INTRODUCTION

I. Volatile compounds applied to the characterisation of vegetable oils and fats: Volatile compounds, especially those with olfactive properties, aroused hu- mans’ interest since ancient times. With the invention of the condenser, humans began isolating essential oils. Meanwhile studies of volatile com- pounds have extended from simple olfactory research to examinations of medicinal properties, physiological and psychological effects. In the 1970s instrumental analysis, particularly capillary Gas Chromatography (GC) and Mass Spectrometry (MS) had reached such a high level of sensitivity that the analytical investigation of micro-samples could be envisaged. Modern head- space isolation methods like Solid Phase Microextraction (SPME) and mod- ern analytical techniques now permit researchers to sample traces of vola- tile compounds (Kaiser, 2006; Teranishi et al., 1993). This provides new po– tentialities for analytical research.

I.1. Current major problems of the analysis of fatty plant oils: Oils of high dietary value (e.g. olive oils) as well as such ones used for phar- maceutical and medicinal purposes (e.g. linseed oil) have to fulfil restrictive quality criteria that can be considerably weakened by blending and adultera- tion. Furthermore, the increasingly complex nature of industrial food proc- essing, questions about food safety and authenticity are of growing interest for consumers and control authorities. Taking into consideration the fact that established routine methods for quality control of fatty plant oils and plant fats (iodine number, refraction index, acid number, peroxide number, , melting point, solidification point and com- position), established some decades ago (Pardun, 1976), often do not pro- vide satisfying results and that blending of high price plant oils (e.g. poppy or seed oils) with cheaper vegetable oils (e.g. sunflower oils) is a serious problem (Ulberth et al., 2000), it seemed to be necessary to establish a new analytical method for the characterisation, quality control and authenticity assessment of fatty plant oils. Adulteration, deliberate or accidental, is often a challenge for routine analytical methods, such as the determination of fatty acid (FA) composition, because of sometimes almost similar FA ratios of different oils. Furthermore, as plant oils are natural products, the FA ratio varies considerably due to natural climatic differences and regional variations. Moreover it was shown that not only the major compounds of oils (e.g. TAG and FA) but also minor

10 constituents (e.g. tocopherols, phytosterols, phospholipids, or aroma active compounds) can play a remarkable role in the evaluation of the quality and authenticity of oils (Cserháti et al., 2005).

I.2. Fatty plant oils in the European Pharmacopoeia: The European Pharmacopoeia (5th edition, 2005) regulates identification of fatty plant oils by use of thin layer chromatography (chapter 2.3.2). A refer- ence chromatogram for groundnut oil, sesame oil, oil, oil, soy oil, linseed oil, olive oil, sunflower oil, sweet almond oil, germ oil, borage oil, evening primrose oil and safflower oil is given. Moreover iodine number, refraction index, acid number, peroxide number, saponification value, melting point, number and hydroxyl value solidification point and fatty acid composition are parameters for testing of purity. Identifica- tion of the fatty acid composition is done by GC-FID analysis (2.4.22). - thermore there is a method for identification of sterols in fatty oils (2.4.23). Monographs for 23 vegetable oils are given in the current European Phar- macopoeia. Identification of adulteration of fatty plant oils with other fatty plant oils is also done by thin layer chromatography (2.4.21), detecting the Rf-value of , and the absence of erucic acid.

I.3. Adulteration of fatty plant oils: According to Ozen and Mauer, adulteration of food products, involving the replacement of high-cost ingredients with cheaper substitutes, is a type of economic fraud, that can pose a major health threat to consumers. The Spanish toxic oil syndrome, causing more than 400 deaths and 20000 ill- nesses by adulterated rapeseed and grape seed oil, is well remembered. Generally, the determination of food authenticity and the detection of adul- terations are of increasing importance in the food industry, especially for products of high commercial value. It was reported, that e.g. the adultera- tion of olive oil with oil causes an economic loss of approximately 4 million euros per year for the member states of the European Union. Hence there is a need for rapid and simple detection methods for oil adulteration (Marcos Lorenzo et al., 2002; Ozen & Mauer, 2002; European Union Re- search Committee, 2001; Posada et al., 1987). Meanwhile various techniques (chromatographic, spectroscopic, mathe- matical and chemometric techniques, chemical sensors) have been proposed for the characterisation of oils and for the detection of adulterations (Reid et al., 2006; Cserháti et al. 2005; Aparicio & Aparicio-Ruíz, 2000), especially for those of olive oils with other vegetable oils (Arvanitoyannis & Vlachos, 2007; 11

Christopoulou et al., 2004; Marcos Lorenzo et al., 2002; Ozen & Mauer, 2002; Vichi et al., 2001; Blanch et al., 2000), but none of them has been universally accepted for the determination of the authenticity of the different types of fatty plant oils, and most of these techniques require too much time to be used routinely in the food industry (Marcos Lorenzo et al., 2002). For the discovery of adulteration of Styrian pumpkin seed oil, an analysis method has been published, too (Wenzl et al., 2002; Mandl et al., 1999). In this case the determination of 7-phytosteroles and 5-phytosteroles, espe- cially β-sitosterol, using GC-FID, has been proven to be a good possibility to detect the admixture of cheaper vegetable oils to high price pumpkin seed oil. For other fatty plant oils similar investigations have not been done so far.

I.4 Solid Phase Microextraction (SPME): Many chromatographic analyses consume less time than preparing the sam- ples. Two third of analysis time is typically spent on sampling and preparation steps. And, of course, the possibility for errors (human, systematic or by con- tamination) occurs with each additional step (Scheppers Wercinski, 1999). With the invention of Solid Phase Microextraction (SPME) by Janusz Pawliszyn in 1990 it was possible to achieve the following analysts´ aims: producing samples with the highest analytical concentration possible and the lowest level of contamination with the easiest way to reproduce and least costly procedure. SPME extracts the analytes of interest without addi- tional sampling and does not require the application of solvents. This sam- pling method can be easily automated using a single fiber to consequently sample numerous vials and desorb the sample into a gas or liquid chromato- graph. Also field sampling is possible with SPME (Scheppers Wercinski, 1999, Pawliszyn, 1997). Solid Phase Microextraction is based on an absorption and partly adsorption of analytes onto a polymer-coated silica fibre and their consequent desorption into the heated injector port of a gas chromatograph (Mildner-Szkudlarz et al., 2003). This non-destructive method is characterised by a very high reproduci- bility of analytical results and a minimal input for sample preparation. The “ideal” sample for SPME-analysis is a relatively clean, aqueous sample con- taining volatile or semi-volatile organic compounds. SPME is also suitable for monitoring vaporising volatiles in solid samples. For many samples, applica- tion of SPME can replace purge and trap, solid phase extraction, Soxhlet ex- traction or liquid-liquid extraction and in some cases also Supercritical Fluid Extraction (Penton, 1999). Worth mentioning is the protection of the chro- matographic system and the environment, as no liquid solvents are applied. A quite serious disadvantage of the SPME-technique concerns its appli- cation in fragrance research, as it is not possible to use SPME for the so-

