GCMS Investigation of Volatile Compounds in Green Coffee Affected

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GCMS Investigation of Volatile Compounds in Green Coffee Affected by Potato Taste Defect and the Antestia Bug Susan C. Jackels,*,† Eric E. Marshall,† Angelica G. Omaiye,† Robert L. Gianan,† Fabrice T. Lee,† and Charles F. Jackels§ †

Chemistry Department, Seattle University, 901 12th Avenue, Seattle, Washington 98122-1090, United States Divisions of Physical Sciences and Computing and Software Systems, University of Washington Bothell, 18115 Campus Way NE, Bothell, Washington 98122-8246, United States

§

ABSTRACT: Potato taste defect (PTD) is a flavor defect in East African coffee associated with Antestiopsis orbitalis feeding and 3-isopropyl-2-methoxypyrazine (IPMP) in the coffee. To elucidate the manifestation of PTD, surface and interior volatile compounds of PTD and non-PTD green coffees were sampled by headspace solid phase microextraction and analyzed by gas chromatography mass spectrometry. Principal component analysis of the chromatographic data revealed a profile of surface volatiles distinguishing PTD from non-PTD coffees dominated by tridecane, dodecane, and tetradecane. While not detected in surface volatiles, IPMP was found in interior volatiles of PTD coffee. Desiccated antestia bugs were analyzed by GCMS, revealing that the three most prevalent volatiles were tridecane, dodecane, and tetradecane, as was found in the surface profile PTD coffee. Coffee having visible insect damage exhibited both a PTD surface volatile profile and IPMP in interior volatiles, supporting the hypothesis linking antestia bug feeding activity with PTD profile compounds on the surface and IPMP in the interior of the beans. KEYWORDS: Green coffee, volatile organic compounds, potato taste defect, GCMS, 2-isopropyl-3-methoxypyrazine, Antestiopsis orbitalis



defects.6−11 In each of these studies, ground green coffee was solvent-extracted, and the extracts were concentrated by distillation, separated by column chromatography, and analyzed by GCMS. Major classes of volatiles reported were alcohols, aldehydes and ketones, acids and esters, furans, and lesser amounts of nitrogen-, sulfur-, and chlorine-containing compounds. Some hydrocarbons were reported, but no alkanes. Some studies found marker compounds associated with coffee defects.8,10,11 IPMP was detected by GCMS at the trace level in coffee unaffected by PTD and at an elevated level in PTD coffee.1 More recently, headspace sampling by solid phase microextraction (SPME) has been developed and effectively applied to the study of volatiles in both green and roasted coffee.12−15 SPME−GCMS has been broadly applied for characterization of roasted coffee volatiles associated with coffee plant variety;16 roasting and brewing processes;17,18 characterization and identification of markers in green and roasted defective coffees;19−22 and markers of climate change effect on coffee quality.23 In each of these studies, ground coffee was used. In the present work, our aim is to elucidate the manifestation of PTD in green coffee by studying the surface volatile organic chemicals associated with the defect. Following the hypothesis that PTD is associated with IPMP on the surface of green coffee beans,1,2 we will study whole beans (surface volatiles sampled), in contrast to all preceding studies on ground beans (interior volatiles

INTRODUCTION Potato taste defect (PTD) is a persistent but sporadic phenomenon in East African coffee responsible for diminished coffee quality and considerable loss of coffee crop. PTD affects only a few beans in many and lends a distinct flavor of dirty potato skins to roasted coffee, rendering it unpalatable. In the 1980s Becker et al.1 analyzed extracts from ground PTD-affected green coffee using gas chromatography/mass spectrometry (GCMS) with olfactory detection and identified 2-isopropyl-3methoxypyrazine (IPMP) and 2-isobutyl-3-methoxypyrazine (IBMP) as the compounds responsible for the taste and aroma of PTD. Field studies of PTD by Bouyjou et al.2 linked PTD with damage from a bug, Antestiopsis orbitalis (known as the antestia bug), that feeds on coffee fruit. Consistent pesticide application during the cherry development period was shown to virtually eliminate PTD, with an infestation level of less than one bug per tree being necessary to avoid it.3 Further, antestia bugs were found to exhibit aggregative behavior that may be semiochemical in origin.3 Finally, PTD and an IPMP-producing bacterium were linked through cell culture studies.4 These authors hypothesized that the bacterium could be introduced into the coffee cherries by antestia, either directly or passively, through holes in the cherry skin, and that IPMP produced by the bacterium adhered to the bean surface and survived the roasting process. Bacterial symbionts of antestia have been identified,5 but the bacterial link with PTD remains elusive. In coffee production, PTD is mitigated by coffee processors who rigorously sort out beans with signs of insect damage, but this method does not entirely eliminate PTD. GCMS has been applied in many studies of the volatile chemicals in green coffees, including those with flavor and processing © 2014 American Chemical Society

