mass spectrometry method for the analysis of wheat bread volatile compounds

mass spectrometry method for the analysis of wheat bread volatile compounds

Accepted Manuscript Title: Improvement of a headspace solid phase microextraction-gas chromatography/mass spectrometry method for the analysis of whea...

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Accepted Manuscript Title: Improvement of a headspace solid phase microextraction-gas chromatography/mass spectrometry method for the analysis of wheat bread volatile compounds Author: Antonio Raffo Marina Carcea Claudia Castagna Andrea Magr`ı PII: DOI: Reference:

S0021-9673(15)00837-7 http://dx.doi.org/doi:10.1016/j.chroma.2015.06.009 CHROMA 356567

To appear in:

Journal of Chromatography A

Received date: Revised date: Accepted date:

22-1-2015 2-6-2015 5-6-2015

Please cite this article as: A. Raffo, M. Carcea, C. Castagna, A. Magr`i, Improvement of a headspace solid phase microextraction-gas chromatography/mass spectrometry method for the analysis of wheat bread volatile compounds., Journal of Chromatography A (2015), http://dx.doi.org/10.1016/j.chroma.2015.06.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Highlights  A semi-quantitative HS-SPME/GC-MS method for bread volatiles was improved.  39 volatiles were fully identified, while 95 volatiles were tentatively identified.

 Method linearity was verified in matrix-matched extraction solutions.

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 Method precision was improved by using an array of ten internal standards.

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 This method may prove useful when studying aroma formation in bakery products.

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Improvement of a headspace solid phase microextraction-gas chromatography/mass

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Antonio Raffo* a, Marina Carcea a, Claudia Castagna b, Andrea Magrì b

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spectrometry method for the analysis of wheat bread volatile compounds.

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*Corresponding author: Phone: +39 0651494573, Fax: +39 0651494550, e-mail: [email protected]

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University of Rome “Sapienza”, Department of Chemistry, P.le Aldo Moro, 5 -00185- Rome, Italy.

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Council for Agricultural Research and Analysis of Agricultural Economy, Research Centre on Food and Nutrition (CRA-NUT), Via Ardeatina, 546 -00178- Rome, Italy.

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Abstract

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An improved method based on headspace solid phase microextraction combined with gas

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chromatography-mass spectrometry (HS-SPME/GC-MS) was proposed for the semi-quantitative

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determination of wheat bread volatile compounds isolated from both whole slice and crust samples.

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A DVB/CAR/PDMS fibre was used to extract volatiles from the headspace of a bread powdered

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sample dispersed in a sodium chloride (20%) aqueous solution and kept for 60 minutes at 50 °C

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under controlled stirring. Thirty-nine out of all the extracted volatiles were fully identified, whereas

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for 95 other volatiles a tentative identification was proposed, to give a complete as possible profile

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of wheat bread volatile compounds. The use of an array of ten structurally and physicochemically

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similar internal standards allowed to markedly improve method precision with respect to previous

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HS-SPME/GC-MS methods for bread volatiles. Good linearity of the method was verified for a

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selection of volatiles from several chemical groups by calibration with matrix-matched extraction

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solutions. This simple, rapid, precise and sensitive method could represent a valuable tool to obtain

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semi-quantitative information when investigating the influence of technological factors on volatiles

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formation in wheat bread and other bakery products.

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Keywords: SPME, aroma, cereal products, headspace analysis, food analysis, GC-MS

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1. Introduction

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The pleasant smell of fresh wheat bread is one of the most important factors contributing to its

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consumer acceptance. More than 500 wheat bread volatile compounds have been reported in the

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literature, belonging to different chemical classes such as alcohols, aldehydes, ketones, pyrazines

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and other N-heterocycles, acids, furans, esters, sulphides and others [1,2]. They are mainly formed

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during the bread making process, through enzymatic activities and fermentation by yeasts and lactic

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bacteria before baking, and through Maillard and caramelisation reactions during baking [3]. During

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baking different temperatures are reached in the inner and the outer part of the dough and thermal

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induced processes by which volatiles are formed at this stage proceed to a different extent in the

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two parts of the dough. As a result, a markedly different volatile profile is produced in the crumb

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and the crust [3]. While only a couple of dozens of these volatiles have been recognised as key

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players imparting the typical aroma of wheat bread crumb and crust [1,3-5], a larger range of

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volatile compounds may be worth of investigation as potential markers of chemical processes

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occurring during bread making or because they may contribute to the perceived aroma through their

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interactions with the recognised most potent bread odorants.

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Several isolation techniques have been proposed for the analysis of wheat bread volatiles. The most

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effective approach in terms of limits of detection and trueness is that based on solvent extraction

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and high vacuum distillation, combined with stable isotope dilution assay for the GC-MS analysis

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[4,5]. This method, which allows for an exhaustive extraction of volatiles from the food matrix,

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provides quantitative information on their concentration in the bread sample, but it is quite labour

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intensive, complex, high time and solvent consuming. In many studies the headspace of wheat

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bread has been analysed by purge and trap techniques [6-9]: by these more simple methods it is

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possible to obtain information on a relatively complete profile of the bread volatile fraction, but

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differently from the above wet method, this information is only semi-quantitative in nature. The

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other common approach used in the last decade is also a semi-quantitative one and is based on the

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headspace analysis by the solid phase microextraction (HS-SPME) technique, combined, similarly

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to the other approaches, with gas chromatography-mass spectrometry [10-15]. In the same field of

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microextraction techniques, a single application of the headspace sorptive extraction technique has

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also been proposed [16].

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SPME has recently become one of the most widely applied isolation technique in the analysis of

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food volatile compounds by virtue of simple and fast sample preparation, high sensitivity and

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enrichment factor, possibility of automation and minimal or no use of solvent [17,18]. However, in

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the majority of cases, SPME has been used only for qualitative rather than quantitative purposes,

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mainly due to the difficulties in quantification arising from the complex volatile compounds-matrix

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interactions. In addition, only a relatively small number of applications have been developed for

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solid foods [17]. In previous applications of HS-SPME to the analysis of wheat bread volatile

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compounds a rather incomplete profile has been generally detected, neglecting several important

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bread odorants [10, 12-15]. Moreover, only in few cases information on method performance

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characteristics has been reported, and a poor precision in the determination of some important

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odorants has been observed [10-15].

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The aim of this study was to improve previous HS-SPME/GC-MS methods for the analysis of

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wheat bread volatiles by providing a more complete profile of the volatile fraction, by enhancing

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method precision through the use of an array of structurally and physicochemically similar internal

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standards, and by giving a more complete description of method performance characteristics.

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2. Experimental

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2.1. Reagents and materials

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All pure volatile compounds and tested internal standards, their CAS no. and purity, were reported

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in Table 1. Citric acid monohydrate was of >99.0% purity, whereas NaCl was of analytical grade.

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All of these reagents, along with a standard solution of C7-C30 saturated alkanes in hexane for

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retention indices determination, were purchased from Sigma-Aldrich Italy (Milan, Italy). Methanol 6 Page 5 of 35

used for preparation of volatile compounds stock solutions was of HPLC grade (Carlo Erba

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Reagents, Milan, Italy). All volatile pure compounds and internal standards stock solutions were

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prepared by dissolving about 10-100 mg of each component in 10 mL of methanol and stored at -20

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°C.

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The SPME holder for manual sampling and fibres were purchased from Supelco (Sigma-Aldrich

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Italy). Two types of fibres were used: a 50/30 m divinylbenzene/carboxen/poly(dimethylsiloxane)

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(DVB/CAR/PDMS) fibre, and a 85 m carboxen/poly(dimethylsiloxane) (CAR/PDMS) fibre. All

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fibres were conditioned as recommended by the manufacturer before the first use.

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2.2. Bread loaves preparation and sampling

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Samples of bread (2 loaves) were prepared according to the International Association for Cereal

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Science and Technology standard method for test baking of wheat flours, namely ICC method no.

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131 [19]. A dough was made from a commercial wheat flour, water, compressed yeast, salt, sucrose

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and malt flour. Two steps of leavening, of 30 and 75 minutes respectively, were carried out

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followed by baking in a ventilated oven at 220 °C for 30 minutes. Bread loaves were cooled at room

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temperature for 1 hour and then cut in slices. At this point two distinct bread samples were

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prepared: whole slice samples, by collecting whole slices, and crust samples, by cutting crosswise a

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bread slice and collecting 1 cm of its outer part. Then, about 60 g of whole slice sample and 30 g of

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crust sample, were frozen with liquid nitrogen and grounded by a laboratory grinding device (Ika,

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Staufen, Germany) to give a powder that was stored at -70 °C until analyses.

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2.3. Preparation of the internal standards solution

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The mixed internal standards aqueous solution was prepared by mixing the following volumes of

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the stock methanol solutions of each internal standard in a 100 mL volumetric flask, 100 µL of 2,2-

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dimethyl butanal (3.21 mg mL-1), 300 µL of 3,3-dimethyl butanal (2.39 mg mL-1), 300 µL of 2-

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ethyl butanal (0.81 mg mL-1), 100 µL of 2-ethyl-2-butenal (4.35 mg mL-1), 100 µL of 4-methyl-2-

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pentanol (4.04 mg mL-1), 1 mL of diethyl disulphide (0.50 mg mL-1), 100 µL of 3-octen-2-one (0.69

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mg mL-1), 500 µL of 1-(2-furyl)-acetone (2.21 mg mL-1), 1 mL of cis-7-decen-1-al (3.37 mg mL-1),

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50 µL of 5-isobutyl-2,3-dimethyl pyrazine (3.70 mg mL-1), 100 µL p-tolualdehyde (3.06 mg mL-1),

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500 µL of 2-ethyl butyric acid (9.20 mg mL-1), 100 µL of 1-phenyl-2-propanol (4.86 mg mL-1) and

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1 mL of 3-acetyl pyridine (5.51 mg mL-1), and then adding deionized water to a total volume of 100

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mL. All the above concentrations were selected to obtain, in the extraction mixture, levels of the

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internal standards similar to those of the most important associated target analytes.