12 called “GC-sniffing” in order to localize trace constituents of decisive olfac- tory importance (Kaiser, 2006). Furthermore, the filigree SPME-fiber is vul- nerable to mechanical damages, especially if used without an auto sampler, and capacity of the fibre is limited. For GC-analysis a special liner suitable for the SPME fibre is needed. For Solid Phase Microextraction a thin skewer of fused silica, coated with an absorbent polymer is used. The coated fused silica fibre, which is very stable even at high temperatures, is attached to a metal rod. The fibre is protected by a metal sheath when it is not in use (Scheppers Wercinski and Pawliszyn, 1999). Meanwhile fibres with various coatings (with film thickness from 7 to 100m) are available (Supelco, 2008). A fibre is chosen based on its selectivity for certain target analytes and their volatility ranges. As both, the matrix and the fibre coating are competing for analytes, the affinity of the fibre coating for target analytes is crucial in SPME sampling. Polar fibre coatings (e.g. carbowax) extract polar compounds such as phenols very well, nonpolar coatings (e.g. polydimethylsiloxane) are most suitable for retaining hydrocarbons. (Scheppers Wercinski and Pawliszyn, 1999).

I.4.1. Sampling with SPME (Stien, 2000):

1. The septum of the sampling vial is pierced by the SPME protective sheath. 2. The plunger is lowered to expose the fibre into the sample headspace. Now the analytes (volatile compounds) are extracted from the sample headspace into the fibre coating. 3. After a defined desorption time the fibre is withdrawn into the protec- tive sheat. 4. The sheat is pulled out of the sampling vial and inserted immediately into the GC injector. 5. The plunger is lowered and the fibre is exposed to high temperature in the GC-injector. The concentrated volatile compounds are thermally desorbed and refocused onto the GC column.

I.4.2. Theory of SPME (Scheppers Wercinski and Pawliszyn, 1999; Louch et al., 1992): Due to the fact that Solid Phase Microextraction is an equilibrium technique, analytes are not completely extracted from the matrix. When the fibre is placed into a closed vial containing the sample, an equilibrium forms be- tween three phases: 1. the fibre coating to the aqueous phase 13

2. the headspace to the aqueous phase 3. the fibre coating to the headspace. The analyte recovery expected from SPME is related to the overall equilib- rium of the three phases in the sampling vial. The distribution among the three phases after equilibrium is represented in the following formula:

∞ ∞ ∞ C0Vs= C hVh+C sVs+C fVf

Where:

C0= initial concentration of analyte in the aqueous solution

Ch= equilibrium concentration of the analyte in the headspace

Cs= equilibrium concentration of the analyte in the aqueous solution

Cf= equilibrium concentration of the analyte in the fiber coating

Vh= volume of the headspace

Vs= volume of the aqueous solution

Vf= volume of the fibre coating

The partion coefficients between the three phases are: Kfh= Cf/Ch Khs= Ch/Cs Kfs= Cf/Cs

As a result, the amount of analyte absorbed by the fibre coating in head- space sampling can be expressed as:

KfsVfVsC0 nf = KfsVf+KhsVh+Vs

I.4.3. Desorption: After sampling, the SPME fiber containing the analytes is ready to be de- sorbed into a GC or HPLC injector for analysis. For GC-analysis, the desorp- tion process starts with inserting the fiber into a hot GC injector. With in- creasing temperature, the coating/gas partion coefficients decrease and the fibre coating´s ability to retain analytes quickly diminishes. The constant flow of carrier gas within the GC injector helps to discharge the analytes from the fibre coating and transfers them to a cool column for refocusing. A desorp- tion time of two minutes is adequate to release all analytes from the fibre coating (Scheppers Wercinski and Pawliszyn, 1999).

14

I.4.4. Applications of SPME: Solid Phase Microextraction is used for pharmaceutical, environmental, food and flavour applications, as well as for forensic and toxicology applications. Concerning pharmaceutical analysis, at first the most obvious application of SPME was the determination of solvent residues in drug substances (Scypin- ski and Smith, 1999; Scypinski et al., 1994). Also terpenoids from herb based formulations have been successfully analysed by SPME coupled with GC-MS (Czerwinski et al. 1996). Kumazawa and his research group published numer- ous applications on the use of SPME for determining various drugs in blood and other body fluids including barbiturates, phenothiazines, benzodiazepi- nes, tricyclic antidepressants and cocain (Kuriki et al., 2006; Iwai et al, 2004; Kumazawa et al., 2000; Seno et al., 1999; Guan et al., 1999; Guan et al. 1998; Lee et al. 1997). Lord and Pawliszyn presented a method optimisation for the analysis of amphetamines in urine by using SPME-analysis (Lord and Pawliszyn, 1997). Also the application of SPME for analysis of essential oils is not to be sneezed (Da Ponte and Decorti, 2008; Yu et al. 2007; Li et al. 2006; Rubiolo et al., 2006; Tranchida et al., 2006; Adam et al. 2005; Deng et al. 2005).

The possible use of SPME for the analysis of volatiles in drinking waters and waste waters has been demonstrated by van der Hoff et al. in 1996. Today, Solid Phase Microextraction is widely used in pesticide analysis (Basheer et al., 2008; Fernandez-Alvarez et al., 2008; Vázquez et al., 2008a; Chai et al., 2007; Stien, 2000).

