Article pubs.acs.org/JAFC
“More than Honey”: Investigation on Volatiles from Monovarietal Honeys Using New Analytical and Sensory Approaches Barbara Siegmund,* Katharina Urdl,Δ Andrea Jurek, and Erich Leitner Institute of Analytical Chemistry and Food Chemistry, NAWI Graz, Graz University of Technology, Stremayrgasse 9/II, A8010 Graz, Austria ABSTRACT: Eight monovarietal honeys from dandelion, fir tree, linden tree, chestnut tree, robinia, orange, lavender, and rape were investigated with respect to their volatile compounds and sensory properties. Analysis of the volatile compounds was performed by gas chromatographic techniques (one-dimensional GC-MS as well as comprehensive GC×GC-MS). For sensory evaluation Napping in combination with ultraflash profiling was applied using sensory experts. For dandelion honey, 34 volatile compounds are described for the first time to be present in dandelion honey. PCA and cluster analysis of the volatile compounds, respectively, show high correlation with the PCA obtained from sensory evaluation. Lavender and linden honey showed sensory characteristics that were not expected from these honey types. Analysis of the volatile compounds resulted in the identification of odor-active compounds that are very likely derived from sources other than the respective honeyflow. Contamination with essential oils used in apiculture is very likely to be the reason for the occurrence of these compounds in the investigated honeys. KEYWORDS: honey, volatile compounds, sensory evaluation, GC-MS, comprehensive GC×GC-MS
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this task, for example, physicochemical values,9−12 spectroscopic characteristics,13,14 melissopalynological data,11,25 composition of carbohydrates.10,12 etc. Many researchers from different parts of the world have been dealing with volatile compounds from various unifloral as well as mixed-source honey or honeydew honeys,15−24 mainly applying gas chromatography−mass spectrometry (GC-MS) to identify the volatiles. More than 600 volatile compounds are reported as being part of honey flavor. 25 Several researchers also investigated the sensory impact of the compounds, mainly by using gas chromatography−olfactometry (GCO),20,22 indicating that not more than 50 odor-active compounds significantly contribute to the aroma of honey. Sensory evaluation of honey has been described by several groups from different regions showing that honey expresses distinct sensory properties, on the one hand depending on the honey type but, on the other hand, also based on the geographical origin of the honey samples.10,12,16,24,26,27 For sensory evaluation, in most cases (quantitative) descriptive analysis is performed, also showing correlations with data from the above-mentioned investigations on analytical data. In this study, a comprehensive methodological investigation was performed regarding the sensory properties as well as the volatile compounds of Austrian honeys in comparison to honeys from nearby Mediterranean regions with special emphasis on the correlation of data from instrumental− analytical and sensory techniques. Whereas the appropriateness of headspace solid phase microextraction (SPME) was proven
INTRODUCTION Honey belongs to the group of traditional foods with great historic importance. In Austria and Germany, the average annual per capita consumption of 1.1 kg1 is significantly higher than the European average (approximately 0.7 kg per capita and year).2 On the basis of recent discussions and concerns regarding bees’ endangerment due to the use of insecticides, most notably the use of neonicotinoids,3−5 at least in Austria, the awareness of the importance of the existence of bees’ colonies has increasedand as a side effectthe consumers’ consciousness of the product honey has risen as well. The internationally awarded documentary film More than Honey (directed by Markus Imhof in 2012) even augmented consumers’ awareness of the bees’ importance to farming and to the product itself. In Austria, honey production has a long tradition. Traditional honey types, based on the Austrian landscape and its agricultural use, include various types of unifloral honeys, honeydew honey from (cultivated) woodland areas (either as monovarietal honeydew honey from fir or spruce trees or as mixed woodland honey) as well as mixed blossom honey and also unifloral dandelion honey as a result of blooming pasture landscape in springtime. Consumers’ appreciation for the product honey is based on its sweetness, on the one hand, and on its very distinct honey flavor, on the other hand. Furthermore, honey was traditionally applied in natural healing and folk medicine; three recent reviews give a survey about medical effects shown from the use of honey.6−8 The main components of honey are fructose and glucose; as in most other foods, volatile and aroma-active compounds are present in only low absolute amounts, nonetheless accounting for the distinct aroma of the product. During the past decades, honey of different sources has been the substrate of many investigations, authenticity control of unifloral or monovarietal honeys being the driving force for many studies.9 Several different approaches were used to fulfill © XXXX American Chemical Society
Special Issue: 11th Wartburg Symposium on Flavor Chemistry and Biology Received: Revised: Accepted: Published: A
November 9, 2016 February 3, 2017 February 6, 2017 February 6, 2017 DOI: 10.1021/acs.jafc.6b05009 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry Table 1. Results from Descriptive Analysis of the Honey Samples honey type
description of the odor
description of the flavor
dandelion lavender orange rape robinia linden chestnut fir tree
honey, sweet, hay-like, musty floral, citrus, fresh menthol, herbal infusion sweet, floral, honey-like, straw-like hay-like, cheesy, sourish sweet, woody, sourish medicinal, herbal, woody-balsamic, condimental medicinal, sweet sweet, caramel, pine needles
very sweet, honey-flavor sweet, herbal infusion, floral, slightly medicinal-licorice sweet, floral, slight bitterness sweet, musty, slightly fermented sweet, bee’s wax, sourish sweet, bitter, medicinal, floral, woody, hay-like bitter, sweet, burnt caramel, woody sweet, slightly bitter, caramel, slightly sourish
in previous studies,19,21,22,28,29,38 there are very few data in the literature regarding the use of comprehensive GC×GC-MS for the investigation of honey volatiles.30,31 Recently, in sensory science, several techniques were developed with respect to sensory methods requiring lower training efforts than, for example, for traditional descriptive analysis.32 Several variations of Napping and projective mapping, respectively, have been described in the literature recently.33−35 In this study, sensory evaluation was performed to receive a classification of the unifloral honey samples. As a consequence, sensory evaluation in terms of Napping in combination with ultraflash profiling (UFP) was performed. The combination of the results from highly sophisticated analytical methods with results obtained by the use of new sensory techniques might contribute to the understanding of the complex world of honey flavor.