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2.4. Headspace solid phase microextraction procedure

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A fixed amount (0.25 g) of bread powder, from whole slice or crust samples, was placed in a 15 mL

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vial for SPME and 5 mL of the extraction solution were added. The extraction solution was daily

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prepared by placing 100 L of the mixed internal standards aqueous solution in a glass flask and

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then adding a NaCl 20% aqueous solution (pH adjusted to 3 by a 0.05M aqueous solution of citric

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acid) to a final volume of 50 mL. The vial containing the bread powder, the extraction solution and

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a magnetic stir bar was then capped with a PTFE/silicone septa for HS-SPME and immersed in a

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water bath kept at 50 °C. Then HS-SPME extraction was carried out by exposing the 50/30 m

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DVB/CAR/PDMS fibre to the headspace of the bread powder suspension for 60 minutes, while

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stirring at 700 rpm. In the first stages of the present study extraction tests were also performed in

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the same conditions by using CAR/PDMS fibres. At the end of the extraction time the fibre was

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immediately inserted into the gas chromatograph split-splitless injection port, for the desorption

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step, and the GC run was started. To minimize carry-over effects, before each extraction the SPME

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fibres were conditioned in the GC injection port at 260 °C, under a gas flow of 150 mL min-1, for 15

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minutes.

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2.5. Gas chromatography-mass spectrometry analysis

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GC/MS analyses were performed on an Agilent 6890 GC 5973N MS system equipped with a

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quadrupole mass filter for mass spectrometric detection (Agilent Technologies, Palo Alto, CA).

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Desorption of extracted volatiles from the fibre was carried out within the GC injector, operating by

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the splitless mode, at 260 °C for 5 minutes. GC separation was achieved on a DB-Wax column

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(0.25 mm i.d. × 60 m, 0.5 m film thickness; J&W, Agilent Technologies, Palo Alto, CA) by

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setting the following chromatographic conditions: inlet temperature was 260 °C; oven temperature

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programme from 40 °C (10 min) to 210 °C at 4 °C min-1, and then to 220 °C (5 min) at 30 °C min-1

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(total run time of 57.8 min); constant flow of He carrier gas was 2 mL min-1 corresponding to a

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linear velocity of 36 cm s-1. Chromatographic separations were also performed on a DB1-MS

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column (0.25 mm i.d. × 60 m, 0.25 m film thickness; J&W, Agilent Technologies, Palo Alto, CA)

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to determine linear retention indices also on this phase.

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The MS detector operated in the electronic impact ionisation mode at 70 eV; transfer line, source,

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and quadrupole temperatures were set, respectively, at 220, 230, and 150 °C. Detection was

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performed in the full scan mode, over the mass range 30-200 amu, for identification purposes, and

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in the single ion monitoring (SIM) mode for quantification purposes.

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Identification of bread samples volatiles was accomplished by comparison of linear retention

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indices (LRI) and mass spectra of chromatographic peaks with those obtained by extraction of an

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aqueous solution of pure reference compounds. Linear retention indices were determined by

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analysing, in the same conditions used for bread samples, a standard solution of C7-C30 saturated

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alkanes, and by applying the equation proposed by van den Dool and Kratz [20]. When a pure

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compound was not available tentative identification was based on the comparison of determined

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linear retention indices with those reported in the literature [21] or in the NIST Chemistry

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WebBook database [22], and on the comparison of mass spectra with those reported in the

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NIST/EPA/NIH Mass Spectra Library 2005. As regards linear retention indices from the literature,

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data reported in a single paper were considered [21], because they were obtained by a study

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specifically designed to obtain precise and robust linear retention indices for analysis of volatile

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compounds in foods. When retention indices were not available from this source, they were

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retrieved from the NIST Chemistry WebBook database, selecting data obtained on the same

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chromatographic phase and by the same calculation method, and were reported as a range (min-max

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values in Table 2). Comparison of mass spectra was performed by means of the NIST Mass

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Spectral Search Program and results of the comparison were given as Match Factor. According to

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the NIST Mass Spectral Search Program user’s guide a Match Factor greater than 900 reveals an

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excellent match, between 800 and 900 a good match, between 700 and 800 a fair match, below 600

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a poor match [23].

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2.6. Evaluation of method performance characteristics

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For the semi-quantitative determination of each compound chromatographic signals obtained by the

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SIM mode were used, calculating the ratio of the peak area of the target analyte to the peak area of

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the most appropriate internal standard (Table 3). Measurement precision was evaluated by

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performing five replicate analyses on the same bread powder sample by using five distinct fibres

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from two commercial lots, and repeating this procedure on the same bread powder sample, kept at -

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70 °C, in a later non-consecutive date. Repeatability standard deviation and intermediate precision

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were calculated from the experimental data by using one-way analysis of variance [24] and

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expressed as relative standard deviation. A one-way analysis of variance allowed to separate the

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variation inherent within the method (repeatability) and the variation due to extended timescale

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(intermediate precision). Taking into account the marked differences in the volatile profile of whole

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slice and crust samples repeatability and intermediate precision were determined on both types of

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bread samples.

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Linearity of the method was evaluated on the basis of calibration curves obtained by using matrix-

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matched test samples. To achieve this the HS-SPME analyses were carried out by placing in the

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extraction vial the same fixed amount of a deodorised bread powder sample (see Section 2.5),

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instead of the bread powder sample itself, and by spiking the pure compounds into the extraction

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solution at six concentration levels, to give the corresponding concentration levels in the bread

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reported in Table 4. At each concentration level duplicate analyses were carried out. Any response

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from bread volatiles detected in the deodorised bread powder sample (mean of duplicates) was

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subtracted to produce the calibration plot. To evaluate the linear regression model the following

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statistics were calculated: determination coefficient (r2), residual standard deviation, Fisher’s F of

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the regression along with the associated p-value, F statistic obtained by the lack of fit test along

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with the associated p-value. The assumption of normality of residuals was checked by the Shapiro-

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Wilk test (p-value > 0.05), and homogeneity of variances was of verified by the Breusch-Pagan test

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(p-value > 0.05). All the statistical calculations were computed by a XLStat software package

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(2015.1.03.15473 ver., Addinsoft), except for the lack of fit test, run on SPSS (22.0 ver., IBM).

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When the assumption of homogeneity of variances was not met, a weighted least squares linear

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regression (WLSLR) was computed besides the common unweighted least squares linear regression

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[24-26]. For each least squares linear regression three weighting factors were evaluated (1/x1/2, 1/x,

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1/x2) and related regression parameters (intercept, slope and r2 reported in Table 4) were obtained

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by introducing the respective formulas on a Microsoft Excel worksheet [25]. The best weighting

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factor was chosen on the basis of the percentage relative error (%RE), which compares the

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regressed concentration computed from the regression equation obtained for each weighting factor

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with the nominal standard concentration. The best weighting factor was that which gave rise to the

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narrowest horizontal band of randomly distributed %RE around the concentration axis (plots were

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not reported) and to the least sum of %RE across the whole concentration range (%RE) (Table 4).

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To estimate limits of detection and quantification, experimental measurements were not carried out

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by using matrix-matched test samples, because low levels of target volatile compounds were still

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present in the deodorized bread sample used for the linearity tests above described. As a second-

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best choice, approximate information on method LODs and LOQs were obtained by performing

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measurements on the reagent blank, i.e., the extraction aqueous solution free of the bread matrix.

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Approximate values for LODs and LOQs were determined, respectively, as three and ten times the

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standard deviation of the sample measurement value, obtained by seven replicates, at a

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concentration level not higher than ten times the estimated detection limit, according to the

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procedure specifically recommended for SPME applications [18]. Calculation of LOD as three

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times the standard deviation of replicate measurements, between 6 and 15, of test samples with

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concentration levels close to or above the LOD, is also considered an appropriate procedure to

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obtain approximate LOD values for all analytical methods [24].

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2.7. Preparation of a deodorized bread sample

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A mixture of 10 g of bread powder and 150 mL of methanol was refluxed under stirring for 4 hours

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at 50 °C. After cooling, the solvent was poured off and the residual solvent was removed by using a

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centrifugal vacuum concentrator (Savant SpeedVac, mod. SPD121P, Thermo Fisher Scientific,

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Waltham, MA). Then, the obtained powder was subjected again to the same extraction procedure.

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A similar procedure was also applied by using dichloromethane and diethyl ether, which were the

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solvents selected for the exhaustive extraction of bread volatiles in the above mentioned isolation

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method based on solvent extraction and high vacuum distillation [5]. In this case a more effective

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removal of volatile compounds was obtained with respect to extraction with methanol, but at the

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end of the procedure much higher levels of both solvents were strongly linked to the solid matrix.

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This, in turn, impaired the following HS-SPME extraction of the obtained deodorised bread powder,

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because the high level of both solvents saturated the adsorption capacity of the fibre, severely

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reducing the enrichment factor for all the target volatiles.

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3. Results and discussion

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3.1. Bread sample collection procedure

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In most previous studies on characterisation of wheat bread volatiles samples were formed by

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collecting crumb or crust pieces separately, but not whole slices. The reason why following a

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different approach in the present study lied in the need to sample bread pieces in a repeatable way,

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which is a key requirement for quantitative purposes, but it is not simple in the case of bread crust.

