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Multigas sensors for the quality control of spice mixtures
Food Control 26 (2012) 23e27
Contents lists available at SciVerse ScienceDirect
Food Control journal homepage: www.elsevier.com/locate/foodcont
Short communication
Multigas sensors for the quality control of spice mixtures Ulrich Banach, Carlo Tiebe, Thomas Hübert* BAM Federal Institute for Materials Research and Testing, 12203 Berlin, Germany
a r t i c l e i n f o
a b s t r a c t
Article history: Received 18 August 2011 Received in revised form 22 December 2011 Accepted 3 January 2012
Spices have an important impact on daily aliment. Changes of their quality resulting in far reaching consequences in different foodstuffs and imply financial losing and even health hazard. In this study it is demonstrated that application of two different portable multi gas sensors (electronic nose and ion mobility spectrometer) supported by multivariate data analysis can contribute to ensure quality control of spice mixtures and to find out product adulteration. Headspace above spice mixtures for sausages and saveloy and product counterfeitings was investigated by a metal oxide based electronic nose (e-nose of KAMINA-type). Linear discriminant analysis (LDA) of sensor resistivity data was performed for differentiation. Simultaneously an ion mobility spectrometer (IMS) was coupled to the emission chamber for detection of gaseous components above spice mixtures. The measured spectra show differences between the two spice mixtures and were discussed using a principal component analysis (PCA). The two multi gas sensors permit discrimination between the types of spice mixtures and can indicate product adulteration. Additionally, a headspace gas analysis by gas chromatography was performed to identify the main volatile components and to prove the chemical basis for the observed differences of the multi gas sensors. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Spice mixtures Product adulteration Electronic nose Ion mobility spectrometer Gas chromatography Multivariate data analysis
1. Introduction Spices as parts of plants, like dried fruits, seeds, barks and roots are components of many foodstuffs. They essentially contribute to flavor, aroma or color of aliments and can affect to human health. Even if in small amounts, changes of quality and composition of spices result in an unwanted impact on foodstuff. Therefore a quality control is indispensible to avoid wastages and customer complaint. However, the chemical composition of spices is very complex and can vary from batch to batch due to climatic and growth conditions or post harvest treatment. Various volatile organic compounds (VOCs) are responsible for the characteristic odor. The quality assessment includes therefore a sensory (organoleptic) test which requires a trained staff and has subjective aspects. An additional chemical analysis of VOC by gas or liquid chromatography can characterize spices and indicate quality changes but is cost and time consuming. Therefore it was tested whether multi gas sensors, electronic nose and ion mobility spectrometer, are capable to rapidly distinct in-situ between slight variations in gas composition and complex fragrance of spices (Chevance & Farmer, 1999).
* Corresponding author. Tel.: þ49 30 81041824; fax: þ49 30 81041827. E-mail address: [email protected] (T. Hübert). 0956-7135/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodcont.2012.01.015
These devices are known as suitable for online process diagnostics and screening across a wide range of application areas (Borsdorf, Mayer, Zarejousheghani, & Eiceman, 2011; Röck, Barsan, & Weimar, 2008). Electronic noses which are able to transform the chemical information of various mixtures of gases and odors instantly into patterns of data (Gardner & Bartlett, 1999) are suggested to use in food industry for long time (Ampuero & Bosset, 2003; Figen & Balaban, 2008; Münchmeyer & Walte, 2004; Peris & Escuder-Gilabert, 2009), but barely for the investigation of spices (Banach, Tiebe, & Hübert, 2009; Zhang, Balaban, Principe, & Portier, 2005). The IMS technique is a well established very sensitive method in rapid gas phase detection of chemical warfare agents and explosives. A promising approach is the application in the field of odor detection (Eiceman & Stone, 2004; Stach & Baumbach, 2002; Vautz et al., 2006). Ion mobility spectrometry is also applied for food chemical analysis to discriminate three classes of olive oils (Garrido-Delago et al., 2011). However, it has to be considered that volatile components in very different concentrations are responsible for the odor of a spice. Due to the different odor sensitivity of human nose, there is no simple relation between odor and the measured sensor signals which are related to the concentration of gaseous components. For that description odor of spices was excluded and the aim of this work was restricted to test how this sensor techniques can contribute to an enhancement in quality control and safety against product adulteration of spice mixtures.