Received: Revised: Accepted: Published: 10222

July 18, 2014 September 29, 2014 October 5, 2014 October 5, 2014 dx.doi.org/10.1021/jf5034416 | J. Agric. Food Chem. 2014, 62, 10222−10229

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Analyses were done in the splitless mode using helium gas carrier at 1.0 mL/min flow. Column temperature was maintained at 40 °C for 11 min, then raised to 190 °C at 3 °C/min, held at 190 °C for 10 min, and finally raised from 190 to 250 °C at 15 °C/min. Mass spectra were recorded following electronic impact ionization at 70 eV. The mass range for data collection was 40−400 Da with 0.3 s scan interval. The data were collected and analyzed by GCMS Agilent ChemStation software (GCMSD1 operating software with Enhanced Data Analysis) using the NIST-05 and Wiley FFNSC-2 mass spectral databases. Peak assignments were made using dual criteria of mass spectral database and linear retention index26,27 match. Retention indices of the eluted compounds were calculated on the basis of the standard alkane mixture (C11−C18). By comparing the retention indices and unique mass spectra with the reference library matches and literature retention indices,28 tentative assignments were obtained, and they were confirmed by running known standards under the bean analysis conditions. Chromatographic Analysis of Ground Bean Samples. Green coffee samples were frozen to −70 °C and then ground in a blender (Waring Commercial, model 51BL30, Fisher Sci., U.S.A.), with the size fraction less than 2 mm (U.S.A. Standard Test Sieve, No. 10, 2 mm, Fisher Sci., U.S.A.) being considered representative of the interior of the beans and analyzed for volatiles. A 3.5 g ground sample in a 40 mL sample vial was heated to 60 °C, sampled by SPME, and analyzed chromatographically by the procedure as described above in the Chromatographic and Mass Spectrometric Analysis section. Statistical Analyses. Principal component analysis (PCA) allows comparison and classification of complex samples using their entire gas chromatographic (GC) profiles, avoiding selection and identification of individual peaks and peak-area integrations, while taking into account the large number of minor peaks and peak shape information. Due to minor drifts in retention times, data alignment is required prior to applying PCA to GC data. This approach, utilizing the entire instrument output, has been applied successfully to chromatographic29,30 and spectral31 analysis of complex systems. The PCA was accomplished using software within the PLS Toolbox v. 7.5.232 running on the Matlab platform v.R2013b.33 See Chapter 4 of Brereton34 for a general discussion of PCA in the chemometric context. The GC/MS signal, total ion current (TIC) as a function of time, was collected every 0.4 s, yielding approximately 11 132 observations for each 75 min run. Visual inspection revealed that all useful data had retention times in the range 17.2−70.9 min, and the GC data sets were truncated accordingly, yielding data objects of 7951 variables corresponding to points in the chromatogram. Prior to analysis, the GC data objects were aligned using correlation-optimized warping (COW) according to the procedures of Tomasi et al.35 The reference chromatogram (pt 61a) was selected as having the maximum cumulative product of correlation coefficients for a subset of 52 chromatograms collected in midstudy.36 Parameters used in the alignment (segment = 100, slack = 15) were determined by their systematic variation with graphical assessment of the resulting aligned chromatograms. After alignment, further preprocessing included baseline correction using the Eilers and Boelens37 method with Whittaker38 filter (p = 0.001, lambda = 100), followed by mean-centering. The resulting principal component model was then subjected to the VARIMAX rotation39 in order to facilitate the interpretation of the potato taste samples in terms of the loadings on a single factor.

sampled). We will apply headspace SPME for the sampling and concentration of surface volatiles followed by GCMS for separation, detection, and identification. Principal component analysis (PCA) will be applied to the chromatograms to characterize surface volatile peak patterns that differentiate PTD from non-PTD coffee. This study is the first both to characterize the volatile organics on the surface of green coffee beans and to utilize SPME−GCMS for the study of potato taste defect. Parts of this research were presented at the Coffee Research Symposium, convened by the Rwandan Ministry of Agriculture24 and the Global Knowledge Initiative,25 March 17−18, 2014, Kigali, Rwanda.



