Abstract
The current study aimed to compare the effectiveness of two extraction techniques, namely simultaneous distillation–extraction (SDE) and solid-phase microextraction (SPME), in evaluating key aroma compounds in butters. Volatile compounds’ contributions to butter flavors were evaluated employing both odor active values (OAVs) and gas chromatography olfactometry (GC-O). The results showed that the species of volatile compounds detected by the two techniques were almost the same, whereas their volatile profiles were obviously different. Using SDE method, methyl ketones took up the largest proportion of the volatile compounds, followed by fatty acids. Using SPME method, the most abundant compounds were the fatty acids, followed by lactones. More methyl ketones were detected in the SDE extract owing to lipid degradation as a consequence of the high temperature during extraction. Lactones were considered to be the key aroma compounds, especially δ-decalactone, which was identified by both OAVs and GC-O.
Keywords: Simultaneous distillation extraction, Solid-phase microextraction, Butter, Volatile organic compound, Key aroma compound
Introduction
Various techniques have been applied to the identification of volatile compounds in dairy products, including mainly solvent assisted flavor evaporation (SAFE), simultaneous distillation–extraction (SDE), purge and trap (PT), and solid-phase microextraction (SPME) (Li et al., 2012; Peterson and Reineccius, 2003a; Povolo and Contarini, 2003). SDE using a Likens–Nickerson extractor combines the advantages of liquid–liquid and steam distillation extraction to provide better extraction performance, however, the SDE method may lack sensitivity and is time-consuming (Cai et al., 2001). In recent years, SPME has been more readily employed to analyze volatiles, due to its convenience. SPME uses coated, 1- to 2 cm-long, fused silica fibers to adsorb volatiles in the headspace (Parker, 2015), however the results of SPME extraction of volatiles are dependent on the characteristics of the particular SPME fibers and the properties of the volatile compounds. Not all volatile compounds detected using GC–MS analysis in dairy products serve as aroma contributors. Thus, OAVs and GC-O methods are in need to evaluate the role of a certain volatile compound in deciding the flavor characteristics of dairy products. OAVs method is based on analyze the ratio of the determined concentration of a certain compound to its perception threshold in similar matrix. GC-O method is based on sniffing the GC effluents of the sample extract by trained assessors.
Butter is an important food ingredient, widely consumed all over the world and more than 230 volatile compounds have been identified in butter (Nursten, 1997). Those key odorants in butter include, mostly, short-chain fatty acids (butyric acid, hexanoic acid, and decanoic acid), ketones (2,3-butanedione, 1-hexen-3-one, and 1-octen-3-one), lactones (δ-hexanolactone, δ-octalactone, δ-decalactone, and γ-dodecanolactone), aldehydes (acetaldehyde, hexanal, nonanal, (Z)-2-nonenal, and (E)-2-nonenal), and sulphur compounds (dimethyl sulfide) (Krause et al., 2007; Nursten, 1997; Peterson and Reineccius, 2003b). The sensory properties of butter are affected by many factors, such as climate, processing (Schieberle et al., 1993), and cows diet (Couvreur et al., 2006), and, consequently, flavor compounds in butters from different regions are also extensively different. However, a comprehensive study using different extraction methods to unveil volatile profiles of butters in the Chinese market has not been established. To address this, the extraction efficiencies of two extraction methods, SDE and SPME, were compared when measuring the flavor profiles of butters, and the primary contributors to the characteristic flavors were analyzed using OAVs and GC-O method respectively in this study.
Materials and methods
Materials
Two kinds of unsalted butter, B1 (produced in New Zealand) and B2 (produced in Belgium), were purchased from a local market in Beijing. Dichloromethane and methanol were purchased from MREDA (USA) and were of HPLC grade. A mixture of hydrocarbons, ranging from heptane (C7) to tetracontane (C40), was purchased from O2SI (USA), and 2-methyl-3-heptenone, used as internal standard, was from Dr. Ehrenstorfer (Germany).
