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Determination of volatile phenols in virgin olive oils and their sensory significance
Journal of Chromatography A, 1211 (2008) 1–7
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Determination of volatile phenols in virgin olive oils and their sensory significance Stefania Vichi a,∗ , Agustí Romero b , Joan Tous b , Elvira López Tamames a , Susana Buxaderas a a Departament de Nutrició i Bromatologia, Xarxa de Referència en Tecnología dels Aliments (XaRTA), Facultat de Farmàcia, Universitat de Barcelona, Avinguda Joan XXIII, s/n, E-08028 Barcelona, Spain b Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Arboricultura Mediterránea Mas de Bover, Carretera De Reus - El Morell 43120 Constantí (Tarragona), Spain
a r t i c l e
i n f o
Article history: Received 26 July 2008 Received in revised form 17 September 2008 Accepted 22 September 2008 Available online 25 September 2008 Keywords: Virgin olive oil Volatile phenols Solid-phase microextraction Off-flavour Odour threshold Phenol Guaiacol o-, m-, p-Cresol 4-Ethylphenol 4-Ethylguaiacol 4-Vinylphenol 4-Vinylguaiacol
a b s t r a c t Volatile phenols are strong odorants produced by microbial activity and reported in several foods, but very scarce information is available on their presence in virgin olive oils (VOOs) and on their relation with VOO chemical and sensory quality. In the present paper, a factorial experimental design was applied for the development of a suitable solid-phase microextraction–gas chromatography/mass spectrometry (SPME–GC/MS) analytical method for the analysis of volatile phenols in olive oil. The memory effects demonstrated by SPME fibres required the optimization of desorption conditions to minimize experimental errors. A series of nine volatile phenols were identified and quantified for the first time in VOOs by analyzing samples with distinct off-flavours. Their limits of detection and quantification (g/kg) were largely below the odour detection thresholds (ODTs) calculated in this study (mg/kg), confirming the capacity of the technique to assess the target compounds at early stages of the oil sensory alteration. The odour activity values (OAVs) of volatile phenols were calculated in VOOs facilitating a first assessment of their potential importance in the aroma of the product. © 2008 Elsevier B.V. All rights reserved.
1. Introduction Volatile phenols are reported as aroma contributors in several foods [1–5], as well as strong odorants in gas emissions from agricultural operations [6]. In some cases, they are essential for the overall food flavour perception like in the case of certain beers [4] and wines [7], but they become undesirable when their concentration exceed certain limits, leading to typical phenolic off-flavour [1–4]. Volatile phenols are principally a result of the activity of microorganisms [1,4,8–11], and their presence and sensory significance have been widely studied in several foods and beverages like wine, beer, spirits [11], fruit juices [2,3], and pepper [5], but very few data are available on their presence in virgin olive oils. The typical volatile profile of virgin olive oil (VOO), highly appreciated and preserved for the absence of refining, can be altered by various factors related with the quality of olives and oil storage [12]. Microbial
∗ Corresponding author. Tel.: +34 93 4024508; fax: +34 93 4035931. E-mail address: [email protected] (S. Vichi). 0021-9673/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2008.09.067
proliferation during the storage of olives in unsuitable conditions or oil in contact with muddy sediments is one of the principal factors affecting VOO quality [12,13]. Numerous volatile compounds are well known to be present in defective VOO and several of them have been shown to contribute to distinct VOO off-flavours [13]. Nevertheless, although fermentations conducted by several fungi and bacteria isolated in olives [14,15] could produce volatile phenols, very scarce information is available on the relation between these compounds and VOO chemical and sensory quality. The studies conducted on this topic indicate that they could contribute to the off-flavour of defective oils: guaiacol was proved to be a key odorant in a VOO reminiscent of black olives [16] and in a musty olive oil [13], while 4-ethylphenol demonstrated some odour impact in stored olive paste and in oils from second centrifugation [17]. Moreover, 4-ethylphenol was found to be especially abundant in oils from ground-picked olives [18], and 4-vinylphenol was detected but not quantified in off-flavour VOOs [19]. The detection of the single guaiacol, ethylguaiacol or vinylphenol among VOO volatiles has been achieved by dynamic headspace [13], solid-phase microextraction (SPME) [18], or distillation [16,19], followed by gas chromatography.
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S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
Ethylphenol was also detected in the phenolic fraction of VOO after liquid-liquid extraction followed by liquid chromatography [19]. The availability of reliable chemical and sensory markers is acquiring an increasing importance in view of the need to guarantee VOO quality. Volatile phenols could be suitable indices of microbiological degradation of olives or oils, as well as possible contributors of the VOO aroma perception. Nevertheless, the data on the occurrence, the concentrations and the odour impact of this class of compounds in VOOs are quite scarce, and there is a lack of specific analytical methods for their determination. The aim of the present paper was to determine the presence of several volatile phenols in VOOs and their potential significance from the organoleptic point of view. With this purpose, a suitable SPME method coupled to GC/MS was developed for the determination of nine volatile phenols, and applied to a selected group of VOOs with different sensory defects. Odour thresholds of the target phenols and their odour activity values in oils were then determined for the first time to assess the sensory significance. 2. Materials and methods 2.1. Reagents and materials The SPME fibres tested were divinylbenzene/Carboxen/polydimethylsiloxane 50 m/30 m, 2 cm long (DVB/CAR/PDMS), polydimethylsiloxane/divinylbenzene 65 m (PDMS/DVB), and Carbowax/divinylbenzene 65 m (CW/DVB), all from Supelco (Bellefonte, PA, USA). Phenol, o-, p-cresol, 4-ethylphenol, 2,3-dimethylphenol, 4vinylphenol (solution 10%, w/w in propylene glycol), guaiacol, 4-ethylguaiacol and vinylguaiacol came from Sigma–Aldrich (St. Louis, MO, USA). 2.2. Standard solutions Standard solutions of the above mentioned phenols were directly prepared in refined sunflower oil in order to avoid interferences due to the use of solvents. For the calibration of the analytical method and determination of repeatability and memory effects, a standard mixture of phenol, o-, p-cresol, 4-ethylphenol, 4-vinylphenol, guaiacol, 4-ethylguaiacol and vinylguaiacol was prepared in refined sunflower oil, while for the determination of phenols’ odour thresholds, solutions of the single phenols in refined sunflower oil were prepared. The internal standard solution of 2,3-dimethylphenol was also prepared by dilution in refined olive oil. Oil standard solutions at various concentrations described in the corresponding sections, were obtained by spiking refined sunflower oil with these stock solutions.
Table 1 Description of the VOO samples Code 1 2 3 4 5 6 7 8
Alteration/defect No defects (control) No defects (control) Fusty/fermented olive paste Fusty Fusty/musty Musty Muddy Muddy
a b c d e f
Oil
Supplier a
EVOO EVOO STDc STD VOOf STD VOO STD
COPb COP MAPAd IOOCe COP IOOC COP COP
Extra virgin olive oils, mean of sensory defects = 0. Catalonian Official Panel. Standard oil used in the training process for assessors to detect sensory defects. MAPA (Spanish Ministerio de Agricultura, Pesca y Alimentación). International Olive Oil Council. Virgin olive oil, median of sensory defects > 0.
