Journal of Integrative Agriculture
Advance Online Publication 2016
Doi:10.1016/S2095-3119(15)61274-6
Differential volatile organic compounds in royal jelly associated with different
nectar plants1
ZHAO Ya-zhou
1,2
2
1
1
2*
, LI Zhi-guo , TIAN Wen-li , FANG Xiao-ming , SU Song-kun and PENG
1*
Wen-jun
1
2
Institute of Apiculture, Chinese Academy of Agricultural Sciences, Beijing 100093, P.R.China
College of Bee Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, P.R.China
Abstract
The aim of this work was to distinguish volatile organic compound (VOC) profiles of royal
jelly (RJ) from different nectar plants. Headspace solid-phase microextraction (HS-SPME) was
used to extract VOCs from raw RJ harvested from 10 nectar plants in flowering seasons.
Qualitative and semi-quantitative analysis of VOCs extracts were performed by gas
chromatography-mass spectrometry (GC-MS). Results showed that VOC profiles of RJ from the
samples were rich in acid, ester and aldehyde compound classes, however, contents of them were
differential, exemplified by the data from acetic acid, benzoic acid methyl ester, hexanoic acid and
octanoic acid. As a conclusion, these four VOCs compounds can be used for distinguishing RJ
harvested in the seasons of different nectar plants.
Keywords ： royal jelly, volatile organic compounds, nectar plant, headspace solid-phase
microextraction, gas chromatography-mass spectrometry
1
ZHAO Ya-zhou, Mobile:+86-15001086875, E-mail: [email protected]; Correspondence PENG Wen-jun,
Tel/Tex: +86-10-62597059, E-mail: [email protected]; SU Song-kun, Tel/Tex: +86-591-83739448, E-mail:
[email protected]
*These authors contributed equally to this study.
Journal of Integrative Agriculture
Advance Online Publication 2016
Doi:10.1016/S2095-3119(15)61274-6
不同蜜源植物花期采收蜂王浆的挥发性成分组成
赵亚周 1, 2, 李志国 2, 田文礼 1, 方小明 1, 苏松坤 2*, 彭文君 1*
1
中国农业科学院蜜蜂研究所，北京市海淀区香山北沟 1 号，100093
2
福建农林大学蜂学学院，福建省福州市仓山区上下店路 15 号，350002
摘要：本研究拟揭示不同蜜源植物花期采收蜂王浆的挥发性成分组成及其影响因素。首先采
用顶空固相微萃取技术萃取 10 种蜂王浆样品的挥发性成分，利用气相色谱-质谱联用技术对
萃取到的挥发性成分进行定性与半定量分析。结果显示，蜂王浆样品具有相似的挥发性成分
组成，即富含酸类、酯类和醛类物质；乙酸、苯甲酸甲酯、己酸和辛酸在蜂王浆挥发性成分
中普遍存在，但含量不尽相同。本文结论认为乙酸、苯甲酸甲酯、己酸和辛酸成分可以用以
区分不同蜜源植物花期采收的蜂王浆样品。
关键词：蜂王浆, 挥发性有机化合物, 蜜源植物, 顶空固相微萃取技术, 气相色谱-质谱联用
技术
Journal of Integrative Agriculture
Advance Online Publication 2016
Doi:10.1016/S2095-3119(15)61274-6
Introduction
Flavor or aroma qualities of natural food are greatly dependent upon the volatile organic
compounds (VOCs) presented both in the matrix and the headspace (Overton and Manura, 1995).
The VOC profile is an important feature of food, for both quality and authenticity (Careri, et al.,
1993). Owing to the large number of VOCs, the VOC profile represents a typical character of food,
which can be used for determining the origins of food (Anklam, 1998; Anklam and Radovic,
2001). It has been demonstrated that sound analysis of the VOCs in royal jelly (RJ) could be an
advisable way to determine its origin, quality and even freshness (Isidorov et al., 2009; Isidorov et
al., 2012). Researches on composition of RJ have been reported extensively (Daniele and
Casabianca, 2012; Isidorov et al., 2011; Ferioli et al., 2014). However, little information about the
VOC profiles of RJ is available up to now. RJ, secreted by the hypopharyngeal and mandibular
glands of young worker bees (Apis mellifera L.), is a pasty and slightly acidic (pH 3.5-4.5)
substance and is used to feed the queen and larvae (Zhou et al., 2012). Raw RJ has a special aroma,
and tastes tart, acrid, and slightly sweet (Ramadan and Al-Ghamdi, 2012). Since the ancient times,
RJ has been utilized broadly for its high nutritional value. As the main source of flavor, VOCs in
RJ are generally influenced by honeybee species, harvesting time, regions, storage methods and
processing technologies, etc. Therefore, different origins of RJ might make a great difference to
VOCs in RJ (Boselli et al., 2003; Isidorov et al., 2009; Wu et al., 2009; Isidorov et al., 2012).