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acetophenone (grape-like odor), benzaldehyde (almonds, marzipan), hexanol (green leaves, grassy), octanal (aldehydic, waxy, citrus, orange peel, green), nonanal (aldehydic, fatty, citrus, orange peel), decanal (aldehydic, waxy, fatty), linalool (fresh, floral, citrus), linalool oxide (mixture of isomers, woody, floral, earthy), hotrienol (fresh, floral, woody), methyl anthranilate (fruity, grape-like, floral), and thymol (herbal, thyme, phenolic). The selection of compounds was based on data found in the literature and on compounds identified in this study. All compounds used for the training except hotrienol were purchased from Sigma-Aldrich (Vienna, Austria). The compounds were of a purity of ≥97%. Hotrienol was kindly provided by esarom (Oberrohrbach, Austria) as a 10% solution in propylene glycol. No specific training was performed regarding the used methods, as the panelists had sufficient experience in performing Napping, both from training samples and from different food matrices. Sensory Evaluation of the Honey Samples. Sensory evaluation of the honey samples was performed in the sensory laboratory under standardized conditions. The honey samples were served in blue glasses that were originally designed for the sensory evaluation of olive oil. The glasses were covered with a lid. The samples were kept at room temperature for several hours prior to the sensory evaluation to equilibrate. All samples were blind-tasted. The samples were coded with three-digit random numbers and were served in random order to avoid first-sample effects. In a first session, the panelists were asked to perform descriptive analysis (DA) of the samples, (i) describing the odor of the samples, and (ii) to taste the samples and describe the overall flavor of the honeys. To be able to compare or to categorize the samples according to their sensory properties, Napping was used in subsequent sessions. Using this procedure, the panelists were asked to arrange the samples on rectangular sheets (A3, 29.7 × 42 cm) according to their sensory similarities or dissimilarities. The more similar samples were perceived, the closer they should be arranged to one another on the sheet and vice versasamples that were judged to be different from one another should be arranged far away from one another. In addition to the arrangement of the samples according to their similarities or dissimilarities, respectively, the panelists were asked to record their sensory impressions on the sheet (ultraflash profiling, UFP). For the statistical evaluation of the results, the positions of the samples were recorded in terms of their x/y coordinates. Enrichment of the Volatile Compounds. Automated headspace solid-phase microextraction (HS-SPME) devices combined with either of the used GC-MS systems were used for the extraction and enrichment of the volatile compounds from the investigated honey samples. For HS-SPME, 50 mg (for comprehensive GC×GC-MS analysis) and 250 mg (for one-dimensional GC-MS analysis) of honey were transferred into 20 mL headspace vials. The following SPME fiber was used: divinylbenzene/Carboxen/polydimethylsiloxane (DVB/Carboxen/PDMS) 50/30 μm, 2 cm stable flex (Supelco, Bellefonte, PA, USA). Sampling was performed using a CTC Combi PAL sampler (CTC Analytics, Switzerland). Prior to the extraction of the volatiles, the samples were equilibrated in the oven of the autosampler at 50 °C for 5 min. In the oven, the samples were stirred thoroughly using a glass-coated magnetic stirrer. The SPME fiber was exposed to the headspace of the sample for 20 min at 50 °C. Immediately after the exposure, the fiber was transferred to the injector of the gas chromatographic system for thermodesorption at 270 °C. The SPME fiber was left in the injection port for
MATERIALS AND METHODS
Honey Samples. Eight different monovarietal/unifloral honey samples were investigated: robinia (Robinia pseudoacacia) honey, rape (Brassica napus) honey, and dandelion (Taraxacum officinale) honey as well fir tree (Abies spp.) honey were obtained from an Austrian apiarist; orange (Citrus × sinensis) honey, lavender (Lavandula angustifolia) honey, linden tree (Tilia platyphyllos) honey, and chestnut (Castanea sativa) honey were obtained from a local Croatian market. As the analysis of the volatiles was the focus of this study with special respect to comparison of the used methods, the authors relied on the labeling of the honeys. As a consequence, no melissopalynological investigations were performed to prove the plant-specific origin of the honey samples. As expected, the blossom honeys had a significantly different visual appearance from the honeydew honeys: blossom honeys showed light, slightly yellowish color, whereas the honeydew honeys showed amber to intense dark brown color. Chestnut honey, which is supposed to be a mixture of blossom and honeydew honey, showed an intense brown color, which is also characteristic for this honey type. Training of the Panelists for Sensory Analysis. Sensory evaluation was performed by a trained panel consisting of 14 welltrained panelists (8 females, 6 males between 30 and 53 years of age). The panelists had vast sensory experience as panelists in an expert panel for periods between 5 and 15 years before conducting this study. Each of them fulfilled the requirements described in EN ISO 858636 including the requirements for the recognition of the basic tastes as well as the ability to recognize a large range of odors and to describe them with conclusive wordings. However, prior to this study a honeyspecific training was carried out to make them sensitive to the sensory impressions they would perceive from the investigated samples. During this training period, special emphasis was put on the perception, recognition, and description of the odors (Table 1) that were expected to be present in the honey samples. Solutions of the compounds were prepared in ethanol in adequate concentrations (1− 2%). Filter strips were dipped into the solutions and stored in cellophane covers for short periods until use to avoid evaporation of the volatiles. The following compounds were used: 2-methyl-1-butanol (fruity, banana, pungent, fermented fruits), 2-phenethyl alcohol (floral, rose, honey), phenyl acetaldehyde (honey, sweet, floral), 2-aminoB
DOI: 10.1021/acs.jafc.6b05009 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
no.
