retention indices in the analysis of food aroma volatile compounds in temperature-programmed gas...

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J. Sep. Sci. 2007, 30, 563 – 572 F. Bianchi et al. 563 Federica Bianchi Maria Careri Alessandro Mangia Marilena Musci Dipartimento di Chimica Generale ed Inorganica, Chimica Analitica, Chimica Fisica, UniversitȤ degli Studi di Parma, Parma, Italy Original Paper Retention indices in the analysis of food aroma volatile compounds in temperature-programmed gas chromatography: Database creation and evaluation of precision and robustness A retention index (RI) database containing 250 volatile compounds was created on a polar stationary phase column and validated for food aroma characterisation. Preci- sion of the retention indices (RIs) was assessed by performing replicated injections of a representative number of volatiles under the same experimental conditions: dif- ferences lower than 1 U were observed for all the compounds. Robustness was eva- luated by carrying out injections of the same set of volatile compounds under differ- ent experimental conditions, i. e. program temperature, column batches and instru- mentation. Excellent results were obtained with a maximum difference in the RI values of 10 U. The capabilities of the created database for food aroma characterisa- tion were finally evaluated by analysing the volatile fractions of different food matrices such as dry sausages, cheese and bread. A great number of volatile com- pounds were identified in the analysed samples on the basis of their RI, thus pro- ving the usefulness of the RI collections in the field of food analysis. Keywords: Database / Food analysis / Gas chromatography / Retention indices / Volatile com- pounds / Received: September 29, 2006; revised: November 27, 2006; accepted: November 29, 2006 DOI 10.1002/jssc.200600393 1 Introduction The characterisation of the aromatic profile represents an important tool for food quality and authenticity assessment [1]. Its importance has been stated by differ- ent studies, thus considering volatile compounds as the chemical fingerprint of the analysed products [2 – 4]. Using GC-MS, volatile identification is usually achieved by library search based on the comparison of the experimental mass spectra with those stored in a suitable library (e. g. via the National Institute of Stan- dards and Technologies, NIST) However, ambiguous iden- tifications can be obtained especially in the case of struc- turally related compounds that give similar spectra, thus reducing the possibility to obtain a complete characteri- sation of the compounds under investigation. Even after many years from their first use, GC retention indices (RIs) still represent a useful tool for identification purposes [5]. In fact, these indices, being independent from the operating conditions, except for the polarity of the uti- lised stationary phase, are fundamental in making reten- tion data useful for interlaboratory comparison. This approach avoids the use of time-consuming and expen- sive procedures in which identification is based on the injection of pure compounds. In addition, when complex matrices containing hundreds of volatiles have to be ana- lysed, the injection of pure standards can be a limiting factor, since such compounds may not be commercially available. The most popular way of measuring retention was pro- posed by KovƁts [6]. In this procedure, RIs are calculated under isothermal conditions and reference substances (usually a homologous series of hydrocarbons) are used by performing a logarithmic interpolation. This approach was further developed by Van den Dool and Kratz [7] in the case of temperature-programmed GC ana- lyses, thus following an approximately linear scale. The use of RIs in temperature-programmed GC has been more recently reviewed by Gonzales [8]. As for RIs, it has been shown that the RI values of many aromatic compounds on comparable polarity stationary phases have been calculated by different laboratories with SD of about 1% [9], thus meaning that DRI from 5 to Correspondence: Professor Maria Careri, Dipartimento di Chi- mica Generale ed Inorganica, Chimica Analitica, Chimica Fisica, Viale Usberti 17/A, I-43100 Parma, Italy E-mail: [email protected] Fax: +39-0521-905557 Abbreviation: RI, retention index i 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com

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Page 1: Retention indices in the analysis of food aroma volatile compounds in temperature-programmed gas chromatography: Database creation and evaluation of precision and robustness

J. Sep. Sci. 2007, 30, 563 – 572 F. Bianchi et al. 563

Federica BianchiMaria CareriAlessandro MangiaMarilena Musci

Dipartimento di ChimicaGenerale ed Inorganica, ChimicaAnalitica, Chimica Fisica,Universit� degli Studi di Parma,Parma, Italy

Original Paper

Retention indices in the analysis of food aromavolatile compounds in temperature-programmedgas chromatography: Database creation andevaluation of precision and robustness

A retention index (RI) database containing 250 volatile compounds was created on apolar stationary phase column and validated for food aroma characterisation. Preci-sion of the retention indices (RIs) was assessed by performing replicated injectionsof a representative number of volatiles under the same experimental conditions: dif-ferences lower than 1 U were observed for all the compounds. Robustness was eva-luated by carrying out injections of the same set of volatile compounds under differ-ent experimental conditions, i. e. program temperature, column batches and instru-mentation. Excellent results were obtained with a maximum difference in the RIvalues of 10 U. The capabilities of the created database for food aroma characterisa-tion were finally evaluated by analysing the volatile fractions of different foodmatrices such as dry sausages, cheese and bread. A great number of volatile com-pounds were identified in the analysed samples on the basis of their RI, thus pro-ving the usefulness of the RI collections in the field of food analysis.

Keywords: Database / Food analysis / Gas chromatography / Retention indices / Volatile com-pounds /

Received: September 29, 2006; revised: November 27, 2006; accepted: November 29, 2006

DOI 10.1002/jssc.200600393

1 Introduction

The characterisation of the aromatic profile representsan important tool for food quality and authenticityassessment [1]. Its importance has been stated by differ-ent studies, thus considering volatile compounds as thechemical fingerprint of the analysed products [2–4].

Using GC-MS, volatile identification is usuallyachieved by library search based on the comparison ofthe experimental mass spectra with those stored in asuitable library (e.g. via the National Institute of Stan-dards and Technologies, NIST) However, ambiguous iden-tifications can be obtained especially in the case of struc-turally related compounds that give similar spectra, thusreducing the possibility to obtain a complete characteri-sation of the compounds under investigation. Even aftermany years from their first use, GC retention indices (RIs)still represent a useful tool for identification purposes

[5]. In fact, these indices, being independent from theoperating conditions, except for the polarity of the uti-lised stationary phase, are fundamental in making reten-tion data useful for interlaboratory comparison. Thisapproach avoids the use of time-consuming and expen-sive procedures in which identification is based on theinjection of pure compounds. In addition, when complexmatrices containing hundreds of volatiles have to be ana-lysed, the injection of pure standards can be a limitingfactor, since such compounds may not be commerciallyavailable.

The most popular way of measuring retention was pro-posed by Kov�ts [6]. In this procedure, RIs are calculatedunder isothermal conditions and reference substances(usually a homologous series of hydrocarbons) are usedby performing a logarithmic interpolation. Thisapproach was further developed by Van den Dool andKratz [7] in the case of temperature-programmed GC ana-lyses, thus following an approximately linear scale. Theuse of RIs in temperature-programmed GC has beenmore recently reviewed by Gonzales [8].

