pentanal with too high or low recovery rates due to inadequate separation. The internal standard was well separated from all other peaks of interest and was used as an indicator for changes vial by vial. The optimized method showed reliable recoveries and repeatabilities of determined substances in raw ham samples with both precisions of intraday and interday and allowed the elimination of water before the analytes were transferred into the chromatographic 18

column. The recovery rates from 81.3 % to 105.1 % (Tab. 3) obtained for the volatiles in the raw ham samples were comparable to the studies by Barani et al. (2006) and Røen et al. (2010a). The trap enrichment of volatile aroma compounds lowered the LOD and LOQ in comparison to a conventional HS analysis in the parts per billion range (Supplemental material 2). Only the highest standard mixture could be detected in common HS measurements (without trap enrichment) with very low peak areas (Supplemental material 2). The correlation coefficients of the calibration curves of raw ham demonstrated high linearity in the concentration ranges investigated. Less sample handling is needed to detect major and minor volatile compounds in North European raw ham, because a manual loading of solid phase micro extraction fiber in a vial in a water bath and the transfer into the injector of the GC is not required. These manual preparation steps performed with SPME can lead for example to times to 45 min to 50 min for preconditioning and 30 min to 45 min for extraction of the system in a water bath (Andrade, et al., 2009; Jurado, et al., 2009). 3.4

Application

The optimized method was used to investigate the volatile marker aroma compounds of the raw material, a Black Forest ham, a butcher’s raw ham, an industrial produced raw ham, a raw ham produced at the University of Hohenheim with and without the starter culture S. carnosus (Tab. 4). Tab. 4 illustrate that the optimized method can detect difference in varied raw hams products. It is possible to detect major compounds such as acetoin and 2-butanaone and minor compounds such as 1-octen-3-ol or nonanone (Tab. 4). The major classes of ketones, aldehydes and alcohols were in agreement with different studies for dry-cured hams and cured pork loins (Muriel, Antequera, Petrón, 19

Andrés, & Ruiz, 2004; Narváez-Rivas, Gallardo, & León-Camacho, 2012; Sabio, VidalAragón, Bernalte, & Gata, 1998).The raw meat was characterized to show the influence of the raw material on the quality of the end product raw ham. Although lipid oxidation is a desired process during ripening, a raw material with increased lipid oxidation or proteolytic activity can lead to soft and rancid raw hams with off-flavors (Narváez-Rivas, et al., 2012; Toldrá, 1998). The major compounds in the studied raw material were acetoin, benzaldehyde and acetophenone, while the lipid oxidation product hexanal was low with 12.3 ng/g. Lipid oxidation products such as hexanal or nonanal varied over the raw hams with lower contents in the hams from the University of Hohenheim and higher contents in the purchased hams. The mushroom-like alcohol 1-octen-3-ol was under the limit of detection in the Black Forest ham, while it was highest in the raw hams of the University of Hohenheim with added starter cultures. Further researches about the influence of starter cultures on the volatile profile are needed. The ketone acetophenone was highest in the butcher’s and industrial hams and lowest in the hams with starter culture. Acetophenone is a volatile compound that originates from the amino acid phenylalanine (Narváez-Rivas, et al., 2012). A volatile that was identified to be related to long ripened raw hams and contribute to a rancid odor and taste (García-González, Tena, Aparicio-Ruiz, & Morales, 2008). This key compound was detected in all four raw ham samples with highest concentration of 64 ng/g in the Black Forest ham and lowest amount of 5.9 ng/g in the control raw ham of the University of Hohenheim. The volatile 3-methyl-butanal arises from degradation of amino acids by staphylococci which were identified to increase such volatiles derivated from branch-chain amino acids (Berdagué, Monteil, Montel, & Talon, 1993; Montel, Reitz, Talon, Berdagué, & Rousset-Akrim,

20

1996). Therefore, the application of starter culture can increase the content of minor volatile compounds. More studies about the influence of starter cultures on the volatile aroma compounds in North European raw ham need to be carried out. 3.5