24
U. Banach et al. / Food Control 26 (2012) 23e27
2. Material and methods 2.1. Spice mixtures Samples provided by Kahler-Gewürze GmbH Berlin, were used to determine differences between original and product adulterations of spice mixtures. The first sample was a “saveloy” spice mixture and the fraud contains an admixture of 20% of a curry spice. The second was a “sausages” spice mixture and the adulteration contains 80% original spices and 20% of garlic powder. Always original and adulteration had the same color. Spice mixtures are complex and their complete ingredients were usually not disclosed by the manufacturer. 2.2. Experimental setup A vitreous emission chamber of 2.5 L volume was used to generate a gaseous headspace atmosphere of spice scent. Always 20 g of each spice mixture was placed in the chamber to investigate headspace composition (Fig. 1). All tube connections of the chamber were closed after a spice mixture was put inside. The spice mixtures were stored in the emission chamber for 1 h at 25 C in order to achieve a defined degree of evaporation before the analyses were started, what enablers a sufficient loading of the enclosed atmosphere by volatile spice components however without overloading the detector system. Then the connections were opened and the pump of the electronic nose initializes a gas flow of 500 sccm min1 for 30 min. The VOC loaded air is divided via a three way valve and flows both the electronic nose and the ion mobility spectrometer. Simultaneously, the consumed loaded air is changed by indoor air. The indoor air was purified by a particle filter and activated charcoal.
reactant ions (RI) of the type (H2O)nHþ are gained. These ions will react with volatile organic compounds from the sample to form product ions - protonated monomers (MHþ) and proton bound dimers (M2Hþ) (Eiceman & Karpas 2005, pp.3e7). Ionized analyte molecules are injected by an ion shutter into a drift tube. The ions move through an electric field toward a Faraday plate (detector) where, accordingly, an ion current can be measured. The results of these measurements are spectra which show a distribution of signal intensity (current) against the drift time of ions (td,i) in an electric field over a certain distance. Details of the measuring procedure of VOCs using a portable IMS are also given in Tiebe, Miessner, Koch, and Hübert, (2009). Because of slightly unsteady experimental conditions, the quotient of drift time (td,i) of an analyte molecules and the drift time of the reactant ions (td,RI), the so called relative drift times (trd) is used (Eiceman & Karpas 2005, pp.3e7):
trd ¼
td;i td;RI
(1)
Whereas the relative drift time for the reactant ions is always 1.00, analyte molecules usually moves slower through the drift tube than the reactant ions and have therefore higher relative drift times. Each spice mixture was measured during the 30 min purging period for three times. 2.5. Gas chromatographyemass spectrometry (GCeMS)
The electronic nose (KAMINA-type, Yson GmbH) contains a chip array of 38 sensor segments based on gas sensitive doped tin oxide. Resistivity of the sensor segments in the range of 105e107 Ohm was measured every second for 30 min in purified air as reference and then for 30 min in headspace of spice mixtures. The original data were processed by program COMMAS and the resistivity data of each sensor were always referenced to the appropriate signal for synthetic air for further discussion.
The analysis of volatile organic compounds (VOCs) from spice mixtures headspace was performed in order to identify the main compounds which are responsible for their odor by Gas chromatographyemass spectrometry (GC: HP6890, MS: HP5972, Agilent Technologies). A SPME fiber of 0.75 mm diameter coated by carboxen/polydimethylsiloxane (CAR/PDMS, SigmaeAldrich) was used for sampling of VOCs from headspace. One gram of each spice mixture sample was put in a 20 mL vial with PTFE-septum at room temperature (25 C) for 1 h. The adsorption time of the SPME fiber was 1 min. VOCs desorption was performed at 250 C for 1 min in the GC inlet. A mass spectrometer detector was used for identification of the desorbed substances. Details of this analytical method are given in Table 1. In Table 2 the performance of the three methods was compared in terms of this application.
2.4. Ion mobility spectrometry (IMS)
3. Results and discussion
The VOCs were detected by the IMS-MINI (Environics-IUT, Berlin). An ion mobility spectrometer measures the drift velocity of gas-phase ions in an electric field at ambient pressure. Water molecules in air were ionized by b-radiation and positive charged
3.1. Electronic nose
2.3. Electronic nose
Raw data of the 38 sensor segments acquired by exposing the sensor array continuously for 30 min of each experiment. The
Fig. 1. Experimental setup for the headspace measurement on spice mixtures in a glass container by e-nose (left) and ion mobility spectrometer (right).