The flowering seasons of RJ refer to the flowering and nectar-secreting periods of the nectar
plants when RJ is produced massively by bee colonies. For example, the flowering season of
rapeseeds, a widely cultivated crop in China, is in late spring. The period is just after spring
propagation of honeybee colonies, thus high activity level of honeybee colonies results in large
amounts of pollen, honey and high yield of RJ as well (Stocker et al., 2005). Since RJ is secreted
by worker bees, which feed on bee bread made by pollens and honey (Sereia et al., 2013).
Therefore, compounds of RJ (both volatile and non-volatile) are influenced by bee bread and
nutrition of which depends on the pollen. As a result, the changing pattern of VOCs in RJ
associates with flowering seasons of nectar plant, when work bees collect pollen intensively.
Analysis of VOCs is also influenced by extraction and detection technologies (Boselli et al., 2003;
Isidorov
et
al.,
2009).
Extraction
technologies
of
VOCs
include
simultaneous
distillation-extraction (SDE), dynamic headspace extraction, static headspace extraction,
ultrasonic-assisted extraction, steam distillation, solvent extraction, solid-phase microextraction,
ect. Some of these technologies may be suitable for extraction of VOCs in RJ (Boselli et al., 2003;
Isidorov et al., 2009; Zhou et al., 2009), however, some technologies still needs to be improved.
For example, steam distillation is time-consuming, especially when the sample size is big. Heating
process of SDE may promote the formation of artificial by-products. Solvent elimination process
of solvent extraction may lead to residues. Besides, low concentrations of VOCs in RJ and
interferences of protein and sugar that are main components of RJ should be concerned. With the
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development of technologies (Snow and Bullock, 2010), headspace extraction appears to be the
optimal method for extracting VOCs in RJ.
In this study, VOC profiles of RJ samples harvested in different flowering seasons in China
were established using gas chromatography-mass spectrometry (GC-MS) preceded by headspace
solid-phase microextraction (HS-SPME) to extract VOCs in RJ. This quick, economical and
efficient method circumvented the issues associated with solvent, protein and sugar. The final
results of VOC profiles of RJ will provide a theoretical basis for assessing the RJ quality.
Results
Water content of raw RJ samples
Isomerization of monosaccharide, e.g. fructose, and formation rate of Amadori compounds in
RJ are known to be influenced by water content. What follows next is composition change of
aldehydes (Ferrer et al., 2002), some of which are volatile; we checked water contents of every
type of RJ samples. As shown in Fig. 1, the water contents of all samples are almost equal.
Samples harvested in flowering season of Citrullus lanatus have water contents at (62.98±0.22)%,
which is significant lower than all the other samples (P<0.05, n=3). Whereas samples harvested in
flowering season of Lichi chinensis have water contents at (68.40±0.37)%, which is significant
higher than all the other samples (P<0.05, n=3). The water contents of the other 8 types of samples
show even smaller differences ranging from (64.81±0.06)% to (65.94±0.13)%.
Total ion chromatogram of VOCs
The total ion chromatograms (TICs) of all samples were similar. Fig. 1 shows an example of
one sample harvested in flowering season of Tilia tuan. The VOC profiles of different types of RJ
only differ in the contents regarding a few rare compounds which exist in low concentration in one
or two samples, suggesting the similar flavor profiles of all RJ samples. The chromatographic
conditions are well suitable to VOCs absorbed by HS-SPME, making the chromatographic peaks
fully separated and overlapped rarely. Except for solvent (n-hexane) peak, impure peaks and ghost
peaks, the first VOC peak was reached at about the 4th minute and the last one was reached at
about the 36th minute. The whole analysis process lasted for 40 min.