Conclusion

Finally, a reliable, rapid and automated instrumental method was developed to allow manufacturers or researchers to assure raw ham quality or investigate the influence of starter cultures on the volatile aroma profile in North European raw ham by screening 13 volatile marker aroma compounds. The HS-Trap technique was chosen due to its improved detection limits. Comparing static headspace sampling to the HS-Trap method, which is rapid and can simply be done in aqueous media without needing timeconsuming sample preparation, allows one to quantitate volatile aroma compounds at low concentrations (ng/g) in food matrices. The establish method was successfully applied to 6 North European raw hams with varying volatile aroma profiles. The optimized HS-Trap GC-FID method can be used as an alternative to solid phase micro extraction or conventional headspace method to detect volatile marker aroma compounds in North European raw ham in research and industrial applications. 4

ACKNOWLEDGEMENTS

This IGF Project of the FEI is/was supported via AiF within the program for promoting the Industrial Collective Research (IGF) of the German Ministry of Economics and Energy (BMWi), based on a resolution of the German Parliament. Project number AiF 17687 N. We would like to thank the team from Perkin Elmer in Rodgau (Germany)

21

for the MS measurements of our samples, particularly Heiko Helms and the technical support.

22

5

REFERENCES

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Muriel, E., Antequera, T., Petrón, M. J., Andrés, A. I., & Ruiz, J. (2004). Volatile compounds in Iberian dry-cured loin. Meat Science, 68(3), 391-400. Narváez-Rivas, M., Gallardo, E., & León-Camacho, M. (2012). Analysis of volatile compounds from Iberian hams: a review. Grasas y Aceites, 63(4), 432-452. Nikfardjam, M. P., & Maier, D. (2011). Development of a headspace trap HRGC/MS method for the assessment of the relevance of certain aroma compounds on the sensorial characteristics of commercial apple juice. Food Chemistry, 126(4), 1926-1933. Pérez-Juan, M., Flores, M., & Toldrá, F. (2007). Effect of ionic strength of different salts on the binding of volatile compounds to porcine soluble protein extracts in model systems. Food Research International, 40(6), 687-693. Pérez-Juan, M., Flores, M., & Toldrá, F. (2008). Effect of pork meat proteins on the binding of volatile compounds. Food Chemistry, 108(4), 1226-1233. Poll, L., & Flink, J. M. (1984). Aroma analysis of apple juice: influence of salt addition on headspace volatile composition as measured by gas chromatography and corresponding sensory evaluations. Food Chemistry, 13(3), 193-207. Røen, B. T., Unneberg, E., Tørnes, J. A., & Lundanes, E. (2010a). Trace determination of sulphur mustard and related compounds in water by headspace-trap gas chromatography–mass spectrometry. Journal of Chromatography A, 1217(5), 761-767. Røen, B. T., Unneberg, E., Tørnes, J. A., & Lundanes, E. (2010b). Headspace-trap gas chromatography–mass spectrometry for determination of sulphur mustard and related compounds in soil. Journal of Chromatography A, 1217(14), 2171-2178. Ruiz, J., Cava, R., Ventanas, J., & Jensen, M. T. (1998). Headspace solid phase microextraction for the analysis of volatiles in a meat product:  dry-cured Iberian ham. Journal of Agricultural and Food Chemistry, 46(11), 4688-4694. Sabio, E., Vidal-Aragón, M. C., Bernalte, M. J., & Gata, J. L. (1998). Volatile compounds present in six types of dry-cured ham from south European countries. Food Chemistry, 61(4), 493-503. Sánchez-Peña, C. M., Luna, G., García-González, D. L., & Aparicio, R. (2005). Characterization of French and Spanish dry-cured hams: influence of the volatiles from the muscles and the subcutaneous fat quantified by SPME-GC. Meat Science, 69(4), 635-645. Schulz, K., Dreßler, J., Sohnius, E.-M., & Lachenmeier, D. W. (2007). Determination of volatile constituents in spirits using headspace trap technology. Journal of Chromatography A, 1145(1-2), 204-209. Shahidi, F., Rubin, L. J., D'Souza, L. A., Teranishi, R., & Buttery, R. G. (1986). Meat flavor volatiles: a review of the composition, techniques of analysis, and sensory evaluation. Critical Reviews in Food Science and Nutrition, 24(2), 141-243. Shrivastava, A., & Gupta, V. B. (2011). Methods for the determination of limit of detection and limit of quantification of the analytical methods. Chronicles of Young Scientists, 2(1), 21-25. Tipler, A., & Mazza, C. (2004). System and method for extracting headspace vapor. In, vol. WO 2004092711 A1). Toldrá, F. (1998). Proteolysis and lipolysis in flavour development of dry-cured meat products. Meat Sci., 49, Supplement 1(0), S 101-S110.