U. Banach et al. / Food Control 26 (2012) 23e27
25
Table 1 GCeMS operation parameter to investigate the qualitative composition of the spice mixtures headspace. Detail
Operating parameter
Inlet (splitless) GCeMS interface Column
250 C 280 C HP DB-624 30 m 320 mm 1.8 mm T0 50 C for 0.5 min T1 9 K min1 to 80 C T2 12 K min1 to 180 C hold for 1 min T3 12 K min1 to 240 C hold for 1 min Helium 12.2 mL min1 Full Scan m/z ¼ 30 to 200 NIST database - NBS75K.L
Oven
Carrier gas Total flow MS MS-Library
compiled signals are shown in Fig. 2. The VOCs in headspace on spice mixtures results in a different reduce of the sensor resistivity. The time dependent decrease in resistivity values reflects above all the measuring dynamics of the sensor elements. One has to consider for data processing that the signals of single sensors are not very specific to a certain spice mixtures. On the other hand, several or all sensor elements together, which have different selectivity and sensitivity, can contain information, which correlates with the odor of the spice. In order to extract this from the large number of resistance values, a Linear Discriminant Analysis (LDA) was performed by using the program LDAMT (FZ Karlsruhe). Hereby the resistivity data of each sensor were referenced to the appropriated values of synthetic air and normalized by the median. In Fig. 3 results of the LDA are given. The data of three headspace measurements on each spice mixture and in between of purified air as reference were used. All four spice mixtures are clearly distinguished and even the two product adulterations can be differentiated from the original. 3.2. Ion mobility spectrometry Spectra from headspace of the saveloy spice mixtures, given in Fig. 4a, show sharp defined peaks between 1.00 and 1.70 as well as broad areas of superposition and increased background. The reactant ion peak (td,RI ¼ 1.00) of reduced intensity is visible in all spectra, what indicates conventional measuring conditions. The three peaks at 1.05, 1.14 and 1.39 were also observed in the spectra from headspace of the empty emission chamber before spice mixtures were put inside (blank). Further peaks at 1.26, 1.33, 1.47 and 1.66 can be related to the spice mixture. Because of the complex headspace composition, an assignment of peaks to ionized species of defined compounds was performed. In Fig. 4b, again peaks at 1.00, 1.05, 1.14 and characteristic to spice mixture at 1.26, 1.33, 1.39, 1.47 1.66 as well as a broad band in the relative drift time range from 1.70 to 1.90 can be observed. It is assumed that this is an interference of many interacting species from various VOCs. Nevertheless, the spectra of different spice mixtures as a whole can be distinguished due to the peak position, intensity and shape. A principal component analysis (PCA) was performed in order to compare the investigated spectra to reveal a correlation between
Fig. 2. Raw data of headspace measurement by e-nose on four spice mixtures and purified air as reference.
the spice mixtures using program RapidMiner 4.6 (Rapid-I GmbH. Dortmund). The set of 812 signal intensity data for each spectrum in the range of relative drift time from 0.75 to 2.00 was used. The plot of the two main principal components (PC) in Fig. 5 displays the results of the threefold measurement of each spice mixture. There are mapped four groups of data - spice mixture for sausages (original and adulteration) and spice mixture for saveloy (original and adulteration). The two different spice mixtures can be distinguished by PC 1. The data which have a negative PC 1 belong to spice mixture for saveloy. Data with a positive PC 1 are assigned to spice mixture for sausages. A differentiation between original and adulterated spice mixtures is given by PC 2. Data which have a positive PC 2 according to the original spice mixture. This multivariate data analysis show that it is possible to achieve an indication of difference between original and adulteration spice mixtures. 3.3. GCeMS investigations Table 3 gives qualitative results of identified VOCs in headspace of saveloy and sausages spice mixtures. The main identified substances detected both from original composition as well as from adulterated were listed. These compounds are ingredients of spices or were added as flavor components. The spice mixtures for saveloy
Table 2 Comparison of sensor performance. Method
Sensitivity
Selectivity
Analysis time in min
Costs
E-nose IMS GCeMS
high very high very high
high low very high
40 <10 >30
15 TV 20 TV >50 TV
Fig. 3. The results of LDA analysis for distinguish spice mixtures.
26
a
U. Banach et al. / Food Control 26 (2012) 23e27 Table 3 VOC in headspace of spice mixtures detected by GCeMS.
25 Original Adultaration
No.
Compound
Original
Signal Intensity in a. i.
20
15
10
5
0 0.80
b
1.00
1.20
1.40
1.60
1.80
2.00
Relative Drift Time 30
1
ethyl butyrate
2
a-phellandrene
3
a-pinene
4
sabinene
5
b-pinene
6
mycrene
7
3-carene
8
b-phellandren
9
limonene
10
g-terpinene
11
ethyl heptanoate
12
linalool
13
ethyl octanoate
Sausages Adulteration
Original
Adulteration
Original Adultaration
25 Signal Intensity in a. i.
Saveloy
20
and sausages can be distinguished by the MS spectra, but the identification of adulteration seems not clear. The addition of curry containing black pepper to saveloy mixture is indicated by 3carene. Although the adulterated spice mixture for sausages contains 20 wt% garlic, the typical natural, volatile ingredient alliin is not observable by GCeMS. One reason may be the enzymatic conversion of alliin to the non-volatile and decomposable allicin of fresh, chopped garlic (Iberl, Winkler, Müller, & Knobloch, 1990; Kourounakis & Rekka, 1991).