10 min, respectively. During each chromatographic run, the fibre was maintained retracted in the holder at ambient temperature. Temperature of desorption was 265 ◦ C for DVB/CAR/PDMS and PDMS/DVB fibres, and 240 ◦ C for CW/DVB, according to the maximum operating temperature recommended by the supplier for each fibre. 2.5. SPME conditions In order to evaluate suitable extraction conditions for the determination of volatile phenols in VOO, distinct variables were tested by a multilevel factorial experimental design. The variables were the type of fibre coating: DVB/CAR/PDMS (1), PDMS/DVB (2), CW/DVB (3), extraction temperature (40, 50, 60 ◦ C) and extraction time (30, 60 min). The factorial design consisted in 18 experiments performed in duplicate. SPME analyses were carried out by weighing 2 g of a virgin olive oil into a 10 ml vial fitted with a silicone septum, then placing it into a silicone oil bath were the sample was maintained under magnetic stirring (700 rpm). After 10 min of sample conditioning, each fibre was exposed for different time periods (30 or 60 min) and immediately desorbed in the gas chromatograph injector. Each extraction was performed in duplicate. Chromatographic responses of volatile phenols were monitored. The results of the experimental design (chromatographic area counts) were analyzed by a standardized Pareto diagram and the optimal value of each factor involved in the extraction was statistically calculated. The sorption of volatiles in the samples headspace was finally performed using the DVB/CAR/PDMS coating, during 30 min at a temperature of 60 ◦ C. 2.6. GC–MS analysis
2.3. Olive oil samples A heterogeneous group of eight olive oils were analyzed by applying the developed method to assess the volatile phenols (Table 1). The samples were selected for having distinct types of alterations, reflected by various sensory defects. 2.4. Memory effects and desorption conditions The memory effects of each fibre (DVB/CAR/PDMS, PDMS/DVB, CW/DVB) were compared under the following conditions: 2 g of a standard solution of volatile phenols in oil (1 mg/kg) was extracted by SPME (60 ◦ C for 60 min). After the extraction, the fibres were desorbed during 5 min, then retracted from the injection port and successively desorbed four consecutive times during 5, 10, 10 and
Identification of compounds was carried out by gas chromatography coupled to quadrupole mass selective spectrometry using an Agilent 5973 Network detector (Agilent Technologies, Palo Alto, CA, USA). Analytes were separated on a Supelcowax-10 (Supelco, Bellefonte, PA) 30 m × 0.25 mm ID, 0.25 mm film thickness. Column temperature was held at 50 ◦ C for 10 min, increased to 240 ◦ C at 8 ◦ C/min. The injector temperature was 265 ◦ C and the time of desorption of the fibre into the injection port was fixed at 10 min. Helium was the carrier gas, at a linear velocity of 38 cm/s. The temperature of the ion source was 175 ◦ C and the transfer line, 280 ◦ C. Positive electron ionization mass spectra (EIMS) were recorded at 70 eV ionization energy, 2 scan/s. GC–MS analysis in the complete scanning mode (SCAN) in the 40–300 m/z range allowed the identification of compounds in oil
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
samples, by comparison of their mass spectra and retention times with those of standard compounds. Quantitative assessment of volatile phenols was carried out in the selected ion monitoring mode (SIM) in order to improve the detection limits. For each phenol the following qualifier and quantifier (underlined) ions were analyzed: m/z 109, 124 (guaiacol), m/z 77, 94 (phenol), m/z 107, 108 (o-, m-, p-cresol); m/z 137, 152 (4ethylguaiacol), m/z 107, 122 (4-ethylphenol, 2,3-dimethylphenol), m/z 135, 150 (4-vinylguaiacol), m/z 91, 120 (4-vinylphenol). Base peak ions were used for quantification of compounds. 2.7. Method assessment Calibration was performed by analyzing deodorized sunflower oil with different concentrations of volatile phenols. Standard solutions were prepared in the range 0.01–10 mg/kg and analyzed in duplicate under the same conditions described for samples. Internal standard (2,3-dimethylphenol) concentration was maintained at 5 mg/kg. The method was assessed by determining relative response factors (with respect to internal standard 2,3-dimethylphenol), linearity of response (regression coefficient values—r), repeatability (as relative standard deviation—RSD), and limits of detection (LOD) and quantification (LOQ). Repeatability of the method was tested by repeating five times the analysis of a 0.05 mg/kg standard mixture. LOD and LOQ were calculated as LOD = 3ı/m and LOQ = 10ı/m, respectively, according with [20] and [21] definitions, where ı is the standard deviation of the baseline noise and m is the slope of the calibration curve. 2.8. Determination of the odour detection threshold (ODT) concentration in oil of volatile phenols and their odour activity values (OAVs) in VOO samples Odour thresholds were determined by a three-alternative forced-choice (3-AFC) procedure. Directional triangular tests of increasing concentrations of volatile phenols in refined sunflower oil were analyzed by 12 trained sensory assessors (30 ml of oil solution were presented in 160-ml covered glasses). The panel room was maintained at 25 ◦ C. The odour detection threshold was the minimum concentration at which 50% of the sensory assessors were able to perceive a difference in odour between the spiked and non-spiked media. Phenol, o-, p-cresol, 4-ethylphenol, 4-vinylphenol, guaiacol, 4-ethylguaiacol, vinylguaiacol were tested from 0.01 to 0.4 mg/kg along two sessions (0.1, 0.2, 0.4 mg/kg concentrations were tested during the first session and 0.01, 0.025, 0.05 mg/kg concentrations were tested during the second session). An additional concentration of 0.005 mg/kg was tested for guaiacol. In order to evaluate the potential sensory importance of volatile phenols in VOO samples, their odour activity values were also calculated as the ratio of concentration and odour threshold.
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the effects that are statistically significant. Bars that extend beyond the line correspond to effects that are statistically significant at the 95% confidence level [22]. The magnitude of the principal effects and the interaction among factors were also evaluated by analyzing their correspondent graphical representations. 3. Results and discussion 3.1. Memory effects and desorption conditions Preliminary assays allowed observing a noticeable memory effect of SPME fibres for volatile phenols. To avoid these undesirable effects, fibres’ desorption efficiency was monitored at increasing periods of desorption performed at the maximum suitable temperature. After the extraction of a standard solution of volatile phenols in oil (1 mg/kg of guaiacol, phenol, o-, p-cresol, 4-ethylphenol, 4ethylguaiacol, 4-vinylphenol and 4-vinylguaiacol), each fibre was desorbed during 5 min. To assess the residual amount of analytes on the fibre, it was desorbed again in the GC injector port during further 5 min, repeating this procedure until a total of 40 min, as detailed in Table 2. After 40 min of desorption the residual volatile phenols were near or below the LOQ, depending on the fibre, and it was assumed that the 100% of analytes were desorbed. The CW/DVB fibre showed the fastest desorption of analytes, while PDMS/DVB and in particular DVB/CAR/PDMS were characterized by a slower desorption and a considerable memory effect. This is in accordance with previously reported results [23]. The slower desorption of DVB/CAR/PDMS could be due in part to the Carboxen phase, which is reportedly characterized by very small pores [24] and long desorption times [25]. The percent amount of analytes desorbed during the first 5 min was 94.5% for DVB/CAR/PDMS, 97.1% for PDMS/DVB, and 99.2% for CW/DVB (Table 2). In particular, 4-vinylguaiacol and 4-vinylphenol showed the slowest desorption from the three coatings, and their amount desorbed after 5 min was lower than 90% for DVB/CAR/PDMS, around 95 and 93% for PDMS/DVB, and around 98% for CW/DVB. Further 5 min of desorption allowed reaching mean amounts of volatile phenols higher than 98%, and amounts of 4-vinylguaiacol and 4-vinylphenol higher than 96%, for all the fibres tested. Mean memory effects of around 0.2% DVB/CAR/PDMS and PDMS/DVB and lower than 0.1% for CW/DVB were reached after 30 min of desorption. The operative desorption conditions were established with the aim to obtain an acceptable percent uptake of volatile phenols and to avoid contamination between samples due to unwanted memory effects. On this basis, desorption time was fixed at 10 min, opening the split valve after this time, while the fibre in was kept the injection port for further 20 min for a cleaning step, until a total of 30 min. A supplementary cleaning was performed after the analysis of very concentrated samples, to ensure that residual phenols were below the LOQ.
2.9. Statistical analysis
3.2. Optimization of SPME conditions
The multilevel factorial experimental design was performed using the package “Statgraphics Plus 5.1”. For the optimization of SPME conditions four variables were tested at four, three, or two factor levels, as described in the SPME conditions paragraph. The results of the experimental design, evaluated at a 5% of significance, were analyzed by a standardized Pareto diagram, which displays a frequency histogram where the length of each bar on the chart is proportional to the absolute value of its associated estimated effect or the standardized effect. The standardized effect is the estimated effect divided by its standard error, which is equivalent to computing a t-statistic for each effect. The vertical line on the plot judges
In order to optimizing the extraction conditions for detection of volatile phenols in VOO, three distinct experimental factors were tested by a multilevel factorial experimental design: type of fibre coating, temperature and time of extraction. Among the commercially available fibres, the DVB/CAR/PDMS (1) fibre was tested due to the high uptakes of organic volatile compounds described to be reached by this coating [25,26], and for the availability of fibres with a higher coating volume (double fibre length). PDMS/DVB (2) and CW/DVB (3) fibres were tested in view of their polarity, which could determine a higher affinity for volatile phenols. The amount of sample was not studied because in the case of lipid matrices
0.0 0.1 0.2 0.5 99.2 0.2 0.5 0.7 1.5 97.1
e
c
d
b
0.2 0.5 1.2 3.6 94.5 Mean
3.3. Method assessment Percent amount of analytes desorbed during the first 5 min. Percent amount of analytes desorbed from 5 to 10 min. From 10 to 20 min. From 20 to 30 min. From 30 to 40 min.