As for RIs, it has been shown that the RI values of manyaromatic compounds on comparable polarity stationaryphases have been calculated by different laboratorieswith SD of about 1% [9], thus meaning that DRI from 5 to

Correspondence: Professor Maria Careri, Dipartimento di Chi-mica Generale ed Inorganica, Chimica Analitica, Chimica Fisica,Viale Usberti 17/A, I-43100 Parma, ItalyE-mail: [email protected]: +39-0521-905557

Abbreviation: RI, retention index

i 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com

Page 2: Retention indices in the analysis of food aroma volatile compounds in temperature-programmed gas chromatography: Database creation and evaluation of precision and robustness

564 F. Bianchi et al. J. Sep. Sci. 2007, 30, 563 – 572

20 should be obtained when compounds with RI from500 to 2000 are considered. However, it should also benoted that larger differences have been observed in lit-erature data for the same compounds [10–13].

As for databases, different collections of RI of volatilecompounds are available (http://www.pherobase.com/database/kovats/kovats-index.php, http://www.flavornet.org/f_kovats.html, http://www.chromtech.net.au/kovats_ri.cfm, http://www.chem.agilent.com/cag/cabu/pdf/b-0279.pdf) [14, 15], but some of them have been cre-ated by collecting the RIs published in different studies.As a consequence, nonhomogeneous values could befound in the corresponding databases. To the best of ourknowledge, a comprehensive and reliable database of RIof food volatiles is not freely available, although similardatabases have been created for the identification of vola-tile compounds of botanical [16], toxicological [17] orindustrial interest [18].

In such a context, the aim of this study was the crea-tion of a suitable database for food aroma characterisa-tion and the assessment of repeatability and robustnessof the calculated RI values under temperature-pro-grammed GC-MS conditions. For this purpose, an RI data-base of 250 compounds of food value was created on apolar stationary phase column. By performing replicatedmeasurements under different conditions (i. e. tempera-ture program, instrumentation, column batch, columnaging) a maximum difference of 10 U among theobtained values was observed, thus proving the reliabil-ity of the calculated RI values. Finally, the database wassuccessfully applied to the characterisation of the aromaof different foods such as ,Fontina Valle d'Aosta’ cheese,the typical Italian sausage ,Salame Mantovano’ and thetraditional product ,Altamura’ bread, thus proving itsusefulness in the identification of a great number of vola-tiles with very small RI differences.

2 Experimental

2.1 Instruments

Two different systems were used: a CP3800 gas chromato-graph (Varian, Palo Alto, CA, USA) equipped with aSaturn 2000 IT mass selective detector (instrument A)and a TRACE GC 2000 gas chromatograph (Thermo Elec-tron Corporation, Walthan, MA, USA) equipped with aFinnigan TRACE MS mass spectrometer (Thermo ElectronCorporation) (instrument B). Helium was used as the car-rier gas at a flow rate of 1 mL/min; both the gas chroma-tographs were operated in splitless mode with the injec-tor maintained at the temperature of 3008C. Chromato-graphic separations were performed on 30 m60.25 mm,df 0.25 lm Supelcowax-10TM (Supelco, Bellafonte, PA,USA) capillary columns belonging to different batchesand characterised by a different age. The column coupled

with the IT was 3 months old, whereas that coupled withthe quadrupole MS was 2 years old.

The following GC oven temperature programmes wereapplied: (i) 358C for 8 min, 48C/min to 608C, 68C/min to1608C, 208C/min to 2008C, 2008C for 1 min (used for bothinstruments); (ii) 408C for 1 min, 108C/min to 1208C,158C/min to 2008C, 2008C for 1 min (used for instrumentA).

IT temperature was 1708C; manifold and transfer linetemperatures were 80 and 2608C, respectively. When theTRACE-MS system was used, transfer line and sourcewere maintained at the temperature of 250 and 2308C,respectively.

MS detection was performed under electron impact(EI) ionisation conditions at 70 eV by operating in thefull-scan acquisition mode in the 30 –350 amu range. Inthe case of the GC-IT/MS detection system, other instru-mental parameters were: emission current of 10 lA; scantime of 0.30 s; automatic gain control of 25000.

Signal acquisition and data processing were perform-ed using the Saturn Workstation v. 5.4 (Varian) and theExcalibur V 1.2 (Thermo Electron Corporation). The iden-tification of the volatile compounds was performed bycomparing the obtained mass spectra with those storedin the National Institute of Standards and Technologies(NIST) US Government library.

2.2 Calculation of RIs

Retention indices were calculated using n-alkanes (C8-C17) (Sigma–Aldrich, Milan, Italy) as reference com-pounds using the following expression:

RIðxÞ ¼ 1006zþ 1006RTðxÞ � RTðzÞ

RTðzþ 1Þ � RTðzÞ

where RI (x) is the retention index of the unknown com-pound x, z the number of carbon atoms of the n-alkaneeluted before the unknown compound x, z + 1 the num-ber of carbon atoms of the n-alkane eluted after theunknown compound x, RT (x) is the retention time of theunknown compound x, RT (z) the retention time of the n-alkane eluted before the unknown compound x, RT (z + 1)n-alkane eluted after the unknown compound x.

All the indices were calculated by performing threereplicated measurements by injecting pure compounds.

2.3 Samples

The volatile fraction of different foods (Fontina Valled’Aosta cheese, Salame Mantovano and Altamura bread)was characterised by using the dynamic headspaceextraction technique coupled with the GC-MS analysis.

Fontina Valle d'Aosta cheese was supplied by

,Consorzio Produttori e Tutela della DOP Fontina’ (Aosta,Italy), whereas Salame Mantovano and Altamura bread

i 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com

Page 3: Retention indices in the analysis of food aroma volatile compounds in temperature-programmed gas chromatography: Database creation and evaluation of precision and robustness

J. Sep. Sci. 2007, 30, 563 – 572 Gas Chromatography 565

were purchased by local producers. Before analysis, allthe samples were cut into small pieces, frozen underliquid nitrogen, ground in a domestic blender and storedat –208C in screw-cap glass vials until analysis.

Ten grams of finely ground cheese and 3 g of SalameMantovano and Altamura bread, respectively, wereplaced in a 200 mL Erlenmayer flask at the temperatureof 408C and submitted to the dynamic headspace extrac-tion for 30 min using purified nitrogen (60 mL/min). Theextracted volatiles were concentrated on a Tenax TAmtrap (Chrompack, Middelburg, The Netherlands) filledwith 90 mg, 20 –35 mesh of the adsorbent material. Theadsorbent trap was then back-flushed with the purifiedgas for 5 min to remove the trapped moisture. Volatileswere automatically thermally desorbed and transferredto the GC column by using a TCT thermal desorptioncold trap (TD800, Fisons Instruments, Milan, Italy). De-sorption was performed at 2808C for 10 min under ahelium flow (10 mL/min): the volatile compounds werecryofocused in a glass lined tube at –1208C with liquidnitrogen and then injected into the GC capillary columnby heating the cold trap to 2408C.

Three independent DHS extractions were performedfor each sample.

3 Results and discussion

A database containing 250 volatile compounds (Table 1)was created by using a polar (PEG) stationary phase col-umn in order to use these data to characterise the aromaof different foods.

Retention indices are indicated as integers, as sug-gested by Ettre [19]. In fact, RI values with a decimal digitare meaningless, taking into account that a difference of0.1 in the RI should correspond to a difference of about0.5 s in the retention time of the analyte.

