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A triple-isotope approach for discriminating the geographic origin of Asian sesame oils
Food Chemistry 167 (2015) 363–369
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Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
A triple-isotope approach for discriminating the geographic origin of Asian sesame oils Hyeonjin Jeon a, Sang-Cheol Lee b, Yoon-Jae Cho c, Jae-Ho Oh c, Kisung Kwon c, Byung Hee Kim a,⇑ a
Department of Food Science and Technology, Chung-Ang University, Anseong 456-756, Republic of Korea Bee Product Research Center, Korea Apicultural Association, Seoul 137-070, Republic of Korea c National Institute of Food and Drug Safety Evaluation, Korea Food and Drug Administration, Cheongwon 363-700, Republic of Korea b
a r t i c l e
i n f o
Article history: Received 17 March 2013 Received in revised form 6 January 2014 Accepted 5 July 2014 Available online 12 July 2014 Keywords: Sesame oil Geographic origin Carbon stable isotope Hydrogen stable isotope Oxygen stable isotope Canonical discriminant analysis
a b s t r a c t The aim of this study was to investigate the effects of the geographic location and climatic characteristics of the sesame-producing sites on the carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil. In addition, the study aimed to differentiate Korean sesame oil from Chinese and Indian sesame oils using isotopic data in combination with canonical discriminant analysis. The isotopic data were obtained from 84 roasted oil samples that were prepared from 51 Korean, 19 Chinese, and 14 Indian sesame seeds harvested during 2010–2011 and distributed in Korea during the same period. The d13C, dD, and d18O values of Korean sesame oil were negatively correlated with latitude, distance from the sea, and precipitation (May–September), respectively. By applying two canonical discriminant functions, 89.3% of the sesame oil samples were correctly classified by their geographic origin, indicating that the triple-isotope approach is a useful tool for the traceability of the oils. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Sesame (Sesamum indicum L.) is an oilseed crop that is primarily cultivated in Asian and African countries. Roasted sesame oil is unrefined edible oil obtained from sesame seeds roasted at 180– 200 °C (Namiki, 1995). This oil is frequently used as a flavor enhancer in Eastern Asian cooking since Eastern Asians, including Koreans, prefer the characteristic flavor of the oil that develops during roasting (Kim & Akoh, 2006). Sesame seeds are available in three different colors, black, brown, and white. White sesame seeds are mostly used in the manufacturing of roasted sesame oil in Korea (Jeon et al., 2013). False indications of the geographic origin of sesame products became an issue of public concern in Korea after the 1990s. In the 2000s, Koreans consumed approximately 100,000 tonnes of sesame seeds per year. Because the annual domestic production (approximately 13,000 tonnes) of sesame seeds could not sustain the national need, Korea imported approximately 140,000 tonnes of sesame seeds during 2009 and 2010 (FAO, 2012). Indian and Chinese sesame seeds occupy approximately 43% and 38% of Korea’s sesame imports, respectively (KFDA, 2012). Chinese and Indian sesame seeds/oils that are deliberately labeled as domestic often
⇑ Corresponding author. Tel.: +82 316703033; fax: +82 316754853. E-mail address: [email protected] (B.H. Kim). http://dx.doi.org/10.1016/j.foodchem.2014.07.032 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
appear in Korean local markets, because Korean sesame seeds/oils are 3–4 times higher in price than Chinese or Indian sesame products. This has created the need for analytical methods to distinguish Korean sesame oil from the oil obtained from imported sesame seeds. The geographic location and climatic conditions of cultivation sites influence the stable isotopic signature of plants. The carbon stable isotope ratio (13C/12C) of plant materials is preferentially affected by the types of photosynthetic processes, i.e., the C3 and C4 pathways, which the plants employ for fixing atmospheric carbon dioxide (Smith & Epstein, 1971). Climatic factors, such as relative humidity, temperature, and the amount of precipitation, which affect the stomatal conductance of carbon dioxide, cause variations in the carbon stable isotope ratio of C3 plants including sesame (Farquhar, Ehleringer, & Hubick, 1989; Farquhar, O’Leary, & Berry, 1982). The hydrogen (D/1H) and oxygen (18O/16O) stable isotope ratios of plant material are strongly correlated with those ratios in the local precipitation water that is incorporated by the plant. The isotopic composition of precipitation is primarily affected by geographic and climatic conditions, such as latitude, distance from the sea, altitude, temperature, and the amount of precipitation (Gat, Mook, & Meijer, 2000). Some climatic factors (e.g., relative humidity and temperature) influence the stomatal transpiration of water, thereby inducing the fractionation of hydrogen and oxygen isotopes in plant materials (Perri, Benincasa, & Muzzalupo, 2012). Therefore, the combined analysis of carbon,
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hydrogen, and oxygen stable isotope ratios could be a useful tool for the traceability of oils derived from plant sources. Several researchers have utilized the triple-isotope approach for identifying the geographic origin of plant oils produced in European regions, such as olive oil and rapeseed oil (Bontempo et al., 2008; Camin, Larcher, Nicolini, et al., 2010; Camin, Larcher, Perini, et al., 2010; Richter, Spangenberg, Kreuzer, & Leiber, 2010). In contrast, little is known about the stable isotopic signature (particularly, D/1H and 18O/16O) of sesame oil. Furthermore, no published studies have characterized the geographic origin of the oil using the triple-isotope approach. The aim of this study was to investigate the effects of the geographic location and climatic characteristics of the sesame-producing sites on the carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil. In addition, the study was designed to differentiate Korean sesame oil