1
Exploring the impact of post-harvest processing on the microbiota and metabolite 1
profiles during a case of green coffee bean production 2
3
Florac De Bruyna†, Sophia Jiyuan Zhanga†, Vasileios Pothakosa†, Julio Torresb, Charles 4
Lambotb, Alice V. Moronic, Michael Callananc, Wilbert Sybesmac, Stefan Weckxa, Luc De 5
Vuysta 6
7a Research Group of Industrial Microbiology and Food Biotechnology, Faculty of Sciences 8
and Bioengineering Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, 9
Belgium 10b Nestlé R&D Centre Tours,101 Avenue Gustave Eiffel, B.P. 49716, 37097 Tours Cedex 2, 11
France 12c Nestlé Research Centre, Route du Jorat 57, Vers-chez-les-Blancs, CH-1000 Lausanne 26, 13
Switzerland 14†Equal contribution 15
16
Short title: Microbiota and metabolites during green coffee processing 17
18
Keywords: coffee bean fermentation; wet processing; dry processing; high-throughput 19
sequencing; metabolite target analysis; UPLC-MS/MS; green coffee beans 20
21
Corresponding author: Prof. Dr. ir. Luc De Vuyst 22
Telephone: +32 2 629 3245 23
Fax: +32 2 629 2720 24
E-mail: [email protected] 25
AEM Accepted Manuscript Posted Online 28 October 2016Appl. Environ. Microbiol. doi:10.1128/AEM.02398-16Copyright © 2016, American Society for Microbiology. All Rights Reserved.
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ABSTRACT 26
The post-harvest treatment and processing of fresh coffee cherries can impact the quality of 27
the unroasted green coffee beans. In the present case study, freshly harvested Arabica coffee 28
cherries were processed through two different wet and dry methods, to monitor differences in 29
the microbial community structure, as well as substrate and metabolite profiles. The changes 30
were followed throughout the entire post-harvest processing chain, from harvest to drying, by 31
implementing up-to-date techniques, encompassing multiple-step metagenomic DNA 32
extraction, high-throughput sequencing and multiphasic metabolite target analysis. During 33
wet processing, a cohort of lactic acid bacteria (i.e., Leuconostoc, Lactococcus, Lactobacillus) 34
was the most commonly identified microbial group, along with enterobacteria and yeasts 35
(Pichia and Starmerella). Several of the metabolites associated with lactic acid bacterial 36
metabolism (e.g., lactic acid, acetic acid, and mannitol) produced in the mucilage were also 37
found in the endosperm. During dry processing, acetic acid bacteria (i.e., Acetobacter, 38
Gluconobacter) were most abundant, along with non-Pichia yeasts (Candida, and 39
Saccharomycopsis). Accumulation of associated metabolites (e.g., gluconic acid and sugar 40
alcohols) took place in the drying outer layers of the coffee cherries. Consequently, both wet 41
and dry processing significantly influenced the microbial community structures and hence the 42
composition of the final green coffee beans. This systematic approach dissecting the coffee 43
ecosystem contributes to a deeper understanding of coffee processing and could constitute a 44
state-of-the-art framework for the further analysis and subsequent control of this complex 45
biotechnological process. 46
47
IMPORTANCE 48
Coffee production is a long process starting with the harvest of coffee cherries and the on-49
farm drying of their beans. In a later stage, the dried green coffee beans are roasted and 50
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ground in order to brew a cup of coffee. The on-farm, post-harvest processing method applied 51
can impact the quality of the green coffee beans. In the present case study, freshly harvested 52
Arabica coffee cherries were processed through wet and dry processing, which are mainly 53
encountered worldwide in four distinct variations. The microorganisms present and the 54
chemical profiles of the coffee beans were analyzed throughout the entire post-harvest 55
processing chain. The implemented, up-to-date techniques facilitated the investigation of 56
differences related to the method applied. For instance, different microbial groups were 57
associated with wet and dry processing. Additionally, accumulation of metabolites associated 58
with the respective microorganisms took place on the final green coffee beans. 59
60
INTRODUCTION 61
Post-harvest processing of coffee cherries yields green coffee beans, which need to be roasted 62
and ground to obtain the desired characteristic coffee aroma and taste (1). These processes are 63
the main drivers of the consumers’ perception of coffee beverage quality. The cherries and 64
beans are the fruits and seeds of the coffee plant (Coffea sp., family Rubiaceae), which is 65
cultivated in plantations mainly in the equatorial zone. 66
The on-farm post-harvest coffee processing is essential to ensure high coffee cup quality (2) 67
and constitutes a chain of interlinked phases mainly aiming at the removal of the mucilage of 68
the cherries as well as the drying of the beans until a low moisture content of 10-12% (m/m). 69
The final quality of the green coffee beans is thus dependent on the agricultural and farm 70
practices applied, which in turn depend on the coffee plant cultivar, geography, weather 71
conditions, and infrastructure available (3). Even when all these factors are fixed within one 72
type of post-harvest processing, a multitude of variations exists, as a standardized pipeline for 73
the production of green coffee beans is lacking (4). After harvesting of the cherries, the outer 74
layers of the coffee drupe (i.e., hull and pulp) are easily removed, while the mucilage, 75
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parchment, and silverskin are firmly attached to the beans. Different methods are employed to 76
eliminate all these layers, commonly referred to as wet and dry coffee processing. During wet 77
processing, the hull and pulp of the cherries are mechanically stripped from the beans 78
(depulping). The inside of the cherries thus gets exposed to environmental contamination and 79
the mucilage is subsequently removed by spontaneous microbial fermentation in a water tank 80
for 6-24 h (5-15). This is followed by washing of the fermented beans and sun-drying. Dry 81
processing involves direct drying of the whole cherries on cement patios or aerated trays for 82
14-30 days, during which spontaneous fermentation occurs (8, 16-18). Both wet and dry 83
processed coffees are finally subjected to dehulling to obtain the green coffee beans (4). In all 84
processes, the spontaneous fermentation step is highly variable, and hence needs to be further 85
investigated to understand its contribution to the final coffee cup quality. 86
Microorganisms are ubiquitous during the different stages of post-harvest coffee processing 87
(2, 19-22). Enterobacteriaceae and other Gram-negative bacteria including acetic acid 88
bacteria (AAB), bacilli, lactic acid bacteria (LAB), yeasts, and filamentous fungi have been 89