Usually, identification of GC peaks can be performedby comparing experimental mass spectra with thosestored in libraries as NIST and Wiley. However, incom-plete information and ambiguous identification can beobtained when an MS spectra library search is perform-ed, especially in the case of compounds characterised bya similar fragmentation pattern like isomers (Fig. 1). Asshown in the figure, the mass spectrum of a-pinene isvery similar to the spectra obtained from other terpenes;under these conditions, the comparison between theexperimental spectrum and those stored in the librariesis not able to provide an unambiguous identification ofthe analyte. Instead, a number of structurally relatedcompounds are proposed with similar probabilities. Inthis case, the combined use of mass spectrometric dataand RIs can provide a more certain identification of thecompound.

i 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com

Table 1. RI database

RI MW Formula CAS

AlcoholsEthanol 932 46 C2H6O 64-17-52-Propanol 975 60 C3H8O 67-63-02-Butanol 1035 74 C4H10O 78-92-21-Propanol 1052 60 C3H8O 71-23-83-Methyl-2-butanol 1094 88 C5H12O 598-75-42-Methyl-1-propanol 1097 74 C42H10O 78-83-13-Pentanol 1112 88 C5H12O 584-02-11-Methoxy-2-propanol 1131 90 C4H10O2 107-98-22-Pentanol 1142 88 C5H12O 6032-29-71-Butanol 1152 74 C4H10O 71-36-31-Penten-3-ol 1176 86 C5H10O 616-25-13-Penten-2-ol 1182 86 C5H10O 1569-50-23-Hexanol 1207 102 C6H14O 623-37-02-Methyl-1-butanol 1212 88 C5H12O 137-32*63-Methyl-1-butanol 1215 88 C5H12O 123-51-32-Hexanol 1238 102 C6H14O 626-93-71-Pentanol 1256 88 C5H12O 71-41-03-Methyl-3-buten-1-ol 1263 86 C5H10O 763-32-6cis-2-Pentenol 1323 86 C5H10O 1576-95-03-Methyl-1-pentanol 1325 102 C6H14O 589-35-52-Heptanol 1334 116 C7H16O 111-70-6trans-2-Pentenol 1335 86 C5H10O 1576-96-11-Hexanol 1354 102 C6H14O 111-27-3trans-3-Hexenol 1371 100 C6H12O 928-97-2cis-3-Hexenol 1388 100 C6H12O 928-96-1Cyclohexanol 1407 100 C6H12O 108-93-0trans-2-Hexenol 1410 100 C6H12O 928-95-0cis-2-Hexenol 1420 100 C6H12O 928-94-92-Octanol 1430 130 C8H18O 123-96-61-Octen-3-ol 1456 128 C8H16O 3391-86-41-Heptanol 1460 116 C7H16O 111-70-62-Ethyl-1-hexanol 1492 130 C8H18O 104-76-72-Nonanol 1528 144 C9H20O 628-99-91-Octanol 1561 130 C8H18O 111-87-51-Nonanol 1668 144 C9H20O 28 473-21-4

AldehydesPropanal 801 58 C3H6O 123-38-62-Methyl propanal 814 72 C4H8O 78-84-2Butanal 878 72 C4H8O 123-72-82-Methyl butanal 914 86 C5H10O 590-86-33-Methyl butanal 917 86 C5H10O 590-86-3Pentanal 977 86 C5H10O 110-62-32-Ethyl butanal 1004 100 C6H12O 97-96-12-Butenal 1041 70 C4H6O 4170-30-3Hexanal 1080 100 C6H12O 66-25-1trans-2-Pentenal 1135 84 C5H8O 1576-87-0cis-2-Pentenal 1142 84 C5H8O 1576-86-9Heptanal 1186 114 C7H14O 111-71-7cis-2-Hexenal 1189 98 C6H10O 505-57-7trans-2-Hexenal 1225 98 C6H10O 6728-26-3Octanal 1286 128 C8H16O 124-13-0trans-2-Heptenal 1320 112 C7H12O 18 829-55-5Nonanal 1396 142 C9H18O 124-19-6trans-2-Octenal 1432 126 C8H14O 2548-87-0trans,trans-2,4-Hepta-dienal

1497 110 C7H10O 4313-03-5

Decanal 1502 156 C10H20O 112-31-2Benzaldehyde 1528 106 C7H6O 100-52-7trans-2-Nonenal 1546 140 C9H16O 18 829-56-6trans-2-Decenal 1652 154 C10H18O 3913-81-3Phenylacetaldehyde 1669 120 C8H8O 122-78-1

Aromatic hydrocarbonsBenzene 936 78 C6H6 71-43-2Toluene 1040 92 C7H88 108-88-3Ethylbenzene 1125 106 C8H10 100-41-4p-Xylene 1127 106 C8H10 106-42-3m-Xylene 1132 106 C8H10 108-38-3o-Xylene 1182 106 C8H10 95-47-6

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566 F. Bianchi et al. J. Sep. Sci. 2007, 30, 563 – 572

i 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.-

com

Table 1. Continued ...

RI MW Formula CAS

Propylbenzene 1207 120 C9H12 103-65-1Styrene 1261 104 C8H8 100-42-5m-Cymene 1264 134 C10H14 535-77-3p-Cymene 1266 134 C10H14 99-87-61,2,3-Trimethylbenzene 1340 120 C9H12 526-73-8

