The Role of Separation in the Identification of Trace Aroma

Chapter 3

Downloaded by OHIO STATE UNIV LIBRARIES on June 7, 2012 | http://pubs.acs.org Publication Date (Web): August 24, 2011 | doi: 10.1021/bk-2011-1068.ch003

The Role of Separation in the Identification of Trace Aroma Compounds J. Lin,*,1 Y. Wang,1 P. L. Perry,1 E. Frerot,1,2 A. Rada,1,3 and J. Impellizzeri1 1Firmenich

Inc., North America R&D, P.O. Box 5880, Princeton, NJ 08543, USA 2Current Address: Firmenich SA, Corporate R&D Division, Route des Jeunes 1, CH-1211 Geneva 8, Switzerland 3Current Address: Firmenich Inc., North America Flavors, P.O. Box 5880, Princeton, NJ 08543, USA *E-mail: [email protected].

Diverse motivations drive the analysis of food aromas and the sensory-directed aroma analysis, namely gas chromatography–olfactometry (GC–O), represents a valuable technique in the detection of trace aroma compounds. Even though the sensitivity of mass spectrometry has significantly improved, the complexity of food aromas and the trace levels of many food aroma compounds demand the development of new methodology for more efficient and unequivocal food aroma analysis. In this paper, the development of two selective solid phase extraction methods for basic volatile compounds and acidic volatile compounds will be presented. The effectiveness of these selective methods will be demonstrated by their application in real samples. The usefulness of two dimensional GC/O/MS in the identification of trace aroma compounds is also illustrated. The combination of traditional fractionation with 2D GC/O/MS analysis enabled the identification of trace aroma-active compounds in a complex mint oil. Finally, examples are used to prove that Amdis deconvolution software is a powerful data mining tool to remove interfering signals or background noises to obtain valuable mass spectral information for unambiguous identification of trace aroma compounds.

© 2011 American Chemical Society In Volatile Sulfur Compounds in Food; Qian, M., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Introduction Diverse motivations, such as discovery of novel chemicals with interesting organoleptic properties, reconstruction of complex food aromas, flavor quality control, off-flavor problem-solving, or simple intellectual curiosity, drive the analysis of food aromas. The sensory-directed aroma analysis, namely gas chromatography–olfactometry (GC–O) represents a valuable technique to detect trace aroma compounds (1, 2). On one hand, the sensitivity of mass spectrometry, especially tandem mass spectrometry allows us to identify compounds at very low levels (3, 4). On the other hand, aroma extracts often require further fractionation to reduce the complexity of the whole extract and to enrich trace aroma compounds to facilitate their identification by MS. A variety of sample preparation methods for GC/O analysis have been developed and recently reviewed (5). But new development in analytical methodology is constantly needed to increase the chance of discovering new chemicals, to improve the speed and throughput of analysis, or to carry out analyses in greener ways. Confronted by the challenges of complex food aroma analyses, we developed several separation techniques, ranging from selective solid phase extraction by chemical functionality to deconvolution by Amdis software. The role of these separation techniques in the identification of trace aroma compounds is demonstrated through a range of concrete examples in this chapter.

Results and Discussion Selective Solid Phase Extraction by Chemical Functionality Selective SPE of Basic Volatile Compounds In the aroma characterization of a Peanut Butter, several roasty, nutty notes were detected in its aroma extract by GC/O. However, they couldn’t be identified by GC/MS because they occurred at trace levels and co-eluted with other volatile compounds present in much higher amount. It is well known that roasty, nutty-smelling compounds are most likely N-containing heterocyclic compounds. A method was therefore developed to selectively extract basic volatile compounds based on SPE using Waters Oasis® MCX cartridges. In this method, all volatile compounds in an aroma hydrodistillate sample are initially retained on the sorbent based on hydrophobic interaction. A solution of formic acid is passed through to acidify the basic volatile compounds and to lock them on the sorbent based on strong ionic interaction. Acidic and neutral compounds are then washed away with organic solvent. The basic compounds are eventually released by neutralization with ammonia and eluted with organic solvent in one step. A schematic representation of the procedure is shown in Figure 1.