found through culture-dependent and -independent methods during coffee fermentation 90
processes (5-18, 22). The occurrence and activity of specific microbial groups can be 91
associated with diverse functionalities during processing, for instance the degradation of pulp 92
pectin and the depletion of mucilage carbohydrates (5-7, 12, 23). Their metabolite production 93
capacities can have beneficial and/or detrimental effects on the sensory characteristics of the 94
green coffee beans and final coffee cup quality (3, 24-26). However, it is not yet clear to what 95
extent microorganisms are essential for the production of high-quality coffee (2). Recently, 96
the ability of naturally occurring yeasts to act as selected starter cultures and to influence the 97
in-cup attributes of coffee has been shown during semi-dry processing (14-15, 27). Also, the 98
beans (endosperms) remain metabolically active during coffee processing and are impacted 99
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by the processing method implemented, thereby affecting the final coffee cup quality (2, 28-100
33). 101
Despite the complexity of coffee processing and the numerous factors contributing to the 102
quality traits of the green coffee beans, all studies conducted so far only targeted specific 103
steps of the processing (2, 19, 21). Their primary goal has been the identification of the 104
microbiota associated with the fermentation part of the processing and the chemical profiling 105
of the green coffee beans and/or bean germination process. However, no study has been 106
performed to unravel the evolution of the microbial species and concomitant substrate 107
degradation and metabolite production or the chemical profiles of distinct cherry layers 108
throughout the coffee processing chain. 109
This study aimed at a systematic approach for monitoring the evolution of the 110
microorganisms, substrates, and metabolites during an entire chain of both wet and dry coffee 111
processing carried out under various conditions in Ecuador. These conditions were chosen to 112
represent a more and less favorable post-harvest practice to gain insight into the potential 113
correlation of specific microorganisms with a certain processing. High-throughput sequencing 114
of metagenomic DNA, targeting both the bacterial and fungal diversity, and robust metabolite 115
target analysis of a broad range of chemical compounds in the coffee pulp, mucilage, and 116
endosperm were undertaken. 117
118
MATERIALS AND METHODS 119
Coffee cultivar and coffee processing experiments. The coffee cultivar used throughout this 120
study was C. arabica L. var. Typica. Four coffee processing experiments were performed at a 121
coffee plantation near Nanegal (Nestlé Ecuador; latitude and longitude coordinates, 122
0°11'25.8"N 78°40'41.4"W; altitude, 1329 m; 123
https://www.google.be/maps/place/0%C2%B011'25.8%22N+78%C2%B040'41.4%22W/@0.124
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190509,-78.678155,13z/data=!4m2!3m1!1s0x0:0x0) in May-July 2014 (Fig. 1). 125
Approximately 160 kg of healthy mature cherries were selectively handpicked and served as a 126
pool of common starting material for all experiments. Two parallel wet processing 127
experiments were performed, which differed in fermentation time. Initially, 100 kg of cherries 128
were depulped mechanically (UCBE 500, Penagos, Bucaramanga, Colombia). The depulped 129
beans were then allowed to ferment spontaneously in clean plastic containers (50 cm x 30 cm 130
x 20 cm). A first part of the depulped beans was left to ferment for 16 h and a second part for 131
36 h. In this way, half of the depulped beans underwent a standard wet process (SW), while 132
the other half was subjected to an extended fermentation wet process (EW). The fermented 133
beans were manually washed with clean water and soaked for 24 h. Finally, the soaked beans 134
were dispersed onto cement patios for drying until they reached a moisture content of 135
approximately 12% (m/m). Simultaneously with the SW and EW experiments, two dry 136
processing experiments were performed. Approximately 30 kg of fresh cherries (originating 137
from the same aforementioned pool of harvested cherries) were equally divided between a 138
standard dry process (SD), in which the cherries were spread in a monolayer on a covered 139
aerated drying tray and stirred daily, and a heaped dry process (HD) wherein the cherries were 140
heaped on the drying tray (4-6 cherries deep) without stirring during the first six days. 141
Afterwards, the HD cherries were stirred daily as well. The cherries underwent sun-drying 142
until a moisture content of approximately 12% (m/m) was reached. The moisture content was 143
evaluated by means of a mini GAC plus moisture tester (Dickey-john, Auburn, IL). 144
Sampling during coffee processing. Coffee processing samples (i.e., freshly harvested 145
cherries, depulped beans, fermented beans, soaked beans, drying beans, and dry processed 146
cherries) were collected at specific time points and immediately stored at -20°C until further 147
analysis. A uniform code was assigned to each processing sample, containing information on 148
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the type of variation [standard (S), extended (E), heaped (H)], processing method [wet (W), 149
dry (D)], and sampling point (1-10) (Fig. 1). 150
The pH was measured by means of pH-fix strips 0-14 (Macherey Nagel, Düren, Germany) at 151
the end of the fermentation steps of SW and EW. The moisture content of all cherry and bean 152
samples was determined by mass difference through drying in an oven at 100°C for 24 h. 153
Microbial community analysis. (i) Total DNA extraction. An innovative approach of 154
metagenomic DNA extraction was performed. Total DNA was extracted from thawed coffee 155
processing samples by firstly detaching microbial cells present on the cherries or beans via 156
manual inversion (2 x 2 min with a 15 min pause) in 25 mL of saline solution (8.5 g/L of 157
NaCl; Merck, Darmstadt, Germany). Depending on the type of sample, six cherries or 20-50 158
beans were used for total microbial DNA extraction. After manual inversion, the resulting 159
suspensions were filtered through a 20 µm average pore-size 50 mL Steriflip (Merck) to 160
eliminate coarse impurities. The filtrates were pelletized by centrifugation (14,000 x g, 10 161
min). The pellets were washed with 1 mL of TES buffer [50 mM Tris-base, 1 mM ethylene 162
diamine tetraacetic acid (EDTA), 6.7% (m/v) sucrose; pH 8.0]. Subsequently, several 163
consecutive enzymatic steps were applied to cover all microbial communities potentially 164
present. To obtain fungal cell lysis, the pellets were resuspended in 300 µL of 50 mM 165
phosphate buffer (pH 6.0) and incubated with chitinase (500 mU/mL; Sigma-Aldrich, St. 166