EstersMethyl acetate 828 74 C3H6O2 79-20-9Ethyl acetate 893 88 C4H8O2 141-78-6Isopropyl acetate 904 102 C5H10O2 108-21-4Methyl propionate 911 88 C4H8O2 554-12-1Methyl isobutanoate 930 102 C5H10O2 547-67-7Ethyl propionate 957 100 C5H8O2 140-88-5Ethyl isobutanoate 960 116 C6H12O2 97-62-1Propyl acetate 976 102 C5H10O2 109-60-4Methyl butanoate 982 102 C5H10O2 623-42-7Isobutyl acetate 1018 116 C6H12O2 110-19-0Ethyl isopentanoate 1024 116 C6H12O2 556-24-1Ethyl butanoate 1040 116 C6H12O2 105-54-4Isopropyl butanoate 1046 130 C7H14O2 638-11-9Propyl propionate 1056 116 C6H12O2 106-36-5Propyl isobutanoate 1058 130 C7H14O2 644-49-5Ethyl isopentanoate 1068 130 C7H14O2 108-64-5Butyl acetate 1077 116 C6H12O2 123-86-4Isobutyl isobutanoate 1085 144 C8H16O2 97-85-8Isobutyl propionate 1087 130 C7H14O2 540-42-1Methyl pentanoate 1087 116 C6H12O2 624-24-8Butyl propionate 1120 130 C7H14O2 590-01-2Propyl butanoate 1123 130 C7H14O2 105-66-8Isopentyl acetate 1125 130 C7H14O2 123-92-2Ethyl pentanoate 1138 130 C7H14O2 539-82-2Isobutyl butanoate 1152 144 C8H16O2 539-90-2Butyl isobutanoate 1154 144 C8H16O2 97-87-0Isobutyl isopentanoate 1175 158 C9H18O2 589-59-3Pentyl acetate 1180 130 C7H14O2 628-63-7Isopentyl isobutanoate 1187 158 C9H18O2 2050-01-3Methyl hexanoate 1190 130 C7H14O2 106-70-7Isopentyl propionate 1192 144 C8H16O2 105-68-0Butyl butanoate 1223 144 C8H16O2 109-21-7Ethyl hexanoate 1238 144 C8H16O2 123-66-0Pentyl propionate 1239 144 C8H16O2 624-54-4Pentyl isobutanoate 1247 158 C9H18O2 2445-72-9Isopentyl butanoate 1267 158 C9H18O2 106-27-4Hexyl acetate 1269 144 C8H16O2 142-92-7Methyl heptanoate 1288 144 C8H16O2 106-73-0Propyl hexanoate 1324 158 C9H18O2 626-77-7Ethyl heptanoate 1331 158 C9H18O2 106-30-9Pentyl butanoate 1340 158 C9H18O2 540-18-1Hexyl isobutanoate 1350 172 C10H208O2 2349-07-7Heptyl acetate 1370 158 C9H18O2 112-06-1Methyl octanoate 1387 158 C9H18O2 111-11-5Butyl hexanoate 1420 172 C10H20O2 626-82-4Propyl heptanoate 1425 172 C10H20O2 0-00-0Ethyl octanoate 1438 172 C10H20O2 106-32-1Heptyl isobutanoate 1449 186 C11H22O2 2349-13-5Ethyl acetoacetate 1466 130 C6H10O3 141-97-9Octyl acetate 1478 172 C10H20O2 112-14-1Methyl nonanoate 1493 172 C10H20O2 1731-84-6Butyl heptanoate 1517 186 C11H22O2 0-00-0Ethyl nonanoate 1528 186 C11H22O2 123-29-5Propyl octanoate 1530 186 C11H22O2 624-13-5Octyl isobutanoate 1543 200 C12H24O2 109-15-9Isobutyl acetotacetate 1586 158 C8H14O3 7779-75-1Methyl decanoate 1590 186 C11H22O2 110-42-9Tetrahydrofurfurylacetate

1590 144 C7H12O3 637-64-9

Butyl octanoate 1621 200 C12H24O2 0-00-0Ethyl decanoate 1647 200 C12H24O2 110-38-3

FuransFuran 802 68 C4H4O 100-00-9

Table 1. Continued ...

RI MW Formula CAS

2-Methylfuran 876 82 C5H6O 534-22-52-Ethylfuran 945 98 C5H6O2 3208-16-02-Propylfuran 1143 110 C7H10O 4229-91-82-Pentylfuran 1240 138 C9H14O 3777-69-32-Methyl-3-tetrahydro-furanone

1266 100 C5H8O2 3188-00-9

2-Furfural 1474 96 C5H4O2 98-01-12-Acetylfuran 1511 110 C6H6O2 1192-62-75-Methyl-2-furfural 1589 110 C6H6O2 620-02-0

Halogen compoundsCarbon tetrachloride 879 151 CCl4 56-23-5Dichloromethane 927 83 CH2Cl2 58 165-12-1Chloroform 1018 117 CHCl3 67-66-3Tetrachloroethylene 1021 164 C2Cl4 127-18-41,2-Dichloropropane 1044 111 C3H6Cl2 78-87-51,3-Dichloropropane 1188 111 C3H6Cl2 142-28-91,1,1,2-Tetrachlor-oethane

1261 165 C2H4Cl4 630-20-6

1,1,2-Trichloroethane 1269 131 C2H3Cl3 79-00-51,2,3-Trichloropropane 1420 145 C5H5Cl3 96-18-4

HydrocarbonsOctane 800 114 C8H18 111-65-92-Octene 846 112 C8H16 13 389-42-9Nonane 900 128 C9H20 111-84-2Decane 1000 142 C10H22 124-18-5Undecane 1100 156 C11H24 1120-21-4Dodecane 1200 170 C12H26 112-40-3Tridecane 1300 184 C13H28 629-50-5Tetradecane 1400 198 C14H30 629-59-4Pentadecane 1500 212 C15H32 629-62-9Hexadecane 1600 226 C16H34 544-76-3Heptadecane 1700 240 C17H36 629-78-7

KetonesAcetone 814 58 C3H6O 67-64-12-Butanone 901 72 C4H8O 78-93-33-Buten-2-one 953 70 C4H6O 78-94-42-Pentanone 980 86 C5H10O 107-87-92,3-Butandione 986 86 C4H6O2 431-03-84-Methyl-2-pentanone 1008 100 C6H12O 108-10-11-Penten-3-one 1024 84 C5H8O 1629-58-93-Hexanone 1052 100 C6H12O 589-38-82,3-Pentandione 1071 100 C5H8O2 600-14-62-Hexanone 1082 100 C6H12O 591-78-62,3-Hexandione 1143 114 C6H10O2 3848-24-63,4-Hexandione 1151 114 C6H10O2 4437-51-83-Heptanone 1160 114 C7H14O 106-35-42-Heptanone 1185 114 C7H14O 110-43-04-Hexen-3-one 1195 98 C6H10O 2497-21-42,4-Pentandione 1196 100 C5H8O2 123-54-63-Octanone 1251 128 C8H16O 106-68-32-Octanone 1280 128 C8H16O 111-13-7Cyclohexanone 1282 98 C6H10O 108-94-13-Hydroxy-2-butanone 1289 88 C4H8O2 513-86-01-Octen-3-one 1299 126 C8H14O 4312-99-66-Methyl-5-hepten2-one 1340 126 C8H14O 110-93-02-Methyl-2-cyclopen-ten-1-one

1368 96 C6H8O 1120-73-6

2-Nonanone 1394 142 C9H18O 821-55-62-Decanone 1484 156 C10H20O 693-54-92-Nonen-4-one 1489 140 C9H16O 32 064-72-53,5-Octadien-2-one 1521 124 C8H12O 30 086-02-33,5,5-Trimethyl-2-cyclo-hexenone

1599 138 C9H14O 78-59-1

2-Undecanone 1606 170 C11H22O 112-12-9Acetophenone 1660 120 C8H8O 98-86-2

PyrazinesPyrazine 1209 80 C4H4N2 290-37-9

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J. Sep. Sci. 2007, 30, 563 – 572 Gas Chromatography 567

In this context, the demand for an extensive and

,validated’ database for food applications is quite increas-ing. In fact, most of the studies dealing with food charac-terisation simply report the RI values calculated for the

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Table 1. Continued ...