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The outer part of a bread loaf is, in fact, characterised by a strong concentration gradient, from the

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surface toward the central part of the loaf, for all the volatiles whose formation is critically affected

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by temperature, and, as a result, it is quite difficult to cut crust pieces across this gradient in a

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repeatable way. Taking into account the great differences in the volatile profile between crumb and

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crust, when a repeatable procedure for crust sampling is not ensured, it becomes possible that

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differences found in analytical results may arise from biases due to the crust sampling procedure

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rather than representing actual compositional differences between bread samples. So in the present

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study it was preferred to collect i) samples formed by whole slices, mainly formed by crumb, which

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allowed to sample in a repeatable way both the crumb and crust portion of the loaf, and ii) samples

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formed by crust only, to obtain the highest sensitivity also in the analysis of this part of the bread

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loaf. By this approach, differences observed between crust samples could be confirmed looking at

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the corresponding results in the whole slice samples, so ruling out possible biases due to the

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sampling procedure.

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3.2. SPME fibre selection

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In the present study improvement of previous HS-SPME/GC-MS methods for determination of

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wheat bread volatiles took as a starting point results of a method development study carried out by

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Ruiz and Colleagues [15]. That study was targeted to the analysis of bread crumb only, and group

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of volatiles mainly formed in the crust, such as furans and N-heterocycles (pyrazines, pyrrolines,

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pyridines, pyrroles), were not considered. In that study method development involved, in particular,

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selection of the fibre type, extraction temperature and time, addition of a NaCl 20% aqueous

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solution to the bread powder, pH optimisation of this extraction solution and amount of bread

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powder sample [15]. In the present study all of these parameters were adopted as optimised in the

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previous paper, except for the selection of the fibre type. In the study by Ruiz and Colleagues [15]

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the extraction performances of PDMS/DVB, CAR/PDMS and CW/DVB fibres was compared, the

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CAR/PDMS resulting the most effective fibre in extracting the target analytes. However, other HS-

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SPME studies on the isolation of volatiles from wheat grain [27], and cocoa products [28]

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highlighted that the DVB/CAR/PDMS fibre, which had not been tested in the above mentioned

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work, was more effective than the CAR/PDMS fibre. So, in the present study the bread volatiles

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extraction performance of the two fibres CAR/PDMS and DVB/CAR/PDMS were compared and it

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was found that, while the former was generally more effective in extracting the most volatile

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compounds (approximately those with LRI<1000), the latter extracted higher amounts of the

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remaining volatiles, and, in particular, of several important odorants, such as the unsaturated C9 and

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C10 aldehydes, the dimethylethylpyrazines, 1-octen-3-one and 4-hydroxy-2,5-dimethyl-3(2H)-

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furanone (Figure 1S, Appendix A). A similar differential extraction ability associated to different

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chemical groups had been previously observed in comparison tests between the same two fibre

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types used with cocoa products [28].

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Guidelines for SPME application to the analysis of food volatile compounds [29] suggest to use

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fibres coated only with absorbing phases (e.g. PDMS) for quantitative purposes. However,

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published papers on volatile isolation by HS-SPME have shown that extraction by the

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DVB/CAR/PDMS fibre, whose coating is formed by both absorbing (PDMS) and adsorbing (DVB

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and CAR) phases, provides good quality results in quantitative analysis of beverages [30] and semi-

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quantitative analysis of solid foods, such as wheat grain, rice, potato snacks and cocoa products [27-

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28,31-32]. So taking into account the higher extracted amounts of several of the less volatile wheat

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bread odorants, which are generally present at relatively low levels, the DVB/CAR/PDMS fibre was

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selected as the best option.

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3.3. Identification of wheat bread volatiles

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In the GC profile isolated by the DVB/CAR/PDMS fibre 39 volatiles were fully identified by

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comparison with reference pure compounds, whereas 95 other volatiles were tentatively identified

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(Table 2). Regarding aldehydes, besides identifying the important crumb and crust odorants formed

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as peroxidation products of linoleic acid ((E)-2-nonenal, (E,Z)-2,6-nonadienal, (E,E)-2,4-

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decadienal) and the Strecker aldehydes, 2- and 3-methyl butanal and phenylacetaldehyde, the potent

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odorant methional formed through the Strecker degradation of the amino acid methionine was also

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identified, whereas in previous HS-SPME studies on wheat bread volatiles it was not detected.

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Moreover, the linoleic acid peroxidation product tr-4,5-epoxy-(E)-2-decenal, which was not

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previously reported in HS-SPME analyses on bread, was tentatively identified with a good match of

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both LRI (LRI ≤ 10, according to the criterion proposed by D’Acampora Zellner and Colleagues

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[20]) and mass spectrum (Match Factor > 800). It is generally present at low level in the crumb but

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due to its very low odour threshold it has been recognized as one of the most important odorant of

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wheat bread crumb [4], also contributing to crust aroma [5]. On the contrary, (Z)-2-nonenal and (Z)-

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4-heptenal, also reported as crumb odorants [1], were not detected in any samples. In the group of

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ketones, besides identification of the crumb and crust aroma compounds 2,3-butanedione and 1-

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octen-3-one, it was worth mentioning the tentative identification of 1-hydroxy-2-propanone, not

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reported in previous HS-SPME analyses on bread. The interest in this compound, which is formed

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through the Strecker degradation of amino acids, came from its being, along with 1-pyrroline, a

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direct precursor in the formation of 2-acetyl-1,4,5,6-tetrahydropyridine [33], a potent odorant of

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bread crust [4]. (E,E)-3,5-Octadien-2-one, previously reported in HS-SPME bread analyses [11],

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was also tentatively identified, but its isomer (Z)-1,5-octadien-3-one, reported as a potent crust

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odorant in some wheat bread samples [1], was not detected.

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A more detailed picture of the groups of N-heterocyclic compounds formed through the Maillard

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reaction with respect to previous HS-SPME studies on bread volatiles was given by the full

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identification of four pyrroles (1-methylpyrrole, 2-acetyl-1-methylpyrrole, 1 furfurylpyrrole, 2-

291

acetylpyrrole), 2-acetylpyridine and three pyrazines (2,5-dimethyl pyrazine, and the two aroma

292

compounds, 3-ethyl-2,5-dimethyl pyrazine and 2-ethyl-3,5-dimethyl pyrazine) and the tentative

293

identification of the crust odorants 2-acetyl-1-pyrroline and 2-acetyl-1,4,5,6-tetrahydropyridine,

294

generally present at low level (g/kg), strongly associated to the matrix and previously not

295

identified in the volatile fraction isolated from bread by HS-SPME. Of particular interest was the

296

possibility to determine 2-acetylpyridine and 2-acetylpyrrole, which are, respectively, oxidation

297

products of 2-acetyl-1,4,5,6-tetrahydropyridine and 2-acetyl-1-pyrroline [34]. 2-Acetylpyridine is

298

also important from the sensory point of view, being characterized, like its precursor, by a popcorn

299

like aroma note but with an approximately ten-fold reduction of odour intensity. In addition, ten

300

other N-heterocyclic compounds were tentatively identified with a good match of LRI and mass

301

spectra. Volatiles belonging to these chemical groups are responsible for the roasty, popcorn like

302

notes of crust aroma, which are highly attractive to the consumer. It was worth noting that in all

303

studies using purge and trap techniques, practically no compounds from the important groups of

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pyrroles, pyridines, pyrrolines had been reported [6-9], with the exception of 2-acetyl-1-pyrroline,

305

which had been identified in one paper where, on the other hand, the reported LRI was not in

306

agreement with values reported in the literature [6].

307

Similarly, the group of furans was characterized in a more detailed way than in previous papers,

308

with four identified compounds (2-pentyl furan, 2-furfural, 2-acetyl furan, 5-methyl-2-furfural) and

309

ten compounds tentatively identified with a good match of LRI and mass spectra. Even though these

310

compounds have a less marked impact on odour perception than the N-heterocycles, they are also

311

formed through the complex processes of the Maillard reaction and are potential informative

312

markers of heat induced chemical changes occurring during baking.

313

The groups of alcohols, esters, carboxylic acids, sulphides and nitrogen compounds completed the

314

list of identified compounds in the isolate obtained by the HS-SPME optimised procedure.