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6

TABLES

Table 1.

List of identified volatile compounds in North European raw ham samples after HS-Trap GC-MS analysis including retention time (min), molecular formula, chemical class, ten largest mass peaks (mass/charge ratio (m/z)), R match factor and the aroma aspect (n = 4).

Nr. Retention Compound time (min)

Molecular Chemical class Ten tallest mass peaks in sample formula (m/z)

R match Sensory aspect factor

1

2.016

1-Propanol

C3H8O

Alcohol

31 (100) 59 (16) 42 (12) 27 (10) 60 (10) 41 (7) 29 (7) 28 (4) 39 (4) 26 (2)

885

2

2.201

Cyclohexane

C6H12

Hydrocarbon

56 (100) 84 (71) 41 (70) 27 (37) 55 (36) 39 (35) 42 (30) 69 (23) 28 (18) 43 (14)

901

3

2.469

Acetone (Propanone)

C3H6O

Ketone

43 (100) 58 (51) 42 (10) 39 (5) 44 (4) 45 (4) 41 (4) 60 (3) 38 (3) 37 (2)

924

Characteristic aromatic odor, pungent1

4

2.709

2-Methyl-1-propanol

C4H10O

Alcohol

43 (100) 41 (47) 42 (44) 39 (15) 44 (13) 58 (10) 45 (8) 74 (6) 56 (6) 55 (6)

900

Wine, penetrating2, fusel oil like3

5

3.426

Ethyl acetate (Ethyl ethanoate)

C4H8O2

Ester

43 (100) 61 (20) 45 (14) 70 (10) 73 (7) 42 (10) 81 (5) 88 (4) 96 (3) 53 (2)

956

Fruity3

6

3.529

1-Penten-3-ol

C5H10O

Alcohol

57 (100) 43 (14) 44 (14) 39 (7) 71 (7) 53 (7) 41 (6) 68 (5) 42 (5) 58 (4)

872

Bitter, mild green odor1, onion, toasted9

7

3.993

2-Butanone (Methyl ethyl ketone)

C4H8O

Ketone

43 (100) 72 (25) 57 (8) 42 (3) 44 (3) 39 (2) 73 (2) 55 (2) 41 (2) 45 (1)

953

Ethereal2,4

26

Fusel oil-like sweet, pleasant odor1

8

4.053

Diacetyl (2,3-Butanedione)

C4H6O2

Ketone

43 (100) 86 (12) 72 (9) 42 (7) 45 (3) 73 (3) 74 (3) 77 (1) 50 (1) 41 (1)

965

9

4.313

3-Methylene-heptane

C8H16

Hydrocarbon

70 (100) 55 (88) 41 (46) 39 (26) 42 (19) 39 (18) 112 (14) 83 (14) 56 (13) 69 (12)

937

10

5.072

3-Methyl-butanal

C5H10O

Aldehyde

41 (100) 44 (95) 58 (64) 43 (60) 71 (32) 94 (32) 57 (29) 39 (23) 45 (19) 42 (16)

865

Acorn, nutty, almond, toasted, flavor of aged ham, cheesy, fruity, pungent, malty2,4,8

11

5.160

2-Methyl-1-butanal

C5H12O

Aldehyde

41 (100) 57 (88) 58 (58) 56 (41) 70 (23) 39 (31) 55 (22) 43 (12) 42 (11) 53 (6)

872

Rancid, almond-like, toasted, fruity6,8

12

5.253

3-Methyl-1-butanol

C5H12O

Alcohol

55 (100) 42 (87) 70 (70) 43 (69) 41 (60) 31 (35) 57 (25) 39 (18) 45 (11) 69 (9)

906

Green, wood, acorn, pleasant green2,4

13

5.463

Toluene (Methylbenzene)