compound name
dimethyl sulfide 2,3-butanedione (diacetyl) hexanal 2-methylbutanenitrile 2-methyl-(E)2-butenal 3-methylbutanenitrile heptanal 1,8-cineole 2-methyl-1-butanol 2,3-dehydro-1,8-cineole 3-methyl-3-buten-1-ol p-cymene 2-methylpyrazine o-cymene 3-hydroxy-2-butanone (acetoin) octanal (E)-3-hexenol dimethyl trisulfide (Z)-3-hexenol nonanal cis-thujone 1-methyl-4-(1-methylethenyl)benzene trans-thujone acetic acid cis-linalool oxide (furanoid) decanal 1-octen-3-ol furfural trans-linalool oxide (furanoid) formic acid 2-acetylfuran camphor benzaldehyde propanoic acid lilac aldehyde A linalool lilac aldehyde B lilac aldehyde C 2-methylpropanoic acid 5-methyl 2-furancarboxaldehyde 2,3-butanediol lilac aldehyde D
94 86 57 55 84 68 55 108 70 109 68 134 94 134 88 84 67 126 67 98 110 132 110 60 94 112 (57 96 94 46 95 95 106 74 93 93 93 93 73 110 75 93
(m/z) 705 974 1075 1079 1088 1120 1175 1200 1207 1190 1246 1258 1260 1265 1278 1281 1361 1368 1382 1388 1417 1437 1434 1437 1445 1446 1449 1454 1469 1492 1495 1511 1513 1531 1536 1546 1549 1558 1563 1564 1581 1581
ZB WAX
RIexp HP5 499 588 802 720 745 731 904 1045 750 993 723 1028 820 1019 710 998 1034 968 855 1122 1108 1096 1124 615 1068 1208 973 831 1075 502 923 1140 955 671 1140 1100 1150 1150 752 955 806 1165
C
751b 962b 806c 1169e
1579b 1575b 1583c 1597e
1560b 1565e
HP5 505c 593c 800b 717e 753c 737e 901b 1031b 755c 991e 720e 1024b 826e 1023e 718c 1003b 1038c 974c 858c 1105b 1102f 1088e 1111f 600c 1072f 1206b 975f 829c 1081e 512g 910b 1146b 958b 668c 1145e 1100b 1154e
WAX 716c 970c 1085b 1094e 1101c 1134e 1189b 1210b 1208c 1213e 1252d 1272b 1263e 1276e 1297c 1293b 1386c 1377c 1391c 1398b 1422f 1435e 1448h 1450c 1438d 1447b 1440f 1455c 1459d 1492g 1507b 1511b 1521b 1523c
RIlit.
Table 2. Volatile Compounds Identified in the Honeys under Investigationsa dandelion 0.04* 0.04* nd 4.28* 0.01 2.66 0.01* nd 0.30* nd 0.48* 0.03* nd 0.01* 0.01* 0.01* nd nd 0.01* 0.08* nd 0.10 nd 1.50* 1.42* 0.04 nd 1.73 0.82 0.03* 0.13* nd 4.24 0.10* 0.34 0.24* 0.09 0.21 7.18* 0.09 0.02* 0.01
robinia 1.62 0.55 0.06 0.40 0.12 0.37 0.04 0.01 1.60 nd 2.20 0.05 nd 0.02 0.11 0.12 nd 0.16 0.21 1.13 nd nd nd 10.03 8.73 0.58 0.02 14.48 2.36 0.35 0.75 nd 17.79 0.28 0.58 1.89 0.55 0.44 0.46 0.72 0.50 0.09
rape 3.57 0.19 nd 5.48 nd 3.38 0.04 0.01 3.02 nd 0.93 0.03 nd 0.01 0.06 0.04 nd 0.51 0.06 0.29 nd 0.24 nd 6.76 4.24 0.17 nd 10.89 1.40 0.26 0.58 nd 10.65 0.25 0.47 0.16 0.49 0.36 1.65 0.30 0.40 0.06
0.33 0.10 0.02 0.09 0.36 0.07 0.24 0.02 5.29 nd 3.64 0.08 nd 0.01 0.43 0.18 0.03 nd 0.38 0.05 0.01 0.22 nd 12.33 4.90 0.08 0.11 6.57 2.47 0.18 1.31 nd 8.92 0.57 0.07 1.57 nd 0.05 0.68 0.57 0.05 14.96
fir tree 0.06 2.76 0.11 0.03 0.25 0.02 0.06 0.01 1.35 nd 0.85 0.03 0.04 0.01 0.49 0.18 0.21 nd 0.70 1.46 0.02 0.26 nd 10.84 1.53 0.59 0.27 15.79 1.43 0.90 2.55 nd 14.51 0.72 0.20 0.34 0.18 0.11 0.61 0.95 0.17 0.09
chestnut
% area (TIC) linden nd 0.20 0.01 0.01 0.17 nd 0.02 0.04 0.23 16.96 0.39 2.46 nd 0.35 0.23 0.03 0.02 nd 0.10 0.44 0.01 52.87 0.01 4.18 0.08 0.26 0.01 1.53 0.25 0.09 0.28 0.14 2.54 0.16 0.08 0.04 0.07 0.99 0.25 0.07 0.11 0.60
orange 0.16 0.65 0.14 0.03 0.59 0.02 0.10 0.04 1.16 nd 3.66 0.10 nd 0.03 0.38 0.10 0.05 nd 0.10 1.69 0.01 0.93 nd 6.04 5.73 1.03 0.02 11.40 1.56 0.28 0.90 0.22 5.10 0.36 8.38 2.17 8.34 5.36 0.25 0.40 7.77 1.40
lavender 0.06 0.03 0.07 0.01 nd nd 0.01 8.76 0.02 nd nd 0.44 0.02 0.02 0.03 nd nd nd 0.01 0.07 17.52 0.45 2.42 0.29 0.23 0.04 0.08 7.52 0.17 0.02 1.29 16.17 0.46 0.01 nd 0.51 nd nd 0.01 0.33 0.03 0.01
Journal of Agricultural and Food Chemistry Article
DOI: 10.1021/acs.jafc.6b05009 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
D
total area counts (TIC)
82 85 93 82 86 60 91 105 98 111 74 122 96 (95 164 60 107 104 190 60 124 108 91 117 124 131 135 117 164 135 135 135 120 151
43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
