Determination of the geographical origin of hops (Humulus lupulus L

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Determination of the geographical origin of hops (Humulus lupulus L.) using stable isotopes of C, N and S Miha Ocvirk, Nives Ogrinc, and Iztok Joze Kosir J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b06010 • Publication Date (Web): 03 Feb 2018 Downloaded from http://pubs.acs.org on February 6, 2018

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Journal of Agricultural and Food Chemistry

Determination of the Geographical and Botanical Origin of Hops (Humulus lupulus L.) Using Stable Isotopes of C, N and S Miha Ocvirk1, Nives Ogrinc2, Iztok Jože Košir1* 1

Institute for Hop Research and Brewing, Cesta Žalskega Tabora 2, SI-3310 Žalec, Slovenia

2

Department of Environmental Sciences, “J. Stefan” Institute, Jamova 39, SI-1000 Ljubljana,

Slovenia *Corresponding author. Tel: 00386 371 21 608, E-mail address: [email protected]

1 ACS Paragon Plus Environment


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ABSTRACT: A need exists for a reliable method for determining the geographical and

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botanical origin of hops. For this study three sets of samples were collected: the first set

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comprised five German samples, the second set comprised samples of hops from ten of the

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world’s major hop growing regions while the third comprised the four main Slovenian. The

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samples were analyzed using Isotope Ratio Mass Spectrometry (IRMS) to obtain δ13C, δ15N

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and δ34S values. The δ15N (2.2 ‰ to 8.4 ‰) and δ34S (0.7 ‰ to 12.3 ‰) values were the most

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discriminating parameters for classifying hop according to geographical origin. ANOVA

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showed distinct groupings for eight out of the ten hop-growing regions. Although it was not

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possible to distinguish the geographical origin of hops based on δ13C (-28.9 ‰ to -24.7 ‰), in

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the case of botanical origin, δ13C values proved to be the most discriminative albeit with

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limited success.

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Keywords: Hop (Humulus lupulus L.), IRMS, geographical origin, botanical origin, isotopic

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ratio


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INTRODUCTION

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The contents and composition of bitter resins and essential oils in hop (Humulus Lupulus L.)

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depend on its variety and on the environmental conditions during growth, both of which can

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vary greatly.1,2 Optimal growth of the hop is achieved at temperatures between 15 to 18 °C,

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with a sufficient water supply and medium to deep soils.3 For these reasons most of the

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world's production of hop occurs close to the 48th parallel north although there are also large

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hop growing areas in the southern hemisphere, e.g., New Zealand and South African

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Republic.

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Since every brand of beer has its own recipe, it is important for brewers to be sure of the

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authenticity of their hops in order to maintain product quality. In addition, fraud with regard

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to basic harvest data, such as mislabeling of plant species or varieties, year of production and

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geographical origin is becoming an increasing problem globally.4-6 This has created a real

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need for new robust tools for determining the geographical origin and variety of hop.

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Classical chemical methods can be used to determine a wide range of parameters but these

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provide only limited information for discerning geographical origin.7 It is important to

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mention, that in the field of hop, great efforts and accomplished a great deal in overcoming

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this problem was done by official certification schemes for hop and hop products.8 To date,

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only a few studies have been published on the botanical authentication of hops, based on the

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analyses of their metabolites, which are genetically and botanically influenced.9-11 The main

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disadvantage of metabolomics is its low sensitivity and in practice such methods are only

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capable of detecting the addition of 10 % or more of different hop varieties. Measuring the

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differences in isotopic composition using isotope ratio mass spectrometry (IRMS), on the

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other hand, has proved to be a valuable and efficient method for controlling the authenticity of

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food and beverages.12,13 Stable isotopes can also be used to determine illegal or undeclared

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additions (adulteration), which is another common fraud.12 Most studies on authentication



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focus on differences in the stable-isotope ratios of light elements H, C, N, O and S. According

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to the photosynthetic pathways used to fix CO2, plant species belong to three categories:

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Calvin cycle plants (C3), the Hatch_Slack cycle plants (C4) and Crassulacean acid

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metabolism plants (CAM). The hop is a C3 plant and has a δ13C between -29 ‰ and -23 ‰.12

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Similarly, the stable isotopic composition of nitrogen (δ15N) and sulfur (δ34S), the two of the

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main soil nutrients,14,15 are mainly influenced by the isotopic composition of nitrate as

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ammonia and sulfur in the soil, which in turn depend on climatic and geographic

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conditions.7,12 Factors, such as soil depth, vegetation type, and climate can affect soil

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processes, such as mineralization, nitrification, volatilization and nitrate reduction, which also

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results in a measurable isotopic fractionation.16 Usually, the analyses of single isotope ratios

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cannot provide satisfactory results for determining geographical origin and two or more

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isotope ratios of elements are required.7,17

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Stable isotopes were first applied in the determination of food quality in the mid 70’s as a way

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of detecting the adulteration of honey with exogenous (low-cost) sugars.18 Since then, it has

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become widely used in agricultural and food science.16 For example Košir et al. (2001), used

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IRMS in combination with chemometrics to determine the geographical origin of wines.19,20

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Hrastar et al. (2009) classified Camelina sativa oil according to geographical origin using

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13C values.21 Angerosa et al. (1999) used stable isotope ratios of 13C and 18O to establish

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the geographical origin of olive oils22 while Potočnik et al. (2016) used 13C values to

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determine the geographical origin and adulteration of pumpkin seed oil.23 IRMS has also been

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used to determine the geographical origin of dairy products, meat products, vegetables and

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fruit juices.16,17,24,25

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To the authors knowledge there has only been one study using IRMS to determine the

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geographical origin of Hops (Humulus lupulus L.)26, which was based on only two samples

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from eight growing regions excluding New Zealand and South African Republic. For this


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reason, we chose to study δ13C, δ15N and δ34S values of hops and hop products from all of the

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world's main growing regions to verify their geographical origin, and, in addition, to see if

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these stable isotopes can be used to distinguish between the major varieties of hop plants

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produced in Slovenia. The aim of this study was to find out if knowing the δ13C, δ15N, and

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δ34S values could be a useful tool for discriminating between the geographical and botanical

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origin of hop.

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MATERIALS AND METHODS

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Chemicals

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Toluene 99.7 %, methanol (HPLC grade) 99.9 %, lead acetate trihydrate 99.9 % and glacial

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acetic acid 99.9 % were purchased from Sigma-Aldrich (Germany). International reference

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materials: IAEA-CH-7 (polyethylene), IAEA-CH-6 (sucrose), IAEA-N-1 (ammonium

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sulfate), IAEA-N-2 (ammonium sulfate), IAEA-S-5 (barium sulfate) and NBS 127 (barium

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sulfate) were purchased by International Atomic Energy Agency IAEA, Vienna (Austria).

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Sampling

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For this study, three sets of hop samples were collected. The first set of samples comprised

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five samples of hop cones, pellets (type 45 or 90) and hop extracts from the German hop-

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growing region of Hallertau. Each set of five samples (cones, pellets and extracts) was

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prepared from the same sample of hop cones. Two additional samples of hop cones were

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separated into the green parts of the cones, lupulin and essential oils. The second set of hop

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cones are representative of the major hop-growing regions of the World: Yakima (USA_Y)

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and Great Lakes (USA_GL) region in the USA, Australia (AUS), New Zealand (NZL),

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Republic of South Africa (RSA), Great Britain (GB), Germany (GER), Austria (AUT), Czech

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Republic (CZ) and Slovenia (SLO). In total, this amounted to 77 different samples. The third 5 ACS Paragon Plus Environment


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set includes samples of hop cones from Slovenian hop growers and comprised 24 samples of

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traditional Slovenian hop varieties including Aurora (AU), Bobek (BO), Celeia (CE) and

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Savinjski Golding (SG). All samples were collected at optimal maturity during the 2014

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harvesting season. These samples were used to study isotopic variations in hop varieties from

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the same geographical area as well as to discriminate hop samples according to geographical

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origin.

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First, the alpha-acids content was determined by measuring the lead conductance values

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(LCV) of the hops according to the Analytica – EBC 7.4 method.27 Briefly, bitter substances

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were extracted from the hops with toluene (100 mL). Then, 10 mL of the toluene extract was

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diluted with 30 mL of methanol and titrated conductometrically (Methrom, Switzerland) with

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a lead acetate solution (7.59 % PbAc) in methanol containing glacial acetic acid (50 %).

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Isotope Ratio Mass Spectrometry (IRMS) 13

C/12C,

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N/14N and

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S/32S ratios were determined using IRMS. A known

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In hop samples

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amount of powdered hop sample (5 mg) was weighed into a tin capsule, closed with tweezers

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and placed into the automatic sampler of the elemental analyzer. All stable C, N and S isotope

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analyses were performed simultaneously using an IRMS IsoPrime 100 - Vario PYRO Cube

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(OH/CNS Pyrolyser/Elemental Analyser; Elementar UK Ltd, Manchester, UK). Isotope data

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are expressed using the conventional δ-notation using the general formula:

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δiE = (R(iE/jE)sample / R(iE/jE)standard) - 1

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Where E is the element (C, N, S), R is the isotope ratio between the heavier “i” and the lighter

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“j” isotope (13C/12C,

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recognized reference standard. The δ-values are multiplied by 1000 and expressed in units

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“per mil” (‰).28 For carbon, we used the Vienna Pee Dee Belemnite (VPDB) as the reference

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standard, for nitrogen we used atmospheric N2 (air), while for sulfur we used the Vienna-

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N/14N,

34

S/32S) in the sample and in the relevant internationally


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Canyon Diablo Troilite (V-CDT) standard. The results were calibrated against the following

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international reference materials: IAEA-CH-7 (polyethylene; δ13C = -32.15 ±0.05 ‰) and

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IAEA-CH-6 (sucrose; δ13C = -10.45 ±0.03 ‰) for carbon; IAEA-N-1 (ammonium sulfate;

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δ15N = 0.4 ±0.2 ‰) and IAEA-N-2 (ammonium sulfate; δ15N = 20.3 ±0.2 ‰) for nitrogen;

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IAEA-S-5 (barium sulfate; δ34S = -0.4 ±0.2 ‰) and NBS 127 (barium sulfate; δ34S = 20.3

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±0.4 ‰) for sulfur with added vanadium pentoxide (International Atomic Energy Agency

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IAEA, Vienna, Austria). Reproducibility of the measurements was ±0.2 ‰ for δ13C and ±0.3

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‰ for δ15N and δ34S.

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Statistical Data analysis

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Microsoft’s Excel software (Microsoft, USA) was used to perform basic univariate statistics

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while a one-way analysis of variance (ANOVA) with a Duncan test (P = 0.05) was performed

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using the Statistical Package for the Social Sciences (SPSS, IBM Corporation, USA).

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RESULTS AND DISCUSSION

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On the market, hops can be in various forms, e.g., cones, different pellet types, and as

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extracts. The first question is, therefore, does the stable isotope ratios remain the same when

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hop cones are processed or does each fraction: green parts of the cones, lupulin, and essential

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oils differ isotopically? To answer this, we collected samples consisting of hop cones, extracts

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and pellets produced from the same variety and separated from the hop cones the lupulin and

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the essential oils. For each fraction, we determined and compared the δ13C, δ15N, and δ34S

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values (data not shown). The results reveal that there is no statistically significant difference

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in the isotopic composition between the hop products made from the same cones. We also

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studied different varieties of hops with differing alpha-acid contents (4.1 % to 13.2 %). The



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data (not shown) reveals that the bitter resin and essential oil content does not affect the

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isotopic ratios. The alpha-acid contents are not shown here and further on in the manuscript.

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Geographical origin

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We described each data set using the three parameters: δ13C, δ15N, and δ34S. For the second

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set of samples, covering all the major hop-growing regions of the World, we grouped the

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results of the univariate statistical analysis according to their geographical origin independent

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of variety (Table 1). Figure 1 shows the distribution of the mean δ13C, δ15N, and δ34S values.

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In the Southern Hemisphere, the δ34S values are significantly higher than in the samples in the

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Northern Hemisphere. The δ15N values of hops from the USA (2.2 ‰ to 4.7 ‰) are lower in

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the European samples (3.3 ‰ to 8.4 ‰). The lowest mean value of δ13C (-27.9 ‰) and the

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highest mean value of δ34S (10.9 ‰) were found in the South African samples. The results of

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ANOVA comparison (Table 1) reveals that the best discrimination between samples from

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different regions is achieved using δ34S, followed by δ15N. The δ13C values enabled only

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partial discrimination of the CZ and RSA samples.

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All possible combinations of scatter plots of C/N and C/S were prepared. Figure 2 shows a

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scatter plot of δ15N vs. δ34S for the whole data set. The plot shows how samples from AUS,

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NZL, RSA, USA_GL and CZ form distinct groups, while in the center are groups of samples

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from other regions where, although they overlap, some clustering is noticeable. These include

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samples from AUT, GER, USA_Y and SLO. Samples from USA_Y and SLO overlap, despite

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the large geographical distance between them. The samples from GB are scattered. Groups of

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samples from GER, AUT, SLO and CZ are closer together, which we expect since they are

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neighboring regions within central Europe. It is interesting that samples from the two major

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hop growing regions in the US: Yakima valley and the Great lakes, form distinct groups. This

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is also not surprising since the geographical difference between them is around 2500 km and

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we expect there to be different pedoclimatic conditions. For more clarity, we put together all


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samples from Europe to see if it is possible to differentiate between hop samples from Europe

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and other parts of the world. Figure 3 shows almost complete separation of the groups with

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the exception of samples from the USA_Y that overlap with the European samples. We then

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focused on hop samples from Europe only, since geographically these regions are closest to

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one another. All samples group according to their country of origin except for samples from

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GB, which are scattered, although they all originated from the same region i.e. Kent (Figure

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4).

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We also applied the same methodology to Slovenian hop samples collected for the purpose of

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determining botanical origin and were obtained directly from the hop growers to be sure of

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varietal purity. The Student’s t-test analysis shows no significant difference between both

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groups of samples for all three measured parameters.

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Clearly, isotopic ratios can act as fingerprints for different growing regions from around the

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world and it is possible to observe clustering of hop samples based on significant differences

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between growing regions that result in large variations in δ15N and δ34S values. The δ13C

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values are closer together (mean: -26.6 ±0.9 ‰) and are the least discriminative, which agrees

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with the fact that δ13C values are biologically conditioned rather than environmentally.

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Botanical origin

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In this study, we also wanted to see if there is any isotopic differentiation of hop samples

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according to variety. For this, we included only samples from Slovenia to exclude

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environmental factors, since hop production in Slovenia is limited to a small central region

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covering only 50 km2. The hop samples belong to four of the most important varieties:

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Savinjski golding (SG), Bobek (BO), Aurora (AU) and Celeia (CE). The results are presented

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in Table 2. A one-way ANOVA analysis reveals that δ34S has little discriminating power

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regarding variety. This is expected, since the δ34S values are predominantly environmentally

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influenced. The δ13C and δ15N similar to δ34S values did not show a strong discriminating



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power with regards to botanical origin. It was also not possible to distinguish between SG and

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CE, whereas AU and BO did form two distinct groups. These results are also in line with the

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fact that CE is bred from the SG variety. Overall, our results reveal a limited capacity for

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δ13C, δ15N and δ34S values for differentiating between different varieties of hop. This also

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agrees with previous research on other plant species and products such as wine, camelina and

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pumpkin seed oil and edible oils, fruit juices and honey. In all cases, using stable isotopic

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values it is only possible to distinguish between different plant species, geographical origin,

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and in some cases year of production whereas separation according to variety was either

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limited or impossible.19-21,23

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In conclusion, we can say that the use of stable isotopes ratios of δ13C, δ15N, and δ34S could

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be used as a new powerful tool for differentiating hops according to geographical origin and

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can be of use to the brewing industry or to hop traders in resolving issues relating to

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authenticity. The methodology is straightforward, fast and cheap, relative to standard GC or

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HPLC techniques and does not need any special sample pretreatment except for weighing the

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samples. In the case of botanical origin, the same methodology gives only limited success. In

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the future, we plan to complete this research by obtaining δ18O and δ2H values and by

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applying Pb isotope analysis. The levels of all three elements relate to the conditions in the

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environment and therefore, we expect them to provide better geographical differentiation of

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hop products.

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FUNDING SOURCES

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This work was financially supported by the Slovenian Research Agency by grant 020-2/2011-

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3. The study is part of two EU projects: MASSTWIN - Spreading excellence and widening

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participation in support of mass spectrometry and related techniques in health, the

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environment and food analysis (H2020, grant agreement no. 692241) and ERA Chair ISO-


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FOOD - for isotope techniques in food quality, safety and traceability (FP7, Grant agreement

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no: 621329).

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SUPPORTING INFORMATIONS. Two scatterplots (C/N and C/S).



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FIGURE CAPTIONS

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Figure 1. Distribution of the mean values of δ13C, δ15N and δ34S in hops according to growing

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regions in the northern and southern hemisphere.

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Figure 2. Scatter plot of δ15N and δ34S values of samples from 10 major hop-growing regions

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worldwide. Samples are marked as in the section materials and methods – sampling.

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Figure 3. Scatter plot of δ15N and δ34S comparing samples of hops from Europe with other

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major hop-growing regions worldwide. Samples are marked as in the section materials and

299

methods – sampling.

300

Figure 4. Scatter plot of δ15N and δ34S values in European hop samples. Samples are marked

301

as in the section materials and methods – sampling.

302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317


Page 17 of 23


TABLES Table 1. Number of samples, Mean, Standard deviation, minimum value, maximum value and grouping of the samples. Mean

n

‰

Minimum Maximum

S.D.

‰

Groupsa

‰

δ13C(‰) AUT

8

-27.3

0.9

-28.9

-26.2

ab

CZ

3

-26.0

1.3

-27.2

-24.7

d

GER

23

-26.3

0.8

-27.9

-24.9

bcd

SLO

16

-26.6

0.7

-27.5

-25.1

bcd

USA_Y

4

-26.5

0.4

-26.9

-25.8

bcd

USA_GL

6

-26.2

0.8

-27.6

-25.1

bcd

GB

4

-27.2

-28.1

-26.7

abc

RSA

5

-27.9

0.6 0.7

-28.9

-27.1

a

NZL AUS

6 2

-26.1

0.5

-26.9

-26.7

0.3

-27.1

-25.4 -26.4

cd bcd

AUT

8

4.6

0.9

3.3

6.3

b

CZ

3

8.0

0.5

7.5

8.4

e

GER

23

5.9

0.6

4.8

7.2

d

SLO

16

4.7

0.6

3.7

5.6

bc

USA_Y

4

3.9

0.5

3.4

4.7

ab

USA_GL

6

3.0

0.8

4.6

a

GB

4

5.1

1.3

2.2 3.7

7.4

cd

RSA

5

4.9

0.8

3.8

6.1

bcd

NZL

6

3.3

2.8

4.1

a

AUS

2

7.3

0.4 0.3

7.0

7.5

e

AUT

8

7.2

1.1

5.4

8.9

e

CZ

3

4.4

0.75

3.6

5.0

cd

GER

23

5.3

0.7

4.1

6.8

d

SLO

16

4.0

0.7

2.7

4.8

bc

USA_Y

4

4.0

0.4

3.5

4.4

bc

USA_GL

6

2.1

1.1

3.8

a

GB

4

3.2

0.5

0.7 2.5

3.7

b

RSA

5

10.9

0.8

10.0

12.3

g

NZL

6

9.2

8.5

10.5

f

AUS 2 ANOVA, p=0.05

8.6

0.7 0.7

7.9

9.3

f

15

δ N(‰)

34

δ S(‰)

a



Page 18 of 23

Table 2. Number of samples, Mean, Standard deviation, minimum value, maximum value and grouping of the Slovenian samples. Mean

n

‰

Minimum Maximum Groupsa

S.D.

‰

‰

15

δ N(‰) SG

6

5.6

0.9

3.8

6.7

ab

BO

6

4.7

4.3

6.1

a

AU

6

5.9

0.7 1.1

4.3

7.9

b

CE

6

4.9

0.7

3.7

5.5

ab

SG

6

-26.8

0.2

-27.0

-26.5

c

BO

6

-27.2

0.2

-27.5

-26.9

a

AU

6

-26.4

0.3

-26.8

-25.9

b

CE

6

-26.3

0.3

-26.6

-25.8

c

SG

6

3.2

1.7

1.4

6.1

a

BO

6

4.0

0.7

3.1

4.8

a

AU

6

4.6

1.1

2.6

6.1

a

CE 6 ANOVA, p=0.05

3.4

0.7

2.4

3.9

a

13

δ C(‰)

δ34S(‰)

a


Page 19 of 23


Figure graphics Figure 1



Page 20 of 23

Figure 2


Page 21 of 23


Figure 3.



Page 22 of 23

Figure 4.


Page 23 of 23


TOC graphic


Determination of the geographical origin of hops (Humulus lupulus L

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