The advantages of SPME as a rapid, solvent free and relatively inexpensive method can be readily utilised in food analysis. Actual SPME is increasingly used as a rapid screening method for the analysis of foods, beverages and ingredients (Pastorelli et al., 2007; Carasek and Pawliszyn, 2006; Díaz-Ma- roto et al., 2004; Triqui and Bouchriti, 2003; Kataoka et al., 2000; Yang and Peppard, 1999; Jia et al., 1998). On the other hand residue-analysis in foods is an upcoming field for SPME-analysis (Hu et al., 2008; Ravelo-Pérez et al., 2008; Schurek et al., 2008; Vázquez et al. 2008b and c). SPME-GC in combi- nation with chemometric analysis was applied to the detection of the adul- teration of purées with different levels of apple purée (Reid et al., 2004a) and to differentiate between apple juice varieties in terms of ap- ple varieties and applied heat treatment (Reid et al., 2004b). This method also proved to be an effective tool for detecting low levels of fat derived fla- vour compounds (Doleschall et al., 2001; Jelen et al., 2000; Marsili, 2000).

Forensic applications include accelerant, explosives and drug odour analysis (Almirall and Furton, 1999). The recovery of accelerants directly from aque- ous solvents has also been demonstrated with SPME-analysis (Almirall et al., 15

1996), as well as for hair analysis (Musshoff et al., 2007). In analytical toxi- cology solid phase microextraction has been utilised for analysis of almost all human biological fluids (Pragst, 2007; Frison et al., 2006; Flanagan et al., 2006; Gallardo et al., 2006; Iwai et al., 2004).

I.5. Own SPME-GC-MS-method: In the present work HS-SPME-GC-MS is applied to the characterisation, quality control and authenticity assessment of fatty plant oils and plant fats. Up to now a widely unexplored area of research and unusual application for solid phase microextraction. For this task the following method of analysis was developed and evaluated:

Volatiles from each fatty plant oil/plant fat were sampled by Headspace Solid Phase Microextraction (HS-SPME) and subsequently analysed with GC- MS. 10.0g of each oil/fat sample were filled into SPME compatible vials. These vials were tightly sealed with aluminium foil, a septum and aluminium caps. Before extraction, stabilisation of the headspace in the vials was ac- complished by equilibration for 1h at room temperature (22°C). Extraction of the analytes was achieved by a pre-conditioned Supelco 57348 2 cm, 50/30μm DVB/Carboxen/PDMS Stable-Flex (Supelco, Bellefonte, USA) fiber. Sampling at room temperature (22°C) was done for 1-10h, respectively, de- pending on the investigated sample. Before and after each oil sample blank values were analysed. After sampling, the SPME device was placed auto- matically into the GC-MS instrument, an HP-6890 model gas chromatograph equipped with an HP-5972 mass selective detector. To separate volatile compounds a 60m x 0.25mm (i.d.) RTx-5 (Restec, Bellefonte, USA, coating 5% phenyl, 95% dimethylpolysiloxane) non-polar column, film thickness 0.25μm, was used with the following GC temperature program. The start temperature of 38°C was held for 1min, followed by a heating rate of 2.5°C/min to 175°C. From this point the temperature was increased 50°C/min to a temperature of 220°C and was held for 2min. The injector port temperature was 250°C. After 4min of using splitless mode, the split ratio was set to 1:40 to expurgate the GC-MS-system. The split flow was 40.3ml/min. A constant flow of 1ml/min was applied (carrier helium 5.0). The transfer line temperature was 250°C, electron impact ionization at 70eV was used and mass spectra were recorded with a scan range of 10-300amu. Volatile compound identification was carried out by comparison of their retention indices and mass spectra with authentic samples and partly tenta- tively by mass spectra library search (Wiley 275, NBS 98 and in-house spec- tra libraries) and calculation of retention indices (RI). RIs of the sample com-

16 pounds were calculated on the basis of homologue n-alkane hydrocarbons analysed under identical GC-MS conditions. All reference compounds for SPME-GC-MS-analysis were obtained from Aldrich (Milwaukee, USA) and Fluka (Darmstadt, Germany). All samples were run at least in triplicate. After analysis of volatile compounds, semi-quantification was performed as % peak area using integration data (percentage to the total level of vola- tiles). For each analysed oil/fat at least three samples and three replications were used (standard deviation <1%).

Usually samples applied to HS-SPME-analysis are heated up to 40°C or higher to enlarge recovery of volatiles (Mildner-Szkudlarz et al., 2003; Vichi et al., 2003; Doleschall et al., 2001). In our case sampling was done at room tem- perature (22°C) to avoid any formation of artefacts (Ruiz del Castillo et al., 2003) and degradation of analysed compounds (Mildner-Szudlarz et al., 2003). To achieve sufficient amounts of analytes, sampling was done from one to ten hours, respectively, depending on the investigated sample. The presented method was tested and evaluated by a large series of preliminary tests.

I.6. Own Results: Above mentioned considerations (I.1.) led to the development of the pre- sented SPME-GC-MS-method as a screening technique for fatty plant oils and plant fats (I.5.). The main advantages of the proposed methodology are the speed of analysis (no prior sample preparation required), the simplicity of the meas- uring process, the low current costs and the nonexistent need for heating the samples, as heating accelerates degradation of volatile compounds.

I.6.1. Analysed fatty plant oils and plant fats: Following fatty plant oils and plant fats have been investigated with the SPME-GC-MS method described above: • Beech oil Oleum Fagi seminis (Fagus sylvatica L.; FAGACEAE) • Camelina Oil Oleum Camelinae ( L.; BRASSICACEAE) • Castor oil Oleum Ricini virginale (Ricinus communis L.; EUPHORBIACEAE) • Chaulmoogra oil Oleum Chaulmoogra (Hydrocarpus Kurzii Warb.; FLACOURTIACEAE) • Chufa oil Oleum Cyperi esculenti (Cyperus esculentus L.; CYPERACEAE) • Grape seed oil Oleum Vitis viniferae (Vitis Vinifera L.; VITACEAE) 17

• Hazelnut oil Oleum Coryli avellanae (Corylus avellana L.; BETULACEAE) • Kapok oil Oleum Ceibae seminis (Ceiba pentandra (L.) Gaertn.; BOMBACACEAE) • Linseed oil Oleum Lini (Linum usitatissimum L; LINACEAE) • Mustard oil Oleum Sinapsis (Sinapsis alba L.; BRASSICACEAE) • Neem oil Oleum Melia (Azadirachta indica A. Juss.; MELIACEAE) • Pistachio oil Oleum pistaciae (Pistacia vera L; ANACARDIACEAE) • Pongamia oil Oleum pongamiae (Pongamia glabra; FABACEAE) • Poppy seed oil Oleum Papaveris seminis (Papaver somniferum L.; PAPAVERACEAE) • Sesame oil Oleum Sesami indicae (Sesamum indicum L; PEDALIACEAE) • Oleum Butyrospermi parkii (Vitellaria paradoxa C.F. Gaertn.; SAPOTACEAE) • Walnut oil Oleum Juglandis (Juglans regia L; JUGLANDACEAE)

Oil samples were purchased from local producers or (some of them) from respective stores and stored at 4°C before analysis. Shea butter samples were provided from African scientists and were stored at 6°C before analysis.