MATERIALS AND METHODS

Chemicals. Standard compounds were obtained from Fisher Scientific Co. or Sigma/Aldrich Co., U.S.A. (C11−C18 standard alkane mixture, hexanal, 2-pentylfuran, nonanal, 1-octen-3-ol, 2-ethyl-1hexanol, benzaldehyde, 3-methylbutanoic acid, heptanal, 2-E-hexenal, pentanol, octanal, 6-methyl-5-hepten-2-one, decanal, hexanoic acid, 2-isopropyl-3-methoxypyrazine, 2-isobutyl-3-methoxypyrazine, 1-hexanol, limonene, octanoic acid, phenol, octyl acetate, 1-dodecene, 2,6dimethylpyridine, methylsalicylate, 1-tetradecene). Note that 1methoxy-4-propylbenzene, phenylethylalcohol, 2,6,10,14-tetramethylpentadecane, hexadecanoic acid, and dodecanal were identified by mass spectral match but not confirmed by standard. Samples and Characterization. Fifty-two samples (Arabica coffee, varietal Bourbon) were sent directly from the coffee growing regions of Rwanda in the 2012 and 2013 harvest seasons to the Rogers Family Company laboratory in Lincoln, California, where they were characterized by physical and sensorial analysis. All samples were conventionally grown in the sun at 5000−8000 feet elevation on small farms. Physical characteristics included moisture content (%), screen size distribution, sorting, and counting defects. Sensorial analysis consisted of standard cupping of a medium roasted sample by four experienced cuppers, which for our purposes classified the samples as either “PTD” or “non-PTD”. PTD samples tested positive at rates from 1 in 6 cups to 1 in 20 cups. Green coffee samples from each batch were forwarded to Seattle University along with the characterization data. For the purpose of this study, the detailed origins of the samples were not included. The samples varied in size from 100 to 400 g and were stored as received in plastic bags at room temperature until analyzed. Sample Preparation. The SPME sampling conditions used here were previously validated and applied in studies of green and roasted coffee.12−15 Whole bean green coffee (70.0 g, approximately 400 beans, randomly selected) was placed in a headspace bottle (125 mL) with a PFTE/silicone septum cap (Supelco, U.S.A., 27236). The SPME fiber used was triple phase 50/30 μm DVB/Carboxen/ PDMS coated (Supelco, U.S.A., 57328-U). Prior to first use, the fiber was preconditioned at 250 °C in the injection port of the GCMS for 30 min. The fiber was exposed in the headspace above the coffee beans for 60 min while the assembly was immersed in a 60 °C water bath. The headspace-to-volume ratio was approximately 1:10. The fiber was desorbed in the GC injection port for 5 min at 250 °C in the splitless mode using a Supelco specific SPME injection insert of 0.75 mm i.d. Organization of Study. Samples selected randomly were subjected to GCMS analysis in batches of three to five per day. Blank samples were run once per day under the bean analysis conditions and provided negligible response. One to four replicates of each sample were analyzed, depending on size of coffee sample received. Usually, replicates were not run on the same day. In all there were 52 samples that resulted in 115 GCMS runs. Gas Chromatographic and Mass Spectrometric Analysis. The GCMS conditions here were previously validated in several studies of green and roasted coffee.16,17 An Agilent 5890 gas chromatograph was used as equipped with a 60 m × 0.25 mm i.d., 0.25 μm film thickness Stabilwax capillary column (Restek, 10641, Supelco, U.S.A.), an Agilent 5972 mass-selective detector, and Agilent ChemStation software.



RESULTS AND DISCUSSION Chromatograms of Whole Bean Samples. In all, 115 chromatographic runs of surface volatiles were performed on 52 characterized whole bean samples. One to four replicates were collected, depending on availability of sample, and in all cases they were reproducible. Six of the samples in the study were confirmed with PTD by the taste testers. Visual inspection of the chromatograms revealed obvious differences between the potato taste (PTD) and nonpotato taste (non-PTD) samples. Typical non-PTD and PTD surface volatile chromatograms are 10223

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Figure 1. Gas chromatograms for whole bean green coffee samples: (a) non-potato-taste (Pt 72a) and (b) potato-taste (Pt 85b). Compounds are labeled according to Table 1.

shown in Figures 1a and 1b, respectively. The sample analyses are labeled in the figures with a number designating their index in our laboratory records and a letter indicating the replication. For example, “Pt 85b” refers to second analysis (“b”) of the sample designated “85”. Note the difference in scale for the ordinate axes: the total ion current scale is 10 times greater (to 4.0 × 106) in the PTD chromatogram as compared to the nonPTD chromatogram (4.0 × 105) The retention times and compound identifications for the major peaks are given in Table 1. Peaks occurring at 31.1, 38.5, 45.4, 62.2, and 67.2 min corresponded to silyl esters originating from the SPME sampling conditions and were eliminated from further analysis. These assignments were confirmed through a blank sampling experiment. A peak of widely varying intensity at 34.3 min was identified as 1-dodecene. The intensity of this peak correlated strongly with the elapsed time between processing of the coffee beans in the field and their analysis in the lab. This is consistent with 1-dodecene being a product of on-the-shelf oxidation of unsaturated plant oils, and the development of a cardboardlike odor.40 Having no significance in the present context, the 1-dodecene peak was eliminated from further analysis. The peaks labeled “8” at 40.1 min (Figure 1a) and “7” at 39.9 min (Figure 1b) are “unidentified” by the MS analysis. Peaks corresponding to tridecane (6), dodecane (3), tetradecane (10), and methylsalicylate (22) are observed to have much larger intensities in the PTD chromatograms than in the non-PTD ones (note the different ordinate scales). Peak “20” at 54.3 min corresponding to 1-methoxy-4-propylbenzene is variable among the PTD chromatograms and observed only at reduced intensity in the non-PTD chromatograms. This pattern of relatively intense alkane peaks in PTD samples is denoted in this study as a “PTD profile.” Two samples (Pts 77a and 80a) that were characterized as “non-PTD” by the taste testers were found to have the PTD profile (i.e., high alkane concentrations) in their surface volatile

Table 1. Selected Observed Peaks for Whole Bean and Ground Samples (non-PTD and PTD) label

retention time (min)

linear retention index

compound

1 2 3 4 − 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

24.8 25.1 31.5 32.5 34.3 35.4 37.3 39.9 40.1 40.7 42.6 43.4 45.1 45.2 45.7 47.0 47.6 48.5 49.7 50.7 54.3 56.1 61.8 63.4 67.3 72.0 73.4

1100 1104 1200 1216 1247 1266 1300 1348 1352 1363 1400 1416 1450 1452 1463 1490 1502 1522 1547 1569 1651 1693 1832 1873 1976 2106 2146

undecane hexanal dodecane limonene 1-dodecene 2,6-dimethylpyridine tridecane unidentified unidentified 1-hexanol tetradecane nonanal 1-tetradecene 2-isopropyl-3-methoxypyrazine 1-octen-3-ol octylacetate 2-ethyl-1-hexanol decanal 2-isobutyl-3-methoxypyrazine benzaldehyde 1-methoxy-4-propylbenzenea 3-methylbutanoic acid methylsalicylate hexanoic acid phenylethylalcohola phenol octanoic acid

a

Identified by mass spectral match, but not confirmed by standard.

chromatograms. The PCA (see below) also characterized them as “PTD.” These samples were from farms adjacent to those 10224

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Figure 2. PCA scores biplot (PC1 vs PC2) for 115 whole bean green coffee samples (after VARIMAX rotation).

that had PTD, which suggested PTD could possibly be verified by further taste testing of these samples. However, due to limited sample availability, further testing was not possible. Surprisingly, neither IPMP nor IBMP was observed in any of the PTD or the non-PTD chromatograms of surface volatiles when the samples were heated at 60 °C. Standards of IPMP and IBMP showed them to be found at 45.2 and 49.7 min, respectively. To determine if a higher temperature would release these pyrazines, PTD and non-PTD samples were heated to 90 or 100 °C, but still no IPMP or IBMP was observed among the surface volatiles. Samples could not be heated over 100 °C because roasting chemistry begins above 100 °C, producing new compounds. PCA of Chromatograms. Principal component analysis (PCA) was utilized to classify the 115 samples as either PTD or non-PTD. In general, a model with two principal components was found to be satisfactory, accounting for 72% of the variance in the data sets. In Figure 2 is the scores biplot (PC1 versus PC2) for the 115 data objects. A VARIMAX rotation has been applied to the component axes to bring the cluster of PTD samples into good alignment with the PC1 axis, facilitating interpretation in terms of the PC1 loadings. Note first that all samples identified as PTD by the taste testers (red diamonds) appear in a cluster well separated from the much larger number of non-PTD samples (black circles). As already noted above from the visual inspection of the chromatograms, Pts 77a and 80a appear firmly within the PTD cluster, strongly suggesting that they would be likely to reveal PTD character upon further sensorial testing. The remaining 107 non-PTD points exhibit very little spread along the PC1 axis as would be indicative of PTD chromatograms. In Figure 3 is presented a plot of the loadings for PC1. Since the PTD cluster of data lies close to the positive PC1 axis in the