C7H8

Hydrocarbon

91 (100) 92 (60) 65 (11) 39 (8) 63 (7) 51 (6) 93 (4) 89 (4) 50 (4) 62 (3)

954

Sweet, fruity, pungent odor1

14

6.122

1-Pentanol

C5H12O

Alcohol

42 (100) 55 (75) 41 (68) 70 (61) 31 (48) 43 (23) 39 (21) 57 (20) 54 (13) 67 (12)

945

Pungent, strong, balsamic, somewhat sweet2,4; characteristic fusel-like sweet, pleasant odor1

15

6.233

n-Pentanal

C5H10O

Aldehyde

44 (100) 41 (63) 58 (59) 57 (36) 43 (36) 39 (26) 42 (17) 45 (12) 55 (11) 53 (5)

921

Powerful, acrid, pungent odor1; nutty, toasted, fruity4,7

16

6.585

2-Pentanone (Methyl propyl ketone)

C5H10O

Ketone

43 (100) 82 (21) 41 (12) 71 (11) 58 (10) 39 (6) 42 (4) 55 (3) 44 (2) 53 (2)

894

Sweet, fruity, green, tropical fruits2,7; wine, acetone-like, characteristic odor1

17

6.963

1-Hydroxy-2-propanone

C3H6O2

Ketone

43 (100) 74 (11) 42 (8) 55 (5) 45 (5) 41 (3) 60 (3) 44 (3) 69 (2) 58 (2)

875

18

7.803

Ethyl benzene

C8H10

Hydrocarbon

91 (100) 106 (37) 44 (16) 69 (12) 65 (11) 51 (9) 39 (9) 92 (8) 78 (6) 79 (4)

915

19

7.914

Acetoin (3-Hydroxy-2-butanone)

C4H8O2

Ketone

45 (100) 43 (53) 88 (10) 42 (10) 86 (7) 44 (7) 73 (2) 58 (2) 72 (2) 46 (2)

884

Bland, woody, yoghurt odor1

20

8.637

1-Hexanol

C6H14O

Alcohol

56 (100) 55 (53) 43 (49) 42 (43) 69 (40) 41 (39) 39 (12) 44 (9) 73 (9) 40 (8)

843

Fruity, green2,4; sweet3

21

8.801

Hexanal

C6H12O

Aldehyde

56 (100) 43 (59) 55 (49) 42 (43) 41 (36) 39 (23) 72 (22) 55 (22) 82 (18) 45 (18)

932

Rancid, fatty, fruity, acorn, green, grassy2,4,5,7

27

Buttery, vanilla, caramel-like, sweet3,4,7

22

9.600

Cyclopentanone

C5H8O

Ketone

55 (100) 84 (59) 41 (38) 56 (26) 39 (13) 42 (10) 76 (10) 46 (8) 54 (5) 50 (4)

889

23

9.709

2,2,4,6,6-Pentamethylheptane

C12H26

Hydrocarbon

57 (100) 56 (50) 41 (32) 43 (12) 55 (11) 71 (8) 85 (6) 99 (4) 58 (4) 69 (3)

942

24

10.452

2,2,4,4-Tetramethyl-octane C12H26

Hydrocarbon

57 (100) 41 (20) 99 (18) 56 (15) 43 (11) 55 (8) 113 (6) 58 (4) 71 (4) 70 (4)

926

25

10.522

Trimethyl-decane

C15H32

Hydrocarbon

57 (100) 43 (44) 71 (33) 41 (21) 56 (13) 70 (7) 55 (7) 95 (8) 96 (7) 85 (5)

918

26

10.629

1-Octen-3-ol

C8H16O

Alcohol

57 (100) 43 (21) 41 (13) 72 (13) 55 (11) 56 (12) 85 (9) 71 (8) 67 (7) 39 (6)

850

Mushroom, earthy, dust, rusty2,4,5; powerful, sweet, earthy odor with strong, herbaceous note1

27

11.514

Pentyl nitrate (Nitric acid, pentyl ester)

C5H11NO3 Ester

41 (100) 57 (68) 46 (48) 76 (39) 43 (29) 55 (29) 42 (28) 44 (21) 71 (20) 39 (15)