0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0
it does not significantly affect the mass of analyte absorbed by the SPME coating [26]. The influence of each experimental factor on the extraction of volatile phenols was evaluated by means of standardized Pareto diagrams (Fig. 1a). To simplify the graphical representation, volatile phenols were grouped according to their behaviour in function to the extraction factors, and showed as sum of phenol and guaiacol and sums of their respective methyl, ethyl, and vinyl derivatives. For all the groups of phenols, the type of coating and the extraction temperature showed significant influence on the chromatographic responses, while the extraction time had no significant effects on the uptake of phenol and guaiacol. Some significant interactions between temperature and the other factors were observed for all the alkylated phenols (Fig. 1c) reflecting an enhancement of the factors’ positive effect on phenols uptake at the highest temperature. The diagram of principal effects (Fig. 1b) shows that the highest uptake of all the volatile phenols was given by the DVB/CAR/PDMS fibre, and extraction temperature of 60 ◦ C. As expected, the positive effect of temperature was higher for less volatile compounds, likely due to an increase of their transfer to the headspace. On the other hand, the uptake of less volatile phenols was less influenced by the type of SPME sorbent. In this case, the positive effect observed for DVB/CAR/PDMS fibre could be given to a higher capacity related to the volume of the coating (2 cm of fibre length versus 1 cm). On the basis of these results, the extraction temperature of 60 ◦ C and the DVB/CAR/PDMS fibre were chosen, in spite of the higher memory effect observed for this coating. Regarding the extraction time, it had a significant effect on the uptake of alkylated phenols, which was higher after 60 min of extraction. Nevertheless, after verifying that at the shortest extraction time the lowest levels of phenols were largely above the LOQ, the time of 30 min was chosen to perform the analysis, taking into account the long desorption step required for the chosen fibre. To prove that the chosen extraction temperature of 60 ◦ C did not induce the formation of artefacts in the samples, and influenced the chromatographic responses only by acting on the extraction efficiency, olive oil samples were analyzed by a SPME extraction at 40 ◦ C during 60 min, with (n = 6) and without (n = 6) a previous thermal treatment (60 ◦ C for 60 min). A student t-test showed that the mean areas of volatile phenols in the two groups were not significantly different (p > 0.05, data not shown), demonstrating that only the extraction efficiency was significantly influenced by the temperature of 60 ◦ C and no alterations of the sample were induced by the extraction conditions.
a
30 min
0.0 0.2 0.0 0.0 0.1 0.0 0.2 0.2 0.1 0.3 0.1 0.1 0.1 0.1 0.6 0.7
20 min 10 min
0.3 0.5 0.3 0.3 0.3 0.3 0.8 1.0 99.6 99.0 99.6 99.6 99.5 99.6 98.5 98.2 0.0 0.4 0.0 0.1 0.1 0.0 0.2 0.4 0.0 1.2 0.1 0.2 0.3 0.1 0.6 1.3 0.1 1.6 0.1 0.3 0.3 0.1 1.4 2.4 1.5 1.0 0.8 1.4 1.3 0.5 2.6 3.1 0.1 0.2 0.1 0.1 0.1 0.1 0.4 0.5 0.4 0.6 0.3 0.4 0.4 0.2 0.9 1.4 1.1 0.8 0.8 1.3 1.0 0.5 2.0 2.8 2.5 1.9 1.8 3.3 2.3 1.2 6.8 8.8 96.0 96.5 97.0 94.7 96.2 98.0 89.9 87.3 Guaiacol Phenol o-Cresol p-Cresol 4-Ethylphenol 4-Ethylguaiacol 4-Vinylguaiacol 4-Vinylphenol
CW/DVB
5 min 40 min 30 min 20 min 10 min
PDMS/DVB
5 min 40 mine 30 mind 20 minc 10 minb 5 mina
DVB/CAR/PDMS Compound
98.3 95.8 99.0 98.0 98.1 99.3 95.3 93.4
40 min
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7 Table 2 Amount of analytes desorbed from three distinct coatings during increasing periods of desorption performed at the maximum suitable temperatures (265 ◦ C for DVB/CAR/PDMS and PDMS/DVB, 240 ◦ C for CW/DVB), after the extraction of a standard solution at 1 mg/kg of each phenol
4
After the determination of suitable SPME parameters, the method performances were assessed by determining relative response factors, linearity of response, repeatability, and limits of detection and quantification for the target volatile phenols (Table 3). A satisfactory linearity was obtained within the whole interval of concentration tested, with regression coefficients higher than 0991. The relative standard deviation (RSD) calculated at a concentration of 0.05 mg/kg standard mixture was lower than 10% for all the volatile phenols. As expected, the highest response factors with respect to the internal standard 2,3-dimethylphenol were calculated for the most volatile compounds phenol and guaiacol, while the highest values were observed for their vinyl derivatives. LODs and LOQs were in the ranges of 0.09–0.78 and 0.3–2.6 g/kg, respectively. The chromatographic resolution and the absence of significant interference due to the oil matrix and therefore the satisfactory selectivity of the developed SPME–GC/MS method can be appreciated in Fig. 2.
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
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Fig. 1. (a) Standardized Pareto diagrams showing degree of influence of each experimental factor on the response of four groups of volatile phenols, taking into account the standard error. Bars that extend beyond the vertical line in the Pareto diagram correspond to effects that are statistically significant at the 95% confidence level. A: temperature; B: time; C: fibre (fibre 1: DVB/CAR/PDMS; fibre 2: PDMS/DVB; fibre 3: CW/DVB). (b) Graphics of principal effects and (c) graphics of interactions among factors.
Table 3 Characterization of volatile phenols detected in virgin olive oils and performances of the SPME–GC/MS method
1 2 3 4 5 6 7 8 9
Guaiacol Phenol o-Cresol p-Cresol m-Cresol 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol 4-Vinylphenol a b c d e f g h i j
IDa
KIb
Ionc
RSDd (n = 5)
RFe
rf
LODg (g/kg)
LOQh (g/kg)
Si S S S MS, RIj S S S S
1855 1994 1992 2073 2080 2024 2165 2193 2480
109 94 107 107 107 137 107 150 120
5.7 5.8 4.2 7.7 – 7.1 6.3 8.9 9.9
3.60 3.54 1.84 1.44 – 1.19 1.33 0.12 0.11
0.9997 0.9988 0.9993 0.9989 – 0.9972 0.9982 0.9961 0.9912
0.09 0.13 0.25 0.32
0.3 0.4 0.8 1.1
0.12 0.35 0.69 0.78
0.4 1.2 2.3 2.6
Identification method. Kovats indices on Supelcowax-10 capillary column. Ion used for quantification. Relative standard deviation (%) calculated on a 0.05 mg/kg standard mixture. Relative response factor (internal standard 2,3-dimethylphenol). Linearity within the range of concentration 0.010–10 mg/kg, expressed as regression coefficient. Limit of detection. Limit of quantification. Identified by comparison with standard compounds. Tentatively identified by mass spectra (MS) and retention index (RI).
2 6 8 2
114 1 3 5 3 5 1 3 8 30 1 1 1 17 346 294 23
201 5
2
1 14 57
48 12 2 1
2 2 5 1
41 1 75 2
2
6 57 1 590 2
2 0.1 0.025 0.025
– 0.05 0.2 0.2
0.4
Phenol o-Cresol p-Cresol
m-Cresold 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol
4-Vinylphenol
Woody, smoky, spicy [13]; phenolic, burnt [16]; bad olives [28]; green, fatty [29]; harsh, earthy [30] – – Faecal, horse-like [5]; phenolic, musty [31] Phenolic [5]; manure, plastic [29]; Sweet [32]; spicy [30] Phenolic [33]; horse-like, stable [34] Clove-like [33,35]; spicy, eugenol-like [30]; pharmaceutical [33] Pharmaceutical, gouache [33,35]; carnation [35]; varnish [34] 0.01
Only OAVs ≥ 1 are reported. a Odour activity value. b Odour detection thresholds. c Odour notes described in literature. d OAVs calculated by using the same ODT of o- and p-cresol.