RI MW Formula CAS

2-Methylpyrazine 1264 94 C5H6N2 109-08-02,5-Dimethylpyrazine 1318 108 C6H8N2 123-32-02,6-Dimethylpyrazine 1325 108 C6H8N2 108-50-92-Ethylpyrazine 1334 108 C6H8N2 13 925-00-32,3-Dimethylpyrazine 1345 108 C6H8N2 5910-89-42,3,5-Trimethylpyrazine 1401 122 C7H10N2 14 667-55-12-Ethyl-6-methylpyra-zine

1402 122 C7H10N2 15 707-23-0

2-Ethyl-5-methylpyra-zine

1406 122 C7H10N2 13 360-64-0

2-Ethyl-3-methylpyra-zine

1411 122 C7H10N2 13 925-03-6

2-Ethyl-3,5-dimethylpyr-azine

1443 136 C8H12N2 13 925-07-0

2,6-Diethylpyrazine 1456 136 C8H12N2 13 067-27-12,3-Diethylpyrazine 1458 136 C8H12N2 15 707-24-12,3,5,6-Tetramethylpyra-zine

1474 136 C8H12N2 1124-11-4

2,3-Diethyl-5-methylpyr-azine

1492 150 C9H14N2 18 138-04-0

2-Isobutyl-3-methoxy-pyrazine

1527 166 C9H14N2O 24 683-00-9

2-Acetyl-3-methyl-pyra-zine

1635 136 C7H8N2O 0-00-0

2-Acetylpyrazine 1639 122 C6H6N2O 22 047-25-22-Acetyl-3-ethylpyrazine 1685 150 C8H10N2O 0-00-0

Sulphur compoundsDimethyl sulphide 745 62 C2H6S 75-18-3Thiophene 1022 84 C4H4S 110-02-1Dimethyl disulphide 1075 94 C2H6S2 624-92-02-Methyl thiophene 1090 98 C5H6S 554-14-3Ethyl thioacetate 1092 104 C4H8OS 625-60-5Cyclopentyl mercaptan 1107 102 C5H10S 1679-07-83-Methyl thiophene 1120 98 C5H6S 616-44-4Allyl sulphide 1143 114 C6H10S 592-88-12,5-Dimethylthiophene 1162 112 C6H8S 638-02-8S-Methyl thiobutanoate 1198 118 C5H10OS 2432-51-1Butyl sulphide 1262 146 C8H18S 544-40-14-Methylthiazole 1280 99 C4H5NS 693-95-82-Ethyl-4-methylthiazole1322 127 C6H9NS 15 679-12-6Allyl isothiocyanate 1372 99 C4H5NS 57-06-72,4,5-Trimethylthiazole 1380 127 C6H9NS 13 623-11-5Dimethyl trisulphide 1383 125 C2H6S3 3658-80-82-Isobutylthiazole 1396 141 C7H11NS 18 640-79-44-Methyl-5-vinyl thiazole1524 125 C6H7NS 179-28-04-Methylbenzenethiol 1617 124 C7H8S 137-06-42-Acetyl thiazole 1661 127 C5H5NOS 24 295-03-2Benzyl methyl sulphide 1680 138 C8H10S 766-92-7Dipropyl trisulphide 1683 182 C6H14S3 6028-61-1

Terpenesa-Pinene 1010 136 C10H16 80-56-8a-Thujene 1013 136 C10H16 2867-05-2Camphene 1053 136 C10H16 79-92-5b-Pinene 1095 136 C10H16 127-91-3Sabinene 1133 136 C10H16 3387-41-53-Carene 1144 136 C10H6 13 466-78-9a-Phellandrene 1160 136 C10H6 99-83-2b-Myrcene 1167 136 C10H16 123-35-3a-Terpinene 1175 136 C10H16 99-86-51,4-Cineole 1176 154 C10H18O 470-67-7Limonene 1194 136 C10H16 138-86-31,8-Cineole 1198 154 C10H18O 470-82-6b-Phellandrene 1202 136 C10H1616 555-10-2Ocimene 1237 136 C10H16 3779-61-1c-Terpinene 1240 136 C10H6 99-85-4a-Terpinolene 1276 136 C10H6 586-62-9Linalool 1554 154 C7H18O2 78-70-6b-Caryophillene 1598 204 C15H244 87-44-5

Table 2. RI obtained by using two different temperature pro-grammes

RIa)calcd RIb)

calcd DK

Octane 800 800 02-Octene 846 848 22-Methylfuran 876 874 2Nonane 900 900 0Benzene 936 938 22-Ethylfuran 945 950 52-Pentanone 980 982 2Methyl butanoate 982 987 5Decane 1000 1000 02-Ethyl-butanal 1004 1007 3Isobutyl acetate 1018 1016 2Isopropyl butanoate isopropile 1046 1051 5Propyl isobutanoate propile 1058 1054 42,3-Pentandione 1071 1076 5Undecane 1100 1100 0Cyclopentyl mercaptan 1107 1111 4trans-2-Pentenal 1135 1139 42,3-Hexandione 1143 1136 72,5-Dimethyl-thiophene 1162 1168 61,4-Cineole 1176 1179 32-Heptanone 1185 1185 0Isopentyl isobutanoate 1187 1195 7Dodecane 1200 1200 02-Methyl-1-butanol 1212 1207 5trans-2-Hexenal 1225 1224 11-Pentanol 1256 1253 3Styrene 1261 1264 3Isopentyl butanoate 1267 1266 14-Methylthiazole 1280 1284 4Tridecane 1300 1300 02,5-Dimethylpyrazine 1318 1323 52-Heptanol 1334 1332 2trans-2-Pentenol 1335 1338 3n-Hexanol 1354 1351 3Tetradecane 1400 1400 02-Ethyl-3-methylpyrazine 1407 1410 32-Furfural 1474 1473 1Octyl acetate 1478 1474 4Pentadecane 1500 1500 0Decanal 1502 1504 22-Isobutyl-3-methoxy-pyrazine 1527 1523 42-Nonanol 1528 1528 0Linalool 1554 1554 01-Octanol 1561 1566 5b-Caryophyllene 1598 1593 5Hexadecane 1600 1600 02-Undecanone 1606 1606 0Ethyl decanoate 1647 1642 51-Nonanol 1668 1663 5Heptadecane 1700 1700 0

a) Temperature programme: 358C for 8 min, 48C/min to608C, 68C/min to 1608C, 208C/min to 2008C, 2008C for1 min.

b) Temperature programme: 408C for 1 min, 108C/min to1208C, 158C/min to 2008C, 2008C for 1 min.

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568 F. Bianchi et al. J. Sep. Sci. 2007, 30, 563 – 572

compounds previously identified on the basis of theirmass spectrum without the comparison with the valuesreported in previous studies [20, 21], thus reducing theeffective usefulness of the RIs. As a consequence, mislead-ing information can be obtained.

In this work, some of the most representative chemicalclasses of aromatic compounds encompassing aldehydes,ketones, alcohols, esters, terpenes, sulphur and N-hetero-cyclic compounds were considered for the database crea-tion. All these compounds are known to contribute tofood aroma [22]: they may be naturally present in thefood, either in the raw matter or produced during foodtreatment, or added as flavouring agents.

The obtained results were very satisfactory, since a dif-ference lower than 1 U in the RI was always obtained,thus proving a good repeatability under the same operat-ing conditions. The excellent results achieved by operat-ing under repeatability conditions could be explainedtaking into account that an instrument equipped withan electronic flow controller was used, thus reducing theretention time variability due to the chromatographicprocess. As expected, a DRI of about 100 was obtained forhomologous compounds differing by one carbon atomunit, thus confirming the reliability of data.