1587 1599 1600 1607 1616 1622 1632 1641 1655 1661 1665 1667 1687 1700 1780 1788 1808 1811 1819 1841 1852 1871 1906 1916 1966 2019 2024 2041 2159 2162 2186 2207 2209 2228
ZB WAX
RIexp HP5 1112 958 1171 1094 1299 825 1050 1041 852 1044 847 1041 1142 1162 1253 975 1475 1274 1402 1085 1089 1039 1127 1145 1067 1280 1252 1238 1375 1292 1323 1312 1317 1354
HP5 1118e 965e 1179e 1101b 891c 825e 1050e 1041c 852b 1039f 847b 1041e 1142e 1162c 1247e 984e 1475e 1258h 1388b 1085f 1089c 1039c 1117e 1145e 1077h 1283c 1252f 1232e 1364c 1292e 1323c 1300e 1309c 1346b
WAX 1595e 1589e 1577e 1606b 1640b 1620e 1661d 1645c 1672b 1684h 1680b 1663e 1677e 1677c 1776e 1775e 1791f 1840h 1824b 1847d 1859c 1865c 1940d 1931e 1991h 2007c 2051f 2036e 2141c 2165e 2198c 2189e 2223c 2240b
RIlit. dandelion
349715792
nd 0.12 nd 15.06 0.08* 0.22* 0.24 0.25 nd nd 43.61 0.05* 0.15 0.09* 0.05 5.15* 0.01* 0.03 0.05 0.47* nd 0.06 1.57 6.13 0.07* 0.03* 0.03* nd 0.21* nd 0.01* 0.01* 0.01* nd
robinia
36695791
0.25 0.17 0.04 6.21 0.13 0.40 0.55 0.07 0.57 0.63 4.24 0.09 0.66 0.13 0.08 0.66 0.02 0.23 0.22 0.25 nd 5.81 7.43 0.31 0.60 0.28 0.22 0.08 0.04 nd 0.10 0.06 0.08 0.02
rape
67039050
0.21 0.21 0.02 3.43 0.14 0.36 0.53 0.09 0.73 0.21 15.93 0.02 0.37 0.11 0.04 4.73 0.02 0.03 0.15 0.79 0.01 5.81 6.44 1.68 0.41 0.11 0.16 0.01 0.05 nd 0.12 0.02 0.01 0.08 112228025
0.31 1.35 0.07 2.07 1.39 2.62 1.16 0.28 4.99 0.23 6.67 0.68 1.42 0.21 0.10 0.26 0.14 0.23 0.03 0.57 0.02 3.23 3.92 0.18 0.15 0.27 0.15 0.11 0.03 nd 0.01 0.11 0.10 0.01
fir tree
62338093
0.38 0.42 0.03 0.85 0.34 0.73 0.90 0.71 1.80 0.10 9.14 0.27 1.63 0.29 0.36 0.18 5.25 1.16 0.09 1.16 0.03 5.51 1.90 0.97 0.27 0.26 0.10 0.35 0.01 nd 0.98 1.23 1.92 0.01
chestnut
% area (TIC) linden
175509445
0.05 0.15 3.06 1.80 0.13 0.19 0.55 0.06 0.25 0.15 2.44 0.03 0.33 0.44 0.01 0.07 0.01 0.02 0.11 0.24 nd 0.28 1.09 0.05 0.20 0.03 0.09 nd 0.02 0.13 0.02 1.70 0.04 0.02
orange
51526435
0.53 0.48 0.05 0.80 0.35 1.20 3.53 0.06 0.63 1.89 2.32 0.03 1.30 nd 0.02 0.09 nd 0.05 0.04 0.46 0.05 1.05 5.08 0.40 1.53 0.11 0.12 0.03 0.01 nd 0.06 0.05 0.02 0.97
lavender
305709384
nd nd 0.32 nd 0.01 0.01 1.77 0.03 3.46 nd 0.08 0.03 6.82 2.11 7.12 0.01 nd 10.30 1.27 0.02 nd 0.03 6.77 0.00 0.02 0.01 0.01 2.54 nd nd 0.07 0.08 nd nd
Relative concentrations are given in % area of the total ion chromatograms determined on one-dimensional GC-MS on the polar stationary phase; nd not detected; *, compounds that are reported for the first time to be present in dandelion honey. m/z, characteristic mass-to-charge ratios that were used to extract the peak areas (polar column) applied for PCA and cluster analysis; RIexp, experimentally determined RIs on the respective column; RIlit, RIs obtained from the literature and databases. bRI obtained from authentic reference compounds and collected in the SKAF Flavor database for Food Research Institute, Slovakia,, © 2001−2002 cRI obtained from http://www.flavornet.org. dRI obtained from literature Castro-Vázquez et al., 2014.43 eRI obtained from http://webbook.nist.gov. fRI obtained from http://www.pherobase.com. gRI obtained from https://pubchem.ncbi.nlm.nih.gov/. hRI obtained from the NIST Mass Spectral Search Program 2.2, 2014.
a
(m/z)
compound name
isophorone dihydro-5-methyl-2(3H)-furanone α-terpinen-4-ol hotrienol dihydro-2(3H)-furanone butanoic acid phenylacetaldehyde acetophenone 2-furanmethanol dihydro-5-methyl-5-vinyl-2(3H)-furanone 2-methylbutanoic acid salicylaldehyde 4-oxoisophorone borneol ethyl phenylacetate 2-methylpentanoic acid 1-phenylethanol 2-phenethyl acetate β-damascenone hexanoic acid guaiacol benzyl alcohol 2-phenylethanol benzylnitrile 2,5-furandicarboxaldehyde (E)-cinnamaldehyde 4-methoxybenzaldehyde 3-phenylpropanol eugenol thymol 2-methoxy-4-vinylphenol carvacrol 2-aminoacetophenone methyl anthranilate
no.