66 In Volatile Sulfur Compounds in Food; Qian, M., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Figure 1. Procedure for Selective SPE of Basic Volatile Compounds from Aroma Hydrodistillates using Oasis® MCX Cartridges (6 cc/500 mg, 60 µm).

When this method was applied to the Peanut Butter sample, a basic volatile extract eliciting strong popcorn, roasty, nutty, pyrazine aroma was obtained. GC/MS analysis of the extract confirmed the sole presence of pyrazines, pyridines and other N-containing heterocyclic compounds. A GC/MS chromatogram of the extract with peak identification is shown in Figure 2. Five potent roasty compounds were easily identified in the basic extract by GC/O/MS. They are 2-acetyl-1-pyrroline, 2-propanoyl-1-pyrroline, 2-acetyl pyrazine and the two forms of acetyl tetrahydropyridine (Figure 2). More than 300 volatile compounds had been identified in roasted peanuts (6). Seveal aldehydes, pyrazines, pyrroles and other compounds were isolated from peanut butter by purge-and-trap techniques (7) and a list of dithiazines had been reported in peanut butter (8). However, these potent odorants were first time identified in peanut products due to the selective extraction method used. As recently reviewed by Adams and De Kimpe (9), these compounds are present in a great variety of processed and cooked food products.



Figure 2. GC/MS Identification of Many N-Containing Compounds in a Basic Volatile Extract of Peanut Butter.

Figure 3. Procedure for Selective SPE of Acidic Volatile Compounds from Aroma Hydrodistillates using Oasis® MAX Cartridges (6 cc/500 mg, 60 µm). 68 In Volatile Sulfur Compounds in Food; Qian, M., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Selective SPE of Lactones and Phenols Similarly, several sweet, lactonic notes and a few smoky, phenolic odors were detected by GC/O in the aroma characterization of toasted oat flakes, but couldn’t be identified by GC/MS. Smoky notes could be from phenolic compounds and sweet notes were likely due to lactones. A SPE method using Oasis® MAX cartridges was then developed to selectively extract acidic volatile compounds. The schematic procedure of this method is shown in Figure 3. In this procedure, all volatile compounds in an aroma hydrodistillate sample are initially retained on the sorbent based on hydrophobic interaction. A solution of aqueous ammonia is passed through to ionize the acidic volatile compounds and to lock them on the sorbent based on strong ionic interaction. Basic and neutral compounds are then washed away with organic solvent. And the acidic compounds are eventually released after neutralization with formic acid and eluted with organic solvent in one step. Recovery of different acidic compounds with this procedure was investigated with an aqueous model aroma solution. Carboxylic acids were almost quantitatively recovered, recoveries for phenolic compounds were good (> 80 %), while the recoveries for lactones were acceptable (60 to 70 %). Applying this procedure to a hydrodistillate of toasted oat flakes, a volatile extract containing only acidic compounds was obtained. GC/MS analysis of the extract revealed that short chain fatty acids were the main constituents of this fraction (Figure 4). Four of them, namely, (E)-2-hexenoic acid, (E)-2-heptenoic acid, decanoic acid and (E)-2-decenoic acid, appeared as small peaks. Six phenols, i.e. guaiacol, phenol, p-cresol, 4-vinylguaiaol, 4-vinylphenol and vanillin were straightforwardly identified in the extract based on mass spectra and retention indice (Figure 4 and Table 1). These phenolic compounds are known to have impacts on many food aromas (10–12). Most excitingly, ten lactones were unambiguously identified due to this selective extraction method (Figure 4 and Table 1). Lactones are widely present in foods and they are one of the most important class of aroma-impact compounds (13). These two procedures enabled the removal of interferering components and the enrichment of targeted compounds. Liters of aroma hydrodistillate can be enriched onto a small cartridge and this step can be carried out unattended with a pump to control the flow. With SPE, a very small amount (12 mL) of organic solvent is used. Most importantly, the target compounds are eluted into a 6 mL fraction, which requires minimum further concentration. Trace levels of labile volatile compounds may disappear during a long concentration process to remove a large volume of solvent due to physical losses or chemical changes. Furthermore, the entire sample preparation starting from hydrodistillation and ending at a concentrated sample for GC/O/MS analysis can be carried out within one day. The short time span of the entire sample preparation reduces the possibility of losing trace aroma compounds or moderately unstable compounds.