315

3.4. Improvement and evaluation of method precision

316

Even though the most accurate method of quantification of bread volatiles involves the use of

317

isotopically labelled standards [5], these are commercially available only for a small number of

318

compounds, are expensive and sometimes unstable, whereas their in-house preparation is, generally,

319

labour intensive and complex [18]. In previous studies on bread volatiles by HS-SPME semi-

320

quantitative information was obtained by internal calibration with one [11,12,14], two [15] or no

321

internal standards [10,13]. However, the volatile fraction of bread includes quite different chemical

322

groups and one or two internal standards are likely poorly able to mimic the extraction and

323

chromatographic behaviour of compounds from all these structurally heterogeneous chemical

324

groups. Moreover, differences in the extraction behaviour between chemical groups may be

325

amplified by the high physicochemical heterogeneity of the extraction system involved in the HS-

326

SPME of bread volatiles, thus further impairing method precision. So, in the present study, the use

327

of an array of structurally and physicochemically similar internal standards was proposed as a way

328

to improve method precision. For the initial selection of candidate internal standards, on the basis of

329

results from previous studies on bread odorants characterization [1,3-5], the following target

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16 Page 15 of 35

chemical groups including the most important bread odorants were identified, with the intention to

331

find at least one appropriate internal standard for each of them: C5 aldehydes (2- and 3-methyl

332

butanal), C6-C7 aldehydes (hexanal), C9 and C10 unsaturated aldehydes ((E)-2-nonenal,

333

nonadienals, decadienals, tr-4,5-epoxy-(E)-2-decenal), aromatic aldehydes (phenylacetaldehyde),

334

low molecular weight diketones (2,3-butanedione), ketones (1-octen-3-one), fusel alcohols (2- and

335

3-methylbutanol), aromatic alcohols (2-phenyl-1-ethanol), furans (2-acetyl furan), furanones

336

(furaneol), pyrazines (ethyl-dimethylpyrazines), pyrroline/pyridines (2-acetyl-1-pyrroline, 2-acetyl-

337

1,4,5,6-tetrahydropyridine), sulphides (dimethyltrisulphide), carboxylic acids (acetic and 2-/3-

338

methyl butanoic acid) and the single mercapto-aldehyde methional. For each of these groups

339

candidate internal standards were searched among commercially available pure compounds, taking

340

into account basic requirements for internal standards, such as absence in the food matrix of the

341

selected compound and of other compounds having ions in common with it in the area of its elution.

342

Specific criteria considered for the selection of internal standards were similarity to the target

343

analytes in chemical structure, as well as in physicochemical properties, such as octanol-water

344

partition coefficient and boiling point, and in chromatographic properties, such as retention time.

345

The following list of candidate internal standards came out of the initial selection: 2,2-dimethyl

346

butanal and 3,3-dimethyl butanal for the C5 aldehydes, 2-ethyl butanal and 2-ethyl-2-butenal for the

347

C6-C7 aldehydes, cis-7-decen-1-al for the C9 and C10 unsaturated aldehydes, p-tolualdehyde for

348

the aromatic aldehydes, 3-octen-2-one for the group of ketones, 4-methyl-2-pentanol for the fusel

349

alcohols, 1-phenyl-2-propanol for the aromatic alcohols, 1-(2-furyl)-acetone for the group of furans,

350

5-isobutyl-2,3-dimethyl pyrazine for the pyrazines, 3-acetyl pyridine for the pyrroline/pyridines,

351

diethyl disulphide for the sulphides and 2-ethylbutyric acid for the carboxylic acids. No specific

352

candidate internal standards were found for low molecular weight diketones, furanones and

353

methional. Two of the selected candidates, 4-methyl-2-pentanol and 2-ethylbutyric, had been

354

previously proposed for internal calibration in the study by Ruiz and Colleagues [15]. Then for each

355

target analyte, the internal standard among the considered candidates that gave place to the best

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17 Page 16 of 35

repeatability standard deviation and intermediate precision was selected as the most appropriate

357

internal standard (Table 3).

358

Results reported in Table 3 on a selection of the most important volatiles from all chemical groups

359

showed that in most cases good repeatability and intermediate precision (RSD<10%) were obtained.

360

Generally, internal standards firstly selected for specific target groups of analytes were found as the

361

most appropriate for their determination, with the exception of 2,2-dimethyl butanal and 3,3-

362

dimethyl butanal that proved not to be the best option for the Strecker aldehydes 2- and 3-methyl

363

butanal, for which calibration with 4-methyl-2-pentanol gave lower RSDs. In some cases it was LRI

364

closeness in the GC chromatogram rather than the presence of similar structural features to dictate

365

which was the most appropriate internal standard (1-methylpyrrole, 2-pentylfuran, 2-acetyl-1-

366

pyrroline, 1-hexanol, 2-furfural). Relatively high RSDs were observed for some analytes for which

367

a poor enrichment factor was provided by the fibre, such as 2-acetyl-1-pyrroline, which was

368

detected only in the crust samples, (E,Z)-2,6-nonadienal, particularly in the crumb, and 4-hydroxy-

369

2,5-dimethyl-3(2H)-furanone. 2-Acetyl-1-pyrroline and 4-hydroxy-2,5-dimethyl-3(2H)-furanone, in

370

particular, are known to be poorly released, at equilibrium and at room temperature, to the

371

headspace of bread and rice samples [11,31]. This is the reason why, besides being poorly extracted

372

by headspace isolation techniques, their impact as odorants is less important when evaluated by

373

means of gas chromatographic/olfactometric analysis of bread headspace rather than estimated as

374

odour active values on the basis of odour thresholds and concentration data determined after their

375

exhaustive solvent extraction from bread samples [5]. The only group of analytes for which the use

376

of the proposed array of internal standards seemed not to be suitable to provide an acceptable

377

precision is that of sulphides.

378

In Table 3 along with the RSD obtained by the most appropriate internal standard selected in the

379

present paper, the RSD obtained by using only the two previously proposed internal standards [15]

380

was also reported in parentheses, to evaluate the improvement in precision for each target

381

compound accomplished by the use of the array of internal standards: in most cases a marked

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18 Page 17 of 35

reduction of the RSD was observed. A definite reduction of RSD was also found when comparing

383

RSD values obtained in the present study with those reported in the previous paper by Ruiz and

384

Colleagues [15] for some target analytes: from 15.0% (average RSD in the previous paper, obtained

385

on bread crumb samples) to 7.2% (RSD determined on whole slice samples in the present study) for

386

(E)-2-nonenal, from 19.2% to 7.9% for hexanal, from 15.5% to 12.9% for (E,E)-2,4 decadienal,

387

from 12.5% to 4.2% for 2,3-butanedione, from 17.2% to 1.6% for 2-phenyl-1-ethanol, from 16.2%

388

to 5.1% for 2-furfural. On the contrary, similar repeatability between the two studies was observed

389

for some other target analytes, such as 3-methyl-1-butanol and carboxylic acids, which were

390

quantified in both studies by using the same two internal standards. It has to be stressed here that

391

the RSDs determined in the present study could be further significantly reduced by using a single

392

fibre, instead of a set of five distinct fibres, in the repeatability test and in the analytical procedure.

393

The use of a single fibre in the analytical procedure requires the availability of a second GC

394

injection port, inside which conditioning the fibre after the completion of the desorption step and

395

prior to the following sample replicate extraction. A conditioning step before each extraction is

396

indeed needed to prevent carry over effects and passive extraction of interfering analytes from room

397

air.

398

3.5. Evaluation of method linearity

399

The only previous evaluation of linearity of a HS-SPME method for bread volatiles determination

400

was given by Ruiz and Colleagues [15], who used standard aqueous solutions for calibration. To

401

provide a more realistic evaluation of linearity in the present study calibration was performed on

402

matrix-matched extraction solutions prepared by using a bread sample that had been previously

403

deodorized as described in Section 2.5. Statistics for the linear regression model obtained over the

404

examined working range for a selection of bread volatile compounds were reported in Table 4.

405

Concentration working ranges were not very large but, generally, covered the actual concentrations

406

observed in bread samples tested in this study. Residual standard deviations, tests of regression

407

significance and lack-of-fit tests showed that in most cases the obtained linear regression model was

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19 Page 18 of 35

appropriate to describe the experimental calibration curve. An exception was represented by 2,3-

409

butanedione, which showed good linearity only in aqueous but not in matrix-matched solutions. For

410

some target analytes the assumption of homogeneity of variances was not met, due to increasing

411

variances with increasing compound concentration. In these cases, to counteract possible

412

impairment of accuracy at the lower end of the working range and to improve the goodness of fit of

413

the regression model, weighted least squares linear regressions were computed and compared with

414

the unweighted linear regressions [25,26] (Table 4). In that way for some target analytes (3-methyl

415

butanal, 2,3-butanedione, -nonalactone, p-vinyl guaiacol, 2-acetyl pyridine, 2-acetyl-1-methyl

416

pyrrole and 1-furfuryl pyrrole) a significant improvement of the quality of the regression was

417

obtained (Table 4).

418

3.6. Other information on method performance characteristics

419

Approximate values for limits of detection and quantitation, determined by using reagent blanks and

420

not matrix-matched test samples, ranged from 0.06 g/kg for ethyl acetate, to 73 g/kg for 2,3-

421

butanedione, and from 0.18 g/kg to 243 g/kg, respectively (Table 5). LODs were generally in the

422

same order of magnitude or lower (2-methyl-1-butanol, 2-phenyl-1-ethanol) than those previously

423

determined by a different method [15]. Approximate values for LOQ higher than levels found in the

424

analysed samples were observed for (E,Z)-2,6-nonadienal (higher than levels in both whole slice

425

and crust) and methional (higher than whole slice level).

426

In the previous paper by Ruiz and Colleagues [15] also trueness was evaluated by determining

427

recovery percentages in bread samples spiked with known amounts of a standard mixture of target

428

compounds. However, it is questionable whether this procedure could be considered appropriate for

429

the evaluation of trueness in this case, in which analytes migrates from a solid matrix to an aqueous

430

solution, then to the headspace and, finally to the fibre. In the HS-SPME conditions of this study,

431

the first extraction step, in particular, from the bread matrix to the aqueous solution was controlled

432

by partition of analytes between the two phases and was not exhaustive. So, the addition of spikes

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20 Page 19 of 35

of target compounds to the extraction solution could, in principle, bring back to some unknown

434

extent the partition equilibrium of compounds between the matrix and the aqueous solution, with

435

respect to non spiked samples, thus altering the extraction conditions and making this procedure

436

unsuitable for trueness evaluation. So, in the present study, no evaluation of method trueness was

437

performed.