15 10 5 0 0.80
1.00
1.20
1.40
1.60
1.80
2.00
Relative Drift Time Fig. 4. IMS spectra of headspace measurements showing odor differences of a) saveloy spice mixtures, b) sausages spice mixtures. Temperature of IMS drift tube 47 C, td,RI ¼ 6.47 ms.
50 40
4. Conclusions These results obtained from a headspace detection of volatile organic compounds by electronic nose and ion mobility spectrometer demonstrate that a discrimination of spice mixtures is possible. Distinct changes in composition of spice mixtures which were not easily observable for example by color changes can be indicated and documented. Conventional chemical analysis and olfactometric investigations will not be obsolete. However, e-noses or ion mobility spectrometer can serve as cost efficient devices in applications where quality control and monitoring is required. Also, these methods can be used to provide information, when a suspicious sample for further chemical analysis should be taken.
30
Acknowledgments
PC 2 (29.7 %)
20 10
We thank Kahler-Gewürze GmbH, Berlin for providing the spice mixtures.
0 -10
References -20 -30 Spice for saveloy Original Adulteration
-40 -50 -70
-60
-50
-40
-30
-20
-10
Spice for sausages Original Adulteration
0
10
20
PC 1 (64.1 %) Fig. 5. PCA of spice mixtures.
30
40
50
60
70
Ampuero, S., & Bosset, J. O. (2003). The electronic nose applied to dairy products: a review. Sensors and Actuators B: Chemical, 94, 1e12. Banach, U., Tiebe, C., & Hübert, T. (2009). Application of electronic nose and ion mobility spectrometer to quality control of spice mixtures. In Proceedings of the 13th International Symposium on Olfaction and Electronic Nose (pp. 301e302). AIP. Borsdorf, H., Mayer, T., Zarejousheghani, M., & Eiceman, G. A. (2011). Recent developments in ion mobility spectrometry. Applied Spectroscopy Reviews, 46, 472e521. Chevance, F. F. V., & Farmer, L. J. (1999). Journal of Agricultural and Food Chemistry, 47, 5151e5160.
U. Banach et al. / Food Control 26 (2012) 23e27 Eiceman, G. A., & Karpas, Z. (2005). Ion mobility spectrometry. Boca Raton: Taylor & Francis Group. Eiceman, G. A., & Stone, J. A. (2004). Analytical Chemistry, 76, 390ae397a. Figen, F., & Balaban, M. (2008). Electronic nose technology in food analysis. In Handbook of food analysis instruments (pp. 365e374). Taylor & Francis. Gardner, J. W., & Bartlett, P. N. (1999). Electronic noses principles and applications (1st ed.). Oxford University Publ. Garrido-Delgado, R., Mercader-Trejo, F., Sielemann, S., de Bruyn, W., Arce, L., & Valcarcel, M. (2011). Direct classification of olive oils by using two types of ion mobility spectrometers. Analytica Chimica Acta, 696, 108. Iberl, B., Winkler, G., Müller, B., & Knobloch, K. (1990). Planta Medica, 56, 320e326. Kourounakis, P. N., & Rekka, E. A. (1991). Research Communications in Chemical Pathology and Pharmacology, 74, 249e252. Münchmeyer, W., & Walte, A. (2004). Elektronische Nasen in der Lebensmittelindustrie. LaborPraxis, 2004, 34e39.
27
Peris, M., & Escuder-Gilabert, L. (2009). A 21st century technique for food control: electronic noses. Analytica Chimica Acta, 638, 1e15. Röck, F., Barsan, N., & Weimar, U. (2008). Electronic nose: principles and future trends. Chemical Reviews, 108, 705e725. Stach, J., & Baumbach, J. I. (2002). International Journal for Ion Mobility Spectrometry, 5, 1e21. Tiebe, C., Miessner, H., Koch, B., & Hübert, T. (2009). Detection of microbial volatile organic compounds (MVOC) by ion-mobility spectrometry. Analytical and Bioanalytical Chemistry, 395, 2313e2323. Vautz, W., Zimmermann, D., Hartmann, M., Baumbach, J. I., Nolte, J., & Jung, J. (2006). Ion mobility spectrometry for food quality and safety. Food Additives and Contaminants: Part A, 23, 1064e1073. Zhang, H., Balaban, M., Principe, J. C., & Portier, K. (2005). Quantification of spice mixture compositions by electronic nose. Journal of Food Science, 70, E253eE258, E259eE264.