841

Ethereal odor10

28

11.59

2-Ethyl-1-hexanol

C8H18O

Alcohol

57 (100) 41 (34) 43 (30) 70 (26) 55 (26) 56 (22) 71 (33) 98 (13) 83 (13) 69 (12)

887

29

12.331

Benzaldehyde

C7H6O

Aldehyde

105 (100) 106 (98) 77 (98) 51 (51) 50 (29) 78 (19) 78 (15) 52 (13) 74 (10) 107 (8)

926

Almond, bitter almond, penetrating2,4

30

12.536

2,3-Octanedione

C8H14O2

Ketone

43 (100) 99 (49) 71 (46) 41 (26) 55 (18) 44 (15) 39 (13) 42 (9) 73 (8) 56 (7)

883

Warmed-over flavor9

31

12.728

2-Octanone

C8H16O

Ketone

43 (100) 58 (61) 41 (16) 71 (12) 55 (11) 59 (11) 79 (10) 137 (10) 77 (9) 70 (9)

811

Fruity, green, floral, fresh2,5

32

13.854

3-Nonanone

C9H18O

Ketone

57 (100) 43 (95) 72 (68) 113 (52) 85 (40) 110 (40) 41 (36) 55 (15) 125 (14) 91 (12)

942

Pungent, leafy, herbaceous and fruity odor1

33

14.082

Nonanal

C9H18O

Aldehyde

57 (100) 41 (89) 43 (88) 56 (80) 44 (72) 55 (59) 70 (42) 69 (39) 67 (34) 68 (33)

875

Rancid, strong fatty odor1,2,3,4, green9

34

14.315

Acetophenone (Methylphenylketone)

C8H8O

Ketone

105 (100) 77 (75) 120 (29) 51 (25) 43 (15) 55 (14) 50 (9) 84 (8) 104 (8) 78 (8)

909

Characteristic sweet, pungent and strong medicinal odor1

35

15.815

1-Methyl-2-pyrrolidinone C5H9NO

Lactam

99 (100) 98 (71) 42 (59) 44 (56) 41 (29) 43 (22) 70 (14) 96 (10) 55 (8) 68 (8)

901

Pungent, undefined11

28

17.070

[1,1'-Bicyclopentyl]-2-one C10H16O

Ketone

84 (100) 67 (34) 83 (24) 41 (21) 69 (19) 68 (12) 85 (10) 54 (10) 81 (9) 53 (9)

918

37

17.683

Butylated hydroxytoluene (2,6-Bis (1,1C15H24O dimethylethyl)-4methylphenol)

Phenol

205 (100) 57 (29) 220 (25) 206 (17) 142 (15) 145 (14) 177 (12) 41 (10) 105 (8) 81 (6)

771

38

19.550

Triacetin

Ester

43 (100) 103 (19) 145 (16) 116 (8) 115 (5) 137 (4) 55 (4) 44 (3) 40 (3) 42 (3)

844

36

C9H14O6

Very faint, fruity odor1

Note: a The reliability of the identification or the structural proposal is indicated by the MS-NIST libraries spectra and the literature. References: 1(Burdock, 2001), 2(García-González, et al., 2008), 3(GESTIS-Stoffdatenbank, 2015), 4(Sánchez-Peña, et al., 2005), 5(Narváez-Rivas, et al., 2012), 6

(Carrapiso, et al., 2002), 7(Carrapiso, et al., 2004), 8(Carrapiso, Martín, Jurado, & García, 2010), 9(Flores, Grimm, Toldrá, & Spanier, 1997),

10

(ChemicalBook, 2015), 11 (Berdagué, et al., 1991).

29

Table 2.

Effect of temperature (thermostatting time 20 min, vial and desorption pressure 220 kPa), vial and desorption pressure (thermostatting time 20 min, thermostatting temperature 40 °C) on peak area (mV*s; mean ± standard deviation) on key volatiles using HS-Trap GC-FID (n = 4; exception: 2-Butanone: n(70 kPa) = 0, n(140 kPa) = 2). The decay time for the study of the vial and desorption pressure was adjusted as follows: 70 kPa vial and desorption pressure with 0.6 min decay time, 140 kPa with 1.2 min and 220 kPa and 1.8 min, respectively. Effect of temperature and vial and desorption pressure are marked as p-value (ANOVA, significance level of α = 0.05).