Extraction of aroma compounds
SDE
One hundred and twenty grammes of a butter sample, 200 μL of 2-methyl-3-heptenone (130 mg/L), and 2 g of zeolites were added to 360 g distilled water and placed in a 1000 mL flask in the appropriate arm of the apparatus. 50 mL dichloromethane was put into a 100 mL vial connected to the other arm of the extractor. Solvent and sample mixtures were respectively incubated at 60 °C and 125 °C for 3 h. After cooling to ambient temperature, the extract was collected and frozen at − 18 °C overnight, while the unfrozen sample was dried by anhydrous Na2SO4 and concentrated to 0.5 mL using a slow nitrogen flow.
SPME
A 50/30 μm DVB/CAR/PDMS fiber (Supelco, Pennsylvania, America) was used for the SPME analysis. Briefly, 16 g of a sample at a time were placed in a 40 mL glass vial, and 50 μL of 2-methyl-3-heptenone solution (dissolved in methanol) at 130 mg/L was added into the vial as internal standard (I.S.). Afterwards, the 40 mL glass vial was crimp-capped with a Teflon-lined septum. After equilibration at 55 °C for 20 min, the fiber was pulled out of the needle and exposed to the headspace above the sample for 40 min.
Volatile compound analysis
The GC–MS analysis was conducted on a 7890 GC equipped with 5977A MS (Agilent, California, USA). A DB-WAX column (30 m × 320 μm × 0.25 μm, Agilent, California, USA) was used for separation. Helium was used as a carrier gas, with a total flow of 3.2 mL/min. The GC oven was held at 40 °C for 3 min, and then heated to 230 °C with increment of 5 °C/min from 40 to 170 °C, increment of 10 °C/min from 170 to 200 °C, and increment of 5 °C/min from 200 to 230 °C. At last, the oven was held at 230 °C for 4 min to confirm the cleanness of the column. The analysis of volatile compounds was performed in the splitless mode. The quadrupole mass spectrometer was operated in the electron impact (EI) mode and the source temperature was set at 230 °C. The mass spectra were acquired using full scans from m/z 50 to m/z 300.
The linear retention index (LRI) of every volatile compound was calculated using the retention times of the n-alkane series, which were injected under the same chromatographic conditions. The compounds were identified by comparing their LRIs to those published in the literature and, also, by comparing their mass spectra with the commercial mass spectral databases. The concentration of each volatile compound was determined by calculating the ratio of the peak area to the I.S. peak area.
Active aroma compounds analysis
In OAVs analysis, OAVs greater than or equal to 1 are considered to be key aroma compounds. In GC-O analysis, the sniffing was carried out using an olfactory detection port olfactometer (ODP3, Mulheim an der Ruhr, Germany). For each sample, GC-O analysis was performed in triplicate, and compounds detected more than twice by GC-O were considered as potential contributors to aroma.
Statistical analysis
SPSS statistical software (v. 20.0, IBM SPSS, USA) was used in the data analysis. The t test was applied to evaluate the differences in the content of volatile compounds in the two butters. The difference was regarded as statistically significant when p < 0.05.
Results and discussion
Aroma compounds analysis
The volatile profiles of butter extracted by SDE and SPME were shown in Table 1. Using SDE, a total of 23 kinds of volatile compounds were identified in two butters, whereas 22 kinds were detected in the SPME extract. The volatiles were divided into several categories, including methyl ketones (10 for SDE, 1 for SPME), lactones (4 for SDE, 4 for SPME), fatty acids (3 for SDE, 7 for SPME), aldehydes (1 for SDE, 3 for SPME), and some other compounds. It was worth noting that the aroma composition in the SDE and SPME extracts were obviously different. Using SDE, the concentration of methyl ketones in butters B1 and B2 were 2844.16 μg/kg and 2552.50 μg/kg, respectively, accounting for the largest proportion of the volatile compound profile. This was followed by the fatty acids (422.28 μg/kg for B1 and 285.11 μg/kg for B2) and the lactones (191.53 μg/kg for B1 and 265.24 μg/kg for B2). In the SPME analysis, the most abundant compounds were the fatty acids (3391.60 μg/kg for B1 and 6197.41 μg/kg for B2), followed by the lactones (1207.96 μg/kg for B1 and 2285.46 μg/kg for B2) and the aldehydes (730.61 μg/kg for B1 and 1748.60 μg/kg for B2). The species of volatile compounds detected in this study were similar with other authors (Krause et al., 2007; Peterson and Reineccius, 2003b).