In addition, taking into account that different experi-mental conditions can be required when differentmatrices are analysed, the reliability of the database wasalso evaluated by varying other parameters such as col-umn aging, column batches, temperature program and

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Table 3. Volatile compounds identified in the Fontina PDOsamples (n = 24)

IDa) RIcalcd RItabb) DK

Alcohols (14)Ethanol MS; RI 937 932 52-Propanol MS; RI 970 975 52-Butanol MS; RI 1039 1035 41-Propanol MS; RI 1051 1052 12-Methyl-1-propanol MS; RI 1107 1097 103-Pentanol MS; RI 1113 1112 11-Butanol MS; RI 1153 1152 11-Penten-3-ol MS; RI 1177 1176 13-Hexanol MS; RI 1204 1207 33-Methyl-1-butanol MS; RI 1222 1215 71-Pentanol MS; RI 1261 1256 52-Heptanol MS; RI 1326 1334 81-Hexanol MS; RI 1359 1354 52-Ethyl hexanol MS; RI 1492 1492 0

Ethyl esters (11)Ethyl acetate MS; RI 891 893 2Ethyl propanoate MS; RI 959 957 2Ethyl isobutanoate MS; RI 969 960 9Propyl acetate MS; RI 977 976 1Ethyl butanoate MS; RI 1046 1040 6Butyl acetate MS; RI 1085 1077 8Propyl butanoate MS; RI 1133 1123 10Ethyl isocaproate MS 1197Ethyl hexanoate MS; RI 1242 1238 4Ethyl heptanoate MS; RI 1327 1337 4Ethyl octanoate MS; RI 1439 1438 1

Ketones (10)Acetone MS; RI 819 814 52-Butanone MS; RI 907 901 63-Buten-2-one MS; RI 946 953 72-Pentanone MS; RI 979 980 12,3-Butandione MS; RI 988 986 24-Methyl-2-pentanone MS; RI 999 1008 9Not identified MS 10352,3-Pentandione MS; RI 1069 1071 22-Heptanone MS; RI 1188 1185 32-Nonanone MS; RI 1392 1394 2

Aldehydes (9)2-Methyl propanal MS; RI 812 814 2Butanal MS; RI 880 878 22-Methyl butanal MS; RI 916 914 23-Methyl butanal MS; RI 920 917 3Pentanal MS; RI 985 977 8Hexanal MS; RI 1082 1080 2Heptanal MS; RI 1191 1186 5Octanal MS; RI 1290 1286 4Nonanal MS; RI 1398 1396 2

Terpenes (7)a-Pinene MS; RI 1017 1010 7Not identified MS 1027Camphene MS; RI 1060 1053b-Pinene MS; RI 1102 1095 7Limonene MS; RI 1193 1194 1p-Cymene MS; RI 1270 1266 7a-Terpinolene MS; RI 1280 1276 4

Aromatic compounds (6)Benzene MS; RI 938 936 2Toluene MS; RI 1043 1040 3Ethylbenzene MS; RI 1121 1125 4p-Xylene MS; RI 1129 1127 2m-Xylene MS; RI 1136 1132 4o-Xylene MS; RI 1175 1182 7

Hydrocarbons (4)Not identified MS a800 a800

Table 3. Continued ...

IDa) RIcalcd RItabb) DK

Not identified MS a800 a800Octane MS; RI 800 800 02-Octene MS; RI 843 846 3

Sulphur compounds (4)S-Methyl-thioacetate MS 1056Dimethyl disulphide MS; RI 1080 1075 5S-Methyl thiopropionate MS 1131Dimethyl trisulphide MS; RI 1381 1383 2

Acids (3)Acetic acid MS 1480Propanoic acid MS 1554Butanoic acid MS 1630

Furans (3)2-Methylfuran MS; RI 872 876 42-Ethylfuran MS; RI 950 945 52-Pentylfuran MS; RI 1236 1240 4

Halogen compounds (3)Not identified MS a800 a800Dichloromethane MS; RI 933 927 6Chloroform MS; RI 1020 1018 2

a) ID: MS = identification by comparison with NIST massspectrum, RI = identification by comparison with RIs.

b) RItab: identification by comparison with RI homemadedatabase.

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J. Sep. Sci. 2007, 30, 563 – 572 Gas Chromatography 569

instrumentation. Among the 250 injected compounds, arepresentative number of volatiles (n = 40) was selectedand the corresponding RI values were evaluated by vary-ing the temperature program conditions. The selectionof these compounds was performed with the goal toencompass a wide-range of volatility. This approachallowed to perform a more robust evaluation of theretention data in comparison with those published inprevious studies, in which the goodness of data had beenevaluated using a reduced set of compounds [23].

As shown in Table 2, a maximum DRI of 7 U among theselected compounds was observed when the same col-umn and the same instrument, but different tempera-ture programmes were used, thus allowing to state thatRIs can be useful for identification purposes also underdifferent chromatographic conditions. These findingsproved the robustness of the database. In fact, the resultsachieved were better than those obtained in previousstudies in which DRI of 50 on the same kind of stationaryphase were obtained [23, 24].

Finally, since the aim of the study was the creation of avalidated RI collection for food aroma characterisation,further experiments were carried out by analysing thevolatile fraction of real matrices like Fontina Valle d'Aostacheese (Table 3), Salame Mantovano (Table 4, Fig. 2) andAltamura bread (Table 5), which are typical Italian foodproducts. Different matrices were appositely chosen onthe basis of their different compositions, thus involvingthe presence of a great variety of compounds both interms of number of volatiles and of their belonging todifferent chemical classes. In fact, ,Fontina’ is mainly

characterised by a high number of alcohols and esters,whereas terpenes and aldehydes are the most abundantcompounds found in the volatile fraction of Salame Man-tovano [25, 26]. The flavour of Altamura bread is charac-terised by a high number of pyrazines and other volatilecompounds produced during the thermal treatment ofcooking as already observed for other bread products[22].

The applicability of the database in the field of foodanalysis is of great concern since the aromatic profilecan be used for the characterisation of the productsunder investigation. Under these circumstances, thecharacterisation of food aroma could allow both to guar-antee and preserve the quality of typical products and toavoid adulterations or frauds. As for the halogen com-pounds found in the aromatic profile of the differentmatrices analysed, it has to be mentioned that these com-pounds are usually present as artefacts, being related topossible contaminations during the production pro-cesses.

As reported in the tables, very good results were alsoobtained when different instrumentation and columnsbelonging to different batches and of different agingwere used. In fact, taking into account that all the ana-lyses regarding the characterisation of the aroma profileof Fontina Valle d'Aosta cheese, Salame Mantovano andAltamura bread were carried out using a gas chromato-graph not equipped with an electronic flow controller(available in the case of the instrument used for the data-base creation) and by using a column 2 years older thanthat used for the calculation of the RI database, the

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Figure 1. Mass spectra of different terpenes.

Figure 2. GC-MS chromatogram (full scan) of a representative sample of Salame Mantovano.

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570 F. Bianchi et al. J. Sep. Sci. 2007, 30, 563 – 572

obtained results are very satisfactory. In fact, a maximumdifference of ten RI units was obtained. This value can beconsidered acceptable for supporting the mass spectro-metric identification when different experimental con-ditions are used. Taking advantage of the database cre-ated, most of the terpenes in the volatile fraction of Sal-ame Mantovano as well as pyrazines in the Altamurabread were identified. The capabilities of the RI collec-tions were proved for food aroma characterisation, espe-cially in the case of structurally related compounds.