from Chinese and Indian sesame oils that are distributed in Korea using isotopic data. 2. Materials and methods 2.1. Sample preparation Samples of white sesame seeds (n = 51) were collected from 36 sites in Korea during the 2010 and 2011 harvests (Fig. 1). Samples of Chinese white sesame seeds (n = 19) and Indian white sesame seeds (n = 14), which were imported by the Korea Agro-Fisheries Trade Corporation between 2010 and 2011, were purchased from local grocery stores in Korea. The sesame seeds were roasted in a drum roaster (model THDR-01; Taehwan Automation Industry Co., Seoul, Korea) at 200 °C for 30 min. The oil was extracted from the roasted sesame seeds using an oil press (model Oil Love; National ENG Co., Goyang, Korea) and was centrifuged at 9600g for 10 min. The roasted sesame oils were completely dried under nitrogen flushing. The water content of the oils was monitored using a Karl-Fisher moisture analyzer (model 803 Ti Stand; Metrohm, Herisau, Switzerland) and was adjusted to <300 mg/kg. A sample of commercial Korean roasted sesame oil was obtained from an edible oil manufacturing company. 2.2. Geographic and climatic data analysis Data of the geographic characteristics (latitude, distance from the sea, and altitude) of the production sites of Korean sesame seeds used in this study were collected from Google Earth (http://earth.google.com). Climatic data including precipitation, mean relative humidity, and mean temperature during the five months (May–September) corresponding to the growth period of the sesame were obtained from the Korea Meteorological Administration (http://www.kma.go.kr). 2.3. Stable isotope analysis The carbon stable isotope ratio of the sesame oil samples was analyzed using an IsoPrime 100 (GV instruments, Manchester, UK) isotope ratio mass spectrometer (IRMS) coupled with a vario MICRO cube (Elementar Analysensysteme GmbH, Hanau, Germany) elemental analyzer (EA). An aliquot of the oil samples was placed into a 5 3.5 mm tin capsule (Elemental Microanalysis, Okehampton, UK) and injected into the EA. The combustion and reduction tubes were maintained at 1150 °C and 850 °C, respectively, in order to convert the carbon in the oil samples into CO2 gas under a stream of helium and oxygen. The resultant CO2 was separated in a gas chromatography (GC) column packed with 5 Å molecular sieves, and its isotopic composition was measured on the IRMS. Reference CO2 gas was inserted into the helium carrier
flow as pulses of pure standard gas. The analysis of the hydrogen and oxygen stable isotope ratios of the oil samples was performed using an HT-PyrOH (EuroVector, Milan, Italy) pyrolyzer connected to the IsoPrime 100 IRMS. An aliquot of the oil samples that was wrapped in a 5 3.5 mm silver capsule (Elemental Microanalysis) was pyrolyzed at 1350 °C under a helium flow and passed through a column packed with glassy carbon chips in order to convert the hydrogen and oxygen in the oil samples into H2 and CO gases, respectively. The H2 and CO were subsequently separated in a GC column packed with 5 Å molecular sieves, and their isotopic compositions were analyzed on the IRMS. Reference H2 and CO gases were inserted into the helium carrier flow as pulses of pure standard gas. The stable isotope ratio was expressed as the delta (d) value in per mille (‰) deviation from the respective international standard, i.e., VPDB (Vienna Pee Dee Belemnite) for carbon and VSMOW (Vienna Standard Mean Ocean Water) for hydrogen and oxygen, according to the following equation:
dð%0 Þ ¼ ½ðRs Rstd Þ=Rstd 1000;
ð1Þ
where R represents the ratio of the heavy to light isotopes, and Rs and Rstd are the isotope ratios of the sesame oil and the international standard, respectively. The isotope analyses were calibrated with the IRMS certified reference material EMA-P2 (Elemental Microanalysis), which had a d13C value of 28.19‰ on the PDB scale and a dD value of 26.88‰ and a d18O value of 87.80‰ on the VSMOW scale. 2.4. Statistical analysis The isotopic values of the sesame oil samples represented the mean of triplicate measurements. All of the statistical analyses were conducted using PASW Statistics 18 software (SPSS Inc., Chicago, IL). Pearson’s correlation test was used to determine whether there was a significant linear relationship between two variables (p < 0.01 or 0.05). A one-way analysis of variance (ANOVA) was performed to determine the differences in the oil samples. When the ANOVA F value was significant, the differences between the means were determined using Duncan’s multiple-range test (p < 0.05). Canonical discriminant analysis was performed with stepwise selection of the variables that best distinguished the Korean, Chinese, and Indian sesame oils. 3. Results and discussion 3.1. Stable isotope ratio of Korean sesame oils South Korea, officially the Republic of Korea, is located in the southern part of the Korean Peninsula, which extends approximately 1100 km southward from the Asian continent into the Pacific Ocean. It lies in the middle latitude zone (between 33.10°N and 38.45°N), is surrounded by seas, and has low mountainous terrain. Geographic and climatic information for the 36 harvesting sites for the Korean sesame seed samples used in this study are given in Table 1. The carbon, hydrogen, and oxygen stable isotope ratios of the oil samples obtained from the sesame seeds are also listed in the same table. Pearson’s correlation test was performed to determine whether there was a significant linear relationship between isotopic values or between the isotopic values and the environmental factors in Korean sesame oil (Table 2). The d13C value of Korean sesame oil showed a significant (p < 0.01) positive correlation with its dD or d18O value. This result was in accordance with the observation of Camin, Larcher, Nicolini, et al. (2010) that the hydrogen and oxygen stable isotope ratios were positively coupled with the carbon stable isotope ratio in European olive oil. The dD and d18O values
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Fig. 1. Map of Korea showing the locations of the sites that produced the sesame seeds used in the present study. The areas that were >50 km away from the sea are shaded in grey on the map.