Contents lists available at SciVerse ScienceDirect
Food Control journal homepage: www.elsevier.com/locate/foodcont
Short communication
Multigas sensors for the quality control of spice mixtures Ulrich Banach, Carlo Tiebe, Thomas Hübert* BAM Federal Institute for Materials Research and Testing, 12203 Berlin, Germany
a r t i c l e i n f o
a b s t r a c t
Article history: Received 18 August 2011 Received in revised form 22 December 2011 Accepted 3 January 2012
Spices have an important impact on daily aliment. Changes of their quality resulting in far reaching consequences in different foodstuffs and imply financial losing and even health hazard. In this study it is demonstrated that application of two different portable multi gas sensors (electronic nose and ion mobility spectrometer) supported by multivariate data analysis can contribute to ensure quality control of spice mixtures and to find out product adulteration. Headspace above spice mixtures for sausages and saveloy and product counterfeitings was investigated by a metal oxide based electronic nose (e-nose of KAMINA-type). Linear discriminant analysis (LDA) of sensor resistivity data was performed for differentiation. Simultaneously an ion mobility spectrometer (IMS) was coupled to the emission chamber for detection of gaseous components above spice mixtures. The measured spectra show differences between the two spice mixtures and were discussed using a principal component analysis (PCA). The two multi gas sensors permit discrimination between the types of spice mixtures and can indicate product adulteration. Additionally, a headspace gas analysis by gas chromatography was performed to identify the main volatile components and to prove the chemical basis for the observed differences of the multi gas sensors. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Spice mixtures Product adulteration Electronic nose Ion mobility spectrometer Gas chromatography Multivariate data analysis
1. Introduction Spices as parts of plants, like dried fruits, seeds, barks and roots are components of many foodstuffs. They essentially contribute to flavor, aroma or color of aliments and can affect to human health. Even if in small amounts, changes of quality and composition of spices result in an unwanted impact on foodstuff. Therefore a quality control is indispensible to avoid wastages and customer complaint. However, the chemical composition of spices is very complex and can vary from batch to batch due to climatic and growth conditions or post harvest treatment. Various volatile organic compounds (VOCs) are responsible for the characteristic odor. The quality assessment includes therefore a sensory (organoleptic) test which requires a trained staff and has subjective aspects. An additional chemical analysis of VOC by gas or liquid chromatography can characterize spices and indicate quality changes but is cost and time consuming. Therefore it was tested whether multi gas sensors, electronic nose and ion mobility spectrometer, are capable to rapidly distinct in-situ between slight variations in gas composition and complex fragrance of spices (Chevance & Farmer, 1999).
* Corresponding author. Tel.: þ49 30 81041824; fax: þ49 30 81041827. E-mail address: [email protected] (T. Hübert). 0956-7135/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodcont.2012.01.015
These devices are known as suitable for online process diagnostics and screening across a wide range of application areas (Borsdorf, Mayer, Zarejousheghani, & Eiceman, 2011; Röck, Barsan, & Weimar, 2008). Electronic noses which are able to transform the chemical information of various mixtures of gases and odors instantly into patterns of data (Gardner & Bartlett, 1999) are suggested to use in food industry for long time (Ampuero & Bosset, 2003; Figen & Balaban, 2008; Münchmeyer & Walte, 2004; Peris & Escuder-Gilabert, 2009), but barely for the investigation of spices (Banach, Tiebe, & Hübert, 2009; Zhang, Balaban, Principe, & Portier, 2005). The IMS technique is a well established very sensitive method in rapid gas phase detection of chemical warfare agents and explosives. A promising approach is the application in the field of odor detection (Eiceman & Stone, 2004; Stach & Baumbach, 2002; Vautz et al., 2006). Ion mobility spectrometry is also applied for food chemical analysis to discriminate three classes of olive oils (Garrido-Delago et al., 2011). However, it has to be considered that volatile components in very different concentrations are responsible for the odor of a spice. Due to the different odor sensitivity of human nose, there is no simple relation between odor and the measured sensor signals which are related to the concentration of gaseous components. For that description odor of spices was excluded and the aim of this work was restricted to test how this sensor techniques can contribute to an enhancement in quality control and safety against product adulteration of spice mixtures.