scores biplot, we can interpret the loadings as characteristic of the chemical “profile” that classifies these points as PTD and separates them from the other samples. This indicates that compared to the non-PTD samples, PTD samples have strongly increased levels of dodecane and tridecane; moderately increased levels of tetradecane, 1-octene-3-ol, 2-ethyl-1-hexanol, and limonene; slightly increased levels of 1-methoxy-4-propylbenzene and methylsalicylate, and decreased levels of 3-methylbutanoic acid. The strongest features of this PTD profile are increased levels of several alkanes and a decreased level of 3-methylbutanoic acid. Of interest is the observation of increased methylsalicylate (oil of wintergreen) in the PTD profile. Methylsalicylate is derived from salicylic acid, a plant hormone, and is known to increase in response to insect attacks.41 This compound has not been reported among the volatiles of “normal” green coffee15,17,19 but has been reported among the volatiles in defective moldy/earthy coffee.8 Consistent with the previous visual observations, no evidence of IPMP or IBMP is found in the loadings for PC1. In Figure 2, the spread within the non-PTD samples is along PC2, with the two replicates of Pt 82 having the largest displacements. Examination of the PC2 loadings and the GC’s for Pt 82 indicates that those samples have relatively large concentrations of nonanal (“11”) and an unidentified compound (“7”). Chromatograms of Ground Samples. The surface volatiles observed in chromatograms of whole bean samples (above) revealed differences between PTD and non-PTD coffees that serve to classify the coffees but were not the same as the reported differences in the literature1 in that the whole bean chromatograms did not include IPMP or IBMP. However, the previous observations1 were based on finely ground samples that were solvent-extracted and put through a multistep process 10225

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Figure 3. PCA loadings plot for PC1. Compounds are labeled according to Table 1.

seeds and not deposited on the seed surface by a bacterial growth in the fruit, as had been suggested by Bouyjou.4 Chromatograms of Insect Damaged PT Coffee Beans. Given that the IPMP occurs inside the beans, it would be illustrative to determine if its level is the same throughout a PTD sample or is concentrated in specific beans, for example, those exhibiting visible signs of insect damage. Further, if the elevated IPMP level is associated with antestia activity, then coffee with known antestia damage should exhibit the PTD profile in the whole beans and the PTD-associated pyrazines in the ground coffee. To test these hypotheses, a large (several kilogram) sample of PTD coffee was needed so that it could be sorted into the defect categories. None of the Rwandan samples was large enough, but we were fortunate to receive a large donated sample of Burundian coffee that had very weak PTD (1 cup in 120 confirmed by a tasting panel). This sample was sorted into the following fractions: insect-damaged (brown spots indicative of antestia activity), UV fluorescent (presumably from the presence of a fluorescent microbe on the bean surface), broken (during removal of the parchment and silverskin), withered (characteristic of poor cultivation conditions), and bulk (no defects, after the other fractions were removed). SPME−GCMS analysis of the bulk fraction gave results indicative of non-PTD coffee, i.e., no prominent alkane PTD profile in the whole bean chromatogram and IBMP with only a trace of IPMP in the ground bulk chromatogram. In contrast, the chromatogram of the whole bean insect-damaged fraction did feature a prominent tridecane peak with accompanying dodecane and tetradecane peaks, similar to the profile that characterized PTD whole bean coffee. The chromatogram of the whole-bean insect-damaged fraction (Figure 4a) did not have peaks attributed to IPMP or IBMP, whereas chromatogram of the ground-bean insect-damaged fraction (Figure 4b) exhibited both. Comparing the chromatograms of the sorted fractions

before chromatography. When using ground samples previously, the volatiles were extracted from the interior of the coffee beans and the concentration of surface volatiles would be insignificant in the mixture. Since in our research (above), IPMP and IBMP, which were assumed to bring about PTD, were not observed in the surface volatiles of PTD coffee, they must have been in the interior of the PTD beans. Thus, further experiments were designed to measure the interior volatiles of the beans. PTD and non-PTD green coffee samples were frozen to −70 °C, ground in a blender with the size fraction less than 2 mm being considered representative of the interior of the beans, and analyzed for volatiles. A 3.5 g ground sample was sampled and analyzed chromatographically by the PSPME− GCMS procedure as described above in the Materials and Methods Section. Due to limited quantity of samples, two non-PTD and four PTD samples were used to collect nine chromatograms of ground samples (two non-PTD and seven PTD). In addition to these samples a large Burundian sample (see section below) was used to collect 13 more chromatograms. In contrast to the surface volatile case, the intense PTD profile (mainly alkanes) was not observed in the interior of either PTD or non-PTD samples. Among the interior volatiles, hexanal, hexanol, nonanal, 3-methylbutanoic acid, and hexanoic acid were prominent and similar in intensity in both the PTD and nonPTD chromatograms. These compounds have been previously observed in studies of ground green coffee beans.14−16,19,20 IBMP was found in both types of sample at approximately the same amount, but IPMP was detected only in the PTD sample, in agreement with the previous findings of Becker1 that IPMP was found at increased levels in PTD coffee. Further, the lack of IPMP or IBMP among the surface volatiles shows that these compounds are found only inside the beans. Our results are consistent with a hypothesis that the IPMP was produced in the 10226

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Figure 4. Expanded GC region from insect damaged sample: (a) whole beans and (b) ground beans.

Figure 5. GC analysis of a whole, male Antestia bug. Peaks without labels are unidentified.

revealed that the IBMP peak was about the same size in all the fractions whereas the IPMP/IBMP peak ratio varied from 0 in the bulk fraction to 0.08, 0.11, and 0.32 in the broken, UV fluorescent, and insect-damaged fractions, respectively. The presence of the PTD profile in the whole-bean insectdamaged fraction, along with the IPMP and IBMP presence in

the ground-bean insect-damaged fraction (and only trace IPMP in the bulk sample), is the first direct evidence observed to date for the association of antestia activity with both the surface alkane and interior pyrazine PTD profiles. Lower levels of IPMP were observed in the UV fluorescent and broken bean samples. Future experiments will focus on establishing a more 10227

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bugs and for the photo. Mr. Andrew Gerard of Global Knowledge Initiative (http://globalknowledgeinitiative.org) is acknowledged for his critical role in facilitating the communication essential to the accomplishment of this research project.

quantitative relationship between interior IPMP level and surface alkane levels. Chromatograms of Whole Desiccated Antestia Bugs. In order to test the hypothesis that the PTD surface profile, consisting mainly of tridecane, dodecane, and tetradecane, is associated with volatile compounds possibly deposited by the antestia bug, specimens of antestia were obtained from Rwanda and chromatograms of whole bug volatiles were collected. Male and female antestia were collected, kept separately, killed by freezing, and then dried before transport to the U.S. The specimens were frozen at −15 °C immediately upon arrival, and when needed, a single whole bug was transferred to a 40 mL sample vial, sealed with a septum cap, heated to 60 °C, and then sampled by headspace SPME for 5 min and subjected to chromatographic analysis by the same procedure described in the Materials and Methods section. Male and female specimens each were analyzed in triplicate and gave very similar chromatograms with the same set of volatiles, including hexanal, dodecane, 1-dodecene, tridecane, 2,6,10,14-tetramethylpentadecane, hexanoic acid, and phenol (see Figure 5). The three major compounds of the antestia chromatograms, tridecane (largest), dodecane, and tetradecane, were also detected as the three major compounds in the PTD profile of the surface volatiles of green coffee. The pheromones of antestia orbitalis have not been studied; however, in the literature, tridecane, dodecane, and tetradecane are prominent among the pheromones identified as defensive compounds in pentadomidae species related to antestia, such as Agroecus griseus,42Cosmopepla bimaculata,43 and Nezara viridula.44 In summary, the results of the analysis of surface volatile compounds on green coffee indicate a clear pattern of distinction between PTD and non-PTD coffees. The four prominent identifiable compounds found at higher levels in PTD coffee surface were dodecane, tridecane, tetradecane, and 2-ethyl-1-hexanol, while 3-methylbutanoic acid was found at decreased levels. Long-chain alkanes have not previously been associated with volatile compounds of ground green coffee.6−9,20,23 However, long-chain alkyl compounds are frequently found as constituents of plants and insects, for example, on leaf surfaces and seed surfaces, and are used as pheromones by insects. Several studies include alkanes such as tridecane, dodecane, tetradecane, and undecane on lists of defensive pheromones secreted by stink bugs related to antestia.42−44 These results support the hypotheses that PTD is associated with antestia feeding activity and that IPMP, which imparts potato taste in roasted coffee, is produced inside the coffee beans, possibly in response to the stress of antestia damage.





REFERENCES

(1) Becker, R.; Dohla, B.; Nitz, S.; Vitzthum, O. G. Identification of the “Peasy” Off-Flavour Note in Central African Coffees. In Proceedings of the 12th International Scientif ic Colloquim of Coffee, Montreaux, Switzerland, 29 June−3 July 1987; Association for Science and Information on Coffee (ASIC): Paris, France, 1987; pp 203 − 215. (2) Bouyjou, B.; Fourny, G.; Perreaux, D. Le Goût de Pomme de Terre du Café Arabica au Burundi. In Proceedings of the 15th International Scientific Colloquim on Cof fee, Montpellier, France, 6− 11 June 1993; Association for Science and Information on Coffee (ASIC): Paris, France, 1993; pp 357−369. (3) Cilas, C.; Bouyjou, B.; Decazy, B. Frequency and distribution of Antestiopsis orbitalis Westwood (Hem., Pentatomidae) in coffee plantations in Burundi: Implications for sampling techniques. J. Appl. Entomol. 1998, 122, 601−606. (4) Bouyjou, B.; Decazy, B.; Fourny, G. L’élimination du “goût de Pomme de Terre” dans le Café Arabica du Burundi. Plant., Rech., Dev. 1999, 6, 107−115. (5) Matsuura, Y.; Hosokawa, T.; Takema, F.; Serracin, M.; Tulgetske, G. M.; Miller, T. A.; Fukatsu, T. Bacterial symbionts of a devastating coffee pest, the stinkbug Antestiopsis thunbergii (Hemiptera: Pentatomidae). Appl. Environ. Microbiol. 2014, 80, 3769−3775. (6) Holscher, W.; Steinhart, H. Aroma compounds in green coffee. In Food Flavors: Generation, Analysis and Process Influence; Charalambous, G., Ed.; Developments in Food Science 37A; Elsevier Science: Amsterdam The Netherlands, 1995; pp 785−803. (7) Czerny, M.; Grosch, W. Potent odorants of raw arabica coffee. Their changes during roasting. J. Agric. Food Chem. 2000, 48, 868− 872. (8) Cantergiani, E.; Brevard, H.; Krebs, Y.; Feria-Morales, A.; Amado, R.; Yeretzian, C. Characterisation of the aroma of green Mexican coffee and identification of mouldy/earthy defect. Eur. Food Res. Technol. 2001, 212, 648−657. (9) Lee, K.-G.; Shibamoto, T. Analysis of volatile components isolated from Hawaiian green coffee beans (Coffea Arabica L.). Flavour Fragrance J. 2002, 17, 349−351. (10) Variyar, P. S.; Ahmad, R.; Bhat, A.; Niyas, Z.; Sharma, A. Flavoring components of raw monsooned arabica coffee and their changes during radiation processing. J. Agric. Food Chem. 2003, 51, 7945−7950. (11) Scheidig, C.; Czerny, M.; Schieberle, P. Changes in key odorants of raw coffee beans during storage under defined conditions. J. Agric. Food Chem. 2007, 55, 5768−5775. (12) Bicchi, C. P.; Panero, O. M.; Pellegrino, G. M.; Vanni, A. C. Characterization of roasted coffee and coffee beverages by solid phase microextractionGas chromatography and principal component analysis. J. Agric. Food Chem. 1997, 45, 4680−4686. (13) Roberts, D. D.; Pollien, P.; Milo, C. Solid-phase microextraction method development for headspace analysis of volatile flavor compounds. J. Agric. Food Chem. 2000, 48, 2430−2437. (14) Rocha, S.; Maeztu, L.; Barros, A.; Cid, C.; Coimbra, M. A. Screening and distinction of coffee brews based on headspace solid phase microextraction/gas chromatography/principal component analysis. J. Sci. Food Agric. 2003, 84, 43−51. (15) Mondello, L.; Costa, R.; Tranchida, P. Q.; Dugo, P.; Lo Presti, M.; Festa, S.; Fazio, A.; Dugo, G. Reliable characterization of coffee bean aroma profiles by automated headspace solid phase microextraction−gas chromatography−mass spectrometry with the support of a dual-filter mass spectra library. J. Sep. Sci. 2005, 28, 1101−1109. (16) Zambonin, C. G.; Balest, L.; De Benedetto, G. E.; Palmisano, F. Solid-phase microextraction−gas chromatography mass spectrometry and multivariate analysis for the characterization of roasted coffees. Talanta 2005, 66, 261−265.

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Funding

E.E.M. and A.G.O. acknowledge research support from Rogers Family Company, the Peach Foundation, and Seattle University Center for Environmental Justice and Sustainability. This research was partially supported by the Seattle University Chemistry Department. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS We thank the Rogers Family Company for characterized green coffee samples and Dr. Mario Serracin for collecting the antestia 10228

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(38) Whittaker, E. T. On a new method of graduation. P. Edinburgh Math. Soc. 1922, 41, 63−75. (39) Kaiser, H. F. The varimax criterion for analytic rotation in factor analysis. Psychometrika 1958, 23, 187−200. (40) Osawa, C. C.; Goncalves, L. A. G.; Da Silva, M. A. A. P. Odor significance of the volatiles formed during deep-frying with palm olein. J. Am. Oil Chem. Soc. 2013, 90, 183−189. (41) James, D. G.; Price, T. S. Field-testing of methyl salicylate for recruitment and retention of beneficial insects in grapes and hops. J. Chem. Ecol. 2004, 30, 1613−28. (42) Favaro, C. F.; Santos, T. B.; Zarbin, P. H. G. Defensive compounds and male-produced sex pheromone of the stink bug Agroecus griseus. J. Chem. Ecol. 2012, 38, 1124−1132. (43) Krall, B. S.; Bartelt, R. J.; Lewis, C. J.; Whitman, D. W. Chemical defense in the stink bug Cosmopepla bimaculata. J. Chem. Ecol. 1999, 25, 2477−2494. (44) Borges, M.; Jepson, P. C.; Howse, P. E. Long-range mate location and close-range courtship behavior of the green stink bug, Nezara viridula, and its mediation by sex pheromones. Entomol. Exp. Appl. 1987, 44, 205−212.

(17) Lopez-Galilea, I.; Fournier, N.; Cid, C.; Guichard, E. Changes in headspace volatile concentrations of coffee brews caused by the roasting process and brewing procedure. J. Agric. Food Chem. 2006, 54, 8560−8566. (18) Baggenstoss, J.; Poisson, L.; Kaegi, R.; Perren, R.; Escher, F. Coffee roasting and aroma formation: Application of different timetemperature conditions. J. Agric. Food Chem. 2008, 56, 5836−5846. (19) Toci, A. T.; Farah, A. Volatile compounds as potential defective coffee beans’ markers. Food Chem. 2008, 108, 1133−1141. (20) Gonzalez-Rios, O.; Suarez-Quiroz, M. L.; Boulanger, R.; Barel, M.; Guyot, B.; Guiraud, J-.P.; Schorr-Galindo, S. Impact of “ecological” post-harvest processing on the volatile fraction of coffee beans. I. Green coffee. J. Food Compos. Anal. 2007, 20, 289−296. (21) Agresti, P. D. C. M.; Franca, A. S.; Oliveira, L. S.; Augusti, R. Discrimination between defective and non-defective Brazilian coffee beans by their volatile profile. Food Chem. 2008, 106, 787−796. (22) Ribeiro, J. S.; Teofilo, R. F.; Salva, T.; Augusto, F.; Ferreira, M. M. C. Exploratory and discriminative studies of commercial processed Brazilian coffees with different degrees of roasting and decaffeinated. Braz. J. Food Technol. 2013, 16, 198−206. (23) Bertrand, B.; Boulanger, R.; Dussert, S.; Ribeyre, F.; Berthiot, L.; Descroix, F.; Joet, T. Climatic factors directly impact the volatile organic compound fingerprint in green Arabica coffee bean as well as coffee beverage quality. Food Chem. 2012, 135, 2575−2583. (24) Coffee Research Symposium Tentative Progam. http://www. naeb.gov.rw/fileadmin/documents/AGENDA.pdf (accessed Sep 12, 2014). (25) Global Knowledge Initiative: International Convening. http:// www.globalknowledgeinitiative.org/news/eliminate-coffee-potatotaste-defect-east-africa.html (accessed Sep 12, 2014). (26) Van den Dool, H.; Kratz, P. D. A generalization of the retention index system including linear temperature programmed gas−liquid partition chromatography. J. Chromatogr. 1963, 11, 463−471. (27) Martos, P. A.; Saraullo, A.; Pawliszyn, J. Estimation of air/ coating distribution coefficients for solid phase microextraction using retention indexes from linear temperature-programmed capillary gas chromatography: Application to the sampling and analysis of total petroleum hydrocarbons in air. Anal. Chem. 1997, 69, 402−408. (28) Goodner, K. L. Practical retention index models of OV-101, DB1, DB-5, and DB-Wax for flavor and fragrance compounds. LWT Food Sci. Technol. 2008, 41, 951−958. (29) Nielsen, N-P.V.; Carstensen, J. M.; Smedsgaard, J. Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimized warping. J. Chromatogr. A 1998, 805, 17−35. (30) Pierce, K.; Hope, J. L.; Johnson, K. J.; Wright, B. W.; Synovec, R. E. Classification of gasoline data obtained by gas chromatography using a piecewise alignment algorithm combined with feature selection and principal component analysis. J. Chromatogr. A 2005, 1096, 101− 110. (31) Indahl, U. G.; Sahni, N. S.; Kirkus, B.; Naes, T. Multivariate strategies for classification based on NIR-spectra with application to mayonnaise. Chemometr. Intell. Lab. 1999, 49, 19−31. (32) PLS Toolbox, V 7.5.2. Software for chemometric multivariate analysis. Eigenvector Research, Inc: Wenatchee, WA, 2014. (33) Matlab, V R2013b. Software for numerical computation, visualization, and programming. Mathworks, Inc: Natick, MA, 2013. (34) Brereton, R. G. Chapter 4: Pattern Recognition. In Chemometrics: Data Analysis for the Laboratory and Chemical Plant; Wiley: Chichester, England, 2003; pp 183−270. (35) Tomasi, G.; van den Berg, F.; Andersson, C. Correlation optimized warping and dynamic time warping as preprocessing methods for chromatographic data. J. Chemometr. 2004, 18, 231−241. (36) Skov, T.; van den Berg, F.; Tomasi, G.; Bro, R. Automated alignment of chromatographic data. J. Chemometr. 2006, 20, 484−497. (37) Eilers, P.H.C.; Boelens, H. F. M. Baseline correction with asymmetric least squares smoothing. October 21, 2005, Amazon Web Services. http://zanran_storage.s3.amazonaws.com/www.science.uva. nl/ContentPages/443199618.pdf (accessed Jul 10, 2014). 10229

dx.doi.org/10.1021/jf5034416 | J. Agric. Food Chem. 2014, 62, 10222−10229