30

Peak Area (mV*s) Vial/ Desorption pressure (kPa)

Thermostatting temperature (°C)

(Decay time)

Compound

Effect

70

140

220*

Effect

(p-value)

(0.6 min)

(1.2 min)

(1.8 min)

(p-value)

129.1 ± 19.80b

< 0.001

n.d.

89.25 ± 2.81b

< 0.001

36.45 ± 21.40a

448.41 ± 25.21b

< 0.001

0.14 ± 0.03a

0.03 ± 0.009 (n = 2) 0.07 ± 0.02b

27.15 ± 2.98c

< 0.001

0.05 ± 0.01a

0.09 ± 0.02a

0.08 ± 0.08a

0.559

0.07 ± 0.06a

0.06 ± 0.03a

0.05 ± 0.01a

0.738

a

b

1.04 ± 0.37

a

0.29 ± 0.18

0.005

a

a

a

0.308

8.96 ± 0.67a

7.53 ± 0.92c

0.002

40*

50

60

2-Butanone

89.25 ± 2.81a

155.99 ± 18.66b

3-Methyl-butanal

27.15 ± 2.98a

1-Pentanol n-Pentanal

0.43 ± 0.11

2-Pentanone

10.11 ± 0.47a a

b

b

0.03 ± 0.01

0.025 ± 0.017a a

0.06 ± 0.02

0.43 ± 0.11

0.09 ± 0.03a

10.11 ± 0.47b

< 0.001

c

b

Acetoin

62.52 ± 4.49

80.74 ± 6.63

92.50 ± 9.83

< 0.001

7.89 ± 0.67

40.64 ± 1.60

62.52 ± 4.49

< 0.001

Hexanal

8.02 ± 0.45a

17.55 ± 2.34b

5.48 ± 0.63a

< 0.001

0.69 ± 0.10a

2.28 ± 0.05b

8.02 ± 0.45c

< 0.001

8.06 ± 0.87a

13.23 ± 1.49b

14.05 ± 2.06b

< 0.001

0.08 ± 0.02a

0.68 ± 0.06b

8.06 ± 0.87c

< 0.001

1-Octen-3-ol

1.11 ± 0.21a

1.82 ± 0.56b

1.24 ± 0.13a

0.043

0.12 ± 0.05a

0.39 ± 0.03b

1.11 ± 0.21c

< 0.001

Benzaldehyde

2.35 ± 0.13a

5.01 ± 0.29b

7.85 ± 0.87c

< 0.001

0.06 ± 0.01a

1.10 ± 0.06b

2.35 ± 0.13c

< 0.001

a

ab

b

a

b

c

2,2,4,6,6-Pentamethyl-heptane

3-Nonanone

1.44 ± 0.06

2.29 ± 0.67

2.59 ± 0.26

0.009

0.03 ± 0.02

0.35 ± 0.02

1.44 ± 0.06

< 0.001

Nonanal

7.74 ± 0.18a

3.91 ± 2.64b

6.54 ± 0.92ab

0.023

0.30 ± 0.04a

2.41 ± 0.09b

7.74 ± 0.18c

< 0.001

a

b

c

a

a

b

< 0.001

Acetophenone

0.91 ± 0.12

0.19 ± 0.01

2.07 ± 0.40

< 0.001

0.06 ± 0.03

0.10 ± 0.02

0.91 ± 0.12

Note: *Data from optimized method (thermostatting time 20 min, thermostatting temperature 40 °C, vial and desorption pressure 220 kPa, decay time 1.8 min, 3 cycles). Different letters indicate significant differences at a significance level of α = 0.05 individually for each parameter. n.d.- not detected.

31

Table 3.

Summary of method validation parameters with linear range (µg/g meat), slope (µg), coefficient of determination R² of the calibration curve, recovery (%) over all calibration levels, limit of detection (LOD; ng/g meat), limit of quantification (LOQ; ng/g meat), precision intraday (%) and interday (%) for raw meat and raw ham using the optimized HS-Trap GC-FID method with standard additional method normalized to an internal standard (n = 24).