24
U. Banach et al. / Food Control 26 (2012) 23e27
2. Material and methods 2.1. Spice mixtures Samples provided by Kahler-Gewürze GmbH Berlin, were used to determine differences between original and product adulterations of spice mixtures. The first sample was a “saveloy” spice mixture and the fraud contains an admixture of 20% of a curry spice. The second was a “sausages” spice mixture and the adulteration contains 80% original spices and 20% of garlic powder. Always original and adulteration had the same color. Spice mixtures are complex and their complete ingredients were usually not disclosed by the manufacturer. 2.2. Experimental setup A vitreous emission chamber of 2.5 L volume was used to generate a gaseous headspace atmosphere of spice scent. Always 20 g of each spice mixture was placed in the chamber to investigate headspace composition (Fig. 1). All tube connections of the chamber were closed after a spice mixture was put inside. The spice mixtures were stored in the emission chamber for 1 h at 25 C in order to achieve a defined degree of evaporation before the analyses were started, what enablers a sufficient loading of the enclosed atmosphere by volatile spice components however without overloading the detector system. Then the connections were opened and the pump of the electronic nose initializes a gas flow of 500 sccm min1 for 30 min. The VOC loaded air is divided via a three way valve and flows both the electronic nose and the ion mobility spectrometer. Simultaneously, the consumed loaded air is changed by indoor air. The indoor air was purified by a particle filter and activated charcoal.
reactant ions (RI) of the type (H2O)nHþ are gained. These ions will react with volatile organic compounds from the sample to form product ions - protonated monomers (MHþ) and proton bound dimers (M2Hþ) (Eiceman & Karpas 2005, pp.3e7). Ionized analyte molecules are injected by an ion shutter into a drift tube. The ions move through an electric field toward a Faraday plate (detector) where, accordingly, an ion current can be measured. The results of these measurements are spectra which show a distribution of signal intensity (current) against the drift time of ions (td,i) in an electric field over a certain distance. Details of the measuring procedure of VOCs using a portable IMS are also given in Tiebe, Miessner, Koch, and Hübert, (2009). Because of slightly unsteady experimental conditions, the quotient of drift time (td,i) of an analyte molecules and the drift time of the reactant ions (td,RI), the so called relative drift times (trd) is used (Eiceman & Karpas 2005, pp.3e7):
trd ¼
td;i td;RI
(1)
Whereas the relative drift time for the reactant ions is always 1.00, analyte molecules usually moves slower through the drift tube than the reactant ions and have therefore higher relative drift times. Each spice mixture was measured during the 30 min purging period for three times. 2.5. Gas chromatographyemass spectrometry (GCeMS)
The electronic nose (KAMINA-type, Yson GmbH) contains a chip array of 38 sensor segments based on gas sensitive doped tin oxide. Resistivity of the sensor segments in the range of 105e107 Ohm was measured every second for 30 min in purified air as reference and then for 30 min in headspace of spice mixtures. The original data were processed by program COMMAS and the resistivity data of each sensor were always referenced to the appropriate signal for synthetic air for further discussion.
The analysis of volatile organic compounds (VOCs) from spice mixtures headspace was performed in order to identify the main compounds which are responsible for their odor by Gas chromatographyemass spectrometry (GC: HP6890, MS: HP5972, Agilent Technologies). A SPME fiber of 0.75 mm diameter coated by carboxen/polydimethylsiloxane (CAR/PDMS, SigmaeAldrich) was used for sampling of VOCs from headspace. One gram of each spice mixture sample was put in a 20 mL vial with PTFE-septum at room temperature (25 C) for 1 h. The adsorption time of the SPME fiber was 1 min. VOCs desorption was performed at 250 C for 1 min in the GC inlet. A mass spectrometer detector was used for identification of the desorbed substances. Details of this analytical method are given in Table 1. In Table 2 the performance of the three methods was compared in terms of this application.
2.4. Ion mobility spectrometry (IMS)
3. Results and discussion
The VOCs were detected by the IMS-MINI (Environics-IUT, Berlin). An ion mobility spectrometer measures the drift velocity of gas-phase ions in an electric field at ambient pressure. Water molecules in air were ionized by b-radiation and positive charged
3.1. Electronic nose
2.3. Electronic nose
Raw data of the 38 sensor segments acquired by exposing the sensor array continuously for 30 min of each experiment. The
Fig. 1. Experimental setup for the headspace measurement on spice mixtures in a glass container by e-nose (left) and ion mobility spectrometer (right).