Louis, MO) at 37°C for 2 h, followed by centrifugation at 8,000 x g for 10 min. The pellets 167
were then resuspended in 600 µL of sorbitol buffer [21% (m/v) sorbitol (VWR International, 168
Darmstadt, Germany), 50 mM Tris-base; pH 7.5] containing a cocktail of 0.2 U lyticase 169
(Sigma-Aldrich), 200 U Zymolyase (G-Biosciences, St. Louis, MO), and 1.23 µL of 2-170
mercaptoethanol (Merck) and the mixtures were incubated at 30°C for 1 h. Following this 171
initial fungal cell lysis treatment, the suspensions were washed with sorbitol buffer. Then, 172
bacterial cells were lysed by adding 300 µL of STET buffer [8% (m/v) sucrose, 50 mM Tris-173
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base, 50 mM EDTA, 5% (m/v) Triton-X100; pH 8.0] and incubating the suspensions with a 174
cocktail of 0.1 U mutanolysin (Sigma-Aldrich) and 8 mg of lysozyme (Merck) at 37°C for 1 h. 175
Subsequently, 40 µL of a 20% (m/m) sodium-dodecyl-sulphate solution and 0.1 g of sterile 176
glass beads were added before the suspensions were vortexed intensively for 1 min. Protein 177
digestion was achieved by incubation of these suspensions with 0.5 mg of proteinase K 178
(Merck) at 56°C for 1 h. Thereupon, 100 µL of a 5 M NaCl solution were added to the 179
suspensions and incubated at 65°C for 2 min, after which 80 µL of a 10% (m/m) 180
cetyltrimethyl ammonium bromide solution were added and the mixtures were incubated at 181
65°C for 10 min. Following this, 600 µL of chloroform:phenol:isoamyl alcohol solution 182
(49.5:49.5:1.0) were added and the lysates were shaken vigorously for 5 min. Finally, the 183
solutions were centrifuged at 13,000 x g for 5 min in 2 mL vials (Phase Lock Gel Heavy, 5 184
Prime, Hilden, Germany). The DNA contained in the supernatants was purified by binding on 185
and elution from a cellulose acetate membrane, using the DNeasy Blood & Tissue Kit 186
(Qiagen, Venlo, The Netherlands) according to the manufacturer’s instructions. DNA 187
concentrations were measured with a NanoDrop ND-2000 (Thermo Scientific, Wilmington, 188
DE). 189
(ii) Amplification of group-specific loci for high-throughput sequencing (HTS). 190
Group-specific loci of both bacterial and fungal DNA were amplified through the polymerase 191
chain reaction (PCR). The V4 hypervariable region of the bacterial 16S rRNA gene was 192
amplified using the primers F515 193
(5’TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGTGCC 194
AGCMGCCGCGGTAA3’) and R806 (5’GTCTCGTGGGCTCGGAGATGTGTATA 195
AGAGACAGGGACTACHVGGGTWTCTAAT3’) with an Illumina platform-specific 5’-tag 196
(underlined) (34). The PCR assay conditions consisted of an initial step at 94°C for 3 min, 197
followed by 35 cycles at 94°C for 45 s, 50°C for 60 s, and 72°C for 90 s. A final extension 198
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was performed at 72°C for 10 min. The fungal ITS1 region was amplified using the primers 199
ITS1 200
(5’TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGTCCGTAGGTGAACCTTGCGG201
3’) and ITS2 (5’GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGC 202
TGCGTTCTTCATCGATGC3’) with an Illumina platform-specific 5’-tag (underlined) (35). 203
The PCR assay conditions consisted of an initial step at 95°C for 2 min, followed by 40 204
cycles of denaturation at 95°C for 30 s, annealing at 50°C for 30 s, and extension at 72°C for 205
60 s. A final extension was performed at 72 °C for 5 min. Each PCR assay mixture contained 206
6 µL of 10x PCR buffer (Sigma-Aldrich), 2.5 µL of 0.1 mg/mL bovine serum albumin 207
(Sigma-Aldrich), 0.2 mM deoxynucleotide triphosphates mixture (Sigma-Aldrich), 1.25 U 208
Taq DNA polymerase (Roche), 10-100 ng of DNA template, and 5 µM of each primer 209
(Integrated DNA Technologies, Leuven, Belgium). The PCR amplicons were purified using 210
the Wizard SV Gel and PCR Clean up system (Promega, Madison, WI) and size-selected 211
using Agencourt AMPure XP PCR Purification magnetic beads (Beckman Coulter, Brea, CA), 212
following the manufacturers’ instructions. The amplicon size distribution was checked 213
qualitatively by means of a 2100 Bioanalyzer instrument (Agilent Technologies, Santa Clara, 214
CA). Finally, double-stranded DNA concentrations were quantified using the fluorometric 215
Qubit 2.0 quantitation assay (Thermo Fisher, Waltham, MA). 216
(iii) HTS of V4 and ITS1 amplicons. A novel approach was followed for HTS. The 217
bacterial and fungal DNA template libraries of each sample were combined and sequenced 218
under the same index. Briefly, bacterial V4 and fungal ITS1 amplicons originating from the 219
same sample were pooled equimolarly, barcoded with the same index, and diluted if 220
necessary before sequencing. Every pooled sample had a total volume of 30 µL. All samples 221
were sequenced using the Illumina MiSeq platform (Illumina, San Diego, CA) in a 222
commercial facility (BRIGHTcore, Jette, Belgium). Two Fastq files were obtained for each 223
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sample, encompassing all forward and reverse reads, both deriving from the bacterial and 224
fungal amplicons. 225
(iv) Bioinformatics analysis. The forward and reverse Fastq files of each sample, 226
containing the sequences of the bacterial V4 and fungal ITS1 fragments, were first split by 227
means of an in house Perl script into two files. Based on the first six nucleotides of the reads 228
corresponding to the respective primers, a first Fastq file contained all the bacterial V4 229
sequences and a second Fastq file comprised the fungal ITS1 sequences. Both the bacterial 230
and fungal diversities were processed through Mothur software v1.36.1, following a workflow 231
described before (36), with some modifications as outlined below. 232
For the V4 sequences (4,440,225 paired reads), removal of primers, generation of contigs, and 233
subsequent quality screening were performed. The unique sequences were aligned against the 234
bacterial 16S rRNA SILVA database and then clustered into groups, allowing a difference of 235
maximum two mismatches. A chimera check was carried out by means of the Uchime 236
algorithm (37). After the removal of chimeric sequences, the taxonomic allocation and 237
generation of operating taxonomical units (OTUs) were performed at a level of 97% identity. 238
For the fungal ITS1 sequences (2,073,445 paired reads), the forward and reverse reads were 239
first trimmed using the Cutadapt software (release 1.9.dev6; 38), due to the short length of the 240
targeted ITS1 region in some cases, which resulted in adapter read-throughs (39). Briefly, the 241
sequenced adapters and the overhangs at the 3’ end of the forward and reverse reads were 242
trimmed off. The trimmed Fastq files were then processed through Mothur for the generation 243
of contigs and quality screening of the paired reads. The unique sequences were classified 244
taxonomically through comparison with the fungal UNITE_ITS1 database (v6_sh_99), as 245
