**PTR-ToF-MS for the Online Monitoring of Alcoholic Fermentation in Wine: Assessment of VOCs Variability Associated with Di**ff**erent Combinations of** *Saccharomyces*/**Non-***Saccharomyces* **as a Case-Study**

**Carmen Berbegal 1,2, Iuliia Khomenko 3, Pasquale Russo 1, Giuseppe Spano 1, Mariagiovanna Fragasso 1, Franco Biasioli 3,\* and Vittorio Capozzi 4,\***


Received: 31 December 2019; Accepted: 24 May 2020; Published: 26 May 2020

**Abstract:** The management of the alcoholic fermentation (AF) in wine is crucial to shaping product quality. Numerous variables (e.g., grape varieties, yeast species/strains, technological parameters) can affect the performances of this fermentative bioprocess. The fact that these variables are often interdependent, with a high degree of interaction, leads to a huge 'oenological space' associated with AF that scientists and professionals have explored to obtain the desired quality standards in wine and to promote innovation. This challenge explains the high interest in approaches tested to monitor this bioprocess including those using volatile organic compounds (VOCs) as target molecules. Among direct injection mass spectrometry approaches, no study has proposed an untargeted online investigation of the diversity of volatiles associated with the wine headspace. This communication proposed the first application of proton-transfer reaction-mass spectrometry coupled to a time-of-flight mass analyzer (PTR-ToF-MS) to follow the progress of AF and evaluate the impact of the different variables of wine quality. As a case study, the assessment of VOC variability associated with different combinations of *Saccharomyces*/non-*Saccharomyces* was selected. The different combinations of microbial resources in wine are among the main factors susceptible to influencing the content of VOCs associated with the wine headspaces. In particular, this investigation explored the effect of multiple combinations of two *Saccharomyces* strains and two non-*Saccharomyces* strains (belonging to the species *Metschnikowia pulcherrima* and *Torulaspora delbrueckii*) on the content of VOCs in wine, inoculated both in commercial grape juice and fresh grape must. The results demonstrated the possible exploitation of non-invasive PTR-ToF-MS monitoring to explore, using VOCs as biomarkers, (i) the huge number of variables influencing AF in wine, and (ii) applications of single/mixed starter cultures in wine. Reported preliminary findings underlined the presence of different behaviors on grape juice and on must, respectively, and confirmed differences among the single yeast strains 'volatomes'. It was one of the first studies to include the simultaneous inoculation on two non-*Saccharomyces* species together with a *S. cerevisiae* strain in terms of VOC contribution. Among the other outcomes, evidence suggests that the addition of *M. pulcherrima* to the coupled *S. cerevisiae*/*T. delbrueckii* can modify the global release of volatiles as a function of the characteristics of the fermented matrix.

**Keywords:** volatile organic compounds; proton-transfer reaction-mass spectrometry; *Saccharomyces cerevisiae*; *Metschnikowia pulcherrima*; *Torulaspora delbrueckii*; wine; flavor

#### **1. Introduction**

Wine is the result of alcoholic fermentation (AF) performed by yeasts that convert the sugars present in grape must into ethanol and carbon dioxide. During this fermentation, other chemical changes are produced as a consequence of yeast metabolic activities. Among the chemical changes, a consistent part of volatile organic compounds (VOCs) is released, influencing wine flavor [1,2]. The interest in the monitoring of this bioprocess is high due to (i) the vast number of variables that can affect AF performances, and (ii) the crucial relevant impact of AF on wine quality. Non-separative approaches based on direct injection mass spectrometry (DIMS) have recently emerged as an alternative for the high-throughput and cost-effective quantitative profiling of volatiles in food and beverages [3]. To the best of our knowledge, no study has explored the potential of DIMS techniques to assess online VOC variability in association with alcoholic fermentation in wine [4].