were also significantly (p < 0.01) and positively correlated with each other as expected. In principle, the water that originates from precipitation displays a positive and linear relationship between the hydrogen and oxygen stable isotope ratios worldwide (Craig, 1961; Dansgaard, 1964). The d13C value was negatively correlated with latitude, distance from the sea, and the precipitation during the previous five months before harvest (i.e., from May to September), and was positively correlated with the mean temperature during May–September, at a 99% level of significance. The dD and d18O values showed significant (p < 0.01 or 0.05) negative correlation with latitude, distance from the sea, and precipitation. These
phenomena occur due to the depletion of the heavier isotopes of hydrogen and oxygen (i.e., deuterium and oxygen-18) in precipitation with an increase in latitude, distance from the ocean, and amount of precipitation, which are referred to as the ‘‘latitude effect’’, ‘‘continental effect’’, and ‘‘amount effect’’, respectively (Gat et al., 2000). No significant linear correlation was found between the kinds of isotopic values and the altitude or mean relative humidity during May–September. However, a significant (p < 0.01) negative relationship was observed between the dD value and the altitude (Pearson coefficient = 0.555) and between the d18O value and the altitude (Pearson coefficient = 0.491) in
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Table 1 Geographic and climatic characteristics of the sites that produced the Korean sesame seeds and the d13C, dD, and d18O values of the Korean roasted sesame oils. No. of samples
Latitude (°N)
Distance from the sea (km)
Altitude (m)
Precipitation (mm)
Mean relative humidity (%)
Mean temperature (°C)
d13C (‰ vs. VPDB)
dD (‰ vs. VSMOW)
d18O (‰ vs. VSMOW)
Yanggu Yeoncheon Inje Hongcheon Hoengseong Yangpyeong Jeongseon Yeongwol Jecheon Eumseong Dangjin Goesan Cheonan Jeungpyeong Yecheon Boeun Cheongyang Sangju Uiseong Nonsan Yeongdong Gimcheon Seocheon Iksan Buan Cheongdo Imsil Hamyang Miryang Gimhae Hampyeong Naju Muan Mokpo Gangjin Jeju Minimum Maximum
1 1 1 1 1 2 1 4 1 1 1 2 1 1 3 2 1 1 2 1 1 1 2 1 1 2 2 2 1 1 1 1 2 1 1 2
38.11 38.10 38.07 37.70 37.49 37.49 37.38 37.18 37.13 36.94 36.89 36.82 36.82 36.79 36.66 36.49 36.46 36.41 36.35 36.19 36.18 36.14 36.08 35.95 35.73 35.65 35.61 35.52 35.50 35.23 35.07 35.02 34.99 34.83 34.64 33.50 33.50 38.11
81 65 40 85 97 70 45 80 105 65 40 80 25 65 85 90 29 110 62 43 105 116 5 15 12 64 50 60 50 17 6 25 26 3 3 1 1 116
388 173 527 260 235 41 321 275 282 208 8 170 43 59 128 467 113 60 104 25 182 98 47 23 6 136 298 223 29 16 264 348 24 29 59 1025 6 1025
1489 1604 1489 1356 1160 1599 1439 1705 1483 1439 1429 893 1641 1089 1421 1503 1517 957 850 1749 1066 1066 1362 1749 887 882 1402 1143 882 1052 1081 1100 629 629 1051 892 629 1749
76 77 76 71 70 74 74 71 72 71 79 72 74 69 72 74 80 76 72 72 76 76 79 72 78 71 73 79 71 73 80 74 84 84 78 72 69 84
19.8 21.6 19.8 21.7 23.1 22.6 20.1 21.6 20.9 22.2 21.2 22.7 21.0 24.0 21.4 21.2 21.7 21.9 22.7 22.5 21.2 21.2 21.9 22.5 22.8 23.7 22.1 21.9 23.7 24.2 23.0 24.1 21.9 21.9 21.4 23.3 19.8 24.2
30.8 30.2 29.8 31.1 30.1 31.1 30.2 31.3 30.2 30.9 31.7 30.4 29.2 29.2 29.5 31.3 30.4 30.7 29.8 29.8 31.1 31.1 30.6 29.5 30.0 30.7 30.9 30.5 29.0 28.8 29.6 28.4 29.6 29.6 30.4 29.8 31.7 28.4
171.9 180.4 170.4 189.0 182.8 180.3 182.3 173.9 191.3 200.7 191.5 193.1 155.2 168.8 160.3 210.3 170.2 177.1 152.3 187.6 199.1 168.0 188.2 168.8 176.6 161.1 185.0 178.0 151.3 148.8 156.5 152.4 142.7 119.0 160.5 172.5 210.3 119.0
20.5 15.5 17.3 14.7 16.9 14.4 15.8 13.9 13.4 13.0 12.6 14.5 18.6 17.3 15.1 13.0 13.0 14.2 18.9 14.9 14.3 14.9 15.1 17.8 16.8 15.8 16.3 13.7 17.3 22.0 17.1 19.2 17.7 15.5 16.3 19.3 12.6 22.0
H. Jeon et al. / Food Chemistry 167 (2015) 363–369
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H. Jeon et al. / Food Chemistry 167 (2015) 363–369 Table 2 Pearson coefficient of the correlation between the isotopic values of the Korean sesame oil and the geographic and climatic factors. Variable
d13C
13
d C dD d18O Latitude Distance from the sea Altitude Precipitation Mean relative humidity Mean temperature * **
0.521 0.521** 0.628** 0.358** 0.412** 0.074 0.405** 0.062 0.393**
d18O
dD **
0.561** 0.368** 0.377** 0.230 0.373** 0.255 0.248
0.628** 0.561** 0.352** 0.491** 0.153 0.296* 0.040 0.335*
Significantly linearly correlated (p < 0.05). Significantly linearly correlated (p < 0.01).
the Korean sesame oil samples produced in regions that were >50 km from the sea. This result suggests that greater depletion of deuterium and oxygen-18 in precipitation at higher elevations, which is called the ‘‘altitude effect’’, occurs in Korea’s inland area only.
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hya Pradesh, which contribute approximately 74% of total production (NAFED, 2009). The d13C values of the sesame oil samples are compared in Fig. 2a. The d13C values ranged from 31.7 to 28.2‰ in the Korean sesame oils, from 29.9 to 28.8‰ in the Chinese sesame oils, and from 30.4 to 28.6‰ in the Indian sesame oils. The mean d13C value was significantly (p < 0.05) lower in the Korean sesame oils (30.3‰) than in the Chinese (29.2‰) and Indian sesame oils (29.6‰). Fig. 2b compares the dD values of the sesame oil samples. The dD value was in the range of 211.8 to 119.0‰ for the Korean sesame oils, 198.5 to 140.2‰ for the Chinese sesame oils, and 215.7 to 163.2‰ for the Indian sesame oils. The mean dD value of the Korean sesame oils (173.0‰) was not significantly different from that of the Chinese sesame oils (172.2‰), but the value was significantly (p < 0.05) greater than that of the Indian sesame oils (189.4‰). The d18O values of the sesame oil samples are compared in Fig. 2c. The d18O value was in the range of 12.2– 22.0‰ for the Korean sesame oils, 8.9–25.3‰ for the Chinese sesame oils, and 16.1–26.3‰ for the Indian sesame oils. The d18O value of the Korean sesame oils (15.8‰) was significantly (p < 0.05) lower than those of the Chinese (18.2‰) and Indian sesame oils (20.3‰).
3.2. Comparison of stable isotope ratios among Asian sesame oils 3.3. Discrimination of sesame oil origin The carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil were compared with those of Chinese and Indian sesame oils that were frequently disguised as being locally produced in Korea. Unlike Korean sesame seed samples, detailed information on the geographic origins of the Chinese and Indian sesame seed samples used in this study was not available. However, it was possible to presume where the imported seed samples were produced. In China, the top three sesame-producing provinces of Henan, Hubei, and Anhui provide approximately 70% of total production (CnAgri, 2012). The five major sesame-producing states of India are Gujarat, West Bengal, Karnataka, Rajasthan, and Mad-
The geographic origins of the sesame oils were determined using stable isotopic data in combination with canonical discriminant analysis, which is a form of multivariate statistical method. This statistical tool helps to find a linear combination of features that best characterizes more than two groups of objects and classifies a new object into one of the groups using the resulting combination, which is called canonical discriminant function. The canonical discriminant analysis was performed with separate-groups covariance, as the group variance–covariance matrices were not equal (Box’M = 73.785, p < 0.05). The three groups of
Fig. 2. Box-and-whisker plots of the d13C (a), dD (b), and d18O (c) values of the roasted sesame oils. Means with the same letter on the boxes are not significantly different (p > 0.05). The sample sizes were 51 for the Korean sesame oils, 19 for the Chinese sesame oils, and 14 for the Indian sesame oils.
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sesame oils, i.e., Korean, Chinese, and Indian sesame oils differed significantly with respect to the means of three variables, i.e., d13C (Wilks’ Lambda = 0.704, F-value = 17.062, p < 0.0001), dD (Wilks’ Lambda = 0.885, F-value = 5.241, p < 0.01), and d18O values (Wilks’ Lambda = 0.737, F-value = 14.484, p < 0.0001); therefore, all of these variables were selected for the canonical discriminant analysis. Two different canonical discriminant functions were generated, because there were three groups and three discriminant variables. The first function explained 85.1% of the variability, and the second function accounted for the remaining variability (Fig. 3). The coefficients of the standardized canonical discriminant function reflect the contribution of one discriminant variable in the context of the other variables in the function. In the first function, the dD value (standardized coefficient, 1.070) was the most important discriminant variable, followed by the d18O (0.820) and d13C (0.632) values. The second function was primarily determined by the d13C (1.013) and d18O (0.727) values, but not the dD value (0.330). When a total of 84 oil samples were reclassified using the canonical discriminant functions, 89.3% of the samples were classified to the correct production site (Table 3). In particular, four of the 51 Korean sesame oil samples were classified incorrectly as being Chinese sesame oil. Fig. 3 also shows that the centroid of the Korean sesame oil is closer to that of the Chinese sesame oil than the Indian sesame oil. These results suggest that it is more difficult to discriminate Korean sesame oil from Chinese sesame oil than from Indian sesame oil. This may be attributed to the fact that half of the 36 Korean sites (18), which produced the sesame seeds used in this study, lie at similar latitudes to China’s major sesame producing regions (i.e., Henan, Hubei, and Anhui), which are located between 29.17°N and 36.33°N. In contrast, India’s major sesame-producing regions (i.e., Gujarat, West Bengal, Karnataka, Rajasthan, and Madhya Pradesh) lie at relatively low latitudes (11.5730.17°N) compared to those in Korea and China. In order to examine the predictive discrimination power of the established model, the origin of an additional sample of commercial Korean sesame oil was characterized using canonical discriminant functions. The oil sample, which had a d13C value of 29.8‰, a
Table 3 Reclassification of the origin of the roasted sesame oils using the canonical discriminant function.
Korean sesame oil Chinese sesame oil Indian sesame oil Total
Korea
China
47 2
4 15 1
India
Total
Correctly classified (%)
2 13
51 19 14 84
92.2 78.9 92.9 89.3
dD value of 181.9‰, and a d18O value of 16.8‰, was accurately predicted to be Korean sesame oil. 4. Conclusions To the best of our knowledge, there are no published data regarding the hydrogen and oxygen isotopic signatures of sesame oil. This is the first study to report the stable isotopic compositions of the sesame oils that originated from Asian regions. The carbon, hydrogen, and oxygen stable isotope ratios of the Korean sesame oil were negatively correlated with latitude, distance from the sea, and precipitation during the previous five months before harvest, respectively. The negative correlations between the isotope ratios and altitude were found in the sesame oil from Korea’s interior, which was greater than 50 km from the sea. Differences in the stable isotopic compositions were observed among the Korean, Chinese, and Indian sesame oils. It was demonstrated that combined analysis of the carbon, hydrogen, and oxygen stable isotope ratios was a useful tool for differentiating Korean sesame oil from the Chinese and Indian sesame oils that were distributed in Korea. Acknowledgement This research was supported by a Grant (11162KFDA079) from Korea Food and Drug Administration in 2011. References
Fig. 3. Score plot of two canonical variables (functions 1 and 2) for the Korean, Chinese, and Indian roasted sesame oils.
Bontempo, L., Camin, F., Larcher, R., Nicolini, G., Perini, M., & Rossmann, A. (2008). Discrimination of Tyrrhenian and Adriatic Italian olive oils using H, O, and C stable isotope ratios. Rapid Communications in Mass Spectrometry, 23, 1043–1048. Camin, F., Larcher, R., Nicolini, G., Bontempo, L., Bertoldi, D., Perini, M., et al. (2010). Isotopic and elemental data for tracing the origin of European olive oils. Journal of Agricultural and Food Chemistry, 58, 570–577. Camin, F., Larcher, R., Perini, M., Bontempo, L., Bertoldi, D., Gagliano, G., et al. (2010). Characterisation of authentic Italian extra-virgin olive oils by stable isotope ratios of C, O and H and mineral composition. Food Chemistry, 118, 901–909. CnAgri (China Agriculture Consultant). Report on China’s Sesame Market, 2012. URL http://en.cnagri.com/report/seedoilsss/20120331/252851.html. Accessed 01.05.12. Craig, H. (1961). Isotopic variation in meteoric waters. Science, 133, 1702–1703. Dansgaard, W. (1964). Stable isotopes in precipitation. Tellus, 16, 436–468. Farquhar, G. D., Ehleringer, J. R., & Hubick, K. T. (1989). Carbon isotope discrimination and photosynthesis. Annual Review of Plant Physiology and Plant Molecular Biology, 40, 503–537. Farquhar, G. D., O’Leary, M. H., & Berry, J. A. (1982). On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Australian Journal of Plant Physiology, 9, 121–137. FAO (Food and Agriculture Organization of the United Nations). FAOSTAT, 2012. URL http://faostat3.fao.org/home/index.html#HOME. Accessed 01.05.12. Gat, J. R., Mook, W. G., & Meijer, H. A. J. (2000). Observed isotope effects in precipitation. In W. G. Mook (Ed.), Environmental isotopes in the hydrological cycle: Principles and applications. Atmospheric water (Vol. II, pp. 197–207). Paris: UNESCO. Jeon, H., Kim, I. H., Lee, C., Choi, H. D., Kim, B. H., & Akoh, C. C. (2013). Discrimination of origin of sesame oils using fatty acid and lignan profiles in combination with canonical discriminant analysis. Journal of the American Oil Chemists Society, 90, 337–347. KFDA (Korea Food and Drug Administration). Imported Foods Information Site, 2012. URL http://www.foodnara.go.kr/importfood. Accessed 01.05.12. Kim, B. H., & Akoh, C. C. (2006). Characteristics of structured lipid prepared by lipase-catalyzed acidolysis of roasted sesame oil and caprylic acid in a bench-
H. Jeon et al. / Food Chemistry 167 (2015) 363–369 scale continuous packed bed reactor. Journal of Agricultural and Food Chemistry, 54, 5132–5141. NAFED (National Agricultural Cooperative Marketing Federation of India Ltd.). Market profiles. Volume II. Product profiles. Chapter 15. Sesame, 2009. URL http://agriexchange.apeda.gov.in/Market%20Profile/MOA/Product/Sesame.pdf. Accessed 01.05.12. Namiki, M. (1995). The chemistry and physiological functions of sesame. Food Reviews International, 11, 281–329.
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Analytical Methods
A triple-isotope approach for discriminating the geographic origin of Asian sesame oils Hyeonjin Jeon a, Sang-Cheol Lee b, Yoon-Jae Cho c, Jae-Ho Oh c, Kisung Kwon c, Byung Hee Kim a,⇑ a
Department of Food Science and Technology, Chung-Ang University, Anseong 456-756, Republic of Korea Bee Product Research Center, Korea Apicultural Association, Seoul 137-070, Republic of Korea c National Institute of Food and Drug Safety Evaluation, Korea Food and Drug Administration, Cheongwon 363-700, Republic of Korea b
a r t i c l e
i n f o
Article history: Received 17 March 2013 Received in revised form 6 January 2014 Accepted 5 July 2014 Available online 12 July 2014 Keywords: Sesame oil Geographic origin Carbon stable isotope Hydrogen stable isotope Oxygen stable isotope Canonical discriminant analysis
a b s t r a c t The aim of this study was to investigate the effects of the geographic location and climatic characteristics of the sesame-producing sites on the carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil. In addition, the study aimed to differentiate Korean sesame oil from Chinese and Indian sesame oils using isotopic data in combination with canonical discriminant analysis. The isotopic data were obtained from 84 roasted oil samples that were prepared from 51 Korean, 19 Chinese, and 14 Indian sesame seeds harvested during 2010–2011 and distributed in Korea during the same period. The d13C, dD, and d18O values of Korean sesame oil were negatively correlated with latitude, distance from the sea, and precipitation (May–September), respectively. By applying two canonical discriminant functions, 89.3% of the sesame oil samples were correctly classified by their geographic origin, indicating that the triple-isotope approach is a useful tool for the traceability of the oils. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Sesame (Sesamum indicum L.) is an oilseed crop that is primarily cultivated in Asian and African countries. Roasted sesame oil is unrefined edible oil obtained from sesame seeds roasted at 180– 200 °C (Namiki, 1995). This oil is frequently used as a flavor enhancer in Eastern Asian cooking since Eastern Asians, including Koreans, prefer the characteristic flavor of the oil that develops during roasting (Kim & Akoh, 2006). Sesame seeds are available in three different colors, black, brown, and white. White sesame seeds are mostly used in the manufacturing of roasted sesame oil in Korea (Jeon et al., 2013). False indications of the geographic origin of sesame products became an issue of public concern in Korea after the 1990s. In the 2000s, Koreans consumed approximately 100,000 tonnes of sesame seeds per year. Because the annual domestic production (approximately 13,000 tonnes) of sesame seeds could not sustain the national need, Korea imported approximately 140,000 tonnes of sesame seeds during 2009 and 2010 (FAO, 2012). Indian and Chinese sesame seeds occupy approximately 43% and 38% of Korea’s sesame imports, respectively (KFDA, 2012). Chinese and Indian sesame seeds/oils that are deliberately labeled as domestic often
⇑ Corresponding author. Tel.: +82 316703033; fax: +82 316754853. E-mail address: [email protected] (B.H. Kim). http://dx.doi.org/10.1016/j.foodchem.2014.07.032 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
appear in Korean local markets, because Korean sesame seeds/oils are 3–4 times higher in price than Chinese or Indian sesame products. This has created the need for analytical methods to distinguish Korean sesame oil from the oil obtained from imported sesame seeds. The geographic location and climatic conditions of cultivation sites influence the stable isotopic signature of plants. The carbon stable isotope ratio (13C/12C) of plant materials is preferentially affected by the types of photosynthetic processes, i.e., the C3 and C4 pathways, which the plants employ for fixing atmospheric carbon dioxide (Smith & Epstein, 1971). Climatic factors, such as relative humidity, temperature, and the amount of precipitation, which affect the stomatal conductance of carbon dioxide, cause variations in the carbon stable isotope ratio of C3 plants including sesame (Farquhar, Ehleringer, & Hubick, 1989; Farquhar, O’Leary, & Berry, 1982). The hydrogen (D/1H) and oxygen (18O/16O) stable isotope ratios of plant material are strongly correlated with those ratios in the local precipitation water that is incorporated by the plant. The isotopic composition of precipitation is primarily affected by geographic and climatic conditions, such as latitude, distance from the sea, altitude, temperature, and the amount of precipitation (Gat, Mook, & Meijer, 2000). Some climatic factors (e.g., relative humidity and temperature) influence the stomatal transpiration of water, thereby inducing the fractionation of hydrogen and oxygen isotopes in plant materials (Perri, Benincasa, & Muzzalupo, 2012). Therefore, the combined analysis of carbon,
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hydrogen, and oxygen stable isotope ratios could be a useful tool for the traceability of oils derived from plant sources. Several researchers have utilized the triple-isotope approach for identifying the geographic origin of plant oils produced in European regions, such as olive oil and rapeseed oil (Bontempo et al., 2008; Camin, Larcher, Nicolini, et al., 2010; Camin, Larcher, Perini, et al., 2010; Richter, Spangenberg, Kreuzer, & Leiber, 2010). In contrast, little is known about the stable isotopic signature (particularly, D/1H and 18O/16O) of sesame oil. Furthermore, no published studies have characterized the geographic origin of the oil using the triple-isotope approach. The aim of this study was to investigate the effects of the geographic location and climatic characteristics of the sesame-producing sites on the carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil. In addition, the study was designed to differentiate Korean sesame oil from Chinese and Indian sesame oils that are distributed in Korea using isotopic data. 2. Materials and methods 2.1. Sample preparation Samples of white sesame seeds (n = 51) were collected from 36 sites in Korea during the 2010 and 2011 harvests (Fig. 1). Samples of Chinese white sesame seeds (n = 19) and Indian white sesame seeds (n = 14), which were imported by the Korea Agro-Fisheries Trade Corporation between 2010 and 2011, were purchased from local grocery stores in Korea. The sesame seeds were roasted in a drum roaster (model THDR-01; Taehwan Automation Industry Co., Seoul, Korea) at 200 °C for 30 min. The oil was extracted from the roasted sesame seeds using an oil press (model Oil Love; National ENG Co., Goyang, Korea) and was centrifuged at 9600g for 10 min. The roasted sesame oils were completely dried under nitrogen flushing. The water content of the oils was monitored using a Karl-Fisher moisture analyzer (model 803 Ti Stand; Metrohm, Herisau, Switzerland) and was adjusted to <300 mg/kg. A sample of commercial Korean roasted sesame oil was obtained from an edible oil manufacturing company. 2.2. Geographic and climatic data analysis Data of the geographic characteristics (latitude, distance from the sea, and altitude) of the production sites of Korean sesame seeds used in this study were collected from Google Earth (http://earth.google.com). Climatic data including precipitation, mean relative humidity, and mean temperature during the five months (May–September) corresponding to the growth period of the sesame were obtained from the Korea Meteorological Administration (http://www.kma.go.kr). 2.3. Stable isotope analysis The carbon stable isotope ratio of the sesame oil samples was analyzed using an IsoPrime 100 (GV instruments, Manchester, UK) isotope ratio mass spectrometer (IRMS) coupled with a vario MICRO cube (Elementar Analysensysteme GmbH, Hanau, Germany) elemental analyzer (EA). An aliquot of the oil samples was placed into a 5 3.5 mm tin capsule (Elemental Microanalysis, Okehampton, UK) and injected into the EA. The combustion and reduction tubes were maintained at 1150 °C and 850 °C, respectively, in order to convert the carbon in the oil samples into CO2 gas under a stream of helium and oxygen. The resultant CO2 was separated in a gas chromatography (GC) column packed with 5 Å molecular sieves, and its isotopic composition was measured on the IRMS. Reference CO2 gas was inserted into the helium carrier
flow as pulses of pure standard gas. The analysis of the hydrogen and oxygen stable isotope ratios of the oil samples was performed using an HT-PyrOH (EuroVector, Milan, Italy) pyrolyzer connected to the IsoPrime 100 IRMS. An aliquot of the oil samples that was wrapped in a 5 3.5 mm silver capsule (Elemental Microanalysis) was pyrolyzed at 1350 °C under a helium flow and passed through a column packed with glassy carbon chips in order to convert the hydrogen and oxygen in the oil samples into H2 and CO gases, respectively. The H2 and CO were subsequently separated in a GC column packed with 5 Å molecular sieves, and their isotopic compositions were analyzed on the IRMS. Reference H2 and CO gases were inserted into the helium carrier flow as pulses of pure standard gas. The stable isotope ratio was expressed as the delta (d) value in per mille (‰) deviation from the respective international standard, i.e., VPDB (Vienna Pee Dee Belemnite) for carbon and VSMOW (Vienna Standard Mean Ocean Water) for hydrogen and oxygen, according to the following equation:
dð%0 Þ ¼ ½ðRs Rstd Þ=Rstd 1000;
ð1Þ
where R represents the ratio of the heavy to light isotopes, and Rs and Rstd are the isotope ratios of the sesame oil and the international standard, respectively. The isotope analyses were calibrated with the IRMS certified reference material EMA-P2 (Elemental Microanalysis), which had a d13C value of 28.19‰ on the PDB scale and a dD value of 26.88‰ and a d18O value of 87.80‰ on the VSMOW scale. 2.4. Statistical analysis The isotopic values of the sesame oil samples represented the mean of triplicate measurements. All of the statistical analyses were conducted using PASW Statistics 18 software (SPSS Inc., Chicago, IL). Pearson’s correlation test was used to determine whether there was a significant linear relationship between two variables (p < 0.01 or 0.05). A one-way analysis of variance (ANOVA) was performed to determine the differences in the oil samples. When the ANOVA F value was significant, the differences between the means were determined using Duncan’s multiple-range test (p < 0.05). Canonical discriminant analysis was performed with stepwise selection of the variables that best distinguished the Korean, Chinese, and Indian sesame oils. 3. Results and discussion 3.1. Stable isotope ratio of Korean sesame oils South Korea, officially the Republic of Korea, is located in the southern part of the Korean Peninsula, which extends approximately 1100 km southward from the Asian continent into the Pacific Ocean. It lies in the middle latitude zone (between 33.10°N and 38.45°N), is surrounded by seas, and has low mountainous terrain. Geographic and climatic information for the 36 harvesting sites for the Korean sesame seed samples used in this study are given in Table 1. The carbon, hydrogen, and oxygen stable isotope ratios of the oil samples obtained from the sesame seeds are also listed in the same table. Pearson’s correlation test was performed to determine whether there was a significant linear relationship between isotopic values or between the isotopic values and the environmental factors in Korean sesame oil (Table 2). The d13C value of Korean sesame oil showed a significant (p < 0.01) positive correlation with its dD or d18O value. This result was in accordance with the observation of Camin, Larcher, Nicolini, et al. (2010) that the hydrogen and oxygen stable isotope ratios were positively coupled with the carbon stable isotope ratio in European olive oil. The dD and d18O values
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Fig. 1. Map of Korea showing the locations of the sites that produced the sesame seeds used in the present study. The areas that were >50 km away from the sea are shaded in grey on the map.