described before (40), and merged into OTUs when the taxonomic allocation was identical. 246
Finally, the representative unique sequences corresponding to the respective bacterial or 247
fungal OTUs were aligned with reference 16S rRNA gene and ITS1 sequences using the 248
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BlastN algorithm (41). When the sequence identity was higher than 99% compared to well-249
described and curated sequences of type and reference strains, an assignment to species level 250
was performed too. In all cases, the ranking of identified taxa presented below is based on a 251
decreasing order of relative abundance.252
All generated sequences were submitted to the European Nucleotide Archive of the European 253
Bioinformatics Institute (ENA/EBI) under the accession number PRJEB14106 and are 254
available at http://www.ebi.ac.uk/ena/data/view/PRJEB14106. 255
Metabolite target analysis. (i) Preparation of extracts from mucilage, pulp, and 256
endosperm. Due to the complexity of wet and dry processing, all coffee cherry layers and 257
endosperms were collected and analysed separately to monitor the shifts of the metabolite 258
profile along the post-harvest processing chain. Therefore, each coffee processing sample was 259
subjected to a standard preparation protocol prior to metabolite extraction. In the case of wet 260
processed samples, the pulp was first separated from the beans, then the mucilage was scraped 261
off, and finally the parchment was detached manually. In the case of dry processed samples, 262
all dried outer layers were removed manually. In all cases, representative samples (20 g) of 263
cherry layers or endosperm were first frozen in liquid nitrogen (Air Liquide, Louvain-la-264
Neuve, Belgium) and ground into fine powders with a malt miller (Corona Mill, Bogotá, 265
Colombia). 266
Three types of extraction were used to analyze the metabolites targeted in the final samples. 267
Water extracts were prepared by submerging 0.1-0.5 g of sample in 5 g of ultrapure water 268
(Milli-Q; Merck Millipore, Billerica, MA) at room temperature for 30 min. Methanol extracts 269
were prepared by treating 0.1-0.5 g of sample in 5 g of 40% (v/v) methanol (Sigma-Aldrich) 270
at 40°C for 20 min. Acidic extracts were prepared by adding 0.1-0.5 g of sample to 5 g of 271
0.01 N HCl and ultra-sonicating (Ultrason 2510; Branson, Danbury, CT) at room temperature 272
for 20 min. All samples were microcentrifuged (14,000 rpm, 10 min), deproteinized with 273
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acetonitrile (Sigma-Aldrich) at a 1:3 ratio, and filtered through 0.2 µm pore-size filters 274
(Whatman filters; GE Healthcare Life Sciences, Little Chalfont, Buckinghamshire, UK) prior 275
to injection. All samples were both prepared and analyzed in triplicate. 276
(ii) Determination of free carbohydrates and sugar alcohols. The concentrations of 277
free carbohydrates (fructose, galactose, glucose, and sucrose) were determined by high-278
performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-279
PAD), using an ICS 3000 chromatograph equipped with an AS-autosampler, a CarboPac PA-280
100 column, and an ED-40 PAD detector (Dionex, Sunnyvale, CA). The mobile phases 281
consisted of ultrapure water (eluent A), 100 mM NaOH (eluent B; J.T. Baker, Deventer, The 282
Netherlands), and 900 mM NaOH (eluent C; J.T. Baker), with a constant flow rate of 1.0 283
mL/min and the following gradient: 0.0-15.0 min, 95% A, 5% B, and 0% C; 15.5-22.0 min, 284
0% A, 0% B, and 100% C; and 22.5-30.0 min, 95% A, 5% B, and 0% C. The identification of 285
the targeted compounds was achieved by injecting pure standards (Sigma-Aldrich). 286
The concentrations of sugar alcohols (arabitol, erythritol, galactitol, glycerol, mannitol, myo-287
inositol, sorbitol, and xylitol) were determined by HPAEC-PAD, using the same 288
chromatograph as mentioned above, but equipped with a CarboPac MA-1 column (Dionex). 289
The mobile phases consisted of ultrapure water (eluent A) and 730 mM NaOH (eluent B; J.T. 290
Baker), with a constant flow rate of 1.0 mL/min and the following gradient: 0.0-15.0 min, 291
90% A and 10% B; 40.0-55.0 min, 0% A and 100% B; and 55.5-65.0 min, 90% A and 10% B. 292
The identification of the targeted compounds was achieved by injecting pure standards 293
(Sigma-Aldrich). 294
Quantifications of all compounds mentioned above were carried out on the water extracts by 295
external calibration, including rhamnose as an IS. 296
(iii) Determination of short-chain fatty acids and ethanol. Short-chain fatty acids 297
(SCFAs, namely acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, 298
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isovaleric acid, and hexanoic acid) and ethanol were quantified through gas chromatography 299
with flame ionization detection (GC-FID), using a Focus GC apparatus equipped with an AS 300
3000 autosampler and a flame ionization detector (Interscience, Breda, The Netherlands) and 301
a Stabilwax-DA column (Restek, Bellefonte, PA). Samples (1 µL) were injected into the 302
column directly, applying a split ratio of 1:20. The injector temperature was set at 270°C. The 303
oven temperature was programmed as follows: firstly 40°C for 5 min, followed by a 304
temperature increase to 225°C at a rate of 10°C/min, and then held at 225°C for 5 min. The 305
detector temperature was set at 250°C. Helium (Air Liquide) was used as carrier gas at a 306
constant flow rate of 1.0 mL/min and nitrogen gas (Air Liquide) was used as make-up gas. 307
The identification of the volatiles was achieved by injecting pure standards (Merck). 308
Quantification was carried out on the water extracts by external calibration, including 1-309
butanol (Merck) as an IS. 310
(iv) Determination of organic acids and coffee bean-specific compounds. Organic 311
acids (citric acid, fumaric acid, gluconic acid, glucuronic acid, isocitric acid, lactic acid, malic 312
acid, oxalic acid, quinic acid, and succinic acid) and coffee bean-specific compounds 313
[caffeine, caffeic acid, six chlorogenic acid (CGA) isomers (3-, 4-, and 5-caffeoylquinic acids 314
(CQAs), and 3,4-, 3,5-, and 4,5-diCQAs), and trigonelline] were determined by ultra-315
performance liquid chromatography coupled to mass spectrometry (UPLC-MS), using an 316
AcquityTM system equipped with a HSS T3 column (150 mm x 2.1 mm; internal diameter, 1.8 317
µm) and a TQ tandem mass spectrometer with a ZSpray™ electrospray ionization source 318
operating both in the negative (organic acids and CGAs) and positive (other coffee bean-319
specific compounds) ion modes (Waters, Milford, MA). The following eluents were used: 320
ultrapure water with 0.2% (v/v) formic acid (eluent A; Fluka, St. Louis, MO) and a mixture of 321
methanol (Sigma-Aldrich) and water (950:50) with 0.2% (v/v) formic acid (eluent B; Fluka). 322