Qualitative and semi-quantitative analysis of VOCs
A total of 89 compounds were identified in all RJ samples. Only 40 of them are listed in Table
2 based on the criteria: 1) the content of the compound was relatively high; 2) the compound was
detected in at least 2 types of RJ samples. Among the identified compounds, 2-nonanone and
acetic acid were both detected in all 10 types of RJ samples; toluene, benzaldehyde, phenol and
octanoic acid in 9; and 2-pentanone, benzoic acid and methyl ester in 8. These commonly shared
compounds may be related to the characteristics of RJ flavor. In terms of quantity, the contents of
VOCs in different types of RJ samples ranged from 0.0010 to 4.0089 μg μL-1. As for specific
VOCs in different RJ samples, although we found 14 specific VOCs in total in the study, these
compounds were absent in most samples (6-8 types of RJ samples). These compounds included
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(1-propen-2-ol, formate), ethanol, (butanoic acid, ethyl ester), (acetic acid, butyl ester), hexanal,
ethylbenzene, octanal, (benzene, 1,2,3,5-tetramethyl-), (2-furancarboxaldehyde, 5-methyl-),
benzoxazole,
2-furanmethanol,
2,3-dihydro-3,5-dihydroxy-6-methyl-)
methyl
and
salicylate,
(2-furancarboxaldehyde,
(4H-pyran-4-one,
5-(hydroxymethyl)-).
Therefore, we concluded that the 14 compounds may be not suitable for differentiate the RJ
samples. However, we also found that acetic acid, benzoic acid methyl ester, hexanoic acid and
octanoic acid exist in the RJ samples universally (7-10 types of RJ samples), and can differentiate
all the RJ samples to a great extent. Maybe there were also some compounds with lower
concentrations than 0.0010 μg μL-1, but they were can't be detected due to detection limit of
chromatogram or SPME efficiency.
Classification of VOCs in RJ samples
Classification of VOCs in all samples is shown Fig. 2. Esters and aldehydes were the most
abundant VOCs among the 40 VOCs, accounting for 25 and 17.5%, respectively. They may
contribute the most to the RJ flavor. There were also other classes of compounds such as ketones
(15%), acids (10%) and alcohols (10%), etc. Fig. 3 shows a significant variation of different
compound classes in each type of RJ samples, and that acids in all samples were at a higher level.
These acids may therefore contribute to the tart and acrid taste of RJ.
Effect of water content on VOC content of different VOC classes
Water content shows significantly negative correlation with esters content and alcohols content
(P<0.05). Besides, there is significantly positive correlation between esters content and acids
content (P<0.05), and a significantly positive correlation (P<0.01) is also observed between esters
content and alcohols content (Table 3).
Hierarchical cluster analysis
Hierarchical cluster analysis was performed based on contents of different types of VOCs. As
shown in Fig. 5, 10 types of RJ samples can be separated into 3 groups. In the group a, samples
harvested in flowering seasons of Schisandra chinensis, Medicago sativa, Vitex negundo and
Citrullus lanatus belong to the same subgroup, showing a slight difference from samples
harvested in the flowering season of Sophora alopecuroides. In the group b, samples harvested in
flowering seasons of Brassica campestris, Robinia pseudoacacia and Helianthus annuus were
grouped as another subgroup, with a difference from samples harvested in flowering season of
Litchi chinensis. The group c was formed of only samples harvested in flowering season of Tilia
tuan, which is considerably different from other samples.
Discussion
In this study, the measured water contents of the 10 types of RJ samples between 62.98% and
68.40%, is according the normal range of 60%-70% (Sabatini et al., 2009). We considered storage
conditions were the main reasons to lead to the difference. Given that honeybees were raised by
beekeepers in China for RJ production, and methods for RJ production are the same (Li et al.,
2007), the RJ production process has low effects on water contents in the studied samples. Chen
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and Chen (1995) reported that the viscosity of RJ would rise due to the prolonged storage or raised
storage temperature. And the viscosity of RJ was found to vary associated with water content and
time (Ramadan and Al-Ghamdi, 2012). These viewpoints agreed with our consideration that
storage condition can affect the water content of RJ. In addition, the results showed that water in
RJ had negative correlation with esters and alcohols in VOCs, which may be resulted from
dilution or medium effects of the water (Liu et al., 2006).
The ideal chromatographic conditions for RJ analysis were obtained based on the preliminary
experiments. There are 89 compounds detected, however, only 40 of them had relative high
contents and were detected in at least 2 types of RJ. Therefore, we can ensure that these 40
compounds are from the RJ samples in which characteristic VOCs exist. The remaining 49
compounds may be natural elements of RJ, baseline drift/spectral background of gas
chromatography (Jalali-Heravi and Parastar, 2011; Moazeni-Pourasil, et al., 2014) or even
honeybee larvae (Isidorov et al., 2009), which therefore were not used for further analysis. This
analysis could be used to checked the freshness, quality and standardization of RJ. There are some
undetected compounds with very low content in volatility, which made a limitation of detection of
gas chromatography and SPME efficiency (Ponnusamy and Jen, 2011). It is well-known that
VOCs contribute to the aroma, and also affect the taste to some content (Baroni et al., 2006;
Manyi-Loh et al., 2011). The abundant acids detected in VOCs coincide with the acidy taste of RJ
studied. Besides, acetic acid, benzoic acid methyl ester, hexanoic acid and octanoic acid present in
the VOCs of all the samples of RJ contribute mostly to the flavor. These compounds can be used
to differentiate the nectar plants of RJ samples. However, we should also consider ethanol and
furfural that do not entirely belong to VOCs of RJ, because their content was high. Ethanol might
be formed by fermentation of carbohydrates, induced by high water content in the system (Bertelli
et al., 2008); also the heating during the extraction process of sample might lead to create furfural
(Vázquez et al., 2006; Wolski et al., 2006; Kaškonienė et al., 2008).