were also significantly (p < 0.01) and positively correlated with each other as expected. In principle, the water that originates from precipitation displays a positive and linear relationship between the hydrogen and oxygen stable isotope ratios worldwide (Craig, 1961; Dansgaard, 1964). The d13C value was negatively correlated with latitude, distance from the sea, and the precipitation during the previous five months before harvest (i.e., from May to September), and was positively correlated with the mean temperature during May–September, at a 99% level of significance. The dD and d18O values showed significant (p < 0.01 or 0.05) negative correlation with latitude, distance from the sea, and precipitation. These
phenomena occur due to the depletion of the heavier isotopes of hydrogen and oxygen (i.e., deuterium and oxygen-18) in precipitation with an increase in latitude, distance from the ocean, and amount of precipitation, which are referred to as the ‘‘latitude effect’’, ‘‘continental effect’’, and ‘‘amount effect’’, respectively (Gat et al., 2000). No significant linear correlation was found between the kinds of isotopic values and the altitude or mean relative humidity during May–September. However, a significant (p < 0.01) negative relationship was observed between the dD value and the altitude (Pearson coefficient = 0.555) and between the d18O value and the altitude (Pearson coefficient = 0.491) in
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Table 1 Geographic and climatic characteristics of the sites that produced the Korean sesame seeds and the d13C, dD, and d18O values of the Korean roasted sesame oils. No. of samples
Latitude (°N)
Distance from the sea (km)
Altitude (m)
Precipitation (mm)
Mean relative humidity (%)
Mean temperature (°C)
d13C (‰ vs. VPDB)
dD (‰ vs. VSMOW)
d18O (‰ vs. VSMOW)
Yanggu Yeoncheon Inje Hongcheon Hoengseong Yangpyeong Jeongseon Yeongwol Jecheon Eumseong Dangjin Goesan Cheonan Jeungpyeong Yecheon Boeun Cheongyang Sangju Uiseong Nonsan Yeongdong Gimcheon Seocheon Iksan Buan Cheongdo Imsil Hamyang Miryang Gimhae Hampyeong Naju Muan Mokpo Gangjin Jeju Minimum Maximum
1 1 1 1 1 2 1 4 1 1 1 2 1 1 3 2 1 1 2 1 1 1 2 1 1 2 2 2 1 1 1 1 2 1 1 2
38.11 38.10 38.07 37.70 37.49 37.49 37.38 37.18 37.13 36.94 36.89 36.82 36.82 36.79 36.66 36.49 36.46 36.41 36.35 36.19 36.18 36.14 36.08 35.95 35.73 35.65 35.61 35.52 35.50 35.23 35.07 35.02 34.99 34.83 34.64 33.50 33.50 38.11
81 65 40 85 97 70 45 80 105 65 40 80 25 65 85 90 29 110 62 43 105 116 5 15 12 64 50 60 50 17 6 25 26 3 3 1 1 116
388 173 527 260 235 41 321 275 282 208 8 170 43 59 128 467 113 60 104 25 182 98 47 23 6 136 298 223 29 16 264 348 24 29 59 1025 6 1025
1489 1604 1489 1356 1160 1599 1439 1705 1483 1439 1429 893 1641 1089 1421 1503 1517 957 850 1749 1066 1066 1362 1749 887 882 1402 1143 882 1052 1081 1100 629 629 1051 892 629 1749
76 77 76 71 70 74 74 71 72 71 79 72 74 69 72 74 80 76 72 72 76 76 79 72 78 71 73 79 71 73 80 74 84 84 78 72 69 84
19.8 21.6 19.8 21.7 23.1 22.6 20.1 21.6 20.9 22.2 21.2 22.7 21.0 24.0 21.4 21.2 21.7 21.9 22.7 22.5 21.2 21.2 21.9 22.5 22.8 23.7 22.1 21.9 23.7 24.2 23.0 24.1 21.9 21.9 21.4 23.3 19.8 24.2
30.8 30.2 29.8 31.1 30.1 31.1 30.2 31.3 30.2 30.9 31.7 30.4 29.2 29.2 29.5 31.3 30.4 30.7 29.8 29.8 31.1 31.1 30.6 29.5 30.0 30.7 30.9 30.5 29.0 28.8 29.6 28.4 29.6 29.6 30.4 29.8 31.7 28.4
171.9 180.4 170.4 189.0 182.8 180.3 182.3 173.9 191.3 200.7 191.5 193.1 155.2 168.8 160.3 210.3 170.2 177.1 152.3 187.6 199.1 168.0 188.2 168.8 176.6 161.1 185.0 178.0 151.3 148.8 156.5 152.4 142.7 119.0 160.5 172.5 210.3 119.0
20.5 15.5 17.3 14.7 16.9 14.4 15.8 13.9 13.4 13.0 12.6 14.5 18.6 17.3 15.1 13.0 13.0 14.2 18.9 14.9 14.3 14.9 15.1 17.8 16.8 15.8 16.3 13.7 17.3 22.0 17.1 19.2 17.7 15.5 16.3 19.3 12.6 22.0
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H. Jeon et al. / Food Chemistry 167 (2015) 363–369 Table 2 Pearson coefficient of the correlation between the isotopic values of the Korean sesame oil and the geographic and climatic factors. Variable
d13C
13
d C dD d18O Latitude Distance from the sea Altitude Precipitation Mean relative humidity Mean temperature * **
0.521 0.521** 0.628** 0.358** 0.412** 0.074 0.405** 0.062 0.393**
d18O
dD **
0.561** 0.368** 0.377** 0.230 0.373** 0.255 0.248
0.628** 0.561** 0.352** 0.491** 0.153 0.296* 0.040 0.335*
Significantly linearly correlated (p < 0.05). Significantly linearly correlated (p < 0.01).
the Korean sesame oil samples produced in regions that were >50 km from the sea. This result suggests that greater depletion of deuterium and oxygen-18 in precipitation at higher elevations, which is called the ‘‘altitude effect’’, occurs in Korea’s inland area only.