Separation by Two Dimensional GC In the characterization of complex aromas, two dimensional GC/O/MS system is very helpful in the identification of potent aroma-impact compounds which often occur at trace levels. Determination of aroma-impact regions is carried out on the first dimension by GC/O analysis. Individual aroma regions are sent to the second column by heartcutting with or without cryotrapping for further separation. The eluent of the second column is split between a sniff port and a mass detector, which allows the detection of the odorants and concurrent MS identification of them. Taking coffee oil as an example, as shown in Figure 5A, two interesting aroma events, the nutty-pyrazine and sweet-honey smell around 14.0 min, the coffeesulfury note right before 17.0 min, were detected in regions showing no peak above the baseline. Each of the interesting aroma events was then heartcut and sent to the second dimension for further separation. Surprisingly, a narrow window of about 0.2 min heartcut could be further separated into 20 to 30 peaks on the second column as shown in Figure 5 (B&C). GC-O of these separated peaks was used to determine which one of the peaks was responsible for the odor of interest and the mass spectra revealed the identities of the peaks as phenylacetaldehyde for the honey note, 6,7-dihydro-5H-cyclopenta[B]pyrazine for the nutty-pyrazine smell and furfuryl methyl disulfide responsible for the coffee odor.

Figure 4. GC/MS Identification of Carboxylic Acids, Phenols and Lactones in an Acidic Volatile Extract of Toasted Oat Flakes (the labeling numbers correspond to the compounds in Table 1).


Table 1. Phenols and Lactones Identified in an Acidic Volatile Extract of Toasted Oat Flakes based on MS and RI No.

Compounds

RT (min)

RI (DB-Wax)


Phenols 1

guaiacol

25.83

1858

2

phenol

28.68

2000

3

p-cresol

30.13

2077

4

4-vinylguaiacol

32.22

2191

5

p-vinylphenol

35.52

2382

6

vanillin

38.27

2553

Lactones 7

gamma-hexalactone

22.58

1705

8

gamma-heptalactone

24.75

1806

9

gamma-octalactone

27.08

1919

10

delta-octalactone

28.07

1969

11

gamma-nonalactone

29.26

2031

12

delta-nonalactone

30.25

2083

13

gamma-decalactone

31.41

2146

14

2-decen-5-olide

32.99

2234

15

gamma-undecalactone

33.45

2260

16

gamma-dodecalactone

35.39

2375

Fractionation Combined with Two Dimensional GC Separation In the GC-O analysis of a Peppermint oil, some intense odorant regions clearly arose from minor components. Due to the low levels and the complexity of the minor components, these aroma events couldn’t be unambiguously perceived by GC/O, not mentioning the identification of the molecules responsible for the odors. Fractionation of the essential oil was found necessary. Fractional distillation was used to remove the low-boiling major components, flash chromatography was used to further fractionate the residue based on polarity. Fifteen fractions were obtained and four of them were found interesting by aroma evaluation (Table 2). These four fractions were further analyzed by two dimensional GC/O/MS analysis.



Figure 5. Identification of Trace Aroma Compounds in Coffee Oil by 2D GC/O/MS Analysis. A. Partial GC-FID Chromatogram Showing Two Aroma Regions; B & C. GC/MS Chromatograms Showing the Separation of the Heartcuts on the Second Column and the Identification of the Compounds.


Table 2. Organoleptically Interesting Peppermint Flash Chromatographic Fractions Revealed by Aroma Evaluation


Fraction

Aroma description

Comments

B

fruity, fresh, slightly aldehydic, good lift, dry pineapple, sweet, very nice, lasting

the most interesting, selected for GC-O analysis

C

lactonic, hay-like, sweet, minty, coconut

interesting, selected for GC-O analysis

H

woody,dry, fruity note, citronella, citral

very interesting, selected for GC-O analysis

I

coconut, ketone, hay-like note, lactonic

interesting, selected for GC-O analysis

Table 3. Three Interesting Aroma Events Detected in Fraction B along with Their Aroma Qualities, Intensities and Heartcut Windows Aroma Event