In the case of organic acids and coffee-specific compounds (except for CGAs), the gradient 323
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elution was as follows: 0.0-1.5 min, isocratic 10% B; 1.5-3.0 min, linear from 10 to 90% B; 324
3.0-4.0 min, isocratic 90% B; 4.0-4.1 min, linear from 90 to 10% B; and 4.1-6.0 min, isocratic 325
10% B. In the case of CGAs, this was: 0.0-1.5 min, isocratic 10% B; 1.5-12.0 min, linear 326
from 10 to 20% B; 12.0-20.0 min, linear from 20 to 68% B; 20.0-20.2 min, linear from 68 to 327
100% B; 20.2-22.0 min, isocratic 100% B; 22.0-22.2 min, linear from 100 to 10% B; and 328
22.2-25.0 min, isocratic 10% B. The flow rate was kept constant at 0.3 mL/min. The 329
identification of the targeted compounds was achieved by injecting pure standards (Sigma-330
Aldrich; Biopurify, Chengdu, China for the CGAs). Quantification was carried out on the 331
methanol or acidic extracts by external calibration for organic acids and CGAs and other 332
coffee bean-specific compounds, respectively. The selected reaction monitoring method was 333
optimized by IntelliStart (Table S1). 334
335
Statistical analysis. The microbial community structure data obtained through HTS were 336
exported in BIOM format files and imported in the R environment for statistical analysis 337
(www.R-project.org). The OTU tables of bacteria and fungi were pre-processed (i.e., removal 338
of global singletons, alpha-diversity, and rarefaction) by implementing the vegan package 339
(http://CRAN.R-project.org/package=vegan). The phyloseq package was used to construct 340
principal coordinates analysis (PCoA) plots based on Bray-Curtis dissimilarities (42). 341
Additionally, a Spearman's rank-order correlation matrix was employed to evaluate the 342
dependence among genera. The co-occurrence and co-exclusion relationships between all 343
microbial genera were only considered when the correlation was significant at a confidence 344
level of 99%. The quantitative data from the metabolite target analyses were subjected to 345
principal component analysis (PCA) to identify patterns associated with the coffee processing 346
method applied. One-way analysis of variance (ANOVA) was conducted for the 347
determination of differences in metabolite concentrations between samples, and Duncan’s test 348
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was employed. A probability level of 0.05 was considered to be significant for all statistical 349
procedures and only those data are reported below. All statistical analyses and tests performed 350
were executed through the SPSS v.20 package (IBM, Chicago, IL). 351
352
RESULTS 353
Microbial community structures. The average number of raw V4 and ITS1 sequences per 354
sample reached approximately 200,000 and 94,000 sequences, respectively. The estimated 355
sequencing coverage ranged between 98.2 and 99.7%. 356
(i) Freshly harvested coffee cherries. The initial surface contamination of the freshly 357
harvested coffee cherries (CB sample) encompassed bacterial OTUs belonging to the 358
Enterobacteriaceae (especially Klebsiella pneumoniae), AAB (Gluconobacter spp.), and soil-359
associated bacteria such as Dyella kyungheensis (Fig. 2A and 3). Only a small portion of the 360
reads was attributed to the LAB species Leuconostoc mesenteroides/pseudomesenteroides. 361
Concerning the fungal diversity, Pichia kluyveri/fermentans was highly abundant (Fig. 2B 362
and 3). Based on the PCoA performed on all microbial community structures, the CB sample 363
clearly differentiated from all other coffee processing samples (Fig. 4). 364
(ii) Wet coffee processing. Upon depulping (W1), the OTU Leuconostoc increased in 365
relative abundance and it was the most prevalent bacterial taxon throughout the entire wet 366
processing, especially during fermentation (SW2 and EW2; Fig. 2A and 3). The most 367
prevalent fungal taxon was Pichia, whereas the OTUs Starmerella and Candida increased in 368
relative abundances mainly during the fermentation and soaking stage (Fig. 2B and 3). Over 369
the course of sun-drying (SW4-5), the arrangement of the OTUs stayed nearly unvaried. 370
Overall, all wet processed samples grouped closer on the PCoA bi-plots, depicting similarities 371
in their microbial community structures that mainly encompassed LAB and only a limited 372
fungal diversity (Fig. 4). However, certain differences in the evolution of the microbial 373
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communities occurred. While Leuconostoc spp., Lactococcus, and Weissella were 374
predominant during fermentation in SW, a higher incidence of lactobacilli was found from 375
fermentation on in EW. This indicated a shift toward more acid-tolerant LAB communities, 376
which corresponded to a decrease of the pH of the fermenting mass from 4.5 (after 16 h of 377
fermentation) to 4.0 (after 36 h of fermentation). LAB-associated OTUs decreased during 378
drying. Further, the abundance of enterobacterial taxa was lower in EW than in SW, 379
especially after fermentation and soaking but increased during drying. Also, a rise in the 380
relative abundance of soil-associated OTUs Acinetobacter, Janthinobacterium, and 381
Cellulosimicrobium followed the decrease in moisture content (Fig. S1 and 3). 382
(iii) Dry coffee processing. During dry processing (both SD and HD), the LAB 383
species L. mesenteroides/pseudomesenteroides and AAB taxa (Acetobacter and 384
Gluconobacter) were present in high relative abundances (Fig. 2A and 3). The OTU 385
Enterobacteriaceae decreased compared to the CB and wet processed samples. Other 386
bacterial OTUs appeared sporadically and in variable relative abundances over the course of 387
drying, for instance reflecting environmental contamination (SD7). Further examples are 388
Lactobacillaceae, Enterobacteriaceae (mostly K. pneumoniae), Enterococcaceae, 389
Brucellaceae (especially Ochrobactrum pseudogrigonense), Stenotrophomonas, and J. 390
lividum. The fungal diversity of the dry processed samples was more diverse compared to the 391
wet processed ones. Although Pichia was still the major fungal taxon, the occurrence of 392
Starmerella bacillaris and Candida spp. was higher compared to wet processing (Fig. 3). The 393
PCoA underpinned the distinction between wet and dry processing samples based on their 394
microbial community structures (Fig. 4). 395
Significant differences between SD and HD were found. During the first six days of HD, the 396
heaped and non-stirred cherries remained moist, as liquid exuded from the pulp, and no 397
significant decrease in the moisture content was noted (Fig. S1). Also, visible chalk-dust 398
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mycelia were formed on these cherries and a strong odor developed, indicating high microbial 399
activity. Moreover, a dominance of AAB and the presence of the mold-like yeast 400
Saccharomycopsis crataegensis were found during HD (Fig. 2 and 3). The co-occurrence and 401