Table 1.
Volatile composition of two butters using SPME and SDE (n = 3)
| Compounds | RI | RI′ | Thresholds (mg/kg) | SDE | SPME | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Estimated contents (μg/kg) | OAVs | Estimated contents (μg/kg) | OAVs | ||||||||
| B1 | B2 | B1 | B2 | B1 | B2 | B1 | B2 | ||||
| Methyl ketones | |||||||||||
| 2-Pentanone | 961 | 978a | 61d | 207.72 ± 25.09 | 192.78 ± 9.81 | 0.00 ± 0.00 | 0.00 ± 0.00 | NI | NI | NI | NI |
| 2-Methyl-3-pentanone | 1041 | NA | NA | 21.87 ± 5.84 | NI | NI | NI | NI | NI | NI | NI |
| 2-Hexanone | 1063 | 1046a | NA | 18.53 ± 0.55 | 24.11 ± 0.37** | NI | NI | NI | NI | NI | NI |
| 3-Penten-2-one | 1103 | 1121a | NA | 13.94 ± 0.34 | NI | NI | NI | NI | NI | NI | NI |
| 2-Heptanone | 1170 | 1180a | 15d | 788.56 ± 54.46 | 688.42 ± 41.61 | 0.05 ± 0.00 | 0.05 ± 0.00 | NI | NI | NI | NI |
| 2-Octanone | 1263 | 1283a | 2.5d | NI | 18.74 ± 0.95 | NI | 0.01 ± 0.00 | NI | NI | NI | NI |
| 2-Nonanone | 1371 | 1389a | 7.7d | 526.76 ± 35.23 | 496.72 ± 37.23 | 0.07 ± 0.00 | 0.06 ± 0.00 | 84.10 ± 39.89 | 193.54 ± 11.83 | 0.01 ± 0.01 | 0.03 ± 0.00 |
| 2-Undecanone | 1579 | 1596a | 100d | 400.54 ± 36.26 | 382.68 ± 32.55 | 0.00 ± 0.00 | 0.00 ± 0.00 | NI | NI | NI | NI |
| 2-Tridecanone | 1788 | 1817a | 182d | 401.97 ± 48.82 | 362.97 ± 39.01 | 0.00 ± 0.00 | 0.00 ± 0.00 | NI | NI | NI | NI |
| 2-Pentadecanone | 2000 | 2022b | NA | 464.25 ± 54.24 | 386.08 ± 51.71 | NI | NI | NI | NI | NI | NI |
| In total | 2844.16 | 2552.50 | 84.10 | 193.54 | |||||||
| Lactones | |||||||||||
| δ-Hexalactone | 1737 | NA | 5f | NI | NI | NI | NI | 105.07 ± 44.42 | 152.18 ± 73.78 | 0.02 ± 0.01 | 0.03 ± 0.01 |
| δ-Octanolactone | 1913 | 1902b | 0.1f | NI | NI | NI | NI | 329.35 ± 149.27 | 551.04 ± 238.57 | 3.29 ± 1.49 | 5.51 ± 2.39 |
| δ-Decalactone | 2143 | 2203c | 1f | 40.07 ± 2.97 | 50.69 ± 7.50 | 0.04 ± 0.00 | 0.05 ± 0.00 | 576.37 ± 276.99 | 1122.93 ± 473.60 | 0.58 ± 0.28 | 1.12 ± 0.47 |
| γ-Dodecalactone | 2325 | NA | 1f | NI | 53.05 ± 5.88 | NI | 0.05 ± 0.00 | NI | NI | NI | NI |
| δ-Dodecalactone | 2375 | 2490b | 10f | 102.35 ± 16.86 | 108.35 ± 11.59 | 0.01 ± 0.00 | 0.01 ± 0.00 | 197.18 ± 95.13 | 459.31 ± 314.85 | 0.02 ± 0.01 | 0.05 ± 0.03 |
| δ-Tetradecalactone | 2607 | NA | 50f | 49.11 ± 7.51 | 53.15 ± 5.49 | 0.00 ± 0.00 | 0.00 ± 0.00 | NI | NI | NI | NI |
| In total | 191.53 | 265.24 | 1207.96 | 2285.46 | |||||||
| Fatty acids | |||||||||||
| Butanoic acid | 1586 | 1629b | 0.66d | NI | NI | NI | NI | 268.81 ± 84.52 | 437.55 ± 156.60 | 0.41 ± 0.13 | 0.66 ± 0.24 |
| Hexanoic acid | 1802 | 1856b | 2.50d | NI | NI | NI | NI | 324.58 ± 137.69 | 1037.92 ± 420.6 | 0.13 ± 0.06 | 0.42 ± 0.17 |
| Octanoic acid | 2018 | 2069b | 350d | NI | NI | NI | NI | 655.62 ± 431.29 | 1310.74 ± 694.61 | 0.00 ± 0.00 | 0.00 ± 0.00 |
| Decanoic acid | 2228 | 2282b | 200d | NI | NI | NI | NI | 870.48 ± 526.82 | 1719.04 ± 749.58 | 0.00 ± 0.00 | 0.00 ± 0.00 |