Table 2. continued
Journal of Agricultural and Food Chemistry Article
DOI: 10.1021/acs.jafc.6b05009 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 1. Results from sensory evaluation of the honey samples in terms of a PCA biplot derived from Napping data. Indicated clusters are derived from cluster analysis. Comprehensive GC×GC MS Analysis. Comprehensive GC×GC-MS analysis was performed on a Shimadzu GC-2010 Plus (Shimadzu Europa GmbH) coupled with a fast-scanning quadrupole mass selective detector (Shimadzu GCMS-QP2010 Ultra, Shimadzu Europa GmbH). Sample injection was performed by the Shimadzu AOC 5000 autosampler using an Optic-4 GC Inlet (GL Science BV, The Netherlands) using HS-SPME as described above. The thermal modulator ZOEX ZX-1 (Zoex Corp., Houston, TX USA) was used to modulate between the two complementary GC olumns. For the firstdimension column a nonpolar ZB5-MS capillary column was used (30 m × 0.25 mm × 0.25 μm; Phenomonex Inc., USA); for the second dimension an analytical column of medium polarity (BPX50; 2.5 m × 0.15 mm × 0.15 μm, SGE GmbH, Germany) was used. The applied temperature ramp was 40 °C (hold time = 1 min) and ramped to 160 °C with a constant ramp of 2 °C min−1, followed by a ramp of 20 °C min−1 to 270 °C. Helium was used as carrier gas in the constant flow mode with an initial column head pressure of 120 kPa. The modulation frequency was set to 4 s with a hot jet temperature of 300 °C and a hot jet pulse of 350 ms. Mass spectra were acquired in the scan mode (35−300 amu with 50 scans s−1, EI (70 eV)). The interface temperature was set to 270 °C, and the ion source temperature was 200 °C. Identification of the compounds was performed as described for one-dimensional GC-MS based on the mass spectra as well as on retention indices in the first dimension. Statistical Analysis of the Data. For the statistical evaluation of sensory data from Napping, principal component analysis (PCA) was performed on the complete set of x/y data obtained from the duplicate Napping analysis (equal weighing of x/y data) as well as clustering by using K-means clustering under consideration of the Euclidean distance between the samples. PCA of the volatile compounds was based on the standardized peak areas (selected ion chromatograms; the used m/z ratios are given in Table 2) obtained from onedimensional GC-MS analysis on the polar column. The selection of compounds used for the PCA was based on relevant compounds described in the literature20 as well as on compounds that were considered to be potential contributors to the honey aroma (Figure 4). Standardization of the peak areas was performed to compensate for the different abundances of the selected ions in the respective mass spectra. PCA was carried out by using The Unscrambler Client, 9.3, Camo, Oslo, Norway. Cluster analysis (formation of the dendrogram) of the honey samples based on the total volatile compounds was performed by the use of normalized peak areas (log areas obtained from selected ion chromatograms) and applying the agglomerative hierarchical clustering (AHC) by considering the Euclidean distance between the samples and using Ward’s procedure as agglomeration method (XLStat statistics add-in for Excel).
reconditioning (20 min) before it was exposed to the headspace of the next sample. GC-MS Analysis. One-dimensional GC-MS analysis was performed on two analytical columns of different polarities to confirm the identity of the volatile compounds. An Agilent system (GC 7890, MS 5975c VL MSD, Santa Clara, CA, USA) was used for the analysis on a nonpolar column (HP5MS, 30 m × 0.25 mm × 1 μm, Agilent Technologies) with the following temperature program: −10 °C for 1 min with a temperature ramp of 12 °C min−1 to 280 °C (holding time = 3 min). Injector temperature was 270 °C, and splitless injection was applied. Cryofocusing by blowing liquid nitrogen into the GC oven was applied to reach the start temperature of −10 °C with the aim to obtain higher resolution and better peak shape for compounds with very high volatility. Helium was used as carrier gas with a linear velocity of 31 cm s−1 (constant flow). The mass selective detection was performed in the scan mode (35−300 amu; EI (70 eV); interface temperature, 270 °C; ion source temperature, 230 °C). The analysis on the analytical column with high polarity (ZB Wax plus, 20 m × 0.18 mm × 0.18 μm, Phenomonex Inc., USA) was performed on a Shimadzu GC-MS system (Shimadzu GC-2010, GCMS-QP 2010 Plus, Shimadzu Europa GmbH) using the following temperature ramp: 40 °C for 1 min with a temperature ramp of 8 °C min−1 to 240 °C (holding time = 3 min). Injector temperature was 250 °C, and splitless injection was applied. Helium was used as carrier gas with a linear velocity of 35 cm s−1 (constant flow). The mass selective detection was performed in the scan mode (46−300 amu; EI (70 eV); interface temperature, 220 °C; ion source temperature, 200 °C). Identification of the volatile compounds was performed by probability-based matching of the obtained mass spectra with the mass spectra from the NIST08 and Adams Essential Oil mass spectral library 2007 as well as from the literature. As a second criterion for the identification, linear temperature-programmed retention indices (RI) were calculated on both columns used according to the method of Farkaš et al.37 Measured RIs were compared to data obtained from authentic reference compounds or from the literature and retention index databases. The reference compounds 2-acetylfuran, benzaldehyde, camphor, 1,8-cineole, p-cymene, decanal, dihydro-2(3H)furanone, 2-furanmethanol, hexanal, linalool, methyl anthranilate, 2methybutanoic acid, 5-methyl-2-furancarboxaldehyde, 2-methylpropanoic acid, and nonanal as well as octanal were purchased from SigmaAldrich (Vienna, Austria). β-Damascenone was kindly provided by Firmenich (Vienna, Austria), and heptanal was purchased from Alfa Aesar (Karslruhe Germany). All compounds were of a purity of ≥97%. Hotrienol was kindly provided by esarom (Oberrohrbach, Austria) as a 10% solution in propylene glycol. E
DOI: 10.1021/acs.jafc.6b05009 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Journal of Agricultural and Food Chemistry
Figure 2. Segments of comprehensive GC×GC-MS chromatograms of (a) lavender and (b) orange honey. Retention times in the first dimension (xaxis) are given in minutes; retention times in the second dimension (y-axis) are given in seconds. Compound numbers refer to the numbers given in Table 2. A, n-dodecane; B, n-tridecane.