I.6.2. Results for fatty vegetable oils: A large number of substances, mainly short chain acids, alcohols, as well as flavour active aldehydes and ketones were detected in the headspace of the examined oil samples. With SPME-GC-MS-analysis it was possible to distinguish between virgin (cold pressed) vegetable oils and those ones produced from previously heated or roasted seeds. In the headspace of the latter typical products from roasting processes (e.g. Maillard reactions) such as various pyrazines, pyra- zoles, γ-butyrolactone, 2-pentylfuran, 2-ethylfuran, furfural and furfurylalco- hol were identified. Also noticeable are the high contents of alcoholic com- pounds, like hexanol, heptanol and octanol, if oils were produced from previously roasted seeds (Krist et al., 2006b). Differences in the headspace composition of oils of the same type, but from varying provenances, could also be detected by SPME-GC-MS-analysis (Krist et al., 2008a). Refining processes obviously led to a reduced number of volatiles in the headspace of the oils. Some components only occured in virgin oils, e.g. hexanol and α-pinene in walnut oils, while refined oils showed significant higher amounts of carbonyl containing compounds. For refined grape seed

18 oils, outstanding high contents of hexanal, presumably resulting from degra- dation of linoleic acid, grape seed oils´ main fatty acid, were detected (Bail et al., 2008a; Bail et al., 2009a). As generally known, cold pressing conditions result in lower yields of oil in comparison to solvent extracted oils, but due to our results it can be stated that cold pressed oils contain much more alcoholic compounds, acids and aroma active in their headspace. Results are shown in detail in Krist et al., 2008a; Krist et al., 2006b; Krist et al., 2006c; Krist et al., 2005; Bail et al., 2009a; Bail et al., 2009b, Bail et al., 2008a.

With these investigations fundamental research has been done, represent- ing a substantiated basis for further investigations. A synopsis of currently available literature concerning volatile compounds of various vegetable oils and fats is shown in Krist et al. 2008c. Applications of these oils, pharmaceu- tical and others, are also given in this encyclopaedia.

I.6.3. Adulteration: In terms of adulteration, the blending of poppy seed oils with sunflower oils was investigated (Krist et al. 2006a). Owing to its high prize, fraudulent prac- tices have involved the adulteration of virgin poppy seed oil with cheaper sunflower oil. Detection of this adulteration with conventional analytical techniques is very difficult, as fatty acid ratios of these two oil types are very similar. With the above mentioned SPME-GC-MS method it was possible to detect an admixture of sunflower oils to poppy seed oils in all relevant amounts (5-40%) by using the volatile compound α-pinene (see Fig. 1) as a marker compound.

Fig.1: α-Pinene

α-Pinene was identified as the predominant substance in the headspace of all examined sunflower oils. In contrast, this volatile compound is a minor or even lacking compound in poppy seed oil varieties. A concrete graphic of the 19 chromatograms of three poppy oil varieties and one representative sun- flower oil is given in Krist et al. 2006a, Figure 1. A reliable method for detecting small amounts of this kind of adultera- tion seems to be needful, as a sensorial evaluation, also done by our re- search group, yielded the result that there is a detection limit for human senses of minimum 30% admixture of sunflower oil to poppy seed oil to identify blendings (Bail et al. 2008b).

I.6.4. Results for plant fats: Concerning analysis of plant fats, the headspace composition of various Afri- can shea butter samples from Chad, Cameroon, Mali, Burkina Faso and Uganda were examined. Shea butter, a valuable African vegetable fat, pro- duced from the kernels of the shea tree (Vitellaria paradoxa), is used for cu- linary, cosmetic as well as pharmaceutical and traditional medicinal pur- poses. This time analysis of volatile compounds was done in terms of improving and standardising shea butter production conditions in Africa. Our investigations were part of the African ProKarité project, implemented by the World Agroforestry Centre (ICRAF) with support of the Common Fund for Commodities (CFC). The composition of volatile compounds in all examined shea butter sam- ples seemed to be mainly a result from degradation of long chain fatty acids by enzymatic influences as well as oxidation processes. The amount of these volatiles varies due to the applied processing technique. According to our results, differences of the composition of volatile fractions of shea butter samples could rather be related to manufacturing processes than to regional variations. Similar to the investigated fatty plant oils, additional or extensive heating/roasting steps during processing led to the formation and detection of different pyrazines, 2-acetylfurane and 2-acetylpyrrole. Besides, with the applied SPME-GC-MS-technique it was possible to detect residues from die- sel driven milling, pollution with pentandiol and possible addition of glycerol. Results are shown in detail in Krist et al., 2006c and Bail et al., 2009a.

I.6.5. Olfactory evaluation: In addition to SPME-GC-MS-analysis, examined oil and shea butter samples have been evaluated for their olfactory properties. A panel (10 assessors) of professional perfumers, flavourists and trained aroma-chemists evaluated the provided oil samples. For smell evaluation procedure 0.5ml of each oil sample were applied on standard smelling strips. Optional evaluation of volatile compounds was done in three 1min steps. Evaluation of flavour was

20 based on intense tasting of 2ml of each oil sample. In case of shea butter, 20g of each butter sample were used for evaluation procedure. Results are also presented in Krist et al., 2008a; Krist et al., 2006b; Krist et al., 2006c; Krist et al., 2005; Bail et al., 2009a; Bail et al., 2009b, Bail et al., 2008a;.