| Dodecanoic acid | 2444 | 2551b | 700d | 40.85 ± 5.03* | 18.43 ± 2.64 | 0.00 ± 0.00 | 0.00 ± 0.00 | 298.63 ± 202.38 | 456.10 ± 212.02 | 0.00 ± 0.00 | 0.00 ± 0.00 |
| Tetradecanoic acid | 2652 | NA | 5000d | 67.00 ± 8.15* | 39.67 ± 1.28 | 0.00 ± 0.00 | 0.00 ± 0.00 | 263.18 ± 103.35 | 295.88 ± 137.04 | 0.00 ± 0.00 | 0.00 ± 0.00 |
| Hexadecanoic acid | 2864 | NA | 10000d | 314.43 ± 33.46* | 227.00 ± 15.33 | 0.00 ± 0.00 | 0.00 ± 0.00 | 710.30 ± 92.69 | 940.17 ± 359.65 | 0.00 ± 0.00 | 0.00 ± 0.00 |
| In total | 422.28 | 285.11 | 3391.60 | 6197.41 | |||||||
| Aldehydes | |||||||||||
| Nonanal | 1373 | 1394a | NA | NI | 20.19 ± 1.82 | NI | NI | 484.79 ± 198.55 | 1392.47 ± 1124.52 | NI | NI |
| Decanal | 1475 | 1495a | 2e | NI | NI | NI | NI | 187.17 ± 72.82 | 356.13 ± 178.10 | 0.09 ± 0.04 | 0.22 ± 0.04 |
| (E)-2-Nonenal | 1505 | 1447a | 45 g | NI | NI | NI | NI | 58.65 ± 26.50 | NI | 0.00 ± 0.00 | NI |
| In total | 201.9 | 730.61 | 1748.60 | ||||||||
| Others | |||||||||||
| Toluene | 1014 | 1035a | NA | NI | NI | NI | NI | 1000.72 ± 451.64 | 458.04 ± 243.77 | NI | NI |
| 1,2-Dutanediol | 1143 | NA | NA | NI | 14.35 ± 3.59 | NI | NI | NI | NI | NI | NI |
| D-Limonene | 1183 | NA | 10e | 30.03 ± 8.81 | 13.89 ± 5.16 | 0.00 ± 0.00 | 0.00 ± 0.00 | NI | NI | NI | NI |
| Styrene | 1230 | NA | NA | NI | 21.29 ± 3.26 | NI | NI | 228.87 ± 77.85 | 579.65 ± 243.13 | NI | NI |
| Ethyl caprylate | 1415 | NA | NA | NI | NI | NI | NI | 75.08 ± 37.99 | NI | NI | NI |
| Furfural | 1423 | 1456a | NA | NI | NI | NI | NI | NI | 84.14 ± 35.48 | NI | NI |
| Benzaldehyde | 1481 | 1515a | NA | NI | NI | NI | NI | 136.08 ± 47.11 | 346.76 ± 119.41 | NI | NI |
| 2-Furanmethanol | 1624 | NA | NA | 50.95 ± 2.22 | 80.43 ± 40.81 | NI | NI | NI | NI | NI | NI |
| 2,4-Dimethyl-benzaldehyde | 1764 | NA | NA | 16.90 ± 5.51 | NI | NI | NI | NI | NI | NI | NI |
| Dimethyl sulfone | 1838 | NA | NA | NI | NI | NI | NI | 181.12 ± 76.35 | 445.04 ± 250.85 | NI | NI |
| Phenol | 1953 | 2051a | NA | NI | NI | NI | NI | 23.79 ± 9.59 | NI | NI | NI |
a–cRIs were mainly gathered from an online database (http://www.odour.org.uk) and the literature (Peterson and Reineccius, 2003b; Wang and Xu, 2009); d–gThreshold values were gathered from literature (Mallia et al., 2007; Urbach et al., 1972) and the online database (http://www.odour.org.uk)
NA, not available; NI, not identified
*p < 0.05; **p < 0.01
Compared with the SPME, SDE extracted less low molecular weight lactones and fatty acids. For example, fatty acids in the SPME extract included butanoic acid, hexanoic acid, octanoic acid, and decanoic acid, all of which were absent in the results of the SDE technique. These findings concurred with several previous reports, in which the SDE method was preferred for the extraction of higher molecular mass and lower volatility compounds when analyzing volatiles in Rabdosia serra (Lin et al., 2013), dry-cured ham (Garcia-Esteban et al., 2004), and mustard paste (Cai et al., 2001). The difference could be attributed to the disparity in the extraction procedures of the two methods.