438

Finally, levels of the target analytes in the extraction solutions determined as the ratio of their peak

439

area to the internal standard peak area were also expressed as equivalent concentration in the bread

440

matrix, and results were reported in Table 5 for crust and whole slice samples. It has to be stressed

441

that these values represented results of measurement of relative, not absolute, concentration. In any

442

case, for most of the considered compounds the levels obtained by this semi-quantitative approach

443

were in the same order of magnitude of actual concentration levels determined in bread samples

444

through the accurate solvent extraction-vacuum distillation method [4,5,35].

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4. Conclusions

447

The improved HS-SPME/GC-MS method for the semi-quantitative determination of wheat bread

448

volatiles proposed in this paper was much more simple than the laborious, complex and high time

449

and solvent consuming quantitative method based on solvent extraction and high vacuum

450

distillation [5]. Similarly to the purge and trap methods proposed for bread volatiles it gave only a

451

semi-quantitative information on the levels of volatiles isolated from the sample headspace, and

452

with a comparable precision [6], but with respect to developed purge and trap methods it provided a

453

more complete volatile profile [6-9], while not requiring specific instrumental devices coupled to

454

the GC apparatus. While in most previous semi-quantitative studies on volatile profiling by HS-

455

SPME internal calibration with only one, two or no internal standards was carried out, in this work

456

a different approach, based on the use of an array of ten structurally and physicochemically similar

457

internal standards, was proposed for a multy-analyte HS-SPME/GC-MS analysis, allowing for a

458

markedly improved method precision with respect to previously developed HS-SPME methods.

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21 Page 20 of 35

Hence it could represent a valuable trade-off option between the use of isotopically-labelled analyte

460

standards and the simple calibration procedure by one or two internal standards, when there is no

461

need to obtain information on the absolute concentrations of volatiles and knowledge of relative

462

concentrations is appropriate to the aim of the study. In addition, a procedure to prepare deodorized

463

bread samples to be used for calibration of bread volatile compounds in matrix-matched extraction

464

solution, rather than in simple reagent blank, was proposed, to provide a more realistic evaluation of

465

method performances. Finally, improvement of the extraction conditions and a thorough analysis of

466

chromatograms allowed to identify many important bread odorants that were neglected in previous

467

HS-SPME applications on bread volatiles.

468

To summarize this simple, rapid and solvent-less method provided precise semi-quantitative

469

information on the levels of most of volatiles present in the wheat bread headspace and so it could

470

represent a useful tool in investigations on the effects of technological factors on volatile formation

471

in wheat bread as well as other bakery products [2]. Moreover, the novelty of the present paper lied

472

also in the proposal of the multi-internal standard approach to improve performances of HS-SPME

473

methods for multi-analyte volatile profiling of both liquid and solid foods, which could be applied

474

to other food matrices, thus extending the range of applications of this technique.

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Acknowledgement

477

This work was done within the frame of the EUSAL Project, financed by the Italian Ministry of

478

Agricultural, Food and Forestry Policies. Thanks are due to Mr. L. Bartoli for technical help in

479

bread making and to Dr. M. Vassallo for support in statistical analyses.

480

Appendix A. Supplementary data

481

Comparative chromatograms obtained by using the DVB/CAR/PDMS or the CAR/PDMS fibre for

482

HS-SPME extraction, on the same bread powder sample and by the same experimental conditions,

483

are reported in Figure 1S, which can be found in the online version of this paper.

22 Page 21 of 35

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[36] M. Rychlik, W. Grosch, Identification and Quantification of Potent Odorants Formed by Toasting of Wheat Bread, LWT-Food Sci. Technol. 29 (1996) 515–525. [37] P. Schieberle, W. Grosch, Evaluation of the flour of wheat and rye bread crusts by aroma extract dilution analysis, Z. Lebensm. Unters. Forsch. 185 (1987) 111-113.

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Table 5. Approximate values for LOD and LOQ, determined on reagent blanks and not on matrix-matched test samples, for a selection of identified wheat bread volatile compounds. Results of semi-quantitative determination of volatile compounds in bread crust and whole slice, expressed as equivalent concentration in bread (g/kg). equivalent concentration in bread (g/kg)a crust

ip t

compound name

LOQ (g/kg)

LOD (g/kg)

whole slice

(3.12± 0.34) × 102 (2.27 ± 0.26) × 102 (5.62 ± 0.37) × 102 3.15 ± 0.25 (1.60 ± 0.13) × 101 (0.69 ± 0.05) × 102 2.91 ± 0.54 (12.48 ± 0.40) × 101 (6.80 ± 0.88) × 101

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us

cr

Aldehydes 2-methyl butanal 0.022 × 102 0.075 × 102 (9.22 ± 0.73) × 102 2 2 3-methyl butanal 0.027 × 10 0.090 × 10 (5.99 ± 0.38) × 102 2 2 hexanal 0.13 × 10 0.42 × 10 (8.75 ± 0.75) × 102 (E)-2-hexenal 0.47 1.58 7.16 ± 0.52 methional 0.50 × 101 1.68 × 101 (2.78 ± 0.25) × 101 (E)-2-nonenal 0.006 × 102 0.020 × 102 (1.72 ± 0.16) × 102 (E,Z)-2,6-nonadienal 2.14 7.13 5.90 ± 0.42 0.33 × 101 (14.69 ± 0.69) × 101 phenylacetaldehyde 0.10 × 101 (E,E)-2,4-decadienal 0.05 × 101 0.16 × 101 (6.29 ± 0.73) × 101 Ketones 2,3-butanedione 0.73 × 102 2.43 × 102 (14.23 ± 0.71) × 102 1 1 1-octen-3-one 0.02 × 10 0.07 × 10 (2.64 ± 0.13) × 101 Esters ethyl acetate 0.06 0.18 10.61 ± 0.89 0.13 × 102 (1.47 ± 0.12) × 102 0.04 × 102 -nonalactone Alcohols 2-methyl-1-butanol 0.006 × 103 0.021 × 103 (2.06 ± 0.12) × 103 b 1 1 1-hexanol 0.07 × 10 0.23 × 10 (3.40 ± 0.33) × 101 1-octen-3-ol 0.16 0.53 20.35 ± 0.73 2-phenyl-1-ethanol 0.11 × 102 0.36 × 102 (19.87 ± 0.20) × 102 p-vinyl guaiacol 0.10 × 102 0.32 × 102 (5.27 ± 0.70) × 102 Furans 2-furfural 0.008 × 103 0.026 × 103 (12.18 ± 0.69) × 103 2 2 2-acetyl furan 0.009 × 10 0.03 × 10 (8.44 ± 0.66) × 102 2 2 5-methyl-2-furfural 0.07 × 10 0.23 × 10 (11.64 ± 0.94) × 102 Pyrazines 2,5-dimethyl pyrazine 0.06 × 101 0.20 × 101 (19.07 ± 0.17) × 101 1 1 3-ethyl-2,5-dimethyl pyrazine 0.03 × 10 0.10 × 10 (1.99 ± 0.16) × 101 1 1 2-ethyl-3,5-dimethyl pyrazine 0.02 × 10 0.08 × 10 (1.98 ± 0.16) × 101 Pyrroles, Pyridines 1-methyl pyrrole 0.03 × 101 0.10 × 101 (2.75 ± 0.32) × 101 1 1 2-acetyl pyridine 0.13 × 10 0.42 × 10 (6.42 ± 0.49) × 101 1 1 2-acetyl-1-methyl pyrrole 0.04 × 10 0.14 × 10 (1.99 ± 0.18) × 101 1 1 1-furfuryl pyrrole 0.02 × 10 0.08 × 10 (7.18 ± 0.78) × 101 2 2 2-acetyl pyrrole 0.04 × 10 0.13 × 10 (9.36 ± 0.78) × 102 a Mean value from three replicate determinations and 95% confidence interval. b Sum of 2 and 3-methyl-1-butanol..

(70.33 ± 0.48) × 102 (1.13 ± 0.12) × 101 5.34 ± 0.74 (1.13 ± 0.02) × 102 (5.91 ± 0.31) × 103 b (6.75 ± 0.60) × 101 23.44 ± 0.82 (23.49 ± 0.38) × 102 (2.66 ± 0.29) × 102 (3.07 ± 0.16) × 103 (2.56 ± 0.15) × 102 (3.34 ± 0.22) × 102 (5.33 ± 0.36) × 101 (0.79 ± 0.04) × 101 (0.66 ± 0.04) × 101 (0.40 ± 0.05) × 101 (1.66 ± 0.10) × 101 (0.44 ± 0.03) × 101 (2.04 ± 0.16) × 101 (2.57 ± 0.12) × 102

Page 25 of 35

ip t cr

us

Table 4. Working range (g/kg), equation and statistics of the linear regression model (determination coefficient (r2), residual standard deviation, regression F and p values, lack of fit test F and p values), p values from tests for normality of residuals and homogeneity of variances, for a selection of identified wheat bread volatile compounds. Regression parameters obtained by a weighted least squares linear regression (WLSLR) for those compounds for which the homoscedasticity assumption was not met.

compound name

linear range (g/kg)

yx +

Aldehydes 0.001001

3-methyl butanal

(0.5-10.6) × 102

3-methyl butanal hexanal (E)-2-hexenal (E)-2-hexenal methional

(0.5-10.6) × 102 (4.0-17.1) × 102 2.1-18.7 2.1-18.7 (0.3-8.5) × 101

0.001290 0.00381 0.00375d 0.000575

0.000 - 0.0001 0.0004d 0.0000

(E)-2-nonenal (E,Z)-2,6-nonadienal phenylacetaldehyde (E,E)-2,4-decadienal Ketones 2,3-butanedione