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RESULTS AND DISCUSSION Sensory Evaluation. Sensory evaluation of the eight honeys of interest was performed in terms of Napping using trained panelists. To the best of our knowledge, the use of fast profiling techniques for the classification of honey has not been described in the literature before. Prior to the honey analysis, the specific training of the panelists with respect to odor-active compounds identified and described in honey as important contributors to honey aroma enabled the panelists to even better describe and classify the perceived impressions. Results from sensory evaluation gave a very clear classification of the investigated honey samples (Figure 1). After PCA of the Napping data, a clear separation of the samples was found. PC1 and PC2 account for 96% of the observed sensory classification. Clustering of the samples results in four clusters corresponding to the groups that are given in Figure 1. The formed clusters correspond well with the descriptors given in DA and UFP, respectively. Honeys achieved from trees (cluster 1, chestnut, linden, and fir tree) are located very close to one another in quadrant I. The similarity in sensory properties is very likely to
be found in the contribution of honeydew honey in the products; fir tree honey usually is pure honeydew honey, whereas chestnut honey and linden honey are described to usually be mixtures of blossom honey and honeydew honey. However, all three honey types show bitter, medicinal characteristics with additional caramel notes in chestnut and fir tree honeys. Robinia honeyas the fourth honey type derived from blooming treesis not associated with the honeys derived from chestnut, linden, and fir tree honeys. Robina honey flavor is found very closely related to rape honey in quadrant III (cluster 2), neither of the two showing pronounced sensory properties. They are both described showing rather weak, woody, hay-like, slightly sourish aromas, with a pronounced sweet and bee’s-wax like odor. According to apiarist general knowledge, the separation of robinia honey from the group of chestnut, linden, and fir tree honeys is not surprising. With its huge amounts of flowers, robinia usually issimilar to the blooming raperegarded as an important bee plant delivering enormous amounts of nectar during the blooming period. As a consequence, honeydew honey is usually F
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Figure 3. Clustering in terms of AHC of the honey samples performed by use of the total of the volatile compounds given in Table 2 based on normalized peak areas (selected ion chromatograms, for m/z ratios, see Table 2).
Figure 4. Results from PCA of the most abundant volatile compounds identified in the eight honey samples based on one-dimensional GC-MS analysis (polar column). PCA was based on the normalized peak areas (selected ion chromatograms; for m/z ratios see Table 2) of the following compounds: diacetyl, acetic acid (AA), 2-methylpropanoic acid (2MePrA), butanoic acid (BA), 2-methylbutanoic acid (2MeBA), 2-methylpentanoic acid (2MePeA), hexanoic acid (HA), phenylacetaldehyde (PAA), phenylethanol (PhE), β-damascenone (damascenone), linalool, 4methoxybenzaldehyde (4MB), guaiacol, eugenol, 2-aminoacetophenone (2-AAP), methyl anthranilate (MA).
Interestingly, dandelion honeyeven though derived from blossomsis situated in quadrant IV (cluster 4), closer to the honeys derived from trees than to the floral blossoms honeys.