I.6.6. Results for Chestnuts: The same SPME-GC-MS-method as presented above was also applied on in- vestigating volatile compounds of roasted Italian chestnuts (Castanea sativa Mill.). In addition to sampling with solid-phase microextraction directly from granulated roasted chestnuts (250g), a dichloromethane extraction from an- other part of the chestnut granulate (also 250g) was produced, filtrated and concentrated. Headspace volatiles of the resulting yellow-brown oil extract with intense odour, recognisable as roasted chestnuts, were sampled with the same SPME-procedure as the granulate. With SPME-sampling directly from the chestnut granulate, almost twice as many volatile compounds could be detected and identified as by sampling the headspace of the sol- vent extract. Furthermore, for those volatiles detected in both sample types (granulate and solvent extract, respectively), higher concentrations were at- tained by direct sampling of the granulate with SPME in all cases except γ-butyrolactone. These facts results militate in favour of simple direct sam- pling instead of laborious production of solvent extracts. Results are presented in detail in Krist et al., 2004.

I.6.7. Combination with MALDI-MS-analysis The absence of solvents, robustness, high reproducibility of results and speed renders solid phase microextraction an attractive method for moni- toring plant oil quality. As a further tool for characterisation of the investi- gated fatty plant oils triacylglycerol profiles were analysed by using MALDI- TOF-mass spectrometry. TAG-profiling was done by G. Stübiger, Vienna Uni- versity of Technology. Generally, it can be stated that the combination of SPME-GC-MS and MALDI-TOF-MS is a novel approach for assessing a variety of complementary parameters for the characterisation of vegetable oils. The uniqueness of this approach becomes obvious in regard to the fact that many volatiles present in the headspace of oils (e.g. acetic acid and hexanal) represent degradation products from the fats (i.e. the triacylglyceroles) forming during oxidation processes (e.g. roasting). In our investigations SPME-GC-MS was proven to be very suitable for the characterisation of the various oils based on their headspace composition, whereas MALDI-MS was a very useful as convenient 21 method for characterising oils based on their TAG composition (TAG profil- ing) in a very rapid way. TAG profiles revealed as stable parameter, rather indifferent to the origin of the oils and production conditions. TAG profiling allowed the discrimination of oils even in the case of very similar fatty acid compositions (Krist & Stuebiger, 2008).

I.7. Vistas: During our investigations, screening of volatile compounds by SPME-GC-MS and TAG-profiling by MALDI-MS turned out to be very promising tools for oil authenticity assessments and the detection of oil adulteration. The combina- tion of these two complementary analytical techniques offers the possibility to obtain information about basic raw materials and processing conditions of the fatty plant oils, as well as the origin of the samples and adulterations. The purpose of further investigations will be to develop combined tech- niques based on volatile compound- and TAG-profiling in combination with bioinformatics software tools (Mildner-Szkudlarz et al., 2003 ; Jakab et al., 2002) for rapid differentiation of various fatty plant oils, for monitoring changes deriving from previously applied heating during production or dur- ing storage and possible adulteration. A powerful, rapid screening for oil quality shall be established.

II. Volatile compounds applied to the reduction of the bacterial count of ambient air: Airborne microbes are still an underestimated cause of risk for human health, as they surround us 24 hours a day. Various airborne microbes have the potential to cause infections and, dropping down on foods, the microbes grow up there and foods become spoiled. Today, mainly formaldehyde, glu- taraldehyde and phenol derivatives such as cresol are used as disinfectants (Wallhäußer, 1995; Hagna, 1977). An application of these chemical com- pounds for decreasing airborne microbes is not optimal because of their toxicity and their unpleasant smell (Moore & Kaczmarek, 1991; Clark, 1983; Coldiron et al., 1983). The antimicrobial (antibacterial and antifungal) potential of volatile compounds and essential oils is well known and scientifically tested (Prashar et al., 2003; Lis-Balchin & Hart, 1999; Kim et al., 1995; Morris et al., 1979). In the majority of studies dealing with the antimicrobial potential of volatile compounds, direct contact between the tested compound and the microbes in a culture medium, such as disc diffusion, well diffusion, agar dilution and broth dilution methods, are used for evaluation. Usually substances are ex- amined by using the agar diffusion method to determine the inhibition zone

22 or the broth dilution test for determining the minimal inhibition concentra- tion (MIC) (de Billerbeck, 2007; Janssen et al., 1987). Very little is yet known about the antimicrobial effects of scents on airborne microbes, besides, available investigations are out of date (Kellner & Kober, 1954; Risler, 1936). Taking these facts into consideration, the idea to investigate the effect of selected volatile compounds and essential oils on airborne microbes was born. Since there are no actual studies on the antimicrobial properties of volatile compounds and essential oils on airborne microbes available, a new method of examination had to be developed.

II.1. Own testing method: First, volatile compounds with known antimicrobial potential were tested for their activity against airborne microbes in washing rooms of the Centre of Pharmacy of the University of Vienna. The air volume of every washroom was 8.0m3. During measurements the doors were kept closed, the room temperature was 24°C and the air humidity was 46%. Stock emulsions (o/w) of the aroma compounds were prepared in differ- ent concentrations, respectively 1:100, 1:200, 1:350, 1:1000 and partly 1:5000. 4.0mg were taken from each stock-emulsion, except for the 1:350 stock-emulsion. In this case 4.2mg were taken. By atomising these 4.0mg re- spectively 4.2mg of diluted aroma-chemicals in the testing rooms, concen- trations of 5.0mg/m³ (1:100 stock-emulsion), 2.5mg/m³ (1:200 stock-emul- sion), 1.5mg/m³ (1:350 stock-emulsion), 0.5mg/m³ (1:1000 stock-emulsion) and 0.1mg/m³ (1:5000 stock-emulsion) were achieved. Thymol, which is of solid state at room temperature, was dissolved in 4ml hexane first, then the stock-emulsions with water (o/w) were prepared and treated like the other stock-emulsions. The air samples were taken with a RCS Air Sampler, purchased from Bio- test AG, Dreieich, Germany. This air sampler uses inertial impaction to col- lect the airborne microbes. The microbes are impacted on commercially available agar strips, which are incubated after sampling in an incubator. Ac- cording to the manufacturer’s specifications, the sampling volume of the RCS Air Sampler is 280l/min and the separation volume is 40l/min for particles with a diameter of 4 µm. The atomizer bottles (10ml), used for spraying the aroma compounds, were purchased from VWR International GmbH, Vienna, Austria (Art. No. 215-6270). The spray angle was 35° and 0.05ml were atomised by one spraying performance. Agar strips TC (Art. No. 941105050) for determination of total counts and agar strips YM (Art. No. 941200050) for detection of yeasts and moulds, obtained from Biotest AG, Dreieich, Germany, were used as culture media. 23