There are a great variety of nectar plants which grown in China, and various species blossom
in different time in one year. Migratory beekeepers therefore choose the flowering seasons of the
chief nectar plants to produce RJ. As a result, flowering seasons play signigicant roles in the
formation of special components in the RJ (Isidorov et al., 2009; Isidorov et al., 2012; Boselli et
al., 2003; Wu et al. 2009), which is in accordance with the clustering results in this study. Besides,
results from cluster analysis showed that the height of nectar plants in group a is lower than that in
group b and c, and the height of basswood (Tilia tuan) in group c is the tallest. Whether the height
of nectar plants has effects on VOCs in RJ, or it is just a coincidence? Some further studies need
to be done to test that.
More information is needed to investigate the relationship between the type of nectar plants
and VOCs in RJ. The results in the study may be helpful for intensive management of RJ
production and building regional brands.
Conclusion
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The storage conditions of RJ may affect its water content, which negatively correlates with the
contents of esters and alcohols in VOCs of RJ due to dilution or medium effects of water. Acetic
acid, benzoic acid methyl ester, hexanoic acid and octanoic acid are present in VOCs of RJ totally,
contributing much more to RJ flavor; for this they can be used for differentiating the RJ samples
harvested in the seasons of different nectar plants. The VOC profiles of RJ are associated with
flowering seasons of different nectar plants whose height may play an important role in the
differential VOC profiles found in the study.
Materials and methods
RJ sampling
Raw RJ samples were collected from honeybee (Apis mellifera L.) apiaries kept in the main
beekeeping areas in China. Thirty RJ samples were collected from 30 apiaries evenly distributed
in 10 different flowering seasons (Table 1). Sampling time was in the mid-term of every flowering
season of the corresponding nectar plant. For each apiary, 3 colonies were used for collecting raw
RJ samples and 20 g raw RJ were collected from each colony, respectively. The 3 different raw RJ
samples were then mixed, and finally a total of 60 g RJ samples were obtained from each apiary.
After collection, the samples were preserved at -20℃ immediately.
Measurement of water content
Precisely weighed RJ (1.000 g) was transferred into an evaporating dish on a constant load.
Then the evaporating dish was put into a vacuum oven (temperature 48℃) for 24 h, and dried to
constant weight. The evaporating dish was weighed after cooling for 15 min (Sesta and Lusco,
2008).
Extraction of VOCs from RJ
Before extraction of VOCs, a SPME extractor was inserted into the chromatograph injection
port to be conditioned at 270℃ for 60 min. Precisely weighed 8 g RJ was transferred into a 100
mL headspace bottle. 1 μL aliquot of internal standard (2-methyl-3-heptanone, 1.632 μg mL-1 in
n-hexane) was then added together with 10 mL saturated NaCl solution into the headspace bottle.
The mixed solution in the headspace bottle was stirred on a magnetic stirrer at 50℃ for 30 min.
The conditioned SPME extractor was then inserted into the headspace bottle and kept at 50℃ for
40 min.
Automatic thermal desorption (TDS3/TDSA2)
After extraction, the SPME extractor was inserted into the chromatograph injection port.
Temperature of the port was initially kept at 35℃ for 3.5 min and was ramped to 230℃ at 60℃
min-1. The temperature was then kept at 230℃ for 1 min. Temperature of transmission line
between thermal desorption system and injection port was set at 300℃. Temperature of the
enclosed cold injection system was initially kept at -100℃ for 12 s, and ramped to 280℃ at 10℃
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min-1. The temperature was kept at 280℃ for 30 s.
Gas chromatography parameters
Temperature of the capillary column (DB-WAX，30 m×0.25 mm，0.25 μm) was initially kept
at 40℃ for 3 min and ramped to 200℃ at 5 ℃ min-1. It was then ramped again to 240℃ at
10℃min-1 and kept at 240℃ for 5 min. Constant current velocity was 1.2 mL min-1 using
ultrapure helium (purity >99.999%) as carrier gas. The injector was operated under spitless mode
at 250℃ and 14.87 psi.