In SDE, solvent extraction and steam distillation extraction occurred simultaneously by heating the sample and organic solvent to boiling respectively. Therefore, more high-molecular-mass and low-volatility compounds were identified. However, the high temperature and long extraction time may cause the loss of low molecular weight compounds due to volatilization. In SPME method, compounds with higher molecular mass or higher boiling points have increased distribution constants and retention index, therefore the amount of lower molecular weight compounds adsorbed by the fiber were higher (Garcia-Esteban et al., 2004).
In this study, the odd-numbered methyl ketones (with the exception of 2-nonanone) were not present in the SPME extracts, while high content of odd-numbered methyl ketones existed in SDE extraction, which is likely due to lipid degradation during the heat treatment used in this extraction. Lee et al. (1991) reported that lipid degradation in butter during heat treatment led to the formation of certain volatiles, including methyl ketones. In order to ensure this, we compared the volatile profiles of milk fat and heated milk fat (butter B1, anhydrous milk fat) using the SPME technique. The results indicated, as expected, that a higher content of methyl ketones was present in the headspace after heating treatment (data not shown here). Those ketones may formed from β-ketoacid glycerides during heating (Larráyoz et al., 2001).
It was obvious from our study, that not all the compounds were present in both butters. Using the SDE technique, four compounds (2-methyl-3-pentanone, 3-penten-2-one, and 2, 4-dimethyl-benzaldehyde) only presented in B1, while γ-dodecalactone, 2-octanone, 1, 2-dutanediol, nonanal, and styrene were only observed in B2. The content of fatty acids in the SDE extract of B1 were higher than in B2 (p < 0.05), while more 2-hexanone was identified in B2 than in B1 (p < 0.01). Apart from these findings, no significant differences were observed in the concentrations of other ketones. In contrast, using SPME, E-2-nonenal, ethyl caprylate, and phenol were only identified in B1, while furfural was only present in B2. The differences in the content of 3-penten-2-one and E-2-nonenal may be due to different levels of freshness, since Mallia et al. (2007) found that the concentrations of 1-octen-3-one, E-2-nonenal, and Z-1,5-octadien-3-one increased when butter oil was stored at room temperature. The content of hydrocarbons was not listed in this study, since few authors had previously reported on the contribution of hydrocarbons to dairy flavors. Aside from the compounds discussed above, no significant differences were found in the concentrations of volatiles.