7 (VOO-muddy) 6 (STD-musty) 5 (VOO-fusty/musty) 4 (STD-fusty) 3 (STD-fusty/ferm.) 2 (EVOO) 1 (EVOO)
OAVa
Guaiacol
An extensive sampling of EVOO, VOO and defective olive oils would be necessary to relate the content of volatile phenols to specific alterations of olive oil flavour or to specific variables of the oil’s production process. In the present study, the concentrations and the proportions of each volatile phenol were monitored within a limited number of selected samples, as a preliminary step to associate these compounds to specific oil alterations and to orientate further investigations on this topic (Table 1). The samples were selected for having distinct types of alterations, reflected by various sensory defects. Their analysis by the method presented in this paper allowed detecting and quantifying for the first time a series of nine volatile phenols with phenol and guaiacol structure, comprising methyl, ethyl and vinyl derivatives. These compounds are reported in Table 3, together with their identification data and the perfor-
Odour note (lit.)c
3.5. Characterization and quantification of volatile phenols in VOO
ODTb (mg/Kg)
Table 4 reports the odour thresholds of volatile phenols determined in refined sunflower oil. The lowest ODT was determined for guaiacol, while the highest ODT were observed for phenol and 4-ethylphenol. The ODT of volatile phenols calculated in oil are in some cases higher but quite in accordance with those observed in hydroalcoholic solution, which were resumed by Escudero et al. [27]. The LOQ of volatile phenols obtained by the proposed analytical method (Table 2) were always much lower (g/kg) than the correspondent ODTs (mg/kg)(Table 4), confirming the suitability of the technique to assess the target compounds at early stages of the oil sensory alteration.
Volatile phenols
3.4. Determination of the odour detection threshold in oil of volatile phenols
Table 4 Odour detection thresholds (ODTs) in refined sunflower oil, odour activity values (OAVs) of volatile phenol in virgin olive oil samples, and odour notes of volatile phenols as described in literature
Fig. 2. Extracted ion chromatogram of volatile phenols, obtained by analyzing virgin olive oil sample 3 (Table 1) by the optimized SPME–GC/MS method. Separation was performed on a Supelcowax capillary column and peaks are identified according to Table 3.
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Table 5 Concentrations (mg/kg) of volatile phenols in virgin olive oils (mean of two replicates) Volatile phenols
Guaiacol Phenol o-Cresol p-Cresol m-Cresol 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol 4-Vinylphenol Sum
Olive oil samples 1 (EVOO)
2 (EVOO)
3 (STD-fusty/fermented)
4 (STD-fusty)
5 (VOO-fusty/musty)
6 (STD-musty)
7 (VOO-muddy)
8 (STD-muddy)
0.003 0.211 0.001 0.005 0.008 0.009 0.079 0.053 0.304 0.548
0.004 0.180 0.003 0.004 0.005 0.007 0.035 0.039 0.294 0.467
0.019 0.167 0.008 0.036 0.034 0.686 11.5 0.127 1.83 14.3
5.91 4.07 0.016 1.46 0.434 17.35 59.0 4.61 80.6 171.2
0.013 0.142 0.004 0.010 0.009 0.048 0.231 0.133 0.960 1.47
0.567 0.535 0.011 0.030 0.075 0.410 5.91 0.270 3.24 10.7
0.063 0.152 0.006 0.230 0.133 0.152 1.02 0.272 2.60 4.60
0.142 0.233 0.006 0.942 2.85 0.032 0.567 0.063 0.912 5.87
mances of the analytical method. The volatile phenols target of this study were detected in all the analyzed samples, at different concentrations (Table 5). The concentration of volatile phenols seems to depend on the presence of oil alterations, as can be observed by comparing their total amounts in the selected samples. Phenol and o-cresol maintained quite similar levels in all the oils, while guaiacol and in particular ethyl derivatives were clearly higher in defective oils. Vinyl derivatives showed higher concentrations in defective oils than in EVOOs, although the difference between these groups of oils was much lower than observed for ethyl derivatives. m- and p-cresol reached the highest amounts in muddy oils. 3.6. Odour activity values The ratio between the odorant concentration and its odour threshold is known as OAV. This parameter allows making a first assessment of the potential importance of a specific compound to the aroma of a product. Table 4 shows the OAVs of volatile phenols present in olive oil samples and the odour notes described in literature for each compound. The results reported in this table indicate that phenol has OAVs ≥1 in all the oils analyzed, comprising EVOOs and oils with strong off-flavour. These data suggest that phenol could contribute in the overall aroma of both EVOO and defective olive oils, even if their role in the aroma perception is probably different according to their concentration. On contrary, vinyl, ethyl derivatives and guaiacol seem to have some sensory significance only in defective oils, especially in musty and fusty olive oils (Table 5). Regarding cresol isomers, the OAVs obtained in the study (by applying to m-cresol the same ODT than o- and p-cresol) showed that p- and m-cresol are the most significant odorant phenols in muddy olive oils. The odour note described in literature for p-cresol suggests that this compound probably contribute to the typical faecal off-flavour of muddy olive oils. On contrary, the ortho isomer seems to have a scarce sensory impact in defective oil, with concentration near to the ODT in the fusty oil. In conclusion, the development of a suitable SPME–GC/MS method by a factorial experimental design and its application to a heterogeneous group of VOOs selected for having distinct types of alterations, led to identify and quantify for the first time a whole series of nine volatile phenols. The optimized desorption conditions prevented from the experimental errors due to the memory effects demonstrated for SPME fibres. The ODTs of volatile phenols in oil matrix calculated in the present study confirmed the capacity of the technique to assess the target compounds at the early stages of the oil sensory alteration, given that LOD and LOQ were largely below the correspondent ODTs. The calculation of OAVs of volatile phenols in EVOOs and defective VOOs made it possible a first assessment of their potential importance in the aroma of the product.
Acknowledgements This study was supported by the Generalitat de Catalunya, project 2005SGR00156; by the Ministerio de Ciencia y Tecnología (MCYT), project AGL2005-03451/ALI, and by the Ministerio de Educación y Ciencia (MEC), Juan de la Cierva program. References [1] P. Chatonnet, D. Dubourdieu, J.N. Boidron, M. Pons, J. Sci. Food Agric. 60 (1992) 165. [2] H. Peleg, M. Naim, U. Zehavi, R.L. Rouseff, S. Nagy, J. Agric. Food Chem. 40 (1992) 764. [3] J.A. Donaghy, P.F. Kelly, A. McKay, J. Sci. Food Agric. 79 (1999) 453. [4] N. Vanbeneden, F. Gils, F. Delvaux, F.R. Delvaux, Food Chem. 107 (2008) 221. [5] M. Steinhaus, P. Schieberle, J. Agric. Food Chem. 53 (2005) 6056. [6] S. Rappert, R. Müller, Waste Manag. 25 (2005) 887. [7] G. Versini, A. Dalla Serra, M. Falcetti, G. Sferlazzo, Rev. Oenol. 18 (1992) 19. [8] T.L. Mathus, D.E. Tovvnsendf, K.W. Miller, Fuel 74 (1995) 1505. [9] R.I. Mackie, P.G. Stroot, V.H. Varel, J. Anim. Sci. 76 (1998) 1331. [10] J. Zhu, Agric. Ecosys. Environ. 78 (2000) 93. [11] S. Van Beek, F.G. Priest, Appl. Environ. Microbiol. 66 (2000) 5322. [12] F. Angerosa, Eur. J. Lipid Sci. Technol. 104 (2002) 639. [13] M.T. Morales, G. Luna, R. Aparicio, Food Chem. 91 (2005) 293. [14] F. Angerosa, B. Lanza, V. Marsilio, Grasas Aceites 47 (1996) 142. [15] E.P. Giannoutsou, C. Meintanis, A.D. Karagouni, Biores. Technol. 93 (2004) 301. [16] J. Reiners, W. Grosch, J. Agric. Food Chem. 46 (1998) 2754. [17] M. Brenes, C. Romero, A. García, F.J. Hidalgo, M.V. Ruiz Jiménez, J. Agric. Food Chem. 52 (2004) 8177. [18] A. Jiménez, M.P. Aguilera, G. Beltrán, M. Uceda, J. Chromatogr. A 1121 (2006) 140. [19] J.J. Sánchez Saez, M.D. Herce Garraleta, T. Balea Otero, Anal. Chim. Acta 247 (1991) 295. [20] G.L. Long, J.D. Winefordner, Anal. Chem. 55 (1983) 712. [21] IUPAC Compendium of Chemical Terminology, 2nd ed., 1997, see http://iupac.org/publications/analytical compendium/Cha18sec437.pdf. [22] Statgraphics Plus 5.1 for Windows, Statistical Graphic Corp., Online Manuals, 1994, Herndon, Virginia. [23] F. Perreau, J. Einhorn, Anal. Bioanal. Chem. 386 (2006) 1449. [24] V. Mani, in: J. Pawliszyn (Ed.), Applications of Solid Phase Microextraction, Royal Society of Chemistry, Cambridge (UK), 1999, p. 57. [25] S. Vichi, A.I. Castellote, L. Pizzale, L.S. Conte, S. Buxaderas, E. López-Tamames, J. Chromatogr. A 983 (2003) 19. [26] B.D. Page, G. Lacroix, J. Chromatogr. A 873 (2000) 79. ˜ J. Cacho, V. Ferreira, J. Agric. Food Chem. 55 [27] A. Escudero, E. Campo, L. Farina, (2007) 4501. [28] R. Iraqi, C. Vermeulen, A. Benzekri, A. Bouseta, S. Collin, J. Agric. Food Chem. 53 (2005) 1179. [29] A. Högnadóttir, R.L. Rouseff, J. Chromatogr. A 998 (2003) 201. [30] B. d’Acampora-Zellner, P. Dugo, G. Dugo, L. Mondello, J. Chromatogr. A 1186 (2008) 123. [31] L. Moio, D. Langlois, P.X. Etievant, F. Addeo, Ital. J. Food Sci. 5 (1993) 227. [32] M. Czerny, W. Grosch, J. Agric. Food Chem. 48 (2000) 868. [33] S. Boutou, P. Chatonnet, J. Chromatogr. A 1141 (2007) 1. [34] P. Ribereau-Gayon, Y. Glories, A. Maujean, D. Dubourdieu, Traité d’oenologie, 2, Chemie du vin - Stabilisation et traitements, Dunod, 1998, Paris. [35] C. Bayonove, R. Baumes, J. Crouzet, Z. Günata, in: C. Flanzy (Ed.), Enología: Fundamentos científicos y tecnológicos, AMV Ediciones, Madrid, 2000, p. 137.