(10.2-43.4) × 101 15.1-32.0 (1.6-41.9) × 101 (1.1-9.7) × 101

0.001038 0.002341 0.003249 0.001656

0.000 0.0016 0.000 0.0006

(0.6-12.6) × 102 f (0.6-12.6) × 102 f

0.000698f 0.000673df

0.050f 0.043df

0.000 - 0.003d

ce pt

Ac

2,3-butanedione 1-octen-3-one 1-octen-3-one Esters ethyl acetate ethyl acetate

0.000637 0.000641d

residual standard deviation

linear regression model

F

- 0.012

ed

(1.2-13.8) × 102

r2

a

a(kg/g)

2-methyl butanal

M an

linear regression equation

0.995 0.982 0.994d 0.977 0.988 0.993d

0.036 0.032

1638 549

lack of fit test

norm. of residuals (p–value Shapiro Wilk test)b

homog. of variances (p-value BreuschPagan test)c

p–value

F

p–value

<0.0001

3.919

0.067

0.642

0.668

<0.0001

0.603

0.675

0.288

0.009

WLSLR with weighting factor 1/x1/2 (%RE 79 vs 92 for the unweighted regression)e <0.0001 0.256 0.896 0.091 0.234 0.095 426 <0.0001 0.224 0.915 0.492 0.022 0.003 810 WLSLR with weighting factor 1/x2 (%RE 69 vs 70 for the unweighted regression)e 0.700 0.369 0.680 0.002 855 <0.0001 0.497

0.991 0.978 0.991 0.998 0.982

0.019 0.001 0.022 0.008

448 926 4627 325

<0.0001 <0.0001 <0.0001 <0.0001

1.191 1.142 2.942 5.423

0.403 0.417 0.115 0.073

0.627 0.015 0.129 0.489

0.110 0.146 0.196 0.342

0.977f

0.047

674

<0.0001

0.784

0.557

0.794

0.032

4.5-33.9 4.5-33.9

0.02092 0.02094d

0.00000 - 0.00046

0.993df 0.948 0.978d

1.1-36.5 1.1-36.5

0.0365 0.0367d

- 0.0000 - 0.0037d

0.953 0.987d

WLSLR with weighting factor 1/x2 (%RE 83 vs 136 for the unweighted regression)e <0.0001 0.447 0.772 0.801 0.011 0.053 181 1/2 WLSLR with weighting factor 1/x (%RE 150 vs 150 for the unweighted regression)e <0.0001 0.106 0.976 0.245 0.003 0.105 203 1/2 WLSLR with weighting factor 1/x (%RE 109 vs 112 for the unweighted regression)e

Page 26 of 35

ip t -nonalactone

0.0003

0.900 0.00248

0.0036

0.111

0.00288d

- 0.0476d

0.973d

(4.8-35.4) × 101

0.221

0.811

0.716

0.009

54.2

WLSLR with weighting factor 1/x2 (%RE 78 vs 139 for the unweighted regression)e

us

-nonalactone Alcohols

cr

(4.8-35.4) × 101

<0.0001 0.394 0.972 1.998 0.233 0.039 4337 <0.0001 4.473 0.095 0.150 0.665 0.318 664 <0.0001 0.429 0.728 0.210 0.015 0.108 444 WLSLR with weighting factor 1/x2 (%RE 28 vs 28 for the unweighted regression)e <0.0001 0.441 0.462 4.356 0.073 0.074 4398 <0.0001 0.092 0.914 0.891 0.036 0.039 161 1/2 WLSLR with weighting factor 1/x (%RE 114 vs 125 for the unweighted regression)e

(1.9-86.3) × 102 (2.9-37.1) × 101 25.0-57.0 25.0-57.0

0.000347 0.02279 0.06001 0.06020d

0.114 0.000 0.0000 - 0.0073d

0.998 0.991 0.978 0.993d

2-phenyl-1-ethanol p-vinyl guaiacol p-vinyl guaiacol Furans

(10.9-51.1) × 102 (0.5-9.2) × 102 (0.5-9.2) × 102

0.001111 0.000494 0.000492d

0.128 - 0.0190 - 0.0170d

0.998 0.964 0.987d

<0.0001

3.705

0.096

0.491

0.437

2-furfural 2-acetyl furan 5-methyl-2-furfural Pyrazines 2,5-dimethyl pyrazine 3-ethyl-2,5-dimethyl pyrazine 2-ethyl-3,5-dimethyl pyrazine Pyrroles, Pyridines

(4.8-20.0) × 103 (0.6-14.4) × 102 (0.9-22.6) × 102

0.000986 0.002870 0.001922

0.81 0.000 0.000

0.996 0.995 0.999

0.338 0.098 0.057

1802 2202 7146

<0.0001 <0.0001

1.363 2.329

0.349 0.170

0.960 0.153

0.125 0.572

(2.6-49.2) × 101 3.7-80.2 3.6-77.6

0.001274 0.00434 0.004370

0.000 0.0000 0.0000

0.986 0.993 0.995

0.028 0.011 0.008

581 1338 2129

<0.0001 <0.0001 <0.0001

0.928 2.657 2.606

0.492 0.137 0.142

0.730 0.850 0.963

0.062 0.128 0.176

ce pt

ed

M an

2-methyl-1-butanol 1-hexanol 1-octen-3-ol 1-octen-3-ol

Ac

<0.0001 0.252 0.182 1.335 0.360 1-methyl pyrrole 6.8-30.8 0.00620 0.0057 0.998 0.003 3176 <0.0001 0.434 0.780 0.520 0.023 2-acetyl pyridine (0.5-25.9) × 101 0.00563 - 0.0204 0.991 0.049 1135 2-acetyl pyridine (0.5-25.9) × 101 0.00543d - 0.0030d 0.998d WLSLR with weighting factor 1/x2 (%RE 61 vs 160 for the unweighted regression)e <0.0001 0.200 0.930 0.875 0.018 2-acetyl-1-methyl pyrrole 0.8-41.6 0.02598 - 0.0017 0.993 0.033 1361 2-acetyl-1-methyl pyrrole 0.8-41.6 0.02572d - 0.0006d 0.998d WLSLR with weighting factor 1/x2 (%RE 58 vs 74 for the unweighted regression)e <0.0001 0.190 0.899 0.192 0.014 1-furfuryl pyrrole (0.2-10.8) × 101 0.0577 - 0.078 0.972 0.427 274 1-furfuryl pyrrole (0.2-10.8) × 101 0.0557d - 0.014d 0.994d WLSLR with weighting factor 1/x2 (%RE 73 vs 158 for the unweighted regression)e <0.0001 1.197 0.401 0.903 0.215 2-acetyl pyrrole (0.4-19.4) × 102 0.001191 0.000 0.999 0.029 8109 a Parameters of the regression  and  were reported with a number of significant figures as determined by writing their standard deviations with two significant figures. b Residuals are normally distributed according to the Shapiro-Wilk test for p-values higher than 0.05 (at a significance level of 0.05). c Homogeneity of variances is met according to the Breusch-Pagan test for p-values higher than 0.05 (at a significance level of 0.05). d Regression parameters obtained by a weighted least squares linear regression (WLSLR) with the reported weighting factor [25]. e %RE is the sum of the relative errors calculated for the WLSLR. It is compared (vs) to the %RE calculated for the unweighted least squares linear regression [25]. f Determined in aqueous extraction solution and not in matrix-matched extraction solution.

Page 27 of 35

Table 3. Repeatability and intermediate precision (RSD%) of the method for a selection of volatiles from all chemical groups as determined on wheat bread whole slice and crust samples. For each target analyte, the most appropriate internal standard, quantifier and qualifier ionic fragments are also reported. int. std.a

SIM ionic fragments (m/z)

method precision crust

whole slice

quant.

qual.

repeat.

interm. prec.

2

72

43

7.5

8.1

2

57

58; 41

8.0

8.1

2 1 1 4 8 6 6 8 6 6 6 6

58 56 55 104 106 70 70 91 81 81 81 68

57; 71 72 69 48 105 83 69 120 67 67 67 55

6.3 8.6 (22.4)b 7.3 (19.7) 8.9 (22.9) 8.4 (19.3) 9.1 (40.6) 7.1 (37.4) 4.7 (29.5) 5.9 (37.8) 12.4 (50.0) 11.6 (48.0) 7.0 (41.5)

2 4 2

43 70 43

86; 42 55 74

11.2

interm. prec.