Mass spectrometry parameters
Temperature of electron impact (EI) ion source was 230℃. The EIMS spectra were obtained at
ionization energy of 70 eV. Temperatures of transmission line and quadrupole were 280℃ and
150℃ respectively. Solvent delay was set at 3 min and scanned mass range was from 55-500 m/z.
Identification of compounds
Compounds were identified either by library search, retention index (RI) match or both. More
specifically, the mass spectrum of an unknown compound was searched in data processing system
(NIST2.0). That matching degree and purity were both higher than 800 was the threshold for
identification. For the RI method, C8-C27 n-alkanes dissolved in n-hexane were separated under
the GC-MS conditions mentioned above. RI was calculated based on retention time of each
individual peak using the equation below.
RI  100  n 
100(ta  tn )
tn 1  tn
Where, ta is the retention time of the unknown peak a; tn is the retention time of n-alkane Cn; and
tn+1 is the retention time of n-alkane Cn+1.
The calculated RI was then compared to the online RI database (www.odour.org.uk).
Difference between calculated RI and reference RI should fall within the range of 0-100 for
identification.
Quantitation
Semi-quantitative analysis was performed on each identified compound according to internal
standard. The concentration of the identified compound was calculated using the following
C  SX
equation.
C  A
X
SA
where CX is the mass concentration of an identified compound; SX is the chromatographic peak
area of the identified compound; CA is the mass concentration of the internal standard; and SA is
the chromatographic peak area of the internal standard.
Data analysis
Data processing was performed using SPSS 18.0 (SPSS, Inc., Chicago, IL, USA). Means and
standard deviations (SDs) were calculated from triplicate measurements of each type of RJ
samples. Analysis of variance was performed using one-way ANOVA method, and differences
within contents of different compounds or water contents of different types of RJ were assessed
using paired t-tests. Bivariate correlation method was used to conduct correlation analysis. Method
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of hierarchical cluster analysis of RJ samples was between-groups linkage, Euclidean distance
(0-25) was used to calculate the similarity among samples.
Acknowledgements
This work was supported by the Agricultural Science and Technology Innovation Program (ASTIP)
and the Building of Modern Agricultural Industry (Bees) R&D Systems in China
(NYCYTI-43-KXJ17).
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components by solid phase microextraction (SPME) and gas chromatography/mass spectrometry
(GC/MS). Journal of Apicultural Science, 50, 115-126.
Zhou J, Xue X, Chen F, Zhang J, Li Y, Wu L, Chen L, Zhao J. 2009. Simultaneous determination
of seven fluoroquinolones in royal jelly by ultrasonic ‐ assisted extraction and liquid
chromatography with fluorescence detection. Journal of Separation Science, 32, 955-964.
Zhou L, Xue X, Zhou J, Li Y, Zhao J, Wu L. 2012. Fast determination of adenosine
5′-triphosphate (ATP) and its aatabolites in royal jelly using ultraperformance liquid
chromatography. Journal of Agricultural and Food Chemistry, 60, 8994-8999.
Journal of Integrative Agriculture
Advance Online Publication 2016
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Table 1. Sampling information of royal jelly samples harvested in flowering seasons of different nectar plants.
Nectar plants
Regions
(Latin names)
( Provinces/Lng. & Lat.)
1
Tilia tuan
2
Royal jelly samples
Flowering time
Sampling environment
Jilin/43.2981°N, 128.1158°E
Jul. 2013
Shrubbery and farmland
Schisandra chinensis
Ningxia/36.3620°N, 106.1336°E
Jun. 2013
Shrubbery and Grassland
3
Vitex negundo
Beijing/39.9941°N, 116.2060°E
Jul. 2013
Shrubbery
4
Sophora alopecuroides
Ningxia/37.5668°N, 107.1823°E
Jun. 2013
Grassland, meadow and
shrubbery
5
Litchi chinensis
Fujian/24.4524°N, 117.6196°E
Jul. 2013
Shrubbery
6
Medicago sativa
Ningxia/35.4617°N, 105.9842°E
Jul. 2013
Shrubbery and farmland
Jul. 2013
Shrubbery, meadow and
7
Helianthus annuus
Xinjiang/47.3636°N, 87.8004°E
everglade
8
Brassica campestris
Chongqing/30.3272°N, 107.3327°E
Mar. 2013
Shrubbery and farmland
9
Robinia pseudoacacia
Liaoning/38.9140°N, 121.6147°E
May 2013
Shrubbery and farmland
Aug. 2013
Grassland, meadow and
10
Citrullus lanatus
Xinjiang/46.5247°N, 83.6283°E
farmland
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Table 2
Doi:10.1016/S2095-3119(15)61274-6
Qualitative and semi-quantitative analysis of volatile organic compounds in royal jelly samples harvested in flowering seasons of different nectar plants.