*Saccharomyces cerevisiae* has a leading role in performing AF in wine [5,6]. However, an increasing interest has been given to non-*Saccharomyces* yeasts as drivers of the differentiation of the quality of final wines [7,8]. Non-*Saccharomyces* yeasts can possess enzymatic activities different from the *S. cerevisiae* enzymatic inventory, catalyzing the synthesis and the release (from non-volatile bound precursors) of VOCs able to modulate aromatic wine complexity [9,10]. Moreover, they may influence other characteristics such as glycerol and mannoprotein content, volatile acidity, color stability, and ethanol levels of wines [11,12]. Usually, as a reason for non-optimal fermentative performances, non-*Saccharomyces* yeasts are used in combination with *S. cerevisiae* strains. Some studies have shown that the strategy of co-inoculating *S. cerevisiae* starter together with selected non-*Saccharomyces* yeasts at high cell density produces wines with distinctive characteristics [13]. The interaction between the different yeast species influences the content of VOCs associated with fermentations [14]. Among the non-*Saccharomyces* species, *Torulaspora delbrueckii*, *Metschnikowia pulcherrima*, *Candida zemplinina*, and *Hanseniaspora uvarum* are mostly cited and have been intensively investigated [9,15–21]. Strains belonging to the species *Lachancea thermotolerans*, *Metschnikowia fructicola*, *Schizosaccharomyces pombe*, *T. delbrueckii*, *Kluyveromyces thermotolerans*, *Pichia kluyveri,* and *M. pulcherrima* are commercialized or have patented applications [16,22]. Belonging to the class of direct injection mass spectrometry (DIMS) approaches, proton transfer reaction mass spectrometry (PTR-MS) is an established method for the rapid, direct, and non-invasive online monitoring of VOCs characterized by short response time and high sensitivity [23]. The coupling of proton transfer ionization with time-of-flight (ToF) mass spectrometers and automated sampling offers several advantages in terms of mass resolution, throughput, and reproducibility [24–26]. This analytical strategy has found several applications in the food field (e.g., [27–31]), with a specific interest in bioprocess monitoring associated with microbial-based processes (e.g., [32–34]). Furthermore, several studies have applied PTR-based approaches to monitor VOC release associated with yeast metabolisms [35], often in association with food matrices [36–38]. In the case of matrices containing ethanol, consistent experimental efforts have been performed to avoid the adverse effects of a high concentration of this alcohol (primary ion depletion and ethanol–ethanol/water clusters formation responsible for the loss of efficiency in the qualitative/quantitative detection) [34,39–42].

In the present work, PTR-ToF-MS was used for the online monitoring of AF in wine and to compare the performance of four (autochthonous and commercial) yeast strains, both in single cultures and in multiple inoculations, using two diverse model matrices as substrates (real grape must and commercial grape juice). This study also aimed to preliminarily explore the interest in PTR-ToF-MS analysis of flavor-related volatile compounds in the control, design, and application of single/mixed starter cultures for wine.

#### **2. Materials and Methods**

#### *2.1. Microorganisms and the Determination of Microbial Population*

The following microorganisms were used for grape juice and grape must inoculation: the commercially available *Saccharomyces cerevisiae* strain DV10 (Lallemand, Montreal, QC, Canada, autochthonous characterized *S. cerevisiae* I6 strain from the Apulian region (Southern Italy) [43], and the commercially available non-*Saccharomyces* strains *Metschnikowia pulcherrima* FLAVIA (Lallemand, USA) and *Torulaspora delbrueckii* BIODIVA (Lallemand, Montreal, QC, Canada). Yeast starters were purchased in active-dried form. Rehydration procedures were done according to the suppliers' instructions. Starter cultures were prepared by growing pure cultures of the yeast strains separately grown in liquid Yeast Peptone Dextrose (YPD) medium (2% glucose, 2% Bacto peptone, 1% yeast extract) at 28 ◦C.

The viable count of yeasts during the AF was enumerated on Wallerstein Laboratory (WL) agar medium (Sigma-Aldrich, St. Louis, USA). WL discriminates between the used yeast species by colony morphology and color (*S. cerevisiae* produces large white colonies, whereas non-*Saccharomyces* yeasts produce green colonies on this medium). Plates were incubated at 28 ◦C for 48 h.

#### *2.2. Micro-Vinifications and Wine Analysis*

Starter cultures were prepared by growing strains in YPD medium as described above and then inoculating the strains into commercial red grape juice (Vitafit, Lidl Stiftung & Co., Neckarsulm, Germany) and red grape must from Apulian autochthonous grape varieties (20◦ Babo; 7.2 g/L total acidity; 3.5 g/L malic acid; pH 3.5; free ammonium 163.5 mg/L). Fermentations were performed inoculating at concentrations of 1 <sup>×</sup> <sup>10</sup><sup>6</sup> cfu/mL (colony-forming units per milliliter) of *M. pulcