Biochemical Stable Isotope Analysis in Food Authenticity

BIOCHEMICAL STABLE ISOTOPE ANALYSIS IN FOOD AUTHENTICITY

7

Takashi Korenaga⁎, Yaeko Suzuki†, Yoshito Chikaraishi‡,§ *

Department of Environmental Risk Management, Faculty of Risk and Crisis Management, Chiba Institute of Science, Choshi, Japan †Food Research Institute, National Agriculture and Food Research Organization, Tsukuba, Japan ‡ Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan § Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan

7.1 Introduction There are unfortunately a number of problems regarding mislabeling and adulteration in food industry. Such mislabeling and adulteration have always been considerable concerns for crediting the quality of beverages and foods, commonly for producers, distributors, and consumers, as well as nations. For the inspection against the mislabeling and adulteration, the establishment of food authenticity is a fundamental/essential issue, which leads to a highly increasing demand to have chemical methods allowing, especially, the characterization of geographical origin, botanical/cultivar origin, and/or the absence of adulterants in beverages and foods. One of potential powerful tools for the characterization of geographical origin of beverages and foods is stable isotope ratio analysis with an elemental analyzer (EA) or a gas chromatography (GC) coupled to isotope ratio mass spectrometer (IRMS) via continuous-flow modules, because a diversity in the isotopic fractionation caused by kinetic and thermodynamic effects results in isotopic identification/ discrimination among products for beverages and foods as well as food ingredients. The EA-IRMS and GC-IRMS allow stable isotope ratio analysis of five major biochemical elements, hydrogen (D/H), carbon (13C/12C), nitrogen (15N/14N), oxygen (18O/16O), and sulfur (34S/32S), of organic materials in, basically, any types (e.g., solid, liquid, and volatile) of beverages and foods: the former can analyze the isotope ratios for whole samples or for separated materials (or tissues) from the samples; and the latter can analyze the ratios for individual compounds Engineering Tools in the Beverage Industry. https://doi.org/10.1016/B978-0-12-815258-4.00007-X © 2019 Elsevier Inc. All rights reserved.

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210  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

in extracts from the samples, even in complex mixture of compounds in the extracts. As an additional/alternative approach with an cavity ring-down spectrometer (CRDS), a highly sensitive absorption spectroscopy stable isotope analysis, has been recently used for the food authenticity, because it confers further advantages in hydrogen and oxygen isotope analysis of water within gas- and gas-phase molecules (e.g., H2O and CO2) of samples (e.g., fruit juice) for a much more rapid and routine screening of the geographical origin of the source water in the samples. After commercial production of EA- and GC-IRMS in the 1990s and of CRDS in the 2000s, stable isotope ratio analysis has thus explosively been used for various studies among the food authenticity community, as a potential powerful tool for tracing sources and delivery of organic materials in geographical samples.

7.2  Analysis and δ Notation IRMS has specifically been used for the stable isotope ratio analysis. Unlike ‘normal type’ mass spectrometer (MS, often called organic MS) can continually scan a large range of mass (e.g., 40–600 amu) for characterizing the ion fragmentation of organic compounds to obtain the structural information, IRMS can continuously determine the isotope abundance of a couple of mass (e.g., 44, 45, and 46) at the expense of the scanning a large mass range. For IRMS, the organic samples must be converted into simple gasses (e.g., H2 for hydrogen, N2 for nitrogen, CO2 for carbon, CO for oxygen, and SO2 for sulfur) with manual (i.e., off-line) or automated “micro-reactor with continuous-flow” modules (i.e., on-line) prior to injection to IRMS. In case of determination of, for example, CO2, the 13C/12C ratio is obtained by the comparison of the abundance (i.e., peak area) of three major isotopomers, 12C16O2 (m/z 44), 13C16O2 (m/z 45), and 12C18O16O (m/z 46), to calculate 13C/12C ratios. CRDS is a unique highly sensitive infrared-absorption spectroscopy of gas- and gas-phase molecules (e.g., H2O and CO2) to quantify the concentration of isotope ratios, by measuring the decay rate (rather than absolute absorbance) of isotopomers (e.g., H218O, HD16O, and H218O) to calculate the isotope ratios. Analytical uncertainties in the absolute abundance of stable isotope ratios still largely exceed those in the relative abundance. Moreover, difference in the stable isotope ratio is generally very small between samples of interests, for example, difference in the 13C/12C is approximately 0.00020–0.00025 between atmospheric CO2 and terrestrial C3 plants (e.g., rice grain). Therefore, the ratio of stable isotopes has traditionally, conventionally been reported in the ubiquitous δ notation:

δ X Sample (‰) = ( RSample / RStandard ) −1 × 1000

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   211

Table 7.1  Isotope Compositions of International Standards International Standards

Element

Isotope

Abundance (%)

Vienna standard mean ocean water (VSMOW)

Hydrogen

H D (H2) 16 O 17 O 18 O 12 C 13 C 16 O 17 O 18 O 14 N 15 N 32 S 33 S 34 S 36 S

99.984426 0.015574 99.76206 0.03790 0.20004 98.8944 1.1056 99.7553 0.0385 0.2062 99.63370 0.36630 95.03957 0.74865 4.19719 0.01459

Oxygen

Vienna peedee belemnite (VPDB)

Carbon Oxygen

Air (AIR)

Nitrogen

Canyon diablo troilite (CDT) and vienna canyon diablo troilite (VCDT)

Sulfur

where RSample and /RStandard are the relative abundance of heavy isotopes to that of light isotopes (e.g., D/H for hydrogen, 13C/12C for carbon, 15N/14N for nitrogen, 18O/16O for oxygen, and 34S/32S for sulfur) in a sample and the international standard (Table 7.1), respectively. X is replaced by the heavy isotope (e.g., 2H or D, 13C, 15 N, 18O, and 34S, respectively) to indicate the element of interest. The δ value (e.g., δD, δ13C, δ15N, δ18O, and δ34S, respectively) thus indicates the relative difference in the isotope ratio between sample and standard, and is expressed in permil unit (‰). A positive δ value represents an enrichment in the heavy isotope relative to the standard, while a negative δ value represents a depletion in the heavy isotope. For both IRMS and CRDS, the δ values of samples have been generally determined by the following two processes: measurement of difference in the isotope ratio between samples and internationally accepted reference materials, and expression to the δ values relative to the international standard on scales normalized to the accepted δ values of the multiple reference materials (the use of single reference may be unacceptable for these determination).

Ratio

Ratio Value

D/H

0.00015576

17 18

0.0003799 0.0020052

13

0.011180

17 18

0.0003859 0.0020672

15

0.0036765

33

0.0078772 0.0441626 0.0001533

O/16O O/16O C/12C O/16O O/16O N/14N

S/32S S/32S 36 32 S/ S 34

212  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

7.3  Application I (IRMS): Discrimination of Geographical Origin of Rice, Koshihikari 7.3.1 Introduction Koshihikari is a brand of rice cultivated in Japan, where the rice from Niigata Prefecture is particularly well known as the finest quality and the most expensive price among various rice cultivars in Japan. Because of this expensive, Koshihikari always has a risk latent in food authenticity, most likely to be a target for the adulteration that undergoes dilution with low-price rice in a commercial process before they appear in the markets. Indeed, a Japanese weekly journal (Weekly Diamond, February 13, 2017, in Japanese) reported a result of the discrimination test of geographical origin of rice (which is sold from rice wholesalers belonging to the JA group, a public agricultural organization of farmers), and aroused suspicion that Chinese rice is mixed in the rice sold as “Shiga production” or “Uonuma production.” In Japan, Koshihikari is abundantly cultivated in several regions in Niigata Prefecture, but the same rice cultivar is commonly cultivated in widely spread areas within Japan. Moreover, Koshihikari is nowadays geographically divided into the world: for example, United States, Europe, Australia, India, and China. However, among them, the most expensive Koshihikari is produced at Minami-Uonuma in Niigata Prefecture, in which the price of Minami-Uonuma’s Koshihikari (ca. 10,000–20,0000 yen per 10 kg) is much higher than the other areas’ ones (ca. 3000–4000 yen) in Japan. Several chemical methods allowing the characterization of geographical origin, botanical/cultivar origin, and/or the absence of adulterants in Koshihikari have been studied as a potential tool for the inspection against convincing disguises in the food authenticity: by using stable isotopic compositions of strontium and boron (e.g., Kawasaki et al., 2002; Oda et al., 2001), molecular balance of fatty acids (e.g., Kitta et al., 2005), proportion of trace elements (e.g., Yasui and Shindoh, 2000), and stable isotopic compositions of five major biochemical elements (i.e., hydrogen, carbon, nitrogen, oxygen, and sulfur) (e.g., Kelly et al., 2002, 2005; Suzuki et al., 2008a,b, 2009; Korenaga et al., 2010). Among these methods, the stable isotope analysis of five major biochemical elements has probably been the most widely applied for the inspection against convincing disguises in the food authenticity, for example, honey, juice, and wine (e.g., Rossmann et al., 1999; Padovan et al., 2003; Nakashita et al., 2008), meats (e.g., Schmidt et al., 2005; Nakashita et al., 2008), eel (e.g., Suzuki et al., 2009), dairy products (e.g., Rossmann et  al., 2000; Ritz et  al., 2005), wine (e.g., Baxter et al., 1997), cereal crops (e.g., Kelly et al., 2005), and long-grain rice (e.g., Kelly et al., 2002).

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   213

In the present study, multi-elemental stable isotopic (δ13C, δ15N, and δ18O) and elemental (C and N) compositions for Koshihikari were determined to evaluate whether or not these isotope and element analysis can work as an indicator to characterize/discriminate the geographical origin of the rice, by using the general, traditional knowledge that the isotopic and element of plants and plant products can vary dependent of environmental difference in, for example, the temperature, nutrients, and water supply (e.g., Craig, 1961; Smith and Epstein, 1971; Kohl et al., 1973; Meints et al., 1975; Shearer and Legg, 1975; Gray and Thompson, 1976) among regions where the plants were grown.

7.3.2 Samples For the present study, 210 samples of the rice cultivar, short grain Koshihikari, were collected from Niigata Prefecture and some other regions in Japan, during 4 years between 2005 and 2008. The samples included polished (n = 99) or unpolished brown rice (n = 111). In addition to the Koshihikari harvested in Japan, rice samples from the same rice cultivar were collected from the world (i.e., our side of Japan) including the United States, Europe, Australia, India, and China.

7.3.3 Elemental and Stable Isotope Ratio Analyses An aliquot amount of dried Koshihikari (approximately 3–5 g) was ground to a fine powder and was sufficiently homogenized before the analyses. About 1.2 mg of the powdered rice was weighted and enclosed into a tin capsule (5 × 9 mm). The enclosed tin capsule was injected to an EA-isotope ratio mass spectrometer (EA-IRMS) with a combustion-reduction mode, to determine the atomic abundance and stable isotope ratios for carbon and nitrogen in the sample. Moreover, about 0.3 mg of the powdered rice was also weighed and enclosed into a silver capsule (5 × 9 mm). The enclosed silver capsule was injected to an EA-IRMS with a pyrolysis mode to determine the stable isotope ratios for oxygen in the sample (note: EA-IRMS is generally unable to determine the isotope ratio of oxygen if the sample has nitrogen, because oxygen and nitrogen are converted to the same mass number gasses, CO (carbon monoxide, m/z 28) and N2 (dinitrogen, m/z 28), respectively). However, the contribution of N2 is generally negligible in the case of rice gran that is composed mainly of starch and cellulose. Analytical uncertainty of the elemental and isotopic compositions was generally better than 0.1%–0.3% and 0.2%–0.3‰, respectively.

7.3.4  Statistical Test The Student’s t test was employed to estimate whether the population mean value of isotopic compositions was significantly different

214  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

between years and between regions, to extract the major components (C and N contents, and C, N, and O isotopic compositions) that significantly affects the geographical discrimination of Koshihikari used in the present study.

7.3.5 Element and Isotopic Compositions of Koshihikari The carbon, nitrogen, and oxygen isotopic compositions of the Koshihikari are plotted in Fig. 7.1, with Koshihikari from a region in Fukushima (4) Nagano (10) Tochigi (28) Niigata (44) Chiba (7) Mie (3) Ibaragi (3) United States AUS Thai China

9.0

7.0

Australia

d 15 N (‰)

China 5.0

Japan China-Organic 3.0 South-East Asia 1.0

United States-F

–1.0 –29.0

–28.0

–27.0

–26.0

d

(A)

13

–25.0

–24.0

C (‰)

40.0 AUS

d 18 O (‰)

35.0

Europe

30.0 South-East Asia

United States

25.0 China-Organic India

China

20.0

Fig. 7.1  Relationships (A) between δ13C and δ15N values and (B) the δ13C and δ18O values of Koshihikari cultivated in Japan and other countries.