Nectar plants
Compounds
Tilia tuan
Schisandra chinensis
Vitex negundo
Sophora alopecuroides
Litchi chinensis
Medicago sativa
Helianthus annuus
Brassica campestris
Robinia pseudoacacia
Citrullus lanatus
1-Propen-2-ol, formate
n.d. ① (c) ②
n.d. (c)
0.1419±0.00272③ (b)
n.d. (c)
n.d. (c)
n.d. (c)
0.1686±0.0091 (a)
n.d. (c)
n.d. (c)
n.d. (c)
Butanal, 2-methyl-
n.d. (d)
0.1601±0.0143 (a)
n.d. (d)
0.0617±0.0540 (c)
0.1943±0.0081 (a)
0.1915±0.0122 (a)
n.d. (d)
0.2132±0.0188 (a)
0.3413±0.0341 (b)
n.d. (d)
Ethyl Acetate
0.8190±0.0786 (a)
n.d. (c)
n.d. (c)
0.0605±0.0275 (b)
n.d. (c)
n.d. (c)
0.0545±0.0238 (b)
n.d. (c)
n.d. (c)
n.d. (c)
Ethanol
3.9314±0.1354 (a)
0.3501±0.0158 (b)
n.d. (e)
0.3502±0.0440 (c)
n.d. (e)
0.1418±0.0035 (d)
n.d. (e)
n.d. (e)
n.d. (e)
n.d. (e)
2-Pentanone
0.0338±0.0198 (bc)
0.0241±0.0082 (c)
0.0411±0.0040 (bc)
n.d. (d)
0.0154±0.0134 (cd)
n.d. (d)
0.0333±0.0058 (bc)
0.0481±0.0039 (b)
0.3024±0.0223 (a)
n.d. (d)
Butanoic acid, ethyl ester
0.1875±0.0135 (a)
n.d. (d)
n.d. (d)
0.1171±0.0070 (b)
n.d. (d)
n.d. (d)
0.0560±0.0313 (c)
n.d. (d)
n.d. (d)
n.d.(d)
Toluene
n.d. (d)
0.0311±0.0104 (d)
0.1405±0.0127 (c)
1.1792±0.0786 (a)
0.0735±0.0129 (cd)
0.1296±0.0124 (cd)
0.1045±0.0121 (cd)
0.0810±0.0181 (cd)
1.0431±0.1802 (b)
n.d. (d)
Acetic acid, butyl ester
n.d. (c)
n.d. (c)
n.d. (c)
0.0579±0.0091 (b)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.1450±0.0153 (a)
n.d. (c)
Hexanal
n.d. (c)
n.d. (c)
0.0869±0.0059 (b)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.4462±0.0124 (a)
n.d. (c)
Ethylbenzene
n.d. (c)
n.d. (c)
n.d. (c)
0.0311±0.0115 (b)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.0985±0.0088 (a)
n.d. (c)
4-Octanone
n.d. (b)
n.d. (b)
n.d. (b)
0.3976±0.0254 (a)
n.d. (b)
n.d. (b)
n.d. (b)
n.d. (b)
n.d. (b)
0.0036±0.0038 (b)
Styrene
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.0819±0.0149 (a)
n.d. (c)
0.0277±0.0028 (b)
0.0288±0.0151 (b)
n.d. (c)
n.d. (c)
Octanal
n.d. (c)
n.d. (c)
n.d. (c)
0.1807±0.0194 (a)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.0853±0.0140 (b)
n.d. (c)
2-Nonanone
0.1279±0.0175 (cd)
0.1715±0.0118 (c)
0.0587±0.0228 (de)
0.5467±0.0548 (b)
0.5711±0.0392 (b)
0.1596±0.0190 (cd)
0.1101±0.0160 (d)
0.5767±0.0501 (b)
0.7896±0.0422 (a)
0.0092±0.0044 (e)
Benzene, 1,2,3,5-tetramethyl-
n.d. (c)
0.0253±0.0100 (b)
n.d. (c)
n.d. (c)
0.1629±0.0177 (a)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
Acetic acid
0.1751±0.0132 (d)
0.0580±0.0159 (g)
0.0877±0.0081 (f)
0.1740±0.0174 (d)
0.4714±0.0187 (a)
0.0942±0.0179 (f)
0.1318±0.0121 (e)
0.2068±0.0194 (c)
0.4034±0.0256 (b)
0.0032±0.0031 (h)
Furfural
0.1287±0.0018 (c)
0.0144±0.0041 (e)
n.d. (e)
n.d. (e)
0.6870±0.0810 (a)
0.0731±0.0169 (d)
n.d. (e)
0.1145±0.0090 (cd)
0.3789±0.0013 (b)
n.d. (e)
Benzaldehyde
0.1688±0.0109 (b)
0.0416±0.0267 (e)
0.0815±0.0124 (d)
0.1522±0.0118 (bc)
0.1333±0.0081 (c)
0.0324±0.0193 (ef)
0.0835±0.0300 (d)
0.5540±0.0168 (a)
n.d. (f)
0.0102±0.0018 (f)
2-Furancarboxaldehyde, 5-methyl-
n.d. (d)
n.d. (d)
n.d. (d)
n.d. (d)
0.3768±0.0182 (a)
0.0176±0.0046 (c)
n.d. (d)
0.0500±0.0141 (b)
n.d. (d)
n.d. (d)
Butanoic acid
n.d. (d)
0.0196±0.0048 (c)
0.0203±0.0031 (c)
n.d. (d)
n.d. (d)
n.d. (d)
0.0533±0.0058 (b)
0.0722±0.0187 (a)
0.0766±0.0112 (a)
n.d. (d)
Methyl butyrate
n.d. (c)
n.d. (c)
0.1607±0.0281 (b)
0.1420±0.0493 (b)
n.d. (c)
n.d. (c)
0.3577±0.0256 (a)
n.d. (c)
n.d. (c)
n.d. (c)
Benzoic acid, methyl ester
0.2622±0.01136 (c)
0.16405±0.0211 (e)
n.d. (f)
n.d. (f)
0.2217±0.0160 (d)
0.1526±0.0286 (e)
n.d. (f)
0.4598±0.0320 (b)
0.5620±0.0304 (a)
0.0134±0.0045 (f)
Benzoxazole
0.3475±0.0149 (a)
0.0327±0.0172 (c)
n.d. (d)
n.d. (d)
n.d. (d)
n.d. (d)
n.d. (d)
n.d. (d)
0.2424±0.0072 (b)
n.d. (d)
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2-Furanmethanol
n.d. (d)
n.d. (d)
0.1541±0.0355 (b)
n.d. (d)
0.2838±0.0351 (a)
n.d. (d)
0.1263±0.0123 (c)
n.d. (d)
n.d. (d)
n.d. (d)
Acetophenone
n.d. (d)
0.0403±0.0158 (c)
n.d. (d)
n.d. (d)
n.d. (d)
0.0527±0.0135 (c)
n.d. (d)
0.2357±0.0427 (b)
0.3422±0.0175 (a)
0.0083±0.0057 (d)
2(3H)-Furanone, 5-ethyldihydro-
0.0441±0.0134 (a)
0.0137±0.0011 (b)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.0161±0.0057 (b)
n.d. (c)
n.d. (c)
n.d. (c)
Naphthalene
n.d. (d)
0.0293±0.0036 (c)
0.0325±0.0078 (c)
n.d. (d)
0.3372±0.0027 (a)
n.d. (d)
0.0346±0.0046 (c)
n.d. (d)
0.1087±0.0079 (b)
n.d. (d)
Methyl salicylate
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.1104±0.0026 (a)
0.0496±0.0089 (b)
n.d. (c)
n.d. (c)
Anethol
n.d. (b)
n.d. (b)
n.d. (b)
n.d. (b)
0.0493±0.0217 (a)
n.d. (b)
n.d. (b)
n.d. (b)
0.0651±0.0251 (a)
n.d. (b)
Hexanoic acid
0.1951±0.0069 (a)
0.0315±0.0059 (e)
0.0400±0.0067 (e)
n.d. (f)
n.d. (f)
0.0384±0.0051 (e)
0.0817±0.0125 (d)
0.1189±0.0111 (c)
0.1431±0.0048 (b)
n.d. (f)
Benzyl Alcohol
0.0647±0.0263 (a)
0.0133±0.0040 (b)
n.d. (b)
n.d. (b)
n.d. (b)
n.d. (b)
n.d. (b)
0.0551±0.0198 (a)
n.d. (b)
n.d. (b)
Phenylethyl Alcohol
0.1202±0.0156 (b)
0.0040±0.0046 (e)
n.d. (e)
n.d. (e)
0.2462±0.0023 (a)
0.0524±0.0121 (c)
n.d. (e)
0.0340±0.0058 (d)
n.d. (e)
n.d. (e)
2(3H)-Furanone, 5-butyldihydro-
0.0531±0.0049 (b)
0.0127±0.0019 (e)
0.0154±0.0035 (e)
n.d. (f)
0.0652±0.0083 (a)
n.d. (f)
0.0360±0.0096 (c)
0.0241±0.0056 (d)
n.d. (f)
0.0019±0.0024 (f)
Ethanone, 1-(1H-pyrrol-2-yl)-
n.d. (b)
0.0031±0.0046 (b)
0.0042±0.0045 (b)
n.d. (b)
n.d. (b)
n.d. (b)
0.0505±0.0204 (a)
0.0452±0.0086 (a)
n.d. (b)
n.d. (b)
0.0394±0.0096 (a)
n.d. (c)
0.0070±0.0026 (b)
n.d. (c)
n.d. (c)
n.d. (c)
0.0426±0.0050 (a)
n.d. (c)
n.d. (c)
n.d. (c)
Phenol
0.1154±0.0104 (c)
0.0734±0.0135 (de)
0.0686±0.0229 (e)
n.d. (f)
0.1139±0.0151 (c)
0.0901±0.0060 (d)
0.0806±0.0104 (de)
0.1844±0.0100 (a)
0.1598±0.0131 (b)
0.0032±0.0032 (f)