Active aroma compounds analysis
The OAVs of some odorants in butter were listed in Table 1. Since the thresholds of some compounds were not available, it was not possible to calculate the OAVs for every aroma. Using SDE, the OAVs of all compounds were found to be lower than 1. The compounds with poor volatility obtained with the SDE method had little effect on the sensorial perception (Lin et al., 2013). Using SPME, δ-octanolactone (OAV = 5.51 ± 2.39) was determined to be the most important active aroma in B2, followed by δ-decalactone (OAV = 1.12 ± 0.47). A similar trend was observed with B1, except that the OAV of δ-decalactone was lower than 1. No significant difference was found between the OAVs in the two butters.
In GC-O analysis, using the two techniques, a total of 29 compounds in two butters were detected at the GC-O port, including eight aroma compounds identified by MS (four species of methyl ketones, three species of lactones and dodecanoic acid), 20 unknown compounds (not shown), and (Z)-6-dodeceno-γ-lactone (LRI = 2339) (Table 2). The analysis indicates that human olfactory is more sensitive in analyzing aroma compounds compared with the MS method, supported by observing that the unknown compounds perceived by assessors at GC-O port failed to cause visible signal in mass spectra. The compound, (Z)-6-Dodeceno-γ-lactone, had also been detected in other dairy products by other authors (Bendall, 2001; Schieberle et al., 1993). In this study, the ketones were not considered as key aroma compounds, since they were not detected in the unheated butter. When using the SDE technique, δ-decalactone, γ-dodecalactone, δ-dodecalactone, and dodecanoic acid were considered to be active odorants for B1, whereas δ-decalactone andγ-dodecalactone were regarded as contributors to the overall flavor of B2. Using SPME, δ-decalactone, the only contributor in B1, was present in B2, along with two other active aroma compounds, namely (Z)-6-dodeceno-γ-lactone and γ-dodecalactone.
Table 2.
Odor description of volatiles identified by GC-O
| RT/min | SDE | SPME | Description | Compounds | ||
|---|---|---|---|---|---|---|
| B1 | B2 | B1 | B2 | |||
| 4.10 | Y | Y | NI | NI | Creamy, fruity | 2-Pentanone |
| 8.97 | Y | Y | NI | NI | Creamy, chemical | 2-Heptanone |
| 14.44 | Y | Y | NI | NI | Creamy, chemical | 2-Nonanone |
| 24.37 | Y | Y | NI | NI | Acid, grassy | 2-Tridecanone |
| 30.97 | Y | Y | Y | Y | Peach, creamy | δ-Decalactone |
| 33.48 | Y | Y | NI | Y | Acid, creamy, flowery | γ-Dodecalactone |
| 33.76 | NI | NI | NI | Y | Acid | (Z)-6-Dodeceno-γ-lactonea |
| 34.26 | Y | NI | NI | NI | Acid, fruity | δ-Dodecalactone |
| 35.42 | Y | NI | NI | NI | Soapy | Dodecanoic acid |
Y/NI, identified at GC-O port, (Y) yes or (NI) no
aIdentified by LRI
The present results indicate that it is mainly lactones that give butter its creamy, fruity or otherwise pleasant odors, whereas dodecanoic acid gives butter a ‘soapy’ odor. The results concurred with other studies, in which lactones had been found to provide Gouda-type cheeses with buttery and fruity aromas (Leuven et al., 2008), while dodecanoic acid gave skim milk powder its waxy and soapy odors. Based on the OAVs and GC-O results, it could be concluded that lactones are the main contributors to butter flavor. δ-decalactone, which was detected at highest frequency by GC-O, is probably the most important aroma compound of butter, thus differentiating butter from margarine in baked products (Nursten, 1997). Our results were similar with those reported by Schieberle et al. (1993), who suggested that δ-decanolactone and butanoic acid were the most important odorants in sweet cream butter. However, in our study, butanoic acid was not considered as a contributor. Short-chain free fatty acids associated with the freshness of the butters were reported to result from triglyceride degradation of milk fat (González-Córdova and Vallejo-Cordoba, 2001).