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hya Pradesh, which contribute approximately 74% of total production (NAFED, 2009). The d13C values of the sesame oil samples are compared in Fig. 2a. The d13C values ranged from 31.7 to 28.2‰ in the Korean sesame oils, from 29.9 to 28.8‰ in the Chinese sesame oils, and from 30.4 to 28.6‰ in the Indian sesame oils. The mean d13C value was significantly (p < 0.05) lower in the Korean sesame oils (30.3‰) than in the Chinese (29.2‰) and Indian sesame oils (29.6‰). Fig. 2b compares the dD values of the sesame oil samples. The dD value was in the range of 211.8 to 119.0‰ for the Korean sesame oils, 198.5 to 140.2‰ for the Chinese sesame oils, and 215.7 to 163.2‰ for the Indian sesame oils. The mean dD value of the Korean sesame oils (173.0‰) was not significantly different from that of the Chinese sesame oils (172.2‰), but the value was significantly (p < 0.05) greater than that of the Indian sesame oils (189.4‰). The d18O values of the sesame oil samples are compared in Fig. 2c. The d18O value was in the range of 12.2– 22.0‰ for the Korean sesame oils, 8.9–25.3‰ for the Chinese sesame oils, and 16.1–26.3‰ for the Indian sesame oils. The d18O value of the Korean sesame oils (15.8‰) was significantly (p < 0.05) lower than those of the Chinese (18.2‰) and Indian sesame oils (20.3‰).
3.2. Comparison of stable isotope ratios among Asian sesame oils 3.3. Discrimination of sesame oil origin The carbon, hydrogen, and oxygen stable isotope ratios of Korean sesame oil were compared with those of Chinese and Indian sesame oils that were frequently disguised as being locally produced in Korea. Unlike Korean sesame seed samples, detailed information on the geographic origins of the Chinese and Indian sesame seed samples used in this study was not available. However, it was possible to presume where the imported seed samples were produced. In China, the top three sesame-producing provinces of Henan, Hubei, and Anhui provide approximately 70% of total production (CnAgri, 2012). The five major sesame-producing states of India are Gujarat, West Bengal, Karnataka, Rajasthan, and Mad-
The geographic origins of the sesame oils were determined using stable isotopic data in combination with canonical discriminant analysis, which is a form of multivariate statistical method. This statistical tool helps to find a linear combination of features that best characterizes more than two groups of objects and classifies a new object into one of the groups using the resulting combination, which is called canonical discriminant function. The canonical discriminant analysis was performed with separate-groups covariance, as the group variance–covariance matrices were not equal (Box’M = 73.785, p < 0.05). The three groups of
Fig. 2. Box-and-whisker plots of the d13C (a), dD (b), and d18O (c) values of the roasted sesame oils. Means with the same letter on the boxes are not significantly different (p > 0.05). The sample sizes were 51 for the Korean sesame oils, 19 for the Chinese sesame oils, and 14 for the Indian sesame oils.
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sesame oils, i.e., Korean, Chinese, and Indian sesame oils differed significantly with respect to the means of three variables, i.e., d13C (Wilks’ Lambda = 0.704, F-value = 17.062, p < 0.0001), dD (Wilks’ Lambda = 0.885, F-value = 5.241, p < 0.01), and d18O values (Wilks’ Lambda = 0.737, F-value = 14.484, p < 0.0001); therefore, all of these variables were selected for the canonical discriminant analysis. Two different canonical discriminant functions were generated, because there were three groups and three discriminant variables. The first function explained 85.1% of the variability, and the second function accounted for the remaining variability (Fig. 3). The coefficients of the standardized canonical discriminant function reflect the contribution of one discriminant variable in the context of the other variables in the function. In the first function, the dD value (standardized coefficient, 1.070) was the most important discriminant variable, followed by the d18O (0.820) and d13C (0.632) values. The second function was primarily determined by the d13C (1.013) and d18O (0.727) values, but not the dD value (0.330). When a total of 84 oil samples were reclassified using the canonical discriminant functions, 89.3% of the samples were classified to the correct production site (Table 3). In particular, four of the 51 Korean sesame oil samples were classified incorrectly as being Chinese sesame oil. Fig. 3 also shows that the centroid of the Korean sesame oil is closer to that of the Chinese sesame oil than the Indian sesame oil. These results suggest that it is more difficult to discriminate Korean sesame oil from Chinese sesame oil than from Indian sesame oil. This may be attributed to the fact that half of the 36 Korean sites (18), which produced the sesame seeds used in this study, lie at similar latitudes to China’s major sesame producing regions (i.e., Henan, Hubei, and Anhui), which are located between 29.17°N and 36.33°N. In contrast, India’s major sesame-producing regions (i.e., Gujarat, West Bengal, Karnataka, Rajasthan, and Madhya Pradesh) lie at relatively low latitudes (11.5730.17°N) compared to those in Korea and China. In order to examine the predictive discrimination power of the established model, the origin of an additional sample of commercial Korean sesame oil was characterized using canonical discriminant functions. The oil sample, which had a d13C value of 29.8‰, a
Table 3 Reclassification of the origin of the roasted sesame oils using the canonical discriminant function.
Korean sesame oil Chinese sesame oil Indian sesame oil Total
Korea
China
47 2
4 15 1
India
Total
Correctly classified (%)
2 13
51 19 14 84
92.2 78.9 92.9 89.3
dD value of 181.9‰, and a d18O value of 16.8‰, was accurately predicted to be Korean sesame oil. 4. Conclusions To the best of our knowledge, there are no published data regarding the hydrogen and oxygen isotopic signatures of sesame oil. This is the first study to report the stable isotopic compositions of the sesame oils that originated from Asian regions. The carbon, hydrogen, and oxygen stable isotope ratios of the Korean sesame oil were negatively correlated with latitude, distance from the sea, and precipitation during the previous five months before harvest, respectively. The negative correlations between the isotope ratios and altitude were found in the sesame oil from Korea’s interior, which was greater than 50 km from the sea. Differences in the stable isotopic compositions were observed among the Korean, Chinese, and Indian sesame oils. It was demonstrated that combined analysis of the carbon, hydrogen, and oxygen stable isotope ratios was a useful tool for differentiating Korean sesame oil from the Chinese and Indian sesame oils that were distributed in Korea. Acknowledgement This research was supported by a Grant (11162KFDA079) from Korea Food and Drug Administration in 2011. References
Fig. 3. Score plot of two canonical variables (functions 1 and 2) for the Korean, Chinese, and Indian roasted sesame oils.
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