Contents lists available at ScienceDirect
Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma
Determination of volatile phenols in virgin olive oils and their sensory significance Stefania Vichi a,∗ , Agustí Romero b , Joan Tous b , Elvira López Tamames a , Susana Buxaderas a a Departament de Nutrició i Bromatologia, Xarxa de Referència en Tecnología dels Aliments (XaRTA), Facultat de Farmàcia, Universitat de Barcelona, Avinguda Joan XXIII, s/n, E-08028 Barcelona, Spain b Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Arboricultura Mediterránea Mas de Bover, Carretera De Reus - El Morell 43120 Constantí (Tarragona), Spain
a r t i c l e
i n f o
Article history: Received 26 July 2008 Received in revised form 17 September 2008 Accepted 22 September 2008 Available online 25 September 2008 Keywords: Virgin olive oil Volatile phenols Solid-phase microextraction Off-flavour Odour threshold Phenol Guaiacol o-, m-, p-Cresol 4-Ethylphenol 4-Ethylguaiacol 4-Vinylphenol 4-Vinylguaiacol
a b s t r a c t Volatile phenols are strong odorants produced by microbial activity and reported in several foods, but very scarce information is available on their presence in virgin olive oils (VOOs) and on their relation with VOO chemical and sensory quality. In the present paper, a factorial experimental design was applied for the development of a suitable solid-phase microextraction–gas chromatography/mass spectrometry (SPME–GC/MS) analytical method for the analysis of volatile phenols in olive oil. The memory effects demonstrated by SPME fibres required the optimization of desorption conditions to minimize experimental errors. A series of nine volatile phenols were identified and quantified for the first time in VOOs by analyzing samples with distinct off-flavours. Their limits of detection and quantification (g/kg) were largely below the odour detection thresholds (ODTs) calculated in this study (mg/kg), confirming the capacity of the technique to assess the target compounds at early stages of the oil sensory alteration. The odour activity values (OAVs) of volatile phenols were calculated in VOOs facilitating a first assessment of their potential importance in the aroma of the product. © 2008 Elsevier B.V. All rights reserved.
1. Introduction Volatile phenols are reported as aroma contributors in several foods [1–5], as well as strong odorants in gas emissions from agricultural operations [6]. In some cases, they are essential for the overall food flavour perception like in the case of certain beers [4] and wines [7], but they become undesirable when their concentration exceed certain limits, leading to typical phenolic off-flavour [1–4]. Volatile phenols are principally a result of the activity of microorganisms [1,4,8–11], and their presence and sensory significance have been widely studied in several foods and beverages like wine, beer, spirits [11], fruit juices [2,3], and pepper [5], but very few data are available on their presence in virgin olive oils. The typical volatile profile of virgin olive oil (VOO), highly appreciated and preserved for the absence of refining, can be altered by various factors related with the quality of olives and oil storage [12]. Microbial
∗ Corresponding author. Tel.: +34 93 4024508; fax: +34 93 4035931. E-mail address: [email protected] (S. Vichi). 0021-9673/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2008.09.067
proliferation during the storage of olives in unsuitable conditions or oil in contact with muddy sediments is one of the principal factors affecting VOO quality [12,13]. Numerous volatile compounds are well known to be present in defective VOO and several of them have been shown to contribute to distinct VOO off-flavours [13]. Nevertheless, although fermentations conducted by several fungi and bacteria isolated in olives [14,15] could produce volatile phenols, very scarce information is available on the relation between these compounds and VOO chemical and sensory quality. The studies conducted on this topic indicate that they could contribute to the off-flavour of defective oils: guaiacol was proved to be a key odorant in a VOO reminiscent of black olives [16] and in a musty olive oil [13], while 4-ethylphenol demonstrated some odour impact in stored olive paste and in oils from second centrifugation [17]. Moreover, 4-ethylphenol was found to be especially abundant in oils from ground-picked olives [18], and 4-vinylphenol was detected but not quantified in off-flavour VOOs [19]. The detection of the single guaiacol, ethylguaiacol or vinylphenol among VOO volatiles has been achieved by dynamic headspace [13], solid-phase microextraction (SPME) [18], or distillation [16,19], followed by gas chromatography.
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S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
Ethylphenol was also detected in the phenolic fraction of VOO after liquid-liquid extraction followed by liquid chromatography [19]. The availability of reliable chemical and sensory markers is acquiring an increasing importance in view of the need to guarantee VOO quality. Volatile phenols could be suitable indices of microbiological degradation of olives or oils, as well as possible contributors of the VOO aroma perception. Nevertheless, the data on the occurrence, the concentrations and the odour impact of this class of compounds in VOOs are quite scarce, and there is a lack of specific analytical methods for their determination. The aim of the present paper was to determine the presence of several volatile phenols in VOOs and their potential significance from the organoleptic point of view. With this purpose, a suitable SPME method coupled to GC/MS was developed for the determination of nine volatile phenols, and applied to a selected group of VOOs with different sensory defects. Odour thresholds of the target phenols and their odour activity values in oils were then determined for the first time to assess the sensory significance. 2. Materials and methods 2.1. Reagents and materials The SPME fibres tested were divinylbenzene/Carboxen/polydimethylsiloxane 50 m/30 m, 2 cm long (DVB/CAR/PDMS), polydimethylsiloxane/divinylbenzene 65 m (PDMS/DVB), and Carbowax/divinylbenzene 65 m (CW/DVB), all from Supelco (Bellefonte, PA, USA). Phenol, o-, p-cresol, 4-ethylphenol, 2,3-dimethylphenol, 4vinylphenol (solution 10%, w/w in propylene glycol), guaiacol, 4-ethylguaiacol and vinylguaiacol came from Sigma–Aldrich (St. Louis, MO, USA). 2.2. Standard solutions Standard solutions of the above mentioned phenols were directly prepared in refined sunflower oil in order to avoid interferences due to the use of solvents. For the calibration of the analytical method and determination of repeatability and memory effects, a standard mixture of phenol, o-, p-cresol, 4-ethylphenol, 4-vinylphenol, guaiacol, 4-ethylguaiacol and vinylguaiacol was prepared in refined sunflower oil, while for the determination of phenols’ odour thresholds, solutions of the single phenols in refined sunflower oil were prepared. The internal standard solution of 2,3-dimethylphenol was also prepared by dilution in refined olive oil. Oil standard solutions at various concentrations described in the corresponding sections, were obtained by spiking refined sunflower oil with these stock solutions.