U. Banach et al. / Food Control 26 (2012) 23e27
25
Table 1 GCeMS operation parameter to investigate the qualitative composition of the spice mixtures headspace. Detail
Operating parameter
Inlet (splitless) GCeMS interface Column
250 C 280 C HP DB-624 30 m 320 mm 1.8 mm T0 50 C for 0.5 min T1 9 K min1 to 80 C T2 12 K min1 to 180 C hold for 1 min T3 12 K min1 to 240 C hold for 1 min Helium 12.2 mL min1 Full Scan m/z ¼ 30 to 200 NIST database - NBS75K.L
Oven
Carrier gas Total flow MS MS-Library
compiled signals are shown in Fig. 2. The VOCs in headspace on spice mixtures results in a different reduce of the sensor resistivity. The time dependent decrease in resistivity values reflects above all the measuring dynamics of the sensor elements. One has to consider for data processing that the signals of single sensors are not very specific to a certain spice mixtures. On the other hand, several or all sensor elements together, which have different selectivity and sensitivity, can contain information, which correlates with the odor of the spice. In order to extract this from the large number of resistance values, a Linear Discriminant Analysis (LDA) was performed by using the program LDAMT (FZ Karlsruhe). Hereby the resistivity data of each sensor were referenced to the appropriated values of synthetic air and normalized by the median. In Fig. 3 results of the LDA are given. The data of three headspace measurements on each spice mixture and in between of purified air as reference were used. All four spice mixtures are clearly distinguished and even the two product adulterations can be differentiated from the original. 3.2. Ion mobility spectrometry Spectra from headspace of the saveloy spice mixtures, given in Fig. 4a, show sharp defined peaks between 1.00 and 1.70 as well as broad areas of superposition and increased background. The reactant ion peak (td,RI ¼ 1.00) of reduced intensity is visible in all spectra, what indicates conventional measuring conditions. The three peaks at 1.05, 1.14 and 1.39 were also observed in the spectra from headspace of the empty emission chamber before spice mixtures were put inside (blank). Further peaks at 1.26, 1.33, 1.47 and 1.66 can be related to the spice mixture. Because of the complex headspace composition, an assignment of peaks to ionized species of defined compounds was performed. In Fig. 4b, again peaks at 1.00, 1.05, 1.14 and characteristic to spice mixture at 1.26, 1.33, 1.39, 1.47 1.66 as well as a broad band in the relative drift time range from 1.70 to 1.90 can be observed. It is assumed that this is an interference of many interacting species from various VOCs. Nevertheless, the spectra of different spice mixtures as a whole can be distinguished due to the peak position, intensity and shape. A principal component analysis (PCA) was performed in order to compare the investigated spectra to reveal a correlation between
Fig. 2. Raw data of headspace measurement by e-nose on four spice mixtures and purified air as reference.
the spice mixtures using program RapidMiner 4.6 (Rapid-I GmbH. Dortmund). The set of 812 signal intensity data for each spectrum in the range of relative drift time from 0.75 to 2.00 was used. The plot of the two main principal components (PC) in Fig. 5 displays the results of the threefold measurement of each spice mixture. There are mapped four groups of data - spice mixture for sausages (original and adulteration) and spice mixture for saveloy (original and adulteration). The two different spice mixtures can be distinguished by PC 1. The data which have a negative PC 1 belong to spice mixture for saveloy. Data with a positive PC 1 are assigned to spice mixture for sausages. A differentiation between original and adulterated spice mixtures is given by PC 2. Data which have a positive PC 2 according to the original spice mixture. This multivariate data analysis show that it is possible to achieve an indication of difference between original and adulteration spice mixtures. 3.3. GCeMS investigations Table 3 gives qualitative results of identified VOCs in headspace of saveloy and sausages spice mixtures. The main identified substances detected both from original composition as well as from adulterated were listed. These compounds are ingredients of spices or were added as flavor components. The spice mixtures for saveloy
Table 2 Comparison of sensor performance. Method
Sensitivity
Selectivity
Analysis time in min
Costs
E-nose IMS GCeMS
high very high very high
high low very high
40 <10 >30
15 TV 20 TV >50 TV
Fig. 3. The results of LDA analysis for distinguish spice mixtures.
26
a
U. Banach et al. / Food Control 26 (2012) 23e27 Table 3 VOC in headspace of spice mixtures detected by GCeMS.
25 Original Adultaration
No.
Compound
Original
Signal Intensity in a. i.
20
15
10
5
0 0.80
b
1.00
1.20
1.40
1.60
1.80
2.00
Relative Drift Time 30
1
ethyl butyrate
2
a-phellandrene
3
a-pinene
4
sabinene
5
b-pinene
6
mycrene
7
3-carene
8
b-phellandren
9
limonene
10
g-terpinene
11
ethyl heptanoate
12
linalool
13
ethyl octanoate
Sausages Adulteration
Original
Adulteration
Original Adultaration
25 Signal Intensity in a. i.
Saveloy
20
and sausages can be distinguished by the MS spectra, but the identification of adulteration seems not clear. The addition of curry containing black pepper to saveloy mixture is indicated by 3carene. Although the adulterated spice mixture for sausages contains 20 wt% garlic, the typical natural, volatile ingredient alliin is not observable by GCeMS. One reason may be the enzymatic conversion of alliin to the non-volatile and decomposable allicin of fresh, chopped garlic (Iberl, Winkler, Müller, & Knobloch, 1990; Kourounakis & Rekka, 1991).