negligible in robinia honey. The Mediterranean blossom honeys (lavender and orange) are located in quadrant II (cluster 3), both showing distinct sweet floral notes. G
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Journal of Agricultural and Food Chemistry Gas Chromatographic Analyses. For the extraction and enrichment of the volatile compounds, headspace solid phase microextraction (HS-SPME) was used and proved to be a suitable tool to enrich the volatile compounds from the honey matrices. Due to the high viscosity of the sample matrix, 50 °C was chosen to equilibrate the system before the SPME enrichment, which led to highly reproducible GC-MS chromatograms (in both one- and two-dimensional GC experiments). The use of the DVB/Carboxen/PDMS fibers enabled us to enrich a broad range of compounds of different polarities. One-dimensional GC-MS as well as comprehensive GC×GC-MS analysis on either of the selected analytical columns resulted in very complex chromatograms. As a consequence, one-dimensional chromatography on either of the used columns resulted in frequent coelution of several compounds, making the identification of compounds present in low amounts especially difficult to impossible. The high separation power of comprehensive GC×GC-MS enables the distinct identification of several coeluting compounds in onedimensional chromatography. Figure 2 gives two examples (blow-ups of comprehensive GC×GC-MS chromatograms of orange and lavender honey, respectively) demonstrating the enormous separation capacity of comprehensive GC×GC-MS. A total of 76 volatile compounds from several compound groups (Table 2) was identified in all investigated honey types; some of them seem to be specific for distinct honey types. The volatile compounds of honey have been the topic of several investigations showing that the volatiles may be closely related with the particular honey types. However, the composition of flavor compounds within one variety varies significantly depending on several external factors such as honey origin or honey maturity.25 Furthermore, the presence and proportion of compounds of different chemical classes depends not only on the plant type but on the honey bee’s metabolism, on the one hand, and the technical processing, on the other hand. As a consequence, the identification of volatile marker compounds for unifloral honeys is generally very difficult. Correlation and Discussion of the Results. PCA on the basis of the volatile compounds given in Table 2 results in clustering of the honey samples in terms of a dendrogram (Figure 3). These results demonstrate similarities in the volatile composition between fir tree and chestnut honey, rape and robinia honey, as well as orange honey and honey derived from linden tree. Lavender and dandelion honey form independent groupings with large dissimilarities to the other honey types. The grouping of the honey types is also well explained by the PCA biplot calculated from selected volatile compounds (Figure 4). In addition, the obtained product groupings given in Figures 3 and 4 show strong similarities to the results obtained from sensory analysis. Honeydew honey obtained from fir, linden, and chestnut trees again form a group in quadrant I; robinia and rape honeys are located very closely to one another near the center of the PCA biplot, whereas dandelion is located in the very edge of quadrant IV. Interestingly, orange and lavender honeys, which are categorized similarly by applying Napping, are clearly differentiated by means of the volatile compounds. Segments of comprehensive GC×GC-MS chromatograms of lavender and orange honeys can be seen from Figure 2. Lavender honey is dominated by the floral- and honey-likesmelling compounds phenyl acetaldehyde, phenylethanol, and β-damascenone, whereas the location of orange honey in the
PCA biplot is mainly based on the presence of high amounts of methyl anthranilate. The high concentrations of methyl anthranilate from orange honey can also be seen from Table 2, whereas significantly lower amounts were identified in the other honeys investigated. The use of methyl anthranilate as a marker compound to control the authenticity of orange honey has been discussed before.25,38 In addition to the high amounts of methyl anthranilate as a unique characteristic of orange honey, the lilac aldehydes A, B, C, and D were identified in orange honey in high relative concentrations. Lilac aldehydes could not be identified in lavender honey and were found in the other investigated honey varieties in low amounts only. The separation of lilac aldehydes in orange honey by comprehensive GC×GC-MS can be seen from Figure 2b (clear separation of lilac aldehydes A and D; lilac aldehydes B and C are coeluting on this system, but can be clearly separated on the polar column used in one-dimensional GC-MS). As methyl anthranilate, the presence of lilac aldehydes as major distinctive compounds for honey flavor was discussed earlier.23,25,26 Linaloola compound that is of great importance for the odor of orange and lavender blossomsis located halfway between orange and lavender honey, indicating equal importance for both honey types. Interestingly, in lavender honey it is not linalool or linalool acetate having the largest impact on the aroma profile, as reported from lavender flowers, but β-damascenone, which was present in very large amounts (by factors of 20−200-fold higher than in the other honey types investigated) as well as phenylacetaldehyde and 2-phenylethanol. All three compounds have been reported in lavender honey before; however, none of them seems to be unique to lavender honey. The high amounts of phenylacetaldeyde and 2phenylethanol correlate well with the high relative concentrations of ethyl phenylacetate and phenethyl acetate, respectively, that were identified in the investigated lavender honey. It was reported before that honey volatiles may react upon storage, leading to changes of the composition of the flavor.9 Esterification of 2-phenylethanol to form phenylethyl acetate and the potential oxidation and subsequent esterification of phenylacetaldehyde forming ethyl phenylacetate might be an indication for a longer storage period or treatment at higher temperatures of the investigated lavender honey. The presence of distinctive amounts of compounds such as cis- and trans-thujone, eucalyptol, and camphor significantly influences the sensory properties of the investigated lavender honey. However, it is very unlikely that lavender flowers are the source of the large relative amounts of these compounds. As for the use of essential oils containing eugenol, thymol, and carvacrol (see below), the presence of the minty/fresh-smelling compounds is probably based on the use of essential oils such as mint oil that are allowed to be used under certain circumstances in the beehive to combat the presence of the Varroa mite. Dandelion honey, which is a very traditional honey type in Austria, has not been the subject of extensive investigations. To the best of our knowledge, there are only three papers dealing with volatile compounds from dandelion honey.38,39,42 Fiftyeight volatile compounds from different compound classes were identified in dandelion honey, 34 of which are described for the first time to be present in dandelion honey (Table 2, compounds that have not been reported in dandelion honey before are marked with “*”). In our study, dandelion honey is separated from the other honey types of investigations; this clear differentiation was achieved by sensory classification as H
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respectivelywas present in chestnut honey in significantly higher relative amounts in comparison to the other honey types. A high correlation of 2-aminoacetophenone amounts and chestnut honey can be seen from Figure 4. High relative amounts of diacetyl in combination with compounds such as benzaldehyde are supposed to contribute to the caramel aroma perceived in chestnut and fir tree honeys. Interestingly, even though pine-needle odor was perceived in fir tree honey, we could not identify compounds that could be responsible for the expression of these sensory characteristics. An interesting fact is the presence of nitriles in honey, even though the presence of several nitriles as honey volatiles has been reported before.38,39,42 In our study, three nitriles (2- and 3-methylbutanenitrile as well as benzylnitrile) were identified in almost all honeys with the lowest amount in lavender honey, whereas dandelion and rape honeys showed (very) high relative concentrations of all three nitriles. The presence of several nitriles in dandelion honey was the subject of previous investigations.42 Soria et al.42 stated that the dandelion flower by itself would not be the source of volatile nitriles but proposed plants from Brassicaceae concurrently being present in the meadows during the blooming of dandelion as the source for these compounds. The similar concentrations of nitriles in dandelion and rape honeys as well as the presence of the nitriles in almost all investigated honeys disagree with this theory, as the incidental presence of Brassicaceae in the vicinity of all honeyflow types is very unlikely. However, a thorough investigation on rape honey performed by Ruisinger and Schieberle20 did not identify nitriles as significant contributors to the aroma of rape honey. It is hoped that the results of this study will contribute to a better understanding of honey flavor. Large numbers of volatile compounds were identified by the use of either onedimensional or multidimensional GC-MS analysis of monovarietal honeys. In several cases, only the use of comprehensive GC×GC-MS enabled us to perform a distinct identification of compounds, especially of compounds present in low amounts. Thirty-four volatile compounds present in dandelion honey are described in this paper for the first time. The overall results confirm that it is almost impossible to characterize volatile compounds that are representative for a certain honey type, even though some compounds are predominantly present in only one type of honey. PCA and cluster analysis of the volatile compounds, respectively, show high correlation with the PCA obtained from sensory evaluation. This similarity in PCA biplots demonstrates that profiling techniques such as the applied Napping are well suitable for a quick classification of monovarietal/unifloral honey types. Some of the investigated honeys (i.e., linden and lavender) showed sensory characteristics that were not expected from these honeys types. Analysis of the volatile compounds showed the presence of several odoractive compounds (i.e., thujone isomers, eucalyptol, camphor, eugenol, and thymol as well as carvacrol) that are very likely derived from sources other than the respective honeyflow. The use of essential oils in apiculture for several reasons is suspected to be the reason for the occurrence of these compounds in the honey. Not only can their presence be proven by analytical measures, but our results demonstrate clearly that this treatment may sustainably affect the sensory characteristics of honey.