At first the total microbial count in the testing room was determined by sampling air for 2min (total microbial count, TC) using the RCS Air Sampler. Afterwards the aroma compounds were vaporized. Fifteen minutes later the total microbial count was measured again with the same experimental set up. Ten measurements were taken for the blanks ans for each spread sub- stance in each concentration. The same procedure was carried out for de- tecting total count of yeasts and moulds (YM) by sampling air for 8min. Afterwards the agar strips were incubated in an incubator at 30°C for 48h (TC) and at 25°C for 120h (YM), respectively. Then the colonies on the agar strips were counted and the total germ count in air in CFU/m³ was cal- culated using the following formula (Fig.2).

counted colonies ⋅ 25 CFU / m³ = sampling time(min)

Fig.2: Calculation of total microbial count in air

Afterwards the average reduction of germ count (formula see Fig.3), the standard deviation (SD) (formula see Fig.4) and the average deviation (AD) (formula see Fig.5) of the average reduction were calculated.

n K 1 x1 + x2 + + xn x = ∑ xi = n i=1 n

Fig.3: Calculation of average germ count reduction; n ….number of measurements, x…result of measurement

n x2 − ( x)2 σ = ∑ ∑ n(n − )1 Fig.4: Calculation of standard deviation σ

1 averagedeviation = (x − x) n ∑

Fig.5: Calculation of average deviation

These experiments were carried out for: carvacrol [CAS-No. 499-75-2], citral [CAS-No. 499-75-2], (-)-citronellal [CAS-No. 5949-05-3], eugenol [CAS-No. 97- 53-0], geraniol [CAS-No. 106-24-1], (R)-(-)-linalool [CAS-No. 126-91-0], (-)-

24 perillaldehyde [CAS-No. 18031-40-8], terpineol [mixture of α- 65 %; β- 10% and γ- 20 %; CAS-No. 8000-41-7], thymol [CAS-No. 89-83-8] and trans-cin- namaldehyde [CAS-No. 14371-10-9] (Krist et al., 2007; Feichtinger, 2005; Strobl, 2005). All aroma compounds were purchased from Sigma-Aldrich Chemie GmbH, Steinheim, Germany. Formula of the investigated volatile compounds are presented in Fig.6.

CHO OH O

Carvacrol 1,8-Cineole trans-Cinnamaldehyde

CHO

CHO CHO

Citronellal Citral a Citral b OH OH OHCH CH OH 3 2

Eugenol Geraniol (R)-(-)-Linalool

CHO

OH

Perillaldehyde γ-Terpinene Thymol

25

OH OH

OH

α β γ Terpineol

Fig.6: Formula of the investigated volatile compounds

II.2. Own Results:

II.2.1. Volatile compounds applied by spraying: Generally, all tested volatile compounds led to a noticeable reduction of germ count of airborne microbes. During data analysis, it was noticed that the average germ count reduction did not always increase with increasing concentration of the volatiles , as expected. Possibly these results could be explained by biological variability and will be inter alia the inducement for further investigations. For reduction of total germ count (R)-(-)-linalool showed the very best results at a concentration of 2.5mg/m3. An average 69.92% of total germ count reduction could be achieved. Almost equal results were performed by eugenol (69.40%) ad thymol (69.50%), in each case at a concentration of 1.5mg/m³. Likewise satisfying results were yielded with 1.5mg/m3 of trans- cinnamaldehyde (65.93% germ reduction), with 0.1mg/m3 of carvacrol (63.08%) and 0.1 mg/m3 of geraniol (53.66%). Citral led to a reduction of total germ count of 51.40% at a concentration of 5.0mg/m3. 1.5mg/m3 terpineol attained an average microbial count reduction of 51.36%. (-)-Perillaldehyde was most effective for total germ reduction at a concentration of 1.5mg/m3, too. The average reduction was 48.6%. the amount of 5.0mg/m3 of (-)- citronellal in the testing room led to an average germ reduction of 46.3%. In case of the reduction of total count of yeasts and moulds, citral was most effective at a concentration of 5.0mg/m3 (average reduction 75.3%), followed by (-)-citronellal (67.2%) at a concentration of 5.0 mg/m3 and car- vacrol (64.12% / 0.1mg/m3). 55.27% of reduction of yeasts and moulds were achieved with geraniol (0.1mg/m3), 50.60% by thymol at a concentration of 0.5mg/m3 and 50.25% by (R)-(-)-linalool at a concentration of 1.5mg/m3. Less than half of total yeasts and moulds were killed by trans-cinnamaldehyde (46.19% / 2.5mg/m3), eugenol (45.33% / 1.5mg/m3) and (-)-perillaldehyde

26

(40.9% / 1.5mg/m3). In this case terpineol was least effective. At a concen- tration of 1.5mg/m3 34.15% reduction of total count of yeasts and moulds were achieved with this volatile compound. Results are shown in detail in Krist et al., 2007; Feichtinger, 2006 and Strobl, 2006. Concerning carvacrol, citral, (-)-citronellal, geraniol, (-)-perill- aldehyde and terpineol a journal publication is in preparation.

II.2.2. Air washer/room diffuser: Based on the promising results mentioned above, further investigations were carried out. In this case cleaned and fumigated air washers and room diffusers, respectively, were used for spreading the aroma compounds. This time a lecture room at the Centre of Pharmacy of the University of Vienna was used as testing room (see Fig.8). The air volume of this lecture room was 168m3, room temperature was 24°C, air humidity was 44%. Doors and win- dows were kept closed during testing. Experiments were carried out once a day, right after the end of a lecture. For taking the air samples the RCS Air Sampler (Biotest AG; Dreieich, Germany) was used. Agar strips TC (Art. No. 941105050) for determination of total microbial counts, obtained from Biotest AG, Dreieich, Germany, were used as culture media. Colony forming units (CFU) /m³ were calculated after incubation at 30°C for 48h. Then the average reductions of germ count were calculated. The measurements were performed ten times for each aroma compound and the blanks.