Table 1 Description of the VOO samples Code 1 2 3 4 5 6 7 8
Alteration/defect No defects (control) No defects (control) Fusty/fermented olive paste Fusty Fusty/musty Musty Muddy Muddy
a b c d e f
Oil
Supplier a
EVOO EVOO STDc STD VOOf STD VOO STD
COPb COP MAPAd IOOCe COP IOOC COP COP
Extra virgin olive oils, mean of sensory defects = 0. Catalonian Official Panel. Standard oil used in the training process for assessors to detect sensory defects. MAPA (Spanish Ministerio de Agricultura, Pesca y Alimentación). International Olive Oil Council. Virgin olive oil, median of sensory defects > 0.
10 min, respectively. During each chromatographic run, the fibre was maintained retracted in the holder at ambient temperature. Temperature of desorption was 265 ◦ C for DVB/CAR/PDMS and PDMS/DVB fibres, and 240 ◦ C for CW/DVB, according to the maximum operating temperature recommended by the supplier for each fibre. 2.5. SPME conditions In order to evaluate suitable extraction conditions for the determination of volatile phenols in VOO, distinct variables were tested by a multilevel factorial experimental design. The variables were the type of fibre coating: DVB/CAR/PDMS (1), PDMS/DVB (2), CW/DVB (3), extraction temperature (40, 50, 60 ◦ C) and extraction time (30, 60 min). The factorial design consisted in 18 experiments performed in duplicate. SPME analyses were carried out by weighing 2 g of a virgin olive oil into a 10 ml vial fitted with a silicone septum, then placing it into a silicone oil bath were the sample was maintained under magnetic stirring (700 rpm). After 10 min of sample conditioning, each fibre was exposed for different time periods (30 or 60 min) and immediately desorbed in the gas chromatograph injector. Each extraction was performed in duplicate. Chromatographic responses of volatile phenols were monitored. The results of the experimental design (chromatographic area counts) were analyzed by a standardized Pareto diagram and the optimal value of each factor involved in the extraction was statistically calculated. The sorption of volatiles in the samples headspace was finally performed using the DVB/CAR/PDMS coating, during 30 min at a temperature of 60 ◦ C. 2.6. GC–MS analysis
2.3. Olive oil samples A heterogeneous group of eight olive oils were analyzed by applying the developed method to assess the volatile phenols (Table 1). The samples were selected for having distinct types of alterations, reflected by various sensory defects. 2.4. Memory effects and desorption conditions The memory effects of each fibre (DVB/CAR/PDMS, PDMS/DVB, CW/DVB) were compared under the following conditions: 2 g of a standard solution of volatile phenols in oil (1 mg/kg) was extracted by SPME (60 ◦ C for 60 min). After the extraction, the fibres were desorbed during 5 min, then retracted from the injection port and successively desorbed four consecutive times during 5, 10, 10 and
Identification of compounds was carried out by gas chromatography coupled to quadrupole mass selective spectrometry using an Agilent 5973 Network detector (Agilent Technologies, Palo Alto, CA, USA). Analytes were separated on a Supelcowax-10 (Supelco, Bellefonte, PA) 30 m × 0.25 mm ID, 0.25 mm film thickness. Column temperature was held at 50 ◦ C for 10 min, increased to 240 ◦ C at 8 ◦ C/min. The injector temperature was 265 ◦ C and the time of desorption of the fibre into the injection port was fixed at 10 min. Helium was the carrier gas, at a linear velocity of 38 cm/s. The temperature of the ion source was 175 ◦ C and the transfer line, 280 ◦ C. Positive electron ionization mass spectra (EIMS) were recorded at 70 eV ionization energy, 2 scan/s. GC–MS analysis in the complete scanning mode (SCAN) in the 40–300 m/z range allowed the identification of compounds in oil
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
samples, by comparison of their mass spectra and retention times with those of standard compounds. Quantitative assessment of volatile phenols was carried out in the selected ion monitoring mode (SIM) in order to improve the detection limits. For each phenol the following qualifier and quantifier (underlined) ions were analyzed: m/z 109, 124 (guaiacol), m/z 77, 94 (phenol), m/z 107, 108 (o-, m-, p-cresol); m/z 137, 152 (4ethylguaiacol), m/z 107, 122 (4-ethylphenol, 2,3-dimethylphenol), m/z 135, 150 (4-vinylguaiacol), m/z 91, 120 (4-vinylphenol). Base peak ions were used for quantification of compounds. 2.7. Method assessment Calibration was performed by analyzing deodorized sunflower oil with different concentrations of volatile phenols. Standard solutions were prepared in the range 0.01–10 mg/kg and analyzed in duplicate under the same conditions described for samples. Internal standard (2,3-dimethylphenol) concentration was maintained at 5 mg/kg. The method was assessed by determining relative response factors (with respect to internal standard 2,3-dimethylphenol), linearity of response (regression coefficient values—r), repeatability (as relative standard deviation—RSD), and limits of detection (LOD) and quantification (LOQ). Repeatability of the method was tested by repeating five times the analysis of a 0.05 mg/kg standard mixture. LOD and LOQ were calculated as LOD = 3ı/m and LOQ = 10ı/m, respectively, according with [20] and [21] definitions, where ı is the standard deviation of the baseline noise and m is the slope of the calibration curve. 2.8. Determination of the odour detection threshold (ODT) concentration in oil of volatile phenols and their odour activity values (OAVs) in VOO samples Odour thresholds were determined by a three-alternative forced-choice (3-AFC) procedure. Directional triangular tests of increasing concentrations of volatile phenols in refined sunflower oil were analyzed by 12 trained sensory assessors (30 ml of oil solution were presented in 160-ml covered glasses). The panel room was maintained at 25 ◦ C. The odour detection threshold was the minimum concentration at which 50% of the sensory assessors were able to perceive a difference in odour between the spiked and non-spiked media. Phenol, o-, p-cresol, 4-ethylphenol, 4-vinylphenol, guaiacol, 4-ethylguaiacol, vinylguaiacol were tested from 0.01 to 0.4 mg/kg along two sessions (0.1, 0.2, 0.4 mg/kg concentrations were tested during the first session and 0.01, 0.025, 0.05 mg/kg concentrations were tested during the second session). An additional concentration of 0.005 mg/kg was tested for guaiacol. In order to evaluate the potential sensory importance of volatile phenols in VOO samples, their odour activity values were also calculated as the ratio of concentration and odour threshold.
3
the effects that are statistically significant. Bars that extend beyond the line correspond to effects that are statistically significant at the 95% confidence level [22]. The magnitude of the principal effects and the interaction among factors were also evaluated by analyzing their correspondent graphical representations. 3. Results and discussion 3.1. Memory effects and desorption conditions Preliminary assays allowed observing a noticeable memory effect of SPME fibres for volatile phenols. To avoid these undesirable effects, fibres’ desorption efficiency was monitored at increasing periods of desorption performed at the maximum suitable temperature. After the extraction of a standard solution of volatile phenols in oil (1 mg/kg of guaiacol, phenol, o-, p-cresol, 4-ethylphenol, 4ethylguaiacol, 4-vinylphenol and 4-vinylguaiacol), each fibre was desorbed during 5 min. To assess the residual amount of analytes on the fibre, it was desorbed again in the GC injector port during further 5 min, repeating this procedure until a total of 40 min, as detailed in Table 2. After 40 min of desorption the residual volatile phenols were near or below the LOQ, depending on the fibre, and it was assumed that the 100% of analytes were desorbed. The CW/DVB fibre showed the fastest desorption of analytes, while PDMS/DVB and in particular DVB/CAR/PDMS were characterized by a slower desorption and a considerable memory effect. This is in accordance with previously reported results [23]. The slower desorption of DVB/CAR/PDMS could be due in part to the Carboxen phase, which is reportedly characterized by very small pores [24] and long desorption times [25]. The percent amount of analytes desorbed during the first 5 min was 94.5% for DVB/CAR/PDMS, 97.1% for PDMS/DVB, and 99.2% for CW/DVB (Table 2). In particular, 4-vinylguaiacol and 4-vinylphenol showed the slowest desorption from the three coatings, and their amount desorbed after 5 min was lower than 90% for DVB/CAR/PDMS, around 95 and 93% for PDMS/DVB, and around 98% for CW/DVB. Further 5 min of desorption allowed reaching mean amounts of volatile phenols higher than 98%, and amounts of 4-vinylguaiacol and 4-vinylphenol higher than 96%, for all the fibres tested. Mean memory effects of around 0.2% DVB/CAR/PDMS and PDMS/DVB and lower than 0.1% for CW/DVB were reached after 30 min of desorption. The operative desorption conditions were established with the aim to obtain an acceptable percent uptake of volatile phenols and to avoid contamination between samples due to unwanted memory effects. On this basis, desorption time was fixed at 10 min, opening the split valve after this time, while the fibre in was kept the injection port for further 20 min for a cleaning step, until a total of 30 min. A supplementary cleaning was performed after the analysis of very concentrated samples, to ensure that residual phenols were below the LOQ.