well as by analysis of the volatile compounds. One group of compounds that is of large impact for the differentiation of dandelion honey from the other investigated unifloral and monovarietal honeys is large amounts of short-chain carboxylic acids. Whereas the straight-chain acids acetic acid, propanoic acid, butanoic acid, and hexanoic acid are present in low amounts that are comparable to the amounts present in other honeys, dandelion honey shows outstanding amounts of the short-chain methyl-branched fatty acids 2-methylpropanoic acid, 2-methylbutanoic acid, and 2-methylpentanoic acid. The importance especially of the propanoic and butanoic acid as well as of 2-methylpentanoic acid for dandelion honey can also be seen from Figure 4. Analogous to the formation of straightchain and methyl-branched aldehydes and alcohols,40 short straight-chain carboxylic acids are most likely derived from lipid degradation, whereas methyl-branched chain carboxylic acids are likely to be formed in the course of the amino acid degradation in the presence of branched-chain amino acid transferase systems. Interestingly, the relative amount of eugenol is 20−500 times higher in dandelion honey than in all other investigated honey types. This is also reflected in the PCA by showing a clear correlation of dandelion honey and eugenol (Figure 4), even though not clearly expressed in the sensory properties. Eugenol has been described in several honey types before.22,26 However, the use of clove oil in apiculture is well-known, on the one hand, as a natural bees’ calmative and apiarists’ protecting agent during harvesting of the honeycomb; on the other hand, essential oils of clove as well as of thyme are used by apiarists as acaricides as alternatives to synthetic measures against insects and other pests.41 Eugenol has not been described as part of dandelion honey before. Due to the use of essential oils in apiculture, a eugenol contamination of dandelion honey is very likely. The presence of carvacrol and thymolidentified in fair concentrations in the investigated linden honeymight be for a similar reason as the presence of eugenol in dandelion honey and is very likely derived from a contamination of the use of essential oils to fight against the Varroa mite, even though carvacrol was reported in linden honey before.25 The honeys of rape and robinia did not show any distinct flavor. Both were described as mainly sweet, woody, bees’-wax like with no sensory peculiarities. The GC-MS chromatograms on either system resulted in chromatograms with rather low amounts of volatile compounds. In addition, in either of the two honeys no compounds could be found that seemed to be unique for these honey types. On the contrary, the three honeys derived from trees containing significant amounts of honeydew honey are grouped in one clusterthis is obtained from sensory evaluation as well as from volatile compound analysis. The presence of guaiacol in these honey types might contribute to the addressed medicinal aroma of these samples. The high relative amounts of thymol and carvacrol in the investigated linden honey are supposed to be further reasons for the perceived medicinal notes of this linden honey, as the odor of thymol is frequently associated with the medicinal notes of cough syrup. However, as linden honey is not supposed to be the natural source for the detected amounts of thymol but more likely evoked by the contamination with essential oils used in the beehive, these results demonstrate a significant impact of the used oils on the sensory properties of the honey. 2-Aminoacetophenonepreviously described as a potential marker compound for chestnut honey25 and wellknown as a contributor to wine flavor and off-flavor, I
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AUTHOR INFORMATION
Corresponding Author
*(B.S.) E-mail:
[email protected]. Phone: +43-316873-32506. ORCID
Barbara Siegmund: 0000-0003-0005-0924 Present Address Δ
(K.U.) Kompetenzzentrum Holz GmbH, Altenberger Straße 69, A-4040 Linz, c/o W3C Wood Carinthian Competence Center, Klagenfurter Straße 87−89, 9300 St. Veit an der Glan, Austria. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We acknowledge the members of the sensory test panel of Graz University of Technology for evaluating the samples.
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ABBREVIATIONS USED AHC, agglomerative hierarchical clustering; amu, atomic mass units; DA, descriptive analysis; DVB, divinylbenzene; EI, electron impact ionization; GC, gas chromatography; HS, headspace; MS, mass spectrometry; m/z, mass charge ratio; PC, principal component; PCA, principal component analysis; PDMS, polydimethylsiloxane; RI, retention index; SPME, solid phase microextraction; UFP, ultraflash profiling
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K
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