32

Raw meat Nr.

Retention

Compound

time

Linear range (µg/g meat)

Raw ham Slope



(µg)

Recovery (%)

LODa

LOQa

Precision Precision b

(ng/g meat) (ng/g meat) intraday interday

(min)

(%)

(%)

b

Linear range

Slope

(µg/g meat)

(µg)



Recovery

LOD a

LOQ a

Precision

Precision

(%)

(ng/g meat)

(ng/g meat)

intradayb

interdayb

(%)

(%)

7

6.47

2-Butanone

0.049-4.93

59.58

0.97

97

0.37

1.13

3.68

7.55

0.049 -4.93

100.46

0.98

105

0.22

0.67

1.90

9.57

10

7.40

3-Methyl-butanal

0.080-2.69

4.38

0.93

90

5.08

15.4

4.68

8.13

0.080-2.0

85.55

0.97

90

0.26

0.79

2.13

10.28

14

8.23

1-Pentanol

2.94-10.0

4.67

0.70

104

4.76

14.42

5.86

10.91

2.94-10.0

7.57

0.96

79

2.94

8.91

1.17

7.57

15

8.27

n-Pentanal

0.077-1.80

31.35

0.80

240

0.71

2.15

4.33

5.10

0.077-1.80

62.09

0.92

13

0.36

1.09

4.36

9.28

16

8.65

2-Pentanone

0.12-1.80

76.57

0.97

87

0.29

0.88

2.10

7.56

0.12-1.80

142.59

0.98

86

0.16

0.47

1.77

9.26

19

9.95

Acetoin

4.35-86.93

0.57

0.96

111

38.97

118.09

3.10

3.23

4.35-86.93

1.21

0.96

85

18.41

55.80

2.98

5.72

21

11.09

Hexanal

0.19-1.97

10.27

0.80

89

2.17

6.57

6.17

12.47

0.079-1.97

49.75

0.99

93

0.45

1.36

3.58

5.14

23

12.56

0.034-0.41

350.55

0.91

99

0.06

0.19

4.38

4.72

0.034-0.51

699.09

0.86

89

0.03

0.1

8.82

14.58

26

13.99

1-Octen-3-ol

0.35-4.45

17.80

0.95

99

1.25

3.79

1.37

5.99

0.35-4.45

24.16

0.95

81

0.92

2.79

3.09

10.90

29

16.57

Benzaldehyde

2.02-6.79

4.68

0.78

43

4.75

14.41

10.18

15.10

0.23-5.76

25.61

0.97

86

0.87

2.63

1.87

7.62

32

18.57

3-Nonanone

0.17-0.91

83.72

0.90

68

0.27

0.81

4.21

7.91

0.17-0.91

74.56

0.92

89

0.30

0.90

3.90

8.69

33

18.88

Nonanal

0.19-4.80

19.31

0.85

79

1.15

3.50

6.07

13.50

0.19-4.80

27.83

0.97

90

0.80

2.42

1.24

4.58

34

19.22

Acetophenone

0.29-5.51

8.42

0.95

84

2.64

8.01

5.13

10.49

0.29-5.51

13.55

0.97

84

1.64

4.98

6.89

9.56

2,2,4,6,6-Pentamethyl-heptane

Note: a Limits of detection (LOD) and quantification (LOQ) were determined by blank sample containing 1.5 mL sodium chloride solution and an approx.1.5 g glass bead. The limits were calculated from the standard deviation of the blank response (n = 12). b

Precision is expressed as relative standard deviation (RSD in %), intraday (n = 3), interday (n = 6).

33

Table 4.

Results of the volatile marker compounds (ng/g meat; mean ± standard deviation) of the raw material pork loin, a Black Forest ham, a butcher’s raw ham, an industrial produced raw ham, a control raw ham without starter culture and a starter raw ham with starter culture (S. carnosus) produced at the University of Hohenheim using the optimized HSTrap GC-FID method (n = 3).