2.9. Statistical analysis
3.2. Optimization of SPME conditions
The multilevel factorial experimental design was performed using the package “Statgraphics Plus 5.1”. For the optimization of SPME conditions four variables were tested at four, three, or two factor levels, as described in the SPME conditions paragraph. The results of the experimental design, evaluated at a 5% of significance, were analyzed by a standardized Pareto diagram, which displays a frequency histogram where the length of each bar on the chart is proportional to the absolute value of its associated estimated effect or the standardized effect. The standardized effect is the estimated effect divided by its standard error, which is equivalent to computing a t-statistic for each effect. The vertical line on the plot judges
In order to optimizing the extraction conditions for detection of volatile phenols in VOO, three distinct experimental factors were tested by a multilevel factorial experimental design: type of fibre coating, temperature and time of extraction. Among the commercially available fibres, the DVB/CAR/PDMS (1) fibre was tested due to the high uptakes of organic volatile compounds described to be reached by this coating [25,26], and for the availability of fibres with a higher coating volume (double fibre length). PDMS/DVB (2) and CW/DVB (3) fibres were tested in view of their polarity, which could determine a higher affinity for volatile phenols. The amount of sample was not studied because in the case of lipid matrices
0.0 0.1 0.2 0.5 99.2 0.2 0.5 0.7 1.5 97.1
e
c
d
b
0.2 0.5 1.2 3.6 94.5 Mean
3.3. Method assessment Percent amount of analytes desorbed during the first 5 min. Percent amount of analytes desorbed from 5 to 10 min. From 10 to 20 min. From 20 to 30 min. From 30 to 40 min.
0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0
it does not significantly affect the mass of analyte absorbed by the SPME coating [26]. The influence of each experimental factor on the extraction of volatile phenols was evaluated by means of standardized Pareto diagrams (Fig. 1a). To simplify the graphical representation, volatile phenols were grouped according to their behaviour in function to the extraction factors, and showed as sum of phenol and guaiacol and sums of their respective methyl, ethyl, and vinyl derivatives. For all the groups of phenols, the type of coating and the extraction temperature showed significant influence on the chromatographic responses, while the extraction time had no significant effects on the uptake of phenol and guaiacol. Some significant interactions between temperature and the other factors were observed for all the alkylated phenols (Fig. 1c) reflecting an enhancement of the factors’ positive effect on phenols uptake at the highest temperature. The diagram of principal effects (Fig. 1b) shows that the highest uptake of all the volatile phenols was given by the DVB/CAR/PDMS fibre, and extraction temperature of 60 ◦ C. As expected, the positive effect of temperature was higher for less volatile compounds, likely due to an increase of their transfer to the headspace. On the other hand, the uptake of less volatile phenols was less influenced by the type of SPME sorbent. In this case, the positive effect observed for DVB/CAR/PDMS fibre could be given to a higher capacity related to the volume of the coating (2 cm of fibre length versus 1 cm). On the basis of these results, the extraction temperature of 60 ◦ C and the DVB/CAR/PDMS fibre were chosen, in spite of the higher memory effect observed for this coating. Regarding the extraction time, it had a significant effect on the uptake of alkylated phenols, which was higher after 60 min of extraction. Nevertheless, after verifying that at the shortest extraction time the lowest levels of phenols were largely above the LOQ, the time of 30 min was chosen to perform the analysis, taking into account the long desorption step required for the chosen fibre. To prove that the chosen extraction temperature of 60 ◦ C did not induce the formation of artefacts in the samples, and influenced the chromatographic responses only by acting on the extraction efficiency, olive oil samples were analyzed by a SPME extraction at 40 ◦ C during 60 min, with (n = 6) and without (n = 6) a previous thermal treatment (60 ◦ C for 60 min). A student t-test showed that the mean areas of volatile phenols in the two groups were not significantly different (p > 0.05, data not shown), demonstrating that only the extraction efficiency was significantly influenced by the temperature of 60 ◦ C and no alterations of the sample were induced by the extraction conditions.
a
30 min
0.0 0.2 0.0 0.0 0.1 0.0 0.2 0.2 0.1 0.3 0.1 0.1 0.1 0.1 0.6 0.7
20 min 10 min
0.3 0.5 0.3 0.3 0.3 0.3 0.8 1.0 99.6 99.0 99.6 99.6 99.5 99.6 98.5 98.2 0.0 0.4 0.0 0.1 0.1 0.0 0.2 0.4 0.0 1.2 0.1 0.2 0.3 0.1 0.6 1.3 0.1 1.6 0.1 0.3 0.3 0.1 1.4 2.4 1.5 1.0 0.8 1.4 1.3 0.5 2.6 3.1 0.1 0.2 0.1 0.1 0.1 0.1 0.4 0.5 0.4 0.6 0.3 0.4 0.4 0.2 0.9 1.4 1.1 0.8 0.8 1.3 1.0 0.5 2.0 2.8 2.5 1.9 1.8 3.3 2.3 1.2 6.8 8.8 96.0 96.5 97.0 94.7 96.2 98.0 89.9 87.3 Guaiacol Phenol o-Cresol p-Cresol 4-Ethylphenol 4-Ethylguaiacol 4-Vinylguaiacol 4-Vinylphenol
CW/DVB
5 min 40 min 30 min 20 min 10 min
PDMS/DVB
5 min 40 mine 30 mind 20 minc 10 minb 5 mina
DVB/CAR/PDMS Compound
98.3 95.8 99.0 98.0 98.1 99.3 95.3 93.4
40 min
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7 Table 2 Amount of analytes desorbed from three distinct coatings during increasing periods of desorption performed at the maximum suitable temperatures (265 ◦ C for DVB/CAR/PDMS and PDMS/DVB, 240 ◦ C for CW/DVB), after the extraction of a standard solution at 1 mg/kg of each phenol
4
After the determination of suitable SPME parameters, the method performances were assessed by determining relative response factors, linearity of response, repeatability, and limits of detection and quantification for the target volatile phenols (Table 3). A satisfactory linearity was obtained within the whole interval of concentration tested, with regression coefficients higher than 0991. The relative standard deviation (RSD) calculated at a concentration of 0.05 mg/kg standard mixture was lower than 10% for all the volatile phenols. As expected, the highest response factors with respect to the internal standard 2,3-dimethylphenol were calculated for the most volatile compounds phenol and guaiacol, while the highest values were observed for their vinyl derivatives. LODs and LOQs were in the ranges of 0.09–0.78 and 0.3–2.6 g/kg, respectively. The chromatographic resolution and the absence of significant interference due to the oil matrix and therefore the satisfactory selectivity of the developed SPME–GC/MS method can be appreciated in Fig. 2.
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
5
Fig. 1. (a) Standardized Pareto diagrams showing degree of influence of each experimental factor on the response of four groups of volatile phenols, taking into account the standard error. Bars that extend beyond the vertical line in the Pareto diagram correspond to effects that are statistically significant at the 95% confidence level. A: temperature; B: time; C: fibre (fibre 1: DVB/CAR/PDMS; fibre 2: PDMS/DVB; fibre 3: CW/DVB). (b) Graphics of principal effects and (c) graphics of interactions among factors.