11.2 11.1

9.7 8.9 (22.4) 10.4 (19.7) 8.9 (22.9) 8.6 (19.7) 10.3 (40.6) 11.2 (37.4) 4.7 (29.5) 12.3 (37.8) 16.8 (50.0) 17.0 (48.0) 14.0 (41.5)

11.5 6.6 (18.5) 7.9 (15.2) 7.9 (22.1) 8.6 (15.9) 7.2 (35.0) 18.6 (31.9) 3.2 (25.0) 7.9 (31.9) 11.1 (39.8) 12.9 (39.9) 14.5 (32.7)

11.5 7.8 (18.5) 7.9 (15.2) 7.9 (22.1) 8.6 (15.9) 11.1 (35.0) 21.6 (31.9) 3.8 (25.0) 9.5 (31.9) 11.1 (39.8) 12.9 (39.9) 14.5 (32.7)

5.5 5.1 (23.5) 9.2

6.7 5.4 (23.5) 10.0

4.2 10.2 (26.6) 8.4

4.2 10.2 (27.6) 9.1

an

us

11.1

M

d

Ac ce p

3-methyl butanal hexanal (E)-2-hexenal methional benzaldehyde (E)-2-nonenal (E,Z)-2,6-nonadienal phenylacetaldehyde (E,E)-2,4-nonadienal (E,Z)-2,4-decadienal (E,E)-2,4-decadienal tr-4,5-epoxy-(E)-2-decenal Ketones 2,3-butanedione 1-octen-3-one 1-hydroxy-2-propanone Esters ethyl acetate ethyl octanoate -nonalactone Alcohols 2- and 3-methyl-1-butanol 1-hexanol 1-octen-3-ol 2-phenyl-1-ethanol p-vinyl guaiacol Furans 2-pentyl furan 2-furfural 2-acetyl furan 5-methyl-2-furfural 4-hydroxy-2,5-dimethyl3(2H)-furanone (furaneol) Pyrazines 2,5-dimethyl pyrazine 2,3-dimethyl pyrazine 3-ethyl-2,5-dimethyl

te

2-methyl propanal 2-methyl butanal

repeat.

cr

Aldehydes

ip t

compound name

2 6 6

43 88 85

61 101 100

8.0 4.2 (34.9) 8.5 (36.1)

11.0 11.7 (34.9) 12.8 (36.1)

13.8 6.6 (28.9) 1.9 (30.8)

18.0 8.0 (28.9) 3.6 (30.8)

2 4 4 10 8

70 56 57 91 150

55 55 72 92 135

5.6 9.8 (13.8) 3.6 (22.9) 1.0 (25.4) 12.7 (44.0)

5.7 9.8 (13.8) 3.7 (22.9) 1.9 (25.4) 12.7 (44.0)

5.2 8.9 (11.8) 3.5 (19.1) 1.6 (22.8) 10.8 (37.3)

5.2 8.9 (11.8) 3.5 (19.1) 1.6 (22.8) 10.8 (37.3)

4 1 5 5

81 96 95 110

138; 82 95 110 109

11.3 (36.3) 5.7 (18.2) 7.8 (19.9) 8.1 (22.6)

11.6 (36.3) 8.5 (18.2) 8.5 (19.9) 9.2 (22.6)

9.2 (26.6) 5.1 (16.7) 5.8 (16.8) 6.6 (20.8)

9.2 (26.6) 5.8 (16.7) 5.8 (16.8) 6.6 (20.8)

8

128

57

15.7 (25.3)

21.2 (25.3)

16.3 (21.1)

16.3 (21.1)

7 7 7

108 108 135

81 67 136

8.7 (20.7) 9.7 (19.9) 7.9 (26.4)

8.7 (20.7) 9.7 (19.9) 7.9 (26.4)

6.7 (17.0) 7.5 (16.6) 5.7 (21.1)

6.7 (17.0) 7.5 (16.6) 5.7 (21.1)

Page 28 of 35

136

8.1 (25.9)

8.1 (25.9)

5.5 (20.7)

5.5 (20.7)

10

126

71

12.6 (27.5)

18.0 (27.5)

13.1 (23.6)

13.1 (23.6)

1 4 11 11 11 11

81 43 79 108 81 94

80 83; 111 93 123 147 109

11.8 (14.0) 21.1 (47.0) 7.7 (25.1) 8.9 (25.7) 10.9 (33.2) 8.3 (26.5)

14.5 (16.4) 21.1 (47.0) 7.7 (25.1) 8.9 (25.7) 10.9 (33.2) 8.3 (26.5)

12.5 (11.2) n.d. 6.2 (21.1) 6.0 (20.9) 7.8 (30.1) 4.8 (23.6)

14.9 (13.6) n.d. 6.2 (21.1) 8.1 (20.9) 7.8 (30.1) 4.8 (23.6)

3 3

94 126

79 79

32.2 (31.2) >40

32.2 (31.2) >40

18.1 (20.6) >40

18.1 (20.6) >40

9

60

45

7.8

14.2

14.2

9

60

87

5.6

5.6

a

7.8 8.2

cr

ip t

135

us

acetic acid 3-methyl butanoic acid

7

an

pyrazine 2-ethyl-3,5-dimethyl pyrazine Pyran derivatives maltol Pyrroles Pyrroline Pyridines 1-methyl pyrrole 2-acetyl-1-pyrroline 2-acetyl pyridine 2-acetyl-1-methyl pyrrole 1-furfuryl pyrrole 2-acetyl pyrrole Sulphides dimethyl disulphide dimethyl trisulphide Carboxylic acids

8.5

Ac ce p

te

d

M

Most appropriate internal standard selected for each target analyte. 1: 2-ethyl-2-butenal (quant. m/z 98, qual. m/z 83;69); 2: 4-methyl-2-pentanol (quant. m/z 45, qual. m/z 69;87); 3: diethyl disulfide (quant. m/z 122, qual. m/z 94;66); 4: 3-octen-2-one (quant. m/z 111, qual. m/z 55;97); 5: 1-(2-furyl)-acetone (quant. m/z 81, qual. m/z 124;53); 6: cis-7-decen1-al (quant. m/z 79, qual. m/z 67;55); 7: 5-isobutyl-2,3-dimethyl pyrazine (quant. m/z 122, qual. m/z 149;164); 8: ptolualdehyde (quant. m/z 119, qual. m/z 91;65); 9: 2-ethyl butyric acid (quant. m/z 88, qual. m/z 73;87); 10: 1-phenyl-2propanol (quant. m/z 92, qual. m/z 91;65); 11: 3-acetyl pyridine (quant. m/z 106, qual. m/z 121;78). b In parentheses, the lowest RSDs among those obtained by using only the two internal standards proposed by Ruiz and Colleagues [15], 4-methyl-2-pentanol and 2-ethyl butyric acid, are reported for comparison. For all target analytes, except for furaneol and 2-acetyl-1-pyrroline, the RSD obtained by using 4-methyl-2-pentanol was lower than that obtained by 2-ethyl butyric acid.

Page 29 of 35

Table 2. List of fully or tentatively identified volatile compounds isolated by HS-SPME/GC-MS. Method of identification, determined linear retention indices (LRI) and their comparison with LRI obtained by reference pure compounds or literature data, Match Factors of mass spectra of unknown compounds in bread samples with spectra obtained on reference pure compounds or retrieved form mass spectra library. LRI

mass spectrum Match Factor

b a a a b a b b b b a a a a a b b a b

811 904 910 1090 1191 1228 1296 1336 1401 1439 1469 1535 1550 1597 1664 1718 1779 1827 2023

814 904 910 1091 1186 1228 1286 1331 1396 1432 1469 1535 1551 1598 1665 1716b 1775 b 1827 2020 b

-3 0 0 -1 5 0 10 5 5 7 0 0 -1 -1 -1 2 4 0 3

942 927 972 961 891 828 850 940 910 909 748 901 938 778 912 878 765 885 892c

0 -10 3 8 -4

936 936 963d 891 910 942 915 933 884 843 866 880 917 897 795 882 911 891 851

cr

e

us

an

M

d

ip t

LRI from reference or literaturee

a b a b b b b b b b b a b a b b b b b

813 891 986 1060 1067 1137 1157 1152 1179 1253 1283 1300 1302 1340 1391 1577 1592 1599 1861

813 901 983 1052 1071 1120-1139 1138-1153 1160 1185 1251 1289 1300 1275-1323 1340 1394 1562-1570 n.a. 1606 1840-1877

a b b a

886 1445 1834 2055

886 1438 1791-1847 2055

0 7 0

955 883 900 944

a b

937 1061

937 1052

0 9

956 883

Ac ce p

Aldehydes 2-methyl propanal 2-methyl butanal 3-methyl butanal hexanal heptanal (E)-2-hexenal 1-octanal (Z)-2-heptenal 1-nonanal (E)-2-octenal methional benzaldehyde (E)-2-nonenal (E,Z)-2,6-nonadienal phenylacetaldehyde (E,E)-2,4-nonadienal (E,Z)-2,4-decadienal (E,E)-2,4-decadienal tr-4,5-epoxy-(E)-2-decenal Ketones acetone 2-butanone 2,3-butanedione 3-hexanone 2,3-pentanedione 3-penten-2-one 2,3-heptanedione 3-heptanone 2-heptanone 3-octanone 3-hydroxy-2-butanone 1-octen-3-one 1-hydroxy-2-propanone 6-methyl-5-hepten-2-one 2-nonanone (E,E)-3,5-octadien-2-one 3,6-heptanedione 2-cyclopentene-1,4-dione geranyl acetone Esters ethyl acetate ethyl octanoate phenyl ethyl acetate -nonalactone Alcohols ethanol 1-propanol

determined LRI

te

compound name

method of identificationa

-8 -6 2 -6 0 0 -3 n.a. -7

Page 30 of 35

b b b b b b a b a b b a b a b b b b

803 853 878 953 1069 1140 1238 1445 1474 1495 1508 1517 1515 1591 1618 1620 1624 1632