15.0 –29.0

(B)

Japan

–28.0

–27.0

–26.0

d 13 C (‰)

–25.0

–24.0

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   215

Japan was given by a dot with xy error bars for an average with a 1σ standard deviation for N > 10 samples. In a general trend, the δ13C values are varied by 4.3‰ from −29.5‰ to −25.2‰, the δ15N values are widely varied by +8.4‰ from −1.6‰ to +6.8‰, and the δ18O values are varied by 6.3‰–19.1‰ for the Koshihikari presented in Fig. 7.1. The mean and 1σ standard deviation of the Koshihikari in Japan, which were collected from the Niigata between 2005 and 2008 and from other six regions (i.e., Fukushima, Nagano, Tochigi, Chiba, Mie, and Ibaragi) in 2006, are −27.3‰ ± 0.6‰ for carbon (δ13C values, relative to Vienna peedee belemnite (VPDB)), +2.7 ± 1.3‰ for nitrogen (δ15N values, relative to air), and +21.7 ± 1.2‰ for oxygen (δ18O values, relative to Vienna standard mean ocean water (VSMOW)). Within Japan, the δ15N values of Koshihikari cultivated in Nigata Prefecture is slightly lower than those in other regions, while the δ13C and δ18O values in Nigata Prefecture are nearly equal to those in other regions. No substantial differences in the δ13C, δ15N, and δ18O values are found between polished and unpolished rice. Moreover, the mean and 1σ standard deviation in carbon and nitrogen contents are 38.5 ± 2.1% and 1.0 ± 0.2%, respectively. The nitrogen content of the Niigata Koshihikari basically falls within a remarkably narrow range (i.e., from 0.7% to 1.9%), with a few outliers, while the carbon content is scattered from 32.8% to 42.7% (as 38.53% for average). Based on the statistical analysis at 5% significant level, the Uonuma Koshihikari have a significantly unique δ15N and δ18O values among other regions within Niigata Prefecture in both 2006 and 2008. Thus at least 2006 and 2008, Uonuma Koshihikari, the most expensive Koshihikari, can be distinguished from any other regions’ Koshihikari even within Niigata Prefecture by using the δ15N and δ18O values. These elemental contents and isotopic compositions in Koshihikari within a single region are generally invariant between samples collected from different years, for the studied regions and countries, expect for Niigata samples. A slight, but significant difference in the mean value is found in Nigata Koshihikari, as the mean in 2006 is slightly different from that in 2008.

7.3.6 Possible Mechanisms Responsible for the Small Isotopic Heterogeneity in Niigata Koshihikari Atmospheric CO2 is the solo source of carbon for rice, where CO2 is fixed by photosynthesis to produce organic materials in rice and some of the fixed carbon is released by respiration. In general, the isotopic composition of plants and plant products (δ13CP value) is explained by

δ 13 CP = δ 13CCO2 − ε t − ( ca − 1.6 WUE ) / ca  × ( ε f − ε t )

216  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

where δ13CCO2 denotes the isotopic composition of CO2, the parameters εt and εf denote the isotopic fractionation associated with CO2 transport into or out of the fixation site by diffusion and with enzymatic carbon fixation by the photosynthesis, respectively, ca denotes the concentration of atmospheric CO2, and WUE denotes water-use efficiency that is a function of the ratio of daily net photosynthesis (A) to daily conductance of water vapor (gH2O) or CO2 (gCO2) (e.g., reviewed in Chikaraishi, 2014). Indeed, the δ13C values of rice are apparently controlled negatively by ambient humidity but positively by ambient temperature where the rice grew (e.g., Suzuki et  al., 2008a,b, 2009; Korenaga et  al., 2010). If this general knowledge is applicable to the rice in Niigata, the atmospheric humidity may be increased and the temperature would be gradually decreased from 2006 to 2008. Fertilizers (i.e., inorganic nitrogen chemicals such as ammonia and nitrate) are the major sources of the nitrogen for rice. It is thought that the δ15N values of artificial fertilizer are similar, or almost the same to the value of the atmospheric nitrogen (δ15N = ~0‰), whereas those of organic fertilizers including manure have high values (e.g., +5‰) due to the metabolism of organisms (Suzuki et al., 2009; Korenaga et al., 2010). Thus, the δ15N values observed in the present study are potentially explained by the general trend that major fertilizers used in Niigata Prefecture are gradually changes from the artificial fertilizer until 2006 to manure in 2006 and latter. Water resources irrigating rice farm are major sources of the oxygen for rice, implying the general scenario that less or almost negligible variation in the δ18O value of water resources for the same farm between years results in no substantial difference in the δ18O value of rice within a single farm. The δ18O values observed in the present study are basically consistent with this scenario. Interestingly, the δ18O values are slightly, but relatively largely, varied by 2.2‰ within the 2  years for Niigata Koshihikari, comparing that the difference in the δ18O value of rice is only ~6‰ even between Hokkaido and Okinawa (Suzuki et al., 2009). Such slight heterogeneity in the δ18O value in the Niigata Koshihikari may be interpreted by isotopically multiple water resources (e.g., meteoric water is derived from Eurasia continent or coastal ocean) with relatively variable evapotranspiration rates in Niigata Prefecture.

7.3.7 Conclusions The δ13C, δ15N, and δ18O values, and C and N contents determined with an EA-IRMS, reveal geographical variation in these elemental and isotopic compositions for Koshihikari, cultivated in Japan and other countries (i.e., the United States, Europe, Australia, India, and China). The Koshihikari cultivated in 2006 and 2008 in Japan has a ­significant

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   217

difference in the δ15N and δ18O values from that cultivated in other countries. Moreover, interestingly, there is no substantial difference in the values between polished and unpolished rice, but there is some significant difference between rice that grew with artificial and organic fertilizers. Thus, the stable isotope ratio analysis can be useful as an indicator to find the geographical difference of Koshihikari found in commercial processes and markets.

7.4  Application II (CRDS): Tracing Geographical Origin of Food Materials Using CRDS Although stable isotope ratio analysis is a useful tool for tracing the geographical origin of beverages and foods, it is highly required expert skills and expensive costs for the operation of IRMS (including measurement of the isotope ratios and maintenance of the instrument). Despite rapidly increasing in demand of the stable isotope ratio analysis in food authenticity, analytical method (or methodology) for the hydrogen and oxygen isotope ratios in organic samples is still in the development stages (because number of atoms for hydrogen and oxygen in organic samples are much/less exchangeable with ambient water in fields and laboratory, and because nitrogen in samples is produced by N2 gas that is the same mass number (i.e., m/z 28) with CO gas used for the oxygen isotope analysis), which always led to considerable concerns in the study of food authenticity. Moreover, the stability, linearity, accuracy, and precision of the observed isotopic compositions are always, strongly dependent on various factors such as sample weight (i.e., injection amount), peak intensity, memory effect, leak and contamination levels, and He dilution ratio in the IRMS measurement. During the last decade of food authenticity, CRDS has been employed as an alternative, but more portable, cheap, and user-friendly tool than traditional IRMS systems (e.g., Jamin et  al., 2003; Magdas and Puscas, 2011; Suzuki, 2016). Indeed, Suzuki (2016) successfully used CRDS for the stable isotope analysis of hydrogen and oxygen of water in gingers, to study in the discrimination of geographical origin of gingers between Japan and China. She reported that there is no substantial difference in the δ18O value of gingers between Japan (−5.7 ± 0.2‰) and China (−5.9 ± 0.1‰), whereas the δD values of gingers from Japan (−31.0 ± 1.5‰) are significantly larger than those from China (−42.6 ± 0.5‰), and suggested that the deuterium excess (d) of water (i.e., 14.9 ± 3.5‰ for Japan and 4.7 ± 2.0‰ for China) can be useful in the discrimination of the gingers’ origin between Japan

218  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

and China. The δD and δ18O values of water in lemon are also determined by using CRDS, to identify the origin (i.e., between Japan and the United States) of lemon. As similar trend to gingers (Suzuki, 2016) there is no significant difference in the δ18O value of lemons between Japan (+2.2 ± 0.3‰) and the United States (+1.2 ± 0.6‰) (Fig.  7.2), whereas the δD values of lemons from Japan (−12.7 ± 1.4‰) are significantly larger than those from the United States (−30.7 ± 2.4‰) (Fig.  7.2). Thus, the hydrogen and oxygen isotope analysis by using CRDS can be useful in the discrimination of the geographical origin of lemon, at least between Japan and the United States. At this moment, however, CRDS has some disadvantages: as the most considerable one is memory effect (e.g., Penna et al., 2010). For CRDS, a liquid sample is introduced into the vaporization chamber and is vapored at 110°C to measure the stable isotope ratios. After the measurement, although the vapor is ejected to the outside of instrument, some percentage of the vapor remains in the vaporization chamber, which is called “memory effect.” Therefore, to minimize the memory effect, it is strongly recommended that 10 continuous injections are required for each sample, where the first five injections are used to flush the memory effect. Moreover, because juices are often produced by squeezing of fruits and vegetables and contain a number of involatile compounds, it is preferred that the vaporization chamber is washed and rinsed at interval between samples (in such a case, centrifuge and/or filtering prior to the injection to CRDS may be also useful to reduce this issue).

10

Methods

Filtration

d D vs VSMOW(‰)

Centrifugation

Japan

0

Squeeze a lemon

–10 –20 –30 –40 –50

Measurement by CRDS

–60

United States –4

–2

0

2

4

6

d18O vs VSMOW(‰)

Fig. 7.2  The δD and δ18O values of water in lemons collected from Japan and the United States.

8

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   219

Unlike IRMS, CRDS sees the specific wavelengths of isotopomers in H2O and CO2. It is expected that such multi-angle analysis of the isotope ratios of beverages and foods can be useful to enhance the applicability of the isotope ratios for the inspection against the mislabeling and adulteration, the establishment of food authenticity. Moreover, CRDS allows us to rapidly and routinely analyze the isotope ratios even for a larger number of samples without time-consuming pretreatments. For popularization of CRDS in food authenticity, we are highly eager for the advances in CRDS technique in measuring the isotope ratios of any type (e.g., solid, liquid, and volatile) of materials.

7.5  Further Approach I: Combination Analysis of Stable Isotopes and Trace Elements Each of analytical methods generally has its advantages and disadvantage (or limitation), and the discrimination of geographical origin of beverages and foods indeed cannot be sufficiently achieved if only one analytical method is employed. To minimize such disadvantage or limitation, the combination of several methods has been preferred in the study of geographical origin of food materials. Since 2000, the combination analysis of stable isotopic and trace element compositions has been reported as a conventional further approach for tracing geographical origin of food products, for example, cereals (e.g., Husted et  al., 2004; Asfaha et  al., 2011; Li et  al., 2016), honey (e.g., Baroni et  al., 2015; Bontempo et  al., 2017), edible oils (e.g., Camin et  al., 2010a,b; Banerjee et  al., 2015), tea (e.g., Chang et  al., 2016), daily foods (e.g., Pillonel et  al., 2003), and meats (e.g., Rees et al., 2016). For example, Camin et al. (2010a,b) reported stable isotopic and trace element compositions in olive oils from eight regions in Europe (i.e., Trentino, Carpentras, Toscana, Barcelona, Chalkidiki, Sicilia, Algarve, and Lakonia). The classification of the origin among these olive oils is sometimes achieved by 97.9%, but the score generally varies from 40% to 90%, if the stable isotopic compositions for carbon, oxygen, and hydrogen are solely used in the discrimination. However, the classification of the origin is almost always achieved by 86%–100%, if the combination analysis for the stable isotopic and 14 element compositions (Mg, K, Ca, V, Mn, Zn, Rb, Sr, Cs, La, Ce, Sm, Eu, and U) is carried out. The discriminability of geographical origin among olive oils is thus considerably improved by combining these two methods (i.e., stable isotope ratio analysis and trace element composition analysis). This combination method is also potentially applicable for tracing the geographical origin of a wide

220  Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity

range of beverages including wine (e.g., Dutra et  al., 2013), apple juice (Magdas et  al., 2012; Suzuki and Nakashita, 2013; Bizjak Bat et al., 2016), orange juice (Rummel et al., 2010), lemon juice (GarcíaRuiz et al., 2007), and cider (García-Ruiz et al., 2007). For example, Bizjak Bat et al. (2016) discriminated Slovenian apple juices among five areas (i.e., Alpine, Dinaric, Pannonian, Mediterranean, and Submediterranean, where are defined by different climatic conditions): percentage of the classification based only on the stable isotopic compositions (i.e., carbon and nitrogen for pulps, oxygen and hydrogen for apple juices, and hydrogen for ethanol) is 66.7% on average, but ranging from 30% for Submediterranean to 90% for Mediterranean, whereas that based only on the trace elements (S, Cl, Fe, Cu, Zn, and Sr) is 58.7% on average, but ranging from 30% for Submediterranean to 78.6% for Alpine; however, percentage of the classification is increased to 83.9% based on combining these two methods, which include 92.9%, 75.0%, 81.3%, 100%, and 70.0% for Alpine, Dinaric, Pannonian, Mediterranean, and Submediterranean, respectively, with a great improvement being found for Alpine, Pannonian, and Mediterranean areas. Since apples, which are found in commercial markets in Japan, are produced from two major regions: Aomori and Nagano Prefectures, as well as are abundantly imported from China, discrimination of the geographical origin among Aomori and Nagano Prefectures and China is frequently required for the apples found in markets. For investigation of the 188 samples of apples collected from China (for five provinces: Shandong Province, Liaoning Province, Shaanxi Province, Gansu Province, and Uighur Autonomous Region) and Japan (for Aomori and Nagano Prefectures), the carbon isotopic composition of Chinese apples (δ13C = −25.2 ± 1.3‰) is slightly higher than that of Japanese apples (δ13C = −26.4 ± 1.4‰ for Aomori, and −26.8 ± 1.3‰ for Nagano) (P < 0.001); the oxygen isotopic composition of Chinese apples (δ18O = +25.4 ± 2.1‰) is significantly higher than that of Japanese apples (δ18O = +21.5 ± 1.5‰ for Aomori and +21.8 ± 1.0‰ for Nagano) (P < 0.001) (Fig.  7.3A); and thus the discriminability between China and Japan is 77% and 96% accuracy for carbon and oxygen isotopic compositions, respectively, but the discriminability between Aomori and Nagano Prefectures within Japan is quite limited (Suzuki and Nakashita, 2013). However, the latter discriminability (i.e., between Aomori and Nagano) can be considerably improved by a combination analysis for the stable isotopic ratios and nine trace element compositions (i.e., Mg, Mn, Zn, Fe, Cu, Mo, As, Cd, and Tl): the classification accuracy for apples for Aomori, Nagano, and China is 96.9%, 90.5%, and 97.9%, respectively (Fig. 7.3B). Thus, combination analysis for the stable isotopic and multiple trace element compositions can be useful as a diagnostic tool in the study of geographical origin of food materials.

Chapter 7  Biochemical Stable Isotope Analysis in Food Authenticity   221

(A)

(B)

Fig. 7.3  Classifications by discriminant analysis of apples collected from Japan (Aomori and Nagano Prefectures) and China: (A) based on the δ13C and δ18O values and (B) based on the δ13C and δ18O values together with nine trace elements (i.e., Mg, Mn, Zn, Fe, Cu, Mo, As, Cd, and Tl).

7.6  Further Approach II: Compound-Specific Isotope Analysis of Organic Compounds Gas chromatography/isotope ratio mass spectrometry (GC/ IRMS) can access the isotopic compositions of hydrogen, carbon, and nitrogen of individual volatile organic compounds in extracts (even still complex mixtures) of samples, which is a potential powerful tool to construct a multi-isotope and multi-compound traceability for illustrating the geographical origin of beverages and foods in the market. In GC/IRMS, individual organic compounds are separately eluted by GC, and (1) pyrolyzed individually into H2 (for hydrogen isotope analysis) or (2) combusted individually into CO2 and NOX in a oxidation furnace and the NOX are subsequently reduced to N2 in a reduction furnace (for carbon and nitrogen isotope analysis), and the H2, CO2, or N2 generated are introduced to IRMS for measuring the isotope ratios of hydrogen, carbon, or nitrogen, respectively, of individual organic compounds. It should be mentioned that the baseline separation between compound peaks (i.e., appearing a single peak for each compound) on the GC/IRMS chromatogram must be required to obtain accurate isotope ratios of organic compounds. When one peak is co-eluted with other peak(s) or impurities, the isotopically heavy tail of the first peak underlies the isotopically light front of the second peak, resulting in the isotope ratios determined has a significant error being sometimes several to

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several 10‰ levels, even if the standard deviation of the measured ratios is nicely small in replicate injections for the samples. Although the number of applications using compound-specific isotope analysis via GC/IRMS in food authenticity is really small compared to that using traditional ‘bulk’ isotope analysis via EA/ IRMS, several studies have successfully used GC/IRMS in the discrimination of the source, property, geographical origin, and adulteration of beverages and foods, such as, for example, seed vegetable oil based on the δ13C values of fatty acids (Kelly et  al., 1997), Scotch whisky based on the δ13C values of volatiles (Parker et  al., 1998), cocoa butter based on the δ13C values of fatty acids (Spangenberg and Dionisi, 2001), tequila based on the δ13C and δ18O values of ethanol (Aguilar-Cisneros et  al., 2002), anise and fennel oils based on the δD and δ13C values of trans-anethole (Bilke and Monsandl, 2002), apple juice based on the δD and δ13C values of hexamethylenetetramine (Kelly et al., 2003), and fruits (e.g., pineapple, pear, and apple) and their products based on the δD and δ13C values of volatile compounds (Preston et al., 2003; Kahle et al., 2005; Elss et al., 2006). The GC/IRMS is also potentially applicable to distinguish cultured fish from genuine (i.e., wild) ones found in markets. The bluefin tuna Thunnus orientalis is often called “diamond of the sea,” and it is deeply apprehensive that its population has been declining due to overfishing particularly during the last 50 years. Although domestic aquaculture has supplied more than 10,000 tons per year of “farmed tuna” to markets, the market prices of genuine ones have still been increased. There is therefore a target for a deceit that the farmed tuna is sold as genuine ones in markets. However, a radar plot for the nitrogen isotopic composition of individual amino acids potentially confronts this deceit issue (Chikaraishi et  al., 2007). Since amino acids in organism are generally classified into two types: “trophic” amino acids (e.g., glutamic acid, isoleucine, and proline) are significantly increased in the δ15N value along food chains; and “source” amino acids (e.g., phenylalanine and methionine) have little change in the δ15N value along food chains (Chikaraishi et al., 2009), a radar plot regarding to the isotopically offset between trophic and source amino acids can distinguish between cultured and genuine tuna (Fig. 7.4). Thus, GC/IRMS can access the isotopic compositions of hydrogen, carbon, and/or nitrogen of individual volatile organic compounds in extracts of samples, which has employed a further potential powerful diagnostic tool to construct a multi-isotope and multi-compound traceability for illustrating the geographical origin of beverages and foods in the market.

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Fig. 7.4  Trophic enrichment in the δ15N value of amino acids: GP for glutamic acid versus phenylalanine, IP for isolucine versus phenylalanine, PP for proline versus phenylalanine, GM for glutamic acid versus methionine, IP for isolucine versus methionine, and PP for proline versus methionine.

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Further Reading Araguás-Araguás, L., Froehlich, K., Rozanski, K., 1998. Stable isotope composition of precipitation over southeast Asia. J. Geophys. Res. 103, 28721–28742. Bricout, J., 1978. Fractionation of the stable isotope of hydrogen and oxygen in some plants. Rev. Cytol. Bio. Vég., Le Botaniste 1, 133–209. Chesson, L.A., Bowen, G.J., Ehleringer, J.R., 2010. Analysis of the hydrogen and oxygen stable isotope ratios of beverage waters without prior water extraction using isotope ratio infrared spectroscopy. Rapid Commun. Mass Spectrom. 24, 3205–3213. Fry, B., 2006. Stable Isotope Ecology. Springer, New York.

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Gaiad, J.E., Hidalgo, M.J., Villafañe, R.N., Marchevsky, E.J., Pellerano, R.G., 2016. Tracing the geographical origin of Argentinean lemon juices based on trace element profiles using advanced chemometric techniques. Microchem. J. 129, 243–248. Kerstel, E.R.T., van Trigt, R., Dam, N., Reuss, J., Meijer, H.A.J., 1999. Simultaneous determination of the 2H/1H, 17O/16O, and 18O/16O isotope abundance ratios in water by means of laser spectrometry. Anal. Chem. 71, 5297–5303. van Geldern, R., Barth, J.A.C., 2012. Optimization of instrument setup and post-run corrections for oxygen and hydrogen stable isotope measurements of water by isotope ratio infrared spectroscopy (IRIS). Limnol. Oceanogr. Methods 10, 1024–1036.