Table 3 Characterization of volatile phenols detected in virgin olive oils and performances of the SPME–GC/MS method
1 2 3 4 5 6 7 8 9
Guaiacol Phenol o-Cresol p-Cresol m-Cresol 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol 4-Vinylphenol a b c d e f g h i j
IDa
KIb
Ionc
RSDd (n = 5)
RFe
rf
LODg (g/kg)
LOQh (g/kg)
Si S S S MS, RIj S S S S
1855 1994 1992 2073 2080 2024 2165 2193 2480
109 94 107 107 107 137 107 150 120
5.7 5.8 4.2 7.7 – 7.1 6.3 8.9 9.9
3.60 3.54 1.84 1.44 – 1.19 1.33 0.12 0.11
0.9997 0.9988 0.9993 0.9989 – 0.9972 0.9982 0.9961 0.9912
0.09 0.13 0.25 0.32
0.3 0.4 0.8 1.1
0.12 0.35 0.69 0.78
0.4 1.2 2.3 2.6
Identification method. Kovats indices on Supelcowax-10 capillary column. Ion used for quantification. Relative standard deviation (%) calculated on a 0.05 mg/kg standard mixture. Relative response factor (internal standard 2,3-dimethylphenol). Linearity within the range of concentration 0.010–10 mg/kg, expressed as regression coefficient. Limit of detection. Limit of quantification. Identified by comparison with standard compounds. Tentatively identified by mass spectra (MS) and retention index (RI).
2 6 8 2
114 1 3 5 3 5 1 3 8 30 1 1 1 17 346 294 23
201 5
2
1 14 57
48 12 2 1
2 2 5 1
41 1 75 2
2
6 57 1 590 2
2 0.1 0.025 0.025
– 0.05 0.2 0.2
0.4
Phenol o-Cresol p-Cresol
m-Cresold 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol
4-Vinylphenol
Woody, smoky, spicy [13]; phenolic, burnt [16]; bad olives [28]; green, fatty [29]; harsh, earthy [30] – – Faecal, horse-like [5]; phenolic, musty [31] Phenolic [5]; manure, plastic [29]; Sweet [32]; spicy [30] Phenolic [33]; horse-like, stable [34] Clove-like [33,35]; spicy, eugenol-like [30]; pharmaceutical [33] Pharmaceutical, gouache [33,35]; carnation [35]; varnish [34] 0.01
Only OAVs ≥ 1 are reported. a Odour activity value. b Odour detection thresholds. c Odour notes described in literature. d OAVs calculated by using the same ODT of o- and p-cresol.
7 (VOO-muddy) 6 (STD-musty) 5 (VOO-fusty/musty) 4 (STD-fusty) 3 (STD-fusty/ferm.) 2 (EVOO) 1 (EVOO)
OAVa
Guaiacol
An extensive sampling of EVOO, VOO and defective olive oils would be necessary to relate the content of volatile phenols to specific alterations of olive oil flavour or to specific variables of the oil’s production process. In the present study, the concentrations and the proportions of each volatile phenol were monitored within a limited number of selected samples, as a preliminary step to associate these compounds to specific oil alterations and to orientate further investigations on this topic (Table 1). The samples were selected for having distinct types of alterations, reflected by various sensory defects. Their analysis by the method presented in this paper allowed detecting and quantifying for the first time a series of nine volatile phenols with phenol and guaiacol structure, comprising methyl, ethyl and vinyl derivatives. These compounds are reported in Table 3, together with their identification data and the perfor-
Odour note (lit.)c
3.5. Characterization and quantification of volatile phenols in VOO
ODTb (mg/Kg)
Table 4 reports the odour thresholds of volatile phenols determined in refined sunflower oil. The lowest ODT was determined for guaiacol, while the highest ODT were observed for phenol and 4-ethylphenol. The ODT of volatile phenols calculated in oil are in some cases higher but quite in accordance with those observed in hydroalcoholic solution, which were resumed by Escudero et al. [27]. The LOQ of volatile phenols obtained by the proposed analytical method (Table 2) were always much lower (g/kg) than the correspondent ODTs (mg/kg)(Table 4), confirming the suitability of the technique to assess the target compounds at early stages of the oil sensory alteration.
Volatile phenols
3.4. Determination of the odour detection threshold in oil of volatile phenols
Table 4 Odour detection thresholds (ODTs) in refined sunflower oil, odour activity values (OAVs) of volatile phenol in virgin olive oil samples, and odour notes of volatile phenols as described in literature
Fig. 2. Extracted ion chromatogram of volatile phenols, obtained by analyzing virgin olive oil sample 3 (Table 1) by the optimized SPME–GC/MS method. Separation was performed on a Supelcowax capillary column and peaks are identified according to Table 3.
14
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7 8 (STD-muddy)
6
S. Vichi et al. / J. Chromatogr. A 1211 (2008) 1–7
7
Table 5 Concentrations (mg/kg) of volatile phenols in virgin olive oils (mean of two replicates) Volatile phenols
Guaiacol Phenol o-Cresol p-Cresol m-Cresol 4-Ethylguaiacol 4-Ethylphenol 4-Vinylguaiacol 4-Vinylphenol Sum
Olive oil samples 1 (EVOO)
2 (EVOO)
3 (STD-fusty/fermented)
4 (STD-fusty)
5 (VOO-fusty/musty)
6 (STD-musty)
7 (VOO-muddy)
8 (STD-muddy)
0.003 0.211 0.001 0.005 0.008 0.009 0.079 0.053 0.304 0.548
0.004 0.180 0.003 0.004 0.005 0.007 0.035 0.039 0.294 0.467
0.019 0.167 0.008 0.036 0.034 0.686 11.5 0.127 1.83 14.3
5.91 4.07 0.016 1.46 0.434 17.35 59.0 4.61 80.6 171.2
0.013 0.142 0.004 0.010 0.009 0.048 0.231 0.133 0.960 1.47
0.567 0.535 0.011 0.030 0.075 0.410 5.91 0.270 3.24 10.7
0.063 0.152 0.006 0.230 0.133 0.152 1.02 0.272 2.60 4.60
0.142 0.233 0.006 0.942 2.85 0.032 0.567 0.063 0.912 5.87
mances of the analytical method. The volatile phenols target of this study were detected in all the analyzed samples, at different concentrations (Table 5). The concentration of volatile phenols seems to depend on the presence of oil alterations, as can be observed by comparing their total amounts in the selected samples. Phenol and o-cresol maintained quite similar levels in all the oils, while guaiacol and in particular ethyl derivatives were clearly higher in defective oils. Vinyl derivatives showed higher concentrations in defective oils than in EVOOs, although the difference between these groups of oils was much lower than observed for ethyl derivatives. m- and p-cresol reached the highest amounts in muddy oils. 3.6. Odour activity values The ratio between the odorant concentration and its odour threshold is known as OAV. This parameter allows making a first assessment of the potential importance of a specific compound to the aroma of a product. Table 4 shows the OAVs of volatile phenols present in olive oil samples and the odour notes described in literature for each compound. The results reported in this table indicate that phenol has OAVs ≥1 in all the oils analyzed, comprising EVOOs and oils with strong off-flavour. These data suggest that phenol could contribute in the overall aroma of both EVOO and defective olive oils, even if their role in the aroma perception is probably different according to their concentration. On contrary, vinyl, ethyl derivatives and guaiacol seem to have some sensory significance only in defective oils, especially in musty and fusty olive oils (Table 5). Regarding cresol isomers, the OAVs obtained in the study (by applying to m-cresol the same ODT than o- and p-cresol) showed that p- and m-cresol are the most significant odorant phenols in muddy olive oils. The odour note described in literature for p-cresol suggests that this compound probably contribute to the typical faecal off-flavour of muddy olive oils. On contrary, the ortho isomer seems to have a scarce sensory impact in defective oil, with concentration near to the ODT in the fusty oil. In conclusion, the development of a suitable SPME–GC/MS method by a factorial experimental design and its application to a heterogeneous group of VOOs selected for having distinct types of alterations, led to identify and quantify for the first time a whole series of nine volatile phenols. The optimized desorption conditions prevented from the experimental errors due to the memory effects demonstrated for SPME fibres. The ODTs of volatile phenols in oil matrix calculated in the present study confirmed the capacity of the technique to assess the target compounds at the early stages of the oil sensory alteration, given that LOD and LOQ were largely below the correspondent ODTs. The calculation of OAVs of volatile phenols in EVOOs and defective VOOs made it possible a first assessment of their potential importance in the aroma of the product.
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