15 10 5 0 0.80
1.00
1.20
1.40
1.60
1.80
2.00
Relative Drift Time Fig. 4. IMS spectra of headspace measurements showing odor differences of a) saveloy spice mixtures, b) sausages spice mixtures. Temperature of IMS drift tube 47 C, td,RI ¼ 6.47 ms.
50 40
4. Conclusions These results obtained from a headspace detection of volatile organic compounds by electronic nose and ion mobility spectrometer demonstrate that a discrimination of spice mixtures is possible. Distinct changes in composition of spice mixtures which were not easily observable for example by color changes can be indicated and documented. Conventional chemical analysis and olfactometric investigations will not be obsolete. However, e-noses or ion mobility spectrometer can serve as cost efficient devices in applications where quality control and monitoring is required. Also, these methods can be used to provide information, when a suspicious sample for further chemical analysis should be taken.
30
Acknowledgments
PC 2 (29.7 %)
20 10
We thank Kahler-Gewürze GmbH, Berlin for providing the spice mixtures.
0 -10
References -20 -30 Spice for saveloy Original Adulteration
-40 -50 -70
-60
-50
-40
-30
-20
-10
Spice for sausages Original Adulteration
0
10
20
PC 1 (64.1 %) Fig. 5. PCA of spice mixtures.
30
40
50
60
70
Ampuero, S., & Bosset, J. O. (2003). The electronic nose applied to dairy products: a review. Sensors and Actuators B: Chemical, 94, 1e12. Banach, U., Tiebe, C., & Hübert, T. (2009). Application of electronic nose and ion mobility spectrometer to quality control of spice mixtures. In Proceedings of the 13th International Symposium on Olfaction and Electronic Nose (pp. 301e302). AIP. Borsdorf, H., Mayer, T., Zarejousheghani, M., & Eiceman, G. A. (2011). Recent developments in ion mobility spectrometry. Applied Spectroscopy Reviews, 46, 472e521. Chevance, F. F. V., & Farmer, L. J. (1999). Journal of Agricultural and Food Chemistry, 47, 5151e5160.
U. Banach et al. / Food Control 26 (2012) 23e27 Eiceman, G. A., & Karpas, Z. (2005). Ion mobility spectrometry. Boca Raton: Taylor & Francis Group. Eiceman, G. A., & Stone, J. A. (2004). Analytical Chemistry, 76, 390ae397a. Figen, F., & Balaban, M. (2008). Electronic nose technology in food analysis. In Handbook of food analysis instruments (pp. 365e374). Taylor & Francis. Gardner, J. W., & Bartlett, P. N. (1999). Electronic noses principles and applications (1st ed.). Oxford University Publ. Garrido-Delgado, R., Mercader-Trejo, F., Sielemann, S., de Bruyn, W., Arce, L., & Valcarcel, M. (2011). Direct classification of olive oils by using two types of ion mobility spectrometers. Analytica Chimica Acta, 696, 108. Iberl, B., Winkler, G., Müller, B., & Knobloch, K. (1990). Planta Medica, 56, 320e326. Kourounakis, P. N., & Rekka, E. A. (1991). Research Communications in Chemical Pathology and Pharmacology, 74, 249e252. Münchmeyer, W., & Walte, A. (2004). Elektronische Nasen in der Lebensmittelindustrie. LaborPraxis, 2004, 34e39.
27
Peris, M., & Escuder-Gilabert, L. (2009). A 21st century technique for food control: electronic noses. Analytica Chimica Acta, 638, 1e15. Röck, F., Barsan, N., & Weimar, U. (2008). Electronic nose: principles and future trends. Chemical Reviews, 108, 705e725. Stach, J., & Baumbach, J. I. (2002). International Journal for Ion Mobility Spectrometry, 5, 1e21. Tiebe, C., Miessner, H., Koch, B., & Hübert, T. (2009). Detection of microbial volatile organic compounds (MVOC) by ion-mobility spectrometry. Analytical and Bioanalytical Chemistry, 395, 2313e2323. Vautz, W., Zimmermann, D., Hartmann, M., Baumbach, J. I., Nolte, J., & Jung, J. (2006). Ion mobility spectrometry for food quality and safety. Food Additives and Contaminants: Part A, 23, 1064e1073. Zhang, H., Balaban, M., Principe, J. C., & Portier, K. (2005). Quantification of spice mixture compositions by electronic nose. Journal of Food Science, 70, E253eE258, E259eE264.