Descriptor

RT (min)

Heartcut Window

Intensity

1

citrus

5.53

5.50-5.60

61

2

citrus peel

6.36

6.30-6.45

61

3

lactonic, sweet

6.88

6.80-7.00

82

Taking fraction B as an example, a list of aroma events were detected on the first dimension by GC/O screening, three of which are listed in Table 3. Heartcutting of Aroma Event 2 led to the detection of two aroma-active peaks at the second dimension by GC/O. They are fruity-green at 12.78 min and citrus, floral, sweet at 13.32 min. Two distinctive second dimension GC/MS peaks corresponded nicely to the two notes as shown in Figure 6 Top. The peak eluting at 12.78 min was tentatively identified as (Z,Z)-8-ocimenyl acetate based on its mass spectrum (Figure 6 Bottom). The identification was subsequently confirmed by the synthesis of the reference compound. The peak eluting at 13.32 min was found to be 1-p-menthen-9-yl acetate based on its mass spectrum and RI. Both compounds had been reported as minor components in Peppermint oil (14).

Deconvolution with Amdis Software During the GC/O/MS analysis of a honeydew melon aroma extract (4), the identification of several aroma-impact compounds could not be confirmed by their mass spectra when we used the manual way of manipulating the MS with the vendor’s software. However, Amdis deconvolution software (15) was able to detect these trace components either automatically or manually, thus led to their unambiguous identification. For instance, a soapy-fatty aroma event was tentatively identified as (Z)-2-nonenal based on aroma quality and RI. Amdis 73 In Volatile Sulfur Compounds in Food; Qian, M., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


deconvolution software automatically detected 2 components, 2-nonenal and 2-hepten-1-ol with 0.014 min difference in retention time. The scan spectrum at the retention time is the fusion of the two spectra, which does not resemble either of the two. In another case, a mushroom-like odor perceived by GC-O was tentatively identified as 1-octen-3-one based on aroma quality and RI. Running automatic Amdis deconvolution did not detect this compound. Extracting two intense ions of 1-octen-3-one (i.e. m/z 70 and m/z 55) suggested the presence of the compound (Figure 7 Top). Performing manual Amdis deconvolution using m/z 70 as model ion gave rise to a good EI spectrum identified as that of 1-octen-3-one, which was hidden in the scan spectrum (Figure 7 Bottom). Similarly, a cabbage note was detected at a retention time corresponding to a well resolved GC-MS peak. The mass spectrum of the peak indicated the coelution of 3-hexen-1-ol with a compound having m/z 126 (Figure 8). Using m/z 126 as a model ion, manual Amdis deconvolution was carried out. The resulting deconvoluted spectrum was that of dimethyltrisulfide. In conjuction with the aroma quality and retention index, the trace aroma compound was unequivocally identified as dimethyltrisulfide.

Figure 6. Two Dimensional GC/O/MS Analysis of a Peppermint Flash Chromatographic Fractions. Top: Second Dimension GC/MS Chromatogram of a Heartcut, Bottom: EI Spectrum of the Compound Eluting at 12.78 min. 74 In Volatile Sulfur Compounds in Food; Qian, M., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Figure 7. Confirmation of the Identification of 1-Octen-3-one by Its Mass Spectrum Obtained via Manual Amdis Deconvolution.

Figure 8. Identification of Dimethyltrisulfide by Its Mass Spectrum Obtained from Manual Amdis Deconvolution.



Conclusions In the GC/O/MS characterization of complex aromas, the identification of trace aroma compounds can be realized or confirmed by their mass spectra after fractionation and enrichment. Separation techniques, such as selective SPE extraction based on chemical functionalities and two dimensional GC separation have been developed and successfully applied. Combination of them with conventional fractional distillation and flash chromatography allowed us to succeed in even more demanding challenges. Finally, Amdis deconvolution software proved to be a powerful data mining tool to remove interfering signals or background noises to obtain valuable mass spectral information for confident trace aroma compound identifications.

Acknowledgments We would like to thank Dr. Jose Matiella and Gio Cipolla for their excellent training of the Amdis Deconvolution Software for us.

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The Role of Separation in the Identification of Trace Aroma

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