34

Compounds

Raw meat

Black Forest ham

Butcher’s raw ham

Industrial raw ham

Control raw ham

Starter raw ham

2-Butanone

11,14 ± 0.67

440.98 ± 25.09

382.47 ± 36.16

233,70 ± 9.55

29.40 ± 0.64

172.42 ± 24.87

3-Methyl-butanal

5.14 ± 1.55

64.38 ± 6.29

41.00 ± 7.59

9.76 ± 0.37

5.89 ± 0.90

47.61 ± 2.43

1-Pentanol

34.85 ± 5.74

< 8.91

11.79 ± 1.97

22.93 ± 2.30

19.60 ± 2.35

< 8.91

n-Pentanal

4.66 ± 0.18

8.35 ± 9.61

1.28 ± 0.11

2.77 ± 0.08

5.13 ± 2.54

< 1.09

2-Pentanone

8.11 ± 0.38

18.67 ± 0.25

5.33 ± 0.22

4.78 ± 0.14

2.49 ± 0.11

5.63 ± 0.44

Acetoin

1632.5 ± 182.7

14221.9 ± 1063.8

5066.7 ± 168.2

2266.3 ± 97.3

2610.8 ± 164.71

1615.05 ± 78.77

Hexanal

12.33 ± 2.29

21.23 ± 1.18

11.40 ± 0.72

15.30 ± 1.37

22.36 ± 3.43

7.45 ± 0.47

2,2,4,6,6-Pentamethyl-heptane

4.49 ± 1.92

42.92 ± 10.96

14.28 ± 4.08

12.01 ± 1.59

1.68 ± 0.23

11.14 ± 0.46

1-Octen-3-ol

11.62 ± 1.54

< 0.92

3.79 ± 0.34

5.66 ± 0.63

8.87 ± 0.46

24.55 ± 1.61

Benzaldehyde

73.03 ± 2.93

22.06 ± 4.10

16.46 ± 3.92

24.21 ± 5.20

7.16 ± 2.36

28.32 ± 1.80

3-Nonanone

3.94 ± 0.11

17.01 ± 1.24

2.31 ± 0.64

3.07 ± 0.32

7.09 ± 0.56

9.37 ± 1.17

Nonanal

34.07 ± 4.01

79.28 ± 5.28

94.13 ± 3.73

95.61 ± 3.99

19.94 ± 2.33

27.28 ± 0.79

Acetophenone

51.84 ± 4.08

98.25 ± 9.65

185.90 ± 12.69

139.78 ± 2.59

33.90 ± 7.43

8.02 ± 0.07

35

7

FIGURE CAPTIONS

Figure 1

(a) Total ion chromatogram of volatile compounds identified in a North European raw ham sample obtained by HS-Trap GC-MS with an example of peak identification of nonanal with sample mass spectra (red) versus NIST library spectra (blue) (n = 2). For peak identification, see Table 1. (b) Typical chromatogram of a North European raw ham using the optimized HS-Trap GC-FID method. For peak identification, see Table 3 (IS – internal standard).

Figure 2

Optimization of HS-Trap GC-FID parameters: (a) Time to reach equilibrium (thermostatting temperature 40 °C) (n = 4), (b) effect of vial extractions (number of cycles) (n = 4) and (c) effect of salting on the peak area of raw meat (RM) and raw ham (RH) samples with water (H2O) or saturated sodium chloride solution (NaCl) separated by a dashed line (n = 3) of selected compounds butanone, 3-methyl-butanal, pentanone, hexanal, 1-octen-3-ol, benzaldehyde and acetophenone. Different letters indicated significant differences at a significance level of α = 0.05 separately for RM and RH.

36

8

FIGURES

Figure 1

(color for online version; black and white for print version)

37

Figure 2

(black and white for online and print version)

38

9

SUPPLEMENTARY MATERIAL

Supplemental material 1

Operating principle of the Headspace-Trap-GC-system (image of the AirToxicTM Trap (center)) with equilibration (top left), pressurization (bottom left), trap load (bottom center), dry purge (bottom right) and trap desorption step (top right) (provided by Perkin Elmer, Germany).

39

Supplemental material 2

Comparison between conventional Headspace-GC-FID (red line; without trap enrichment) and Headspace-TrapGC-FID (blue line; with trap enrichment) for (a) raw ham added with highly concentrated calibration standard and (b) raw ham with internal standard (Section 2.3).

40