Octanoic Acid
2.0303±0.0232 (b)
0.5979±0.0354 (e)
0.2739±0.0187 (g)
n.d. (h)
1.6542±0.0232 (c)
0.4327±0.0537 (f)
1.4900±0.0924 (d)
2.7575±0.1780 (a)
1.5872±0.0911 (cd)
0.0267±0.0191 (h)
8-Nonen-2-one
n.d. (e)
0.0389±0.0042 (d)
0.0525±0.0102 (d)
n.d. (e)
0.3494±0.0315 (b)
n.d. (e)
0.1634±0.0129 (c)
0.4105±0.0233 (a)
n.d. (e)
n.d. (e)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
0.5598±0.0227 (a)
0.0239±0.0051 (b)
n.d. (c)
n.d. (c)
n.d. (c)
n.d. (c)
n.d.(c)
n.d. (c)
n.d. (c)
n.d. (c)
1.0696±0.0358 (a)
n.d. (c)
n.d. (c)
0.0593±0.0179 (b)
n.d. (c)
n.d. (c)
2H-Pyran-2-one,
tetrahydro-6-propyl-
4H-Pyran-4-one,
2,3-dihydro-3,5-dihydroxy-6-methyl2-Furancarboxaldehyde,
5-(hydroxymethyl)①
②
③
The n.d. means that the target compound has not been detected.
In a specific row, different letters in parentheses represent significant difference level (P < 0.05).
Contents of volatile organic compound in royal jelly harvested in flowering seasons of different nectar plants (μg/μL, mean±standard deviation, n=3).
Journal of Integrative Agriculture
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Journal of Integrative Agriculture
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Table 3
Doi:10.1016/S2095-3119(15)61274-6
Correlation analysis of water contents and contents of different compound classes of volatile organic
compound.
Water
Water
Esters
1
①
Esters
Aldehydes
Ketones
-0.714*
-0.095
-0.009
1
-0.078
0.198
1
0.514
1
Aldehydes
Ketones
Acids
Alcohols
Others
*
Correlation is significant at the 0.05 level (2-tailed).
**
①
Correlation is significant at the 0.01 level (2-tailed).
Correlation coefficient.
Acids
Alcohols
Others
-0.468
-0.713*
-0.203
0.640*
0.784**
0.133
0.504
-0.055
0.399
0.578
-0.300
0.478
1
0.327
0.158
1
-0.069
1
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Fig. 1 Water contents of royal jelly samples harvested in flowering seasons of different nectar plants: different
letters (a, b, c, d, e) above the bars represented significant difference level (P<0.05, n=3)
Fig. 2 Exemple of the total ion chromatogram of volatile organic compounds in Tilia tuan royal jelly sample
harvested in flowering season: X axis represents retention time; Y axis represents abundance.
Journal of Integrative Agriculture
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Fig. 3 Compound classes of volatile organic compounds in all royal jelly samples.
Fig. 4 Contents (μg μL-1) of compound classes of volatile organic compounds in royal jelly samples harvested in
the flowering seasons of the different nectar plants.
Journal of Integrative Agriculture
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Fig. 5 Hierarchical cluster analysis of royal jelly samples based on contents of compound classes of volatile
organic compounds: three groups (a, b, c) are formed by cluster analysis.