802 851-854f 876 945 1060 1112-1140 1238 1448 1476 1488 1503 1516 1486-1521 1592 1629 1614 1628 1608-1620

an

M

d

te

9 5 0 -1 1 0 0 -2 6 7 0 0

913 870 936 914 906 950 868 861 927 906 905 978 926

ip t

1097 1152 1212 1215 1256 1356 1379-1447 1458 1564 1668 1697 1927 2202

cr

1106 1157 1212 1214 1257 1356 1418 1458 1562 1674 1704 1927 2202

1

us

b b a b b a b a a b b a a

2 8 9

0 -3 -2 7 5 1

-1 -11 6 -4

b b b b b b

1649g 1669 1690 1703 1880 1996

n.a. 1678 1655-1710 1669-1700 1839-1851 1977-1986

b

2051

1997-2060

b b a b b b b b b b b b

1215 1269 1326 1335 1340 1355 1402 1409 1421 1436 1451 1455

1209 1264 1326 1325 1334 1345 1402 1406 1411 1404-1447 1456 1429-1438

6 5 0 10 6 10 0 3 10

a b b a

1458 1467 1474 1476

1458 1458 1425-1463 1476

0 9

Ac ce p

2-methyl-1-propanol 1-butanol 2-methyl-1-butanol 3-methyl-1-butanol 1-pentanol 1-hexanol 2-butoxy ethanol 1-octen-3-ol 1-octanol 1-nonanol (Z)-3-nonen-1-ol 2-phenyl-1-ethanol p-vinyl guaiacol Furans furan 3-methyl furan 2-methyl furan 2-ethyl furan 2,3,5-trimethyl furan 2-n-butyl furan 2-pentyl furan 3-furaldehyde 2-furfural 2-acetyl-5-methyl furan furfuryl methyl sulfide 2-acetyl furan benzo furan 5-methyl-2-furfural 2,2'-bifuran 2-methyl benzofuran 2-furfuryl furan 2-acetyl-5-methylfuran 2-acetyl-3-hydroxyfuran (isomaltol) 2-furan methanol 2-furfuryl-5-methyl furan 5-methyl-2-propionyl furan 2-furan acrolein difurfuryl ether 4-hydroxy-2,5-dimethyl3(2H)-furanone (furaneol) Pyrazines pyrazine 2-methyl pyrazine 2,5-dimethyl pyrazine 2,6-dimethyl pyrazine 2-ethyl pyrazine 2,3-dimethyl pyrazine 2-ethyl-6-methyl pyrazine 2-ethyl-5-methyl pyrazine 2-ethyl-3-methyl pyrazine 2-propyl pyrazine 2,6-diethyl pyrazine 2-vinylpyrazine 3-ethyl-2,5-dimethyl pyrazine 2,3-diethyl pyrazine 2,5-diethylpyrazine 2-ethyl-3,5-dimethyl

n.a. -9

912 939 911 847 847 815 922 888 970 930 911 966 850 945 971 889 910 963 933 926 913 874 911 954 731

-5

0

886 921 904 896 910 927 752 903 908 910 916 880 905 850 722 905

Page 31 of 35

1503

1485-1522

934

b

1506

1469-1503

778

b

1514

n.a.

826

b

1548

1535-1539

827

b

1656

1596-1616

b a b b b b a b b

1994 1159 1219 1357 1527 1575 1607h 1627 1628h

1943-2012 1159 1190-1224 1349 1525 1554-1583 1607 1610-1651 n.a.

a b

1659 1714

a b

1829 1837

a b b

ip t

b

914

n.a.

928 964 919 790 937 801 910 834 808

1659 n.a.

0 n.a.

817 810

1829 n.a.

0 n.a.

927 883

1988 2046i 2113

1988 2006-2059 2046-2079

0

922 948 853

1078 1390

1078 1390

0 0

907 926

a b b b b b b b b b

1471 1585 1683 1684 1764 1871 1976 2090 2196 2305

1472 1520-1588 1647-1694 1641-1680 1713-1780 1810-1874 1943-1971 2030-2106 2144-2211 2246-2318

-1

954 889 857 895 874 916 886 924 912 912

b b

1410 1513

1405-1434l 1502-1533l

a

1056

1054

cr

0

8 2

us

an

M

d

te

a a

Ac ce p

pyrazine 2-methyl-6-vinylpyrazine 2-methyl-3,5diethylpyrazine 2-isobutyl-3-methyl pyrazine 2-methyl-6-propenyl pyrazine 5-methyl-6,7-dihydro-(5H)cyclopentapyrazine Pyran derivatives maltol 1-methyl pyrrole 2,4,5-trimethyloxazole 2-acetyl-1-pyrroline 1-pyrrole 2-pentyl pyridine 2-acetyl pyridine 1-methyl-2-formyl pyrrole 2-acetyl-1,4,5,6tetrahydropyridine 2-acetyl-1-methyl pyrrole N-acetyl-4(H)-pyridine or 1-acetyl-1,4dihydropyridine 1-furfuryl pyrrole 1-acetyl-1,2,3,4tetrahydropyridine 2-acetyl pyrrole 2-formyl pyrrole 5-methyl-2-formyl pyrrole Sulphides dimethyl disulphide dimethyl trisulphide Carboxylic acids acetic acid 2-methyl propanoic acid 3-methyl butanoic acid 2-methylbutanoic acid pentanoic acid hexanoic acid heptanoic acid octanoic acid nonanoic acid n decanoic acid Nitrocompounds 1-nitro pentane 1-nitro hexane Hydrocarbons toluene

0

907 928 2

937

a

Fully identification (a) obtained by comparison to LRI and mass spectrum of reference compound. Tentative identification (b) obtained by comparison with LRI from the literature and mass spectra form spectra library. b LRI determined on a DB-Wax column on a bread sample by Rychlik & Grosch [36]. c Reference mass spectrum was that reported by Schieberle & Grosch [4]. d Mass spectrum of the chromatographic peak obtained by GC separation on a DB1-MS column. e When a LRI was not available from the paper by Bianchi and Collagues [21], a range of values obtained on the same chromatographic phase and by the same calculation method was retrieved from the NIST Chemistry WebBook database [22], and reported as a range (min-max). In this cases the corresponding LRI was not calculated.

Page 32 of 35

f

Ac ce p

te

d

M

an

us

cr

ip t

LRI reported by Bianchi and Collagues [21], 907, was in disagreement with LRI reported in the NIST Chemistry WebBook database [22] and with LRI determined in the present study. g LRI determined on a DB1-MS column, 987, showed a LRI of -8 vs a LRI reported for the same chromatographic phase in the NIST Chemistry WebBook database, 995 [22]. h Schieberle & Grosch [37] observed on a DB-Wax column a similar increase (+20) in the LRI from 2-acetyl pyridine (1585) to 2-acetyl-1,4,5,6-tetrahydropyridine (1605), as in the present tentative identification (+21). i LRI determined on a DB1-MS column was 977, while in the NIST Chemistry WebBook database [22] the range 983997 was reported. l LRI determined by a GC isothermal separation.

Page 33 of 35

ip t cr

98 ≥97 98 98 98 ≥99 97 95 ≥99 ≥97.0

67-64-1 431-03-8 4312-99-6 110-93-0

M an

96-17-3 590-86-3 66-25-1 6728-26-3 3268-49-3 100-52-7 18829-56-6 557-48-2 122-78-1 25152-84-5

ed

purity (%)

≥99.9 ≥99.0 96 99

141-78-6 104-61-0

99.8 ≥98

64-17-5 137-32-6 111-27-3 3391-86-4 111-87-5 60-12-8 7786-61-0

≥99.8 ≥99 ≥99 ≥98 ≥99 ≥99.0 ≥98.0

3777-69-3 98-01-1 1192-62-7 620-02-0

≥98 99 ≥99 ≥98.5

Ac

Aldehydes 2-methyl butanal 3-methyl butanal hexanal (E)-2-hexenal methional benzaldehyde (E)-2-nonenal (E,Z)-2,6-nonadienal phenylacetaldehyde (E,E)-2,4-decadienal Ketones acetone 2,3-butanedione 1-octen-3-one 6-methyl-5-hepten-2-one Esters ethyl acetate -nonalactone Alcohols ethanol 2-methyl-1-butanol 1-hexanol 1-octen-3-ol 1-octanol 2-phenyl-1-ethanol p-vinyl guaiacol Furans 2-pentyl furan 2-furfural 2-acetyl furan 5-methyl-2-furfural Pyrazines

CAS no.

ce pt

compound name

us

Table 1. List of pure volatile compounds and tested internal standards used in the study, their CAS no. and purity (%).

Page 34 of 35

ip t 624-92-0 3658-80-8

≥99.0 ≥98

64-19-7

≥99.7

108-88-3

99.8

n.a.b 95 ≥92 n.a.b 98 99 ≥98 n.a.b 96

ce pt

2094-75-9 2987-16-8 97-96-1 63883-69-2 108-11-2 110-81-6 18402-82-9 6975-60-6 21661-97-2

cr

≥99 ≥99 ≥98 99 ≥98.5

us

96-54-8 1122-62-9 932-16-1 1438-94-4 1072-83-9

M an

≥98.5 96.5a 96.5a

ed

123-32-0 27043-05-6a 27043-05-6a

54410-83-2 104-87-0 88-09-5 698-87-3 350-03-8

Ac

2,5-dimethyl pyrazine 3-ethyl-2,5-dimethyl pyrazine 2-ethyl-3,5-dimethyl pyrazine Pyrroles, Pyridines 1-methyl pyrrole 2-acetyl pyridine 2-acetyl-1-methyl pyrrole 1-furfuryl pyrrole 2-acetyl pyrrole Sulphides dimethyl disulphide dimethyl trisulphide Carboxylic acids acetic acid Hydrocarbons toluene List of internal standards 2,2-dimethyl butanal 3,3-dimethyl butanal 2-ethyl butanal 2-ethyl-2-butenal 4-methyl-2-pentanol diethyl disulfide 3-octen-2-one 1-(2-furyl)-acetone cis-7-decen-1-al 5-isobutyl-2,3-dimethyl pyrazine p-tolualdehyde 2-ethyl butyric acid 1-phenyl-2-propanol 3-acetyl pyridine

97 ≥97 99 98 ≥98

Page 35 of 35