Repeatability
The repeatability associated relative standard deviation (RSD) for most analytes is shown in Table 3. The results indicated higher repeatability of the SDE method comparing to SPME method. For example, the RSDs of fatty acids in the SDE extracts ranged from 3.21 to 14.35%, while the RSDs for SPME determination of fatty acids (with the exception of hexadecanoic acid) were greater than 30%. Superior performance of the SDE technique in the quantitative analysis of volatiles has also been observed by other authors (Cai et al., 2001). Quantification of the adsorption process using the SPME fiber is often very difficult, and results obtained using SPME strongly depend on experimental conditions and the sample matrices (Peppard and Yang, 1994). Using longer fiber exposure time may be a feasible way to better the results with higher precision (González-Córdova and Vallejo-Cordoba, 2001). More experimental investigation is, thus, required to improve the precision of SPME in future studies. To our knowledge, this is the first time that the active aroma compounds in butters were analyzed and compared by the two techniques. We conclude that both SDE and SPME are efficient in extracting the active aroma compounds (lactones), and SDE provides a better performance in the quantitative analysis.
Table 3.
Relative standard deviation of SPME and SDE (RSD, %)
| Compounds | SDE (n = 3) | SPME (n = 3) | ||
|---|---|---|---|---|
| B1 | B2 | B1 | B2 | |
| Methyl ketones | ||||
| 2- Pentanone | 12.08 | 5.09 | NI | NI |
| 2-Methyl-3-pentanone | 26.68 | NI | NI | NI |
| 2-Hexanone | 2.97 | 1.52 | NI | NI |
| 3-Penten-2-one | 2.43 | NI | NI | NI |
| 2-Heptanone | 6.91 | 6.04 | NI | NI |
| 2-Octanone | NI | 5.09 | NI | NI |
| 2-Nonanone | 6.69 | 7.50 | 47.44 | 6.11 |
| 2-Undecanone | 9.05 | 8.50 | NI | NI |
| 2-Tridecanone | 12.15 | 10.75 | NI | NI |
| 2-Pentadecanone | 11.68 | 13.39 | NI | NI |
| Lactones | ||||
| δ-Hexalactone | NI | NI | 42.28 | 48.48 |
| δ-Octanolactone | NI | NI | 45.32 | 43.29 |
| δ-Decalactone | 7.41 | 14.80 | 48.06 | 42.18 |
| γ-Dodecalactone | NI | 11.09 | NI | NI |
| δ-Dodecalactone | 16.47 | 10.70 | 48.25 | 68.55 |
| δ-Tetradecalactone | 15.30 | 10.33 | NI | NI |
| Fatty acids | ||||
| Butanoic acid | NI | NI | 31.44 | 35.79 |
| Hexanoic acid | NI | NI | 42.42 | 40.52 |
| Octanoic acid | NI | NI | 65.78 | 52.99 |
| Decanoic acid | NI | NI | 60.52 | 43.60 |
| Dodecanoic acid | 12.31 | 14.35 | 67.77 | 46.48 |
| Tetradecanoic acid | 12.16 | 3.21 | 39.27 | 46.32 |
| Hexadecanoic acid | 10.64 | 6.75 | 13.05 | 38.25 |
NI, not identified
Acknowledgements
This work was supported by the earmarked fund for China Agriculture Research System (CARS-36; Beijing, China), the National Natural Science Foundation of China (Grant No. 31471689) and Beijing Postdoctoral Research Foundation (2018-ZZ-010).
Compliance with ethical standards
Conflict of interest
No conflict of interest exits in the submission of this manuscript, and the manuscript is approved by all authors for publication.
Footnotes
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Contributor Information
Yang Li, Email: yang_li17@126.com.
Yunna Wang, Email: wang_yn92@163.com.
Dongdong Yuan, Email: ydong2010@sina.cn.
Yan Li, Email: liyan@th.btbu.edu.cn.
Liebing Zhang, Email: liebzhang@gmail.com.
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