4 Concluding remarks

A database containing RIs of 250 volatile compounds wascreated and used for the characterisation of the aromaticprofile of different food products. The precision androbustness of the calculated RIs allowed to demonstrate

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Table 4. Volatile compounds detected in Salame Mantovano

Peaka) Compound IDb) RIcalcd RItabc) DRI

Terpenes (33)25 Not identified MS 99828 a-Pinene MS; RI 1012 1010 229 a-Thujene MS; RI 1015 1013 234 Not identified MS 105635 Camphene MS; RI 1057 1053 436 Not identified MS 107041 b-Pinene MS; RI 1096 1095 142 Not identified MS 110549 3-Carene MS; RI 1149 1144 551 a-Phellandrene MS; RI 1164 1160 452 Not identified MS 116853 b-Myrcene MS; RI 1169 1167 256 a-Terpinene MS; RI 1179 1175 460 Limonene MS; RI 1197 1194 361 b-Phellandrene MS; RI 1198 1202 463 Not identified MS 120468 b-(Z)-Ocimene MS 124069 c-Terpinene MS; RI 1244 1240 470 Not identifed MS 124871 b-(E)-Ocimene MS 125075 p-Cymene MS; RI 1269 1266 376 a-Terpinolene MS; RI 1278 1276 277 Not identified MS 128381 Not identified MS 131482 Not identified MS 132088 Not identified MS 137890 Not identified MS 139691 Not identified MS 139892 Not identified MS 1429

108 a-Copaene MS 1470110 Camphor MS 1510112 Linalool MS; RI 1554 1554 0114 b-Caryophyllene MS; RI 1592 1598 6

Aldehydes (13)6 Propanal MS; RI 801 801 09 2-Propenal MS 840

11 Butanal MS; RI 883 878 514 2-Methyl butanal MS; RI 915 914 115 3-Methyl butanal MS; RI 920 917 322 Pentanal MS; RI 983 977 640 Hexanal MS; RI 1085 1080 559 Heptanal MS; RI 1188 1186 265 (E)-2-Hexenal MS; RI 1224 1225 179 Octanal MS; RI 1292 1286 683 (Z)-2-Heptenal MS 133193 (E)-2-Octenal MS; RI 1432 1432 0

101 Benzaldehyde MS; RI 1529 1528 1

Ketones (11)7 Acetone MS; RI 813 814 1

13 2-Butanone MS; RI 905 901 417 3-Buten-2-one MS; RI 947 953 621 2-Pentanone MS; RI 980 980 027 4-Methyl-2-pentanone MS; RI 1010 1008 237 2,3-Pentanedione MS; RI 1071 1071 058 2-Heptanone MS; RI 1187 1185 282 2-Octanone MS; RI 1285 1280 580 1-Octen-3-one MS; RI 1300 1299 184 2,3-Octanedione MS 133589 2-Nonanone MS, RI 1394 1394 0

Alcohols (9)17 Ethanol MS; RI 934 932 230 2-Butanol MS; RI 1031 1035 433 1-Propanol MS; RI 1052 1052 047 2-Pentanol MS; RI 1139 1142 355 1-Penten-3-ol MS; RI 1175 1176 164 3-Methyl-1-butanol MS; RI 1221 1215 673 1-Pentanol MS; RI 1262 1256 687 1-Hexanol MS; RI 1362 1354 8

Table 4. Continued ...

Peaka) Compound IDb) RIcalcd RItabc) DRI

97 1-Octen-3-ol MS; RI 1458 1456 2

Esters (8)8 Methyl acetate MS; RI 825 828 3

12 Ethyl acetate MS; RI 899 893 619 Ethyl propanoate MS; RI 960 957 320 Ethyl isobutanoate MS; RI 962 960 232 Ethyl butanoate MS; RI 1040 1040 039 Ethyl isopentanoate MS; RI 1073 1068 545 Isopentyl acetate MS; RI 1127 1125 294 Ethyl octanoate MS; RI 1440 1438 2

Aromatic hydrocarbons (10)32 Toluene MS; RI 1035 1040 544 Ethylbenzene MS; RI 1125 1125 046 p-Xylene MS; RI 1130 1127 354 Not identified MS 117657 o-Xylene MS; RI 1186 1182 466 Not identified MS 123074 Styrene MS; RI 1263 1261 286 Anisole MS 135595 Not identified MS 1456

Sulphur compounds (5)2 Carbon disulphide MS 701

18 Allyl methyl sulphide MS 95624 1-Propene-1-methylthio MS 99738 Dimethyl disulphide MS; RI 1072 1075 350 1-Propene-3,3'-thiobis MS 1150

Linear hydrocarbons (3)1 Heptane MS; RI 700 700 03 Methyl cyclohexane MS 7625 Octane MS; RI 800 800 0

Furans (2)10 2-Methyl THF MS 87667 2-Pentyl furan MS; RI 1239 1240 1

a) Peak number according to retention time in Fig. 2.b) ID: MS = identification by comparison with NIST mass

spectrum, RI = identification by comparison with RIs.c) RItab: identification by comparison with RI homemade

database.

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J. Sep. Sci. 2007, 30, 563 – 572 Gas Chromatography 571

that the availability of a suitable and validated database,in conjunction with the interpretation of the mass spec-trometric data, can represent a useful tool in the field offood analysis in order to obtain a more certain identifica-tion of the analysed compounds.

The authors acknowledge funding support from LaboratorioRegionale per la Sicurezza e la Qualit� degli Alimenti (SIQUAL)(project no. 9, Programma Regionale per la Ricerca industriale,l'Innovazione e il Trasferimento tecnologico (PRRIITT)).

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Table 5. Volatile compounds identified in the crust and in thecrumb of Altamura bread.

IDa) RIcalcd RItabb) DRI

Aldehydes (18)Propanal MS;RI 800 801 12-Methyl-propanal MS;RI 812 814 22-Propenal MS 846Butanal MS;RI 881 878 32-Methylbutanal MS;RI 917 914 33-Methylbutanal MS;RI 921 917 4Pentanal MS;RI 984 977 7Hexanal MS;RI 1089 1080 92-Methyl-2-butenal MS 1100Heptanal MS;RI 1191 1186 5Octanal MS;RI 1292 1286 6trans 2-Heptenal MS;RI 1323 1320 3Nonanal MS;RI 1397 1396 1trans 2-Octenal MS;RI 1438 1432 6Decanal MS;RI 1509 1502 7Benzaldehyde MS;RI 1529 1528 1trans 2-Nonenal MS;RI 1543 1546 3Phenylacetaldehyde MS;RI 1663 1669 6

Furans (17)Furan MS;RI 801 798 32-Methylfuran MS;RI 873 876 32-Ethylfuran MS;RI 950 945 52,3,5-Trimethylfuran MS2-Pentylfuran MS;RI 1243 1240 3Dihydro-2-methyl-3(2H)furanone