co-exclusion plot, based on a Spearman’s rank-order correlation matrix (Fig. S2) confirmed 402
the positive relationship among Gluconobacter spp., Acetobacter spp. and S. crataegensis as 403
well as non-Pichia yeasts. 404
Metabolite target analysis. (i) Freshly harvested coffee cherries. The moisture content of 405
the mucilage (85%) and endosperm (51%) of the fresh coffee cherries as well as the 406
concentrations of all targeted metabolites differed substantially (Fig. 5A,B). The mucilage 407
was rich in fructose (27% on dry mass), glucose (21%), sucrose (9%), and organic acids 408
(7.3%), among which malic acid, quinic acid, and gluconic acid were the most abundant. In 409
contrast, the endosperm had high levels of sucrose (8% on dry mass) and low concentrations 410
of monosaccharides, whereas the most prevalent organic acids (2.4%) were citric acid, malic 411
acid, and quinic acid. In addition, the trigonelline (1.0%) and caffeine concentrations (0.9%) 412
were higher in the endosperm than in the mucilage, whereas the acetic acid concentration was 413
lower. 414
(ii) Wet coffee processing. As the mucilage was completely removed from the 415
endosperm after fermentation, metabolite quantification of the mucilage was performed up to 416
the soaking stage. In the mucilage, sucrose was completely consumed by the end of 417
fermentation in both SW and EW. Fructose and glucose concentrations decreased and this 418
drop was more intense during EW. A substantial accumulation of metabolites associated with 419
microbial activity occurred, including acetic acid, ethanol, glycerol, lactic acid, and mannitol 420
(Fig. 5A). An accumulation of these compounds started after depulping and the 421
concentrations increased proportionally to the time of fermentation. The organic acid profile 422
of the mucilage was also modified during fermentation, as the concentrations of gluconic acid, 423
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malic acid, and quinic acid decreased. Propionic acid, butyric acid, isobutyric acid, valeric 424
acid, isovaleric acid, hexanoic acid, and oxalic acid concentrations were below the 425
quantification limits. The caffeine and trigonelline concentrations decreased upon processing. 426
Compared to the mucilage, less extensive change in metabolite concentrations occurred in the 427
endosperms of the coffee processing samples. After fermentation, the fructose, glucose, 428
sucrose, and caffeine concentrations in the endosperms decreased significantly (p < 0.05). The 429
extended fermentation time resulted in a further drop of the sucrose concentration and in an 430
increase of the acetic acid, ethanol, glycerol, glucuronic acid, lactic acid, mannitol, and 431
succinic acid concentrations. The accumulation of these compounds was proportional to the 432
duration of fermentation. After 24 h of soaking, the concentrations of the majority of these 433
targeted compounds dropped, especially ethanol, fructose, glucose, glucuronic acid, lactic 434
acid, and mannitol. In addition, the concentrations of citric acid, quinic acid, caffeine, and 435
trigonelline decreased after the soaking step. During drying, the endosperms of both SW and 436
EW followed a comparable pattern, with a decrease of sucrose, glucose, fructose, ethanol, 437
caffeine, and trigonelline concentrations, and a slight increase of caffeic acid and erythritol 438
concentrations (Fig. 5B). 439
(iii) Dry coffee processing. Clear changes in metabolite concentrations occurred in the 440
dried outer layers of SD and HD (Fig. 5C), whereas fewer changes were found in the 441
endosperms (Fig. 5D). No sucrose was found in the outer layers of dry-processed cherries, 442
indicating a fast and complete depletion upon drying. In addition, glucose and fructose 443
concentrations decreased; however, this drop was more gradual in SD compared to HD. The 444
glycerol and mannitol concentrations increased intensively and peaked in the SD3 and HD5 445
samples. Arabitol, sorbitol, and xylitol concentrations also increased in the outer layers during 446
drying. Organic acid concentrations, encompassing lactic acid (1.0% in SD5, 2.1% in HD3), 447
gluconic acid (8.7% in SD5, 14.3% in HD3), and glucuronic acid (1.7% in SD3, 3.1% in 448
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HD1) also increased during drying, with higher concentrations generated in the HD samples 449
than in the SD ones (Fig. 5C). A sharp increase of acetic acid concentrations took place in 450
SD1 and HD1, whereas they decreased afterwards. 451
Regarding the endosperm, the monosaccharide and sucrose concentrations decreased 452
gradually during drying, whereas the glucose and fructose concentrations had a secondary 453
peak in the SD6 and HD3 samples (Fig. 5D). Small concentrations of glycerol were found, 454
reaching their highest values in the SD3 and HD3 samples. Acetic acid, ethanol, and lactic 455
acid reached their highest concentrations in the SD2 and HD3 samples, and they decreased 456
afterwards (slower during HD compared to SD). Accumulation of glucuronic acid, gluconic 457
acid, and succinic acid concentrations took place at the beginning of drying, and followed a 458
gradual decrease upon processing as was found for the aforementioned compounds. Overall, 459
the PCA analysis performed on the endosperm metabolite data showed not only a clear 460
distinction between wet and dry processed samples, but also clear grouping between samples 461
during the beginning of processing and those close to the end (Fig. 6). These clusters were 462
corroborated by the drop in lactic acid, mannitol, and sucrose concentrations (Fig. 6). 463
(iv) Final green coffee beans. The metabolite profiles of the green coffee bean 464
samples (SW7, EW7, SD10, and HD10) differed. Significantly higher concentrations of 465
monosaccharides, myo-inositol, ethanol, fumaric acid, lactic acid, succinic acid, and 5-CQA 466
were found in EW7 than in SW7, whereas lower sucrose concentrations were found in EW7 467
than in SW7 (Fig. S3). In HD10, significantly higher concentrations of glucose, fumaric acid, 468
gluconic acid, succinic acid, and caffeic acid occurred than in SD10, while the concentrations 469
of glycerol, mannitol, myo-inostiol, acetic acid, and 5-CQA were lower. Overall, wet 470
processed green coffee beans contained higher citric acid and erythritol concentrations and 471
lower concentrations of fructose, glucose, caffeic acid, caffeine, trigonelline, and certain CQA 472
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isomers (i.e., 3-CQA, 4-CQA, 3,4-diCQA, and 4,5-diCQA) than dry processed green coffee 473
beans. 474
475
DISCUSSION 476
The present case study on coffee processing represents a systematic approach for the 477
monitoring of both microbial community shifts and metabolite profiles associated with coffee 478
cherry substrates (i.e., pulp and mucilage) and coffee beans throughout the entire post-harvest 479
processing chain. The conducted molecular analysis was based on an enzymatic total DNA 480
extraction method, targeting bacteria, yeasts, and filamentous fungi, suitable for metagenomic 481
purposes. The HTS of short-length amplicons of bacteria and fungi under the same barcode 482
was an economical way to evaluate the total microbial diversity of this complex ecosystem. 483
Challenges were the equimolar pooling of the two DNA template libraries that resulted in a 484
2:1 ratio of generated reads (V4:ITS1) and adapter read-throughs in the ITS1 sequences 485
because of the varying length of the ITS regions of Ascomycota and Basidiomycota (35). The 486
metabolite target analysis employed rapid sample preparation steps combined with three 487
different extraction methods and various chromatographic separation and detection techniques, 488
allowing high discriminatory power among structurally related compounds in complex 489
matrices. 490
The microbial community structure on the surface of the freshly harvested coffee cherries was 491
composed of Enterobacteriaceae, fungi, and soil microorganisms that naturally occur in the 492
phyllosphere (43-44). As soon as the coffee cherries started exuding, these prototrophic 493
microorganisms were succeeded by fermentative LAB species such as L. 494
mesenteroides/pseudomesenteroides and the yeast species P. kluyveri/fermentans that 495
dominated during processing. In general, L. mesenteroides is associated with cereal, vegetable, 496
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and fruit fermentations (45-48) and P. klyuveri has often been found in coffee and cocoa bean 497
fermentations (19, 49). 498
During wet processing, acidification was ascribed to the accumulation of lactic acid and acetic 499
acid by LAB species belonging to the taxa Lactococccus, Leuconostoc, and Weissella in the 500
mucilage. Extended fermentation selected for more acid-tolerant lactobacilli. The concomitant 501
increase of the mannitol concentration in the mucilage corroborated the activity of 502
heterofermentative leuconostocs. These are common patterns and activities during plant 503
fermentation processes (45, 47-48, 50-53). The yeast diversity of coffee processing often 504
encompasses the taxa Candida, Hanseniaspora, Pichia, and Saccharomyces (11, 14, 16-19). 505
In the current study, the yeast diversity was more restricted, as shown by the high relative 506
abundance of P. kluyveri/fermentans. Changes in the fermenting mucilage were also reflected 507
in the endosperms, where high concentrations of microbial end-metabolites (e.g., acetic acid, 508
ethanol, glycerol, lactic acid, and mannitol) occurred. In addition, the anoxia of underwater 509
submersion triggered the germination of the endosperms, resulting in an anaerobic 510
carbohydrate consumption response, which was even more intense during the extended 511
fermentation of depulped and thus injured coffee beans (28, 32-33, 54-55). The coffee beans 512
under anoxia consumed the carbohydrate resources continuously through glycolysis, as the 513
sucrose concentration decreased in the endosperms. Alternatively, during soaking the osmotic 514
pressure facilitated the loss of monosaccharides and microbial metabolites accumulated upon 515
fermentation. Hence, the soaking step carried out on the fermented coffee beans facilitated a 516
significant washout of these compounds, which may impact quality of the brewed coffee 517
because of a lower degree of acidity and will lead to a milder flavor. It is well known that the 518
loss of dry matter is associated with fermentation and soaking due to endogenous metabolism 519
and exosmosis, thereby influencing coffee cup quality (4, 56). During drying of the coffee 520
beans, the moisture content decreased and shifted their microbial contamination to 521
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environmental taxa related to soil (mainly Gram-negative bacteria; 57). Also, the drying step 522
induced a drought stress response and aerobic respiration in the endosperms (31), which 523
slowed down the glucose and fructose turnover rate (31). All these processing steps 524
contributed to differences in the concentrations of coffee-specific compounds too. 525
Consequently, technological aspects (especially the duration of fermentation, soaking, and 526
drying) can be decisive for the composition of the endosperms, as the accumulation of 527
microbial metabolites and endogenous mobilization of resource macromolecules could alter 528
the overall coffee bean composition. 529
In the case of dry processing, mainly AAB occurred next to yeast communities composed of 530
P. kluyveri/fermentans, Candida spp., and S. bacillaris. Hence, a clear distinction between the 531
microbial community structures of wet and dry processing of coffee could be made, which 532
was confirmed by the evolution patterns of the targeted chemical compounds. Especially in 533
the case of the heaped dry process, the prevalence of Acetobacter, Gluconobacter, and the 534
appearance of S. crataegensis was facilitated. The latter species was able to produce an 535
extensive mycelium, which could explain the mold-like appearance of the heaped beans upon 536
processing. Also, this yeast species has a negative or weak capacity to ferment glucose and 537
can assimilate gluconic acid, which is produced by AAB (58-59). These metabolic 538
characteristics could give it a competitive advantage over other microorganisms in the heaped 539
dry coffee processing malpractice. 540
The incidence of yeasts along with the Acetobacter and Gluconobacter species increased the 541
concentrations of acetic acid, ethanol, glycerol, and gluconic acid in the dried outer layers, 542
especially during heaped dry processing. Also, a minor accumulation of microbial metabolites, 543
such as gluconic acid, glycerol, and mannitol took place in the endosperm. These findings 544
support the effect of microorganisms on the chemical profile of dry processed coffee beans 545
and could imply a slow but observable migration of microbial metabolites to the endosperm. 546
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This is for instance the case when beans are spoiled by fungal contamination, resulting in 547
poor-quality, moldy-, and earthy-flavored coffee (24). In addition, stress during drying can 548
result in a bimodal pattern response, which corresponded to the relapsing peak in glucose and 549
fructose concentrations (31). The absence of depulping injury and anoxia contributed to 550
higher concentrations of free monosaccharides in the final dry processed green coffee beans 551
compared to wet ones. Moreover, the slow aeration and subsequent decrease of moisture in 552
the heaped dry process could account for the CGA degradation and caffeic acid generation by 553
endogenous enzymes as well as the higher concentration of volatiles in the endosperms 554
compared to wet processed coffee beans (60). Higher concentrations of caffeic acid, caffeine, 555
fructose, glucose, trigonelline, and certain CGA isomers in dry rather than wet processed 556
green coffee beans have also been shown for beans from different origins (9, 30, 61). 557
In general, the resulting chemical profiles of green coffee beans are strongly associated with 558
the final coffee cup quality (62-66). For instance, caffeine, CGAs, and trigonelline are 559
responsible for the bitterness and astringency of the final coffee beverage. As the dry 560
processed green coffee beans contain more of such compounds, higher bitterness and 561
astringency levels would be expected in the corresponding coffee beverages than in the wet 562
processed ones (9, 66-68). Finally, most compounds mentioned above undergo extensive 563
changes during roasting, mainly Maillard reactions, and hence contribute to differences in 564
coffee flavors (24, 30, 68-69). 565
In conclusion, the present case study monitored the evolution of the bacterial and fungal 566
diversity along with substrates consumed and metabolites produced during the entire chain of 567
both wet and dry processing under favorable and less favorable processing conditions. At the 568
same time, specific endosperm metabolite changes were followed. This was made possible by 569
simultaneous HTS of metagenomic DNA and metabolite target analysis of a broad range of 570
chemical compounds. The results showed that the different processing conditions influenced 571
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the composition and activity of the microbial communities as well as metabolite accumulation 572
in the endosperms. In addition, the current findings corroborate the effect of microorganisms 573
on the chemical profiles of coffee beans and support the idea to use a starter culture during 574
coffee processing for improved process control, prevention of spoilage, and eventually 575
steering the sensory differentiation of roasted coffee, as has been performed for cocoa bean 576
fermentation (70-71). Further studies should ultimately allow strengthening the understanding 577
of the impact of the microbiota on coffee cup quality and provide robust data for the 578
development of commercial starter cultures. 579
580
ACKNOWLEDGEMENTS 581
The authors would like to acknowledge their financial support from the Research Council of 582
the Vrije Universiteit Brussel (SRP7 and IOF342 projects), the Hercules Foundation (grant 583
UABR09004), and Nestec S.A., a subsidiary of Nestlé S.A. Cyril Moccand and Jay Siddharth 584
are acknowledged for critical reading of the manuscript and Arne Glabasnia and Frédéric 585
Mestdagh for their advice on the analytical methods. 586
587
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785
LEGENDS TO THE FIGURES 786
787
FIG 1. Experimental setup of the case study of four coffee processing experiments carried out 788
at the Nanegal station (Ecuador). For the wet and dry processing, the orange line depicts the 789
standard wet process (SW) and standard dry process (SD). The green line represents the 790
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extended fermentation wet process (36 h; EW) and heaped dry process (HD). A pool of 791
freshly handpicked coffee cherries (CB sample) served for all wet and dry processing 792
experiments. Concerning the wet processing, sample W1 refers to the depulped beans used 793
for both wet processing variations. Samples SW2 and EW2 correspond to the beans post-794
fermentation and prior to washing, SW3 and EW3 constitute beans post-soaking, whereas 795
samples SW4-7 and EW4-7 represent beans during sun-drying. Regarding the dry processing, 796
samples SD1-10 and HD1-10 were recovered during sun-drying. 797
FIG 2. Relative abundance (%) of bacterial (A) and fungal (B) operational taxonomic units 798
(OTUs) occurring in selected samples throughout the four post-harvest coffee processing 799
experiments. (A) Bacterial OTUs with relative abundance values above 0.1% in at least three 800
samples. (B) Distribution of minor fungal OTUs with a scale from 85-100% to better show 801
the fungal diversity because of the dominance (87-99%) of a large OTU assigned to the genus 802
Pichia. 803
FIG 3. Pseudo-heatmap showing the species diversity and relative abundances (%) of 804
bacterial and fungal species occurring in selected samples throughout the four post-harvest 805
coffee processing experiments. The color key at the bottom of the heatmap indicates the 806
relative abundances of the species in the sample. 807
FIG 4. Principal coordinates analysis (PCoA) bi-plots based on Bray-Curtis dissimilarities of 808
the bacterial (A) and fungal (B) community structures for the coffee samples analyzed. 809
FIG 5. Metabolite profiles of mucilage (A) and endosperm (B) from wet-processed coffee 810
samples and of hull and pulp (C) and endosperm (D) from dry-processed ones. In the case of 811
the compositional analysis of the endosperms (B and D), all other layers (i.e. hull and pulp, 812
parchment and silverskin, or dried hull) were manually removed prior to extraction. The 813
metabolite target analysis encompassed carbohydrates, sugar alcohols, organic acids, short-814
chain fatty acids, ethanol, and coffee-specific compounds. The metabolite concentrations 815
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represent the averages of three independent extractions. The standard error in all cases was 816
below ± 5 % and is thus not shown in the charts. 817
FIG 6. 3-D plot of the PCA of the chemical composition of the coffee samples analyzed. The 818
plot is based on the quantification data of the metabolite target analyses. The ellipses indicate 819
the approximate grouping of the two sample clusters corresponding to the coffee processing 820
methods. The coordinates of the centroid of each cluster (i.e., wet and dry processing 821
samples) are given. Principal components PC1, PC2, and PC3 account for 71 % of the 822
variance in the data matrix and their correlation with the different variables is graphically 823
shown next to the axes. PC1 was positively correlated with the presence of free glucose and 824
fructose, whereas it was negatively correlated with that of erythritol. PC2 was positively 825
correlated with the caffeic acid concentration and reversely to that of sucrose. Lastly, PC3 826
correlated with high lactic acid and mannitol concentrations. 827
828
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Figure 1
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Figure 3
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Figure 4
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Figure5
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Figure 6
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