The air samples in the testing room were taken with the RCS Air Sampler for 8min at each of five well-defined measuring points (see Fig.7). In the case the air washer (purchased from Venta, Germany) was used, at first, pure dis- tilled water was spread. The germ count increased significantly in compari- son to blank values taken before. The colony forming units increased ap- proximately 35% (Sato et al., 2007; Sato et al., 2006). Then 0.84g of volatile compounds were added to 7l distilled water in the air washer and were va- porized. The resulting concentration of aroma compounds was 5.0 mg/m3. One hour later, the air samples were collected again by the same procedure as described above. The measurements were performed ten times with each aroma compound and the blank values. The statistical comparisons between control and each volatile compound as well as value comparison prior and after fragrance application were per- formed using Student’s t-test. p < 0.05 was considered to be significant.

27

Fig.7: Testing room with air washer/room diffuser and measuring points. The air washer/room diffuser was fixed on the desk at measuring point 1. Point 1: 0 m away from the air washer/room diffuser and 1 m height. Point 2-5: 5 m away from the air washer/room diffuser and 1 m height. (Krist et al. 2008b)

Carvacrol [CAS-No. 499-75-2], 1,8-cineole [CAS-No. 470-82-6], citral [CAS-No. 499-75-2], (-)-citronellal [CAS-No. 5949-05-3], eugenol [CAS-No. 97-53-0], geraniol [CAS-No. 106-24-1], (R)-(-)-linalool 8CAS-No. 126-91-0], (-)-perill- aldehyde [CAS-No. 18031-40-8], γ-terpinene [CAS-No. 99-85-4[ and terpineol (mixture of α- 65 %; β- 10% and γ- 20 %; [CAS-No. 8000-41-7]) were tested for their activity against airborne microbes with the above presented method. By applying this method, terpineol gave the best results. It was possible to reduce 68% of total microbial count with this volatile compound. Almost equal promising results were achieved by using 1,8-cineole (64% of germ re- duction). The application of (R)-(-)-linalool and (-)-perillaldehyde, respec- tively resulted in 53% reduction of total germ count. Also geraniol (46% germ reduction), trans-cinnamaldehyde (46%) and γ-terpinene (40%) gave satisfying results. In this case the application of carvacrol (34% reduction), (-)-citronellal (30%), citral (17%) and eugenol (11%) was less successful. Re- sults are shown in detail at Sato, Krist et al., 2007 and Sato, Krist et al., 2006.

28

In comparison to the results achieved by spraying the volatile compounds with atomizer bottles, using an air washer reduced the antimicrobial effect of the tested volatile compounds significantly. In almost all cases the appli- cation of the air washer led to a lower reduction of total germ count al- though higher concentrations of volatile compounds were applied. This might be due to the fact, that distilled water, obviously vaporising while us- ing the air washer, leads to a higher total germ count in the testing room. The increase of germ count in the testing room of average 35%, when using daitilled water without adding volatile compounds, is an evidence for this theory.

When the room diffuser was used, the volatile compounds were sprayed with this apparatus for five hours. In this case an interaction of water and airborne microbescan be excluded. Carvacrol [CAS-No. 499-75-2], 1,8- cineole [CAS-No. 470-82-6], (R)-(-)-linalool [CAS-No. 126-91-0], (-)-perillalde- hyde [CAS-No. 18031-40-8] and terpineol (mixture of α- 65 %; β- 10% and γ- 20 %; [CAS-No. 8000-41-7]) were tested with this method. In that case different amounts of volatiles were vaporised within five hours due to the varying volatility of the tested aroma compounds. Ter- pineol reduced total germ count for 59.4%. 0.069g (±0.007g) of this com- pound vaporised during five hours. Also the application of 0.079g (±0006g) (-)-perillaldehyde was very successful. A reduction of total germ count of 42.3% could be achieved. With 0.028g (±0.003g) of carvacrol it was possible to reduce 37.5% of the germs in the testing room. At least 0.23g (±0.002g) of (R)-(-)-linalool reduced total germ count for 29.7%. Solely with 1,8-cineole no reduction of germ count was achieved. Results are given in detail in Krist et al. 2008b. With this method the economy on water by using a diffuser instead of an air washer is significant. Furthermore much lower amounts of volatiles led to comparable results in germ count reduction when using a room diffuser in- stead of an air washer. Again this might be due to the fact that water, va- porising while using an air washer, leads to a higher total germ count in the testing room.

II.2.3. Essential oils: For further investigations essential oils were taken instead of single volatile compounds as antimicrobial agent. My research group already investigated the effect of essential oils of pine (Pinus pinaster), tea tree (Melaleuca alter- nifolia), rosemary (Rosmarins officinalis), dill herb and dill seed (Anethum graveolens L.), East Indian sandal wood (Santalum album L.), West Indian sandal wood (Amyris balsamifera L.), Australian sandalwood (Santalum spi- 29 catum R.Br.), palmarosa (Cympobogon martinii J.F. Wats.), leave (Eu- genia caryphyllus), Siberian fir needles (Abies sibirica) and of a jasmine ab- solute from India (Jasminum grandiflorum L.). Samples were purchased from Kurt Kitzing GmbH, Wallerstein, Germany; Mt. Romance Australia Ptd. Ltd., Albany, Australia and Symrise Co., Holzminden, Germany.