MS 1288

Furan-3-carboxaldehyde MS 1448Furfural MS;RI 1478 1474 4Furfuryl methyl sulphide MS 1503Furfuryl formate MS 15152-Acetylfuran MS;RI 1519 1511 8Furfuryl acetate MS 15545-Methyl-2-furaldehyde MS;RI 1591 1589 22,29-Bifuran MS 16142,29-Methylene difuran MS 1628Dihydro-2(3H)-furanone MS 16502-Furanmethanol MS 1678

Ketones and diketones (13)Acetone MS;RI 812 814 22-Butanone MS;RI 908 901 72-Pentanone MS;RI 984 980 42,3-Butandione MS;RI 989 986 32,3-Pentandione MS;RI 1070 1071 13-Penten-2-one MS 11402,3-Hexandione MS;RI 1147 1143 43,4-Hexandione MS;RI 1157 1151 62-Heptanone MS;RI 1189 1185 43-Hydroxy-2-butanone MS;RI 1299 1289 106-Methyl-5-hepten-2-one MS;RI 1345 1340 52-Cyclopenten-1,4-dione MS 1605Acetophenone MS;RI 1664 1660 4

Aromatic hydrocarbons (12)Benzene MS;RI 938 936 2Toluene MS;RI 1035 1040 5Not identified MSEthylbenzene MS;RI 1122 1125 3p-Xylene MS;RI 1125 1127 2m-Xylene MS;RI 1138 1132 6o-Xylene MS;RI 1190 1182 8Not identified MSStyrene MS;RI 1263 1261 2Not identified MS 1378Not identified MS 1428Not identified MS 1624

Alcohols (10)Ethanol MS;RI 937 932 5

Table 5. Continued ...

IDa) RIcalcd RItabb) DRI

1-Propanol MS;RI 1052 1052 02-Butanol MS;RI 1029 1035 62-Methyl-1-propanol MS;RI 1105 1097 821-Butanol MS;RI 1155 1152 33-Methyl-1-butanol MS;RI 1221 1215 61-Pentanol MS;RI 1265 1256 91-Hexanol MS;RI 1360 1354 6Not identified MS 1462Ethyl hexanol MS;RI 1496 1492 4

Pyrazines (10)Pyrazine MS;RI 1207 1209 22-Methyl pyrazine MS;RI 1267 1264 32,5-Dimethylpyrazine MS;RI 1321 1318 32,6-Dimethylpyrazine MS;RI 1328 1325 32-Ethylpyrazine MS;RI 1336 1334 22,3-Dimethylpyrazine MS;RI 1344 1345 12-Ethyl-3-methylpyrazine MS;RI 1397 1402 52-Ethyl-5-methylpyrazine MS;RI 1399 1406 72-Ethyl-6-methylpyrazine MS;RI 1413 1411 22-Ethyl-3,5-dimethylpyrazine MS;RI 1444 1443 1

Terpenes (4)Not identified MS 1133a-Phellandrene MS;RI 1164 1160 4Limonene MS;RI 1192 1194 2Ocimene MS;RI 1239 1237 2

Halogen compounds (4)Chloroform MS;RI 1023 1018 5Tetrachloroethylene MS;RI 1026 1021 5Not identified MS 1257Not identified MS 1361

Pyrroles (3)2-Acetyl-1-pyrroline MS 13301-Methylpyrrole MS 1153Pyrrole MS 1525

Sulphur compounds (2)Dimethyl disulphide MS;RI 1077 1075 2Thiazole MS 1262

Hydrocarbons (2)Octane MS;RI 800 8002-Octene MS;RI 842 846 4

Esters (1)Ethyl acetate MS;RI 896 893 3

a) ID: MS = identification by comparison with NIST massspectrum, RI = identification by comparison with Kov�tsindices.

b) RItab: identification by comparison with KI homemadedatabase.

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572 F. Bianchi et al. J. Sep. Sci. 2007, 30, 563 – 572

5 References

[1] Careri, M., Mangia, A., in: W. M. A. Niessen, Ed., Current Practice ofGas Chromatography-Mass Spectrometry, Marcel Dekker, Inc., NewYork 2001, 409 – 440.

[2] Barbieri, G., Bolzoni, L., Careri, M., Mangia, A., et al., J. Agric. FoodChem. 1994, 42, 1170 – 1176.

[3] Bianchi, F., Careri, M., Musci, M., Food Chem. 2005, 89, 527 – 532.

[4] Radovic, B. S., Careri, M., Mangia, A., Musci, M., et al., Food Chem.2001, 72, 511 – 520.

[5] Milman, B. L., Trends Anal. Chem. 2005, 24, 493 – 508.

[6] Kov�ts, E., Adv. Chromatogr. 1965, 1, 229 – 247.

[7] Van den Dool, H., Kratz, P. D., J. Chromatogr. 1963, 11, 463 – 471.

[8] Gonzales, F. R., Nardillo, A. M., J. Chromatogr. A. 1999, 842, 29 – 49.

[9] International Organization of Flavor Industry (IOFI), Z. Lebensm.Unters. Forsch. 1991, 192, 530 – 534.

[10] Alves, G. L., Franco, M. R. B., J. Chromatogr. A 2003, 985, 297 – 301.

[11] Mallia, S., Fernandez-Garcia, E., Bosset, J. O., Int. Dairy J. 2005, 15,741 – 758.

[12] Shimoda, M., Wu, Y., Osajima, Y., J. Agric. Food Chem. 1996, 44,3913 – 3918.

[13] Mondello, L., Dugo, P., Cotroneo, A., Basile, Dugo, G., Atti II Con-gresso di Chimica degli Alimenti, 24 – 27 May 1995.

[14] Jennings, W., Shibamoto, T., Qualitative Analysis of Flavor Volatilesby GC MS, Academic Press, New York 1980.

[15] Vernin, G., Metzger, J., Suon, K. N., Fraisse, D., et al., Lebensm. Wiss.Technol. 1990, 23, 25 – 33.

[16] Ruther, J., J. Chromatogr. A 2000, 890, 313 – 319.

[17] Streete, P. J., Ruprah, M., Ramsey, J. D., Flanagan, R. J., Analyst,1992, 117, 1111 – 1127.

[18] Miller, K. E., Bruno, T. J., J. Chromatogr. A 2003, 1007, 117 – 125.

[19] Ettre, L. S., Chromatographia 2003, 58, 491 – 494.

[20] Macku, C., Shibamoto, T., Food Chem. 1991, 42, 121 – 127.

[21] Guyot, C., Bouseta, A., Scheirman, V., Collin, S., J. Agric. FoodChem. 1998, 46, 625 – 633.

[22] Belitz, H.-D., Grosch, W., Schieberle, P., Food Chemistry, 3rd edn.,Springer-Verlag, Berlin, Germany 2004.

[23] Bicchi, C., Binello, A., D'Amato, A., Rubiolo, P., J. Chrom. Sci. 1999,37, 288 – 294.

[24] Grob, K., Grob, G., Chromatographia 1983, 17, 481 – 486.

[25] Berard, J., Bianchi, F., Careri, M., Chatel, et al., Food Chem. 2006 (inpress).

[26] Bianchi, F., Cantoni, C., Careri, M., Chiesa, L., et al., Talanta 2007(in press).

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