Likewise to the first testing of the single volatile compounds, the essential oils were sprayed with atomizer bottles in the tested rest rooms of the Center of Pharmacy of the University of Vienna. Again concentrations of 5.0mg/m³, 2.5mg/m³, 1.5mg/m³, 0.5mg/m³ and partly 0.1mg/m³ were tested for their antimicrobial effect on airborne microbes. At first the total microbial count (TC) in the testing room was deter- mined by sampling air for 2min using the RCS Air Sampler. Afterwards the essential oils were vaporized. Fifteen minutes later the total microbial count was measured again with the same experimental set up. Ten measurements were taken for each essential oil in each concentration and the blanks. The agar strips were incubated in an incubator at 30°C for 48h. Afterwards the colonies on the agar strips were counted and the total germ count in the air was calculated in CFU/m³. The same procedure was carried out for the main components (previously identified and quantified by GC-MS-analysis) of each essential oil. These vola- tile compounds were sprayed in the testing room in the same concentration in which the essential oil performed best antimicrobial activity. In addition a mixture of the main volatile compounds of each essential oil, in the concentration in which they were originally found in the respective essential oil, was tested for its antimicrobial properties against airborne mi- crobes. These mixtures were sprayed in the testing room in that concentra- tion in which the respective essential oil performed best. In the highest concentration (5.0mg/m3) all tested essential oils showed highest antimicrobial activity, except (32.2% at 0.5mg/m3) and jasmine absolute, which showed almost equal reductions of germ count in all concentrations (average 38.7%). Especially successful in reducing airborne microbes were sandalwood oils from Australia (up to 67.1% germ reduction) and from East India (up to 58.0%). Also a mixture of α- and β-santalol, the main components of essential , gave respectable germ count reduction of average 43.8%. Siberian fir needle oil (51.0% germ reduction), rosemary oil (49.4%), dill herb oil (43.68%), palmarosa oil (43.52%) and clove leave oil (42.38%) yielded considerable results, too. Rather disappointing an- timicrobial activity was performed by dill seed oil (35.17%), tea tree oil (32.2%) and pine oil (25.6% germ reduction). With the exception of (-)-limonene (one of the main components of dill herb oil) (55.42% germ reduction), isophytol (60.6% germ reduction) and

30

(-)-linalool (55.5% germ reduction) (two main components of jasmine abso- lute) and geraniol (52.1% germ reduction) (the main component of palma- rosa oil), all other tested single volatile compounds gave almost equal or lower results in reducing airborne microbes in comparison to the respective essential oil, applied in the same concentration. The application of the mixtures of the main components of palmarosa oil (50.4% germ reduction) and clove leave oil (49.36% germ reduction), respec- tively were more successful in reducing airborne microbes than the respec- tive essential oils. In all other cases the essential oils performed better in re- ducing airborne microbes than the mixtures of their main components at the same concentration. Results are presented in detail in Zaussinger, 2008; Kretz, 2007; Pasierb, 2007; Pasierb et al. 2007; Wosny, 2007 and Wosny et al., 2007. Further jour- nal publications are in preparation.

II.2.4. Identification of airborne microbes: Identification of airborne microbes was carried out by S. Glasl, Department of Pharmacognosy, University of Vienna. The different colonies were inocu- lated from the agar strips, transferred into standard I nutrient broth (Merck, Darmstadt, Germany) and cultivated for 24h at 30°C. Afterwards a Gram stain using crystal violet, iodine/alcohol and safranin (all Merck, Darmstadt, Germany) was done. The bacteria were isolated on standard I nutrient agar (Merck, Darmstadt, Germany), examined with a light microscope (Alphaphot 2 YS”-H, Nikon, Japan) and identified by performing a respective API-test (bioMérieux, Marcy l´Etoile, France). Macroscopic examination showed shining white or yellow colour and en- tire margins for a vast majority of the colonies. Few bacteria formed charac- teristic colonies with cell fibres resembling to fungi. The characterisation of the colonies was performed by microscopy after Gram stain, hanging drop, API-test and biochemical reactions. Approximately 60% of the examined colonies turned out to be cocci (Micrococcus luteus, Micrococcus sp., Staphylococcus epidermidis), circa 25% were bacilli (Bacillus cereus ssp. my- coides, Bacillus sp.) and about 15% consisted of miscellaneous germs such as Corynebacterium sp. Only very few fungi were detectable (Penicillum sp.) (Krist et al., 2008b.).

II.3. Vistas: In consideration of the fact that commonly used disinfectants like glutaral- dehyde or phenol derivatives are not optimal to decrease airborne microbes due to their human toxicity, possible mucosa irritations and unpleasant 31 smell, volatile compounds and essential oils with antimicrobial activity pos- sibly represent a suitable alternative. The small amounts of volatiles used in this study are generally recognised as not being harmful when inhaled (Pappas et al., 2000). Therefore, people could stay in the room when volatile compounds are spread for reducing germ number. The convenient safe me- thod presented in this study is considered to improve environmental health at places where people gather together, such as lecture halls, theatres, sta- tions or airports. Further investigations on this research topic seem to be auspicious and seminal. Testings that will be carried out in pharmacies and waiting rooms of medical practices are in planning stage.

III. REFERENCES:

Adam M; Juklová M; Bajer T; Eisner A; Ventura K. Comparison of three dif- ferent solid-phase microextraction fibres for analysis of essential oils in yacon (Smallanthus sonchifolius) leaves. Journal of Chromatography A, 2005, 1084 (1-2), 2-6. Almiral, JR; Furton, KG. Forensic Applications. In: Scheppers Wercinski, S.A., editor. Solid Phase Microextraction. A practical guide. New York, Mar- cel Dekker, Inc.; 1999; 203-216. Almiral, JR; Bruna, J; Furton, KG. The recovery of accelerants in aqueous samples from fire debris using solid phase microextraction (SPME). Science and Justice, 1996, 36, 283-287. Aparicio, R; Aparicio-Ruíz, R. Authentication of vegetable oils by chromato- graphic techniques. Journal of Chromatography A, 2000, 881 (1-2), 93- 104. Arthur, C; Pawliszyn, J. Solid Phase MicroExtraction with Thermal Desorp- tion. Analytical Chemistry, 1990, 62, 2145-2148. Arvanitoyannis, IS; Vlachos, A. Implementation of physicochemical and sen- sory analysis in conjunction with multivariate analysis towards assess- ing olive oil authentication/adulteration. Critical Revues in Food Sci- ence and Nutrition ,2007, 47 (5), 441-98. Bail, S; Stuebiger, G; Unterweger, H; Buchbauer, G; Krist, S. Characetrization of volatile compounds and triacylglycerol profiles of oils using SPME-GC- and MALDI-TOF-mass spectrometry. European Journal of Lipid Science and Technology, 2009a, 111, 170-182. Bail, S; Krist, S; Masters, E; Unterweger, H; Buchbauer, G. Volatile Com- pounds of shea butter samples made in West, Central and Eastern Af- rica under different production conditions. Journal of Food Composi- tion and Analysis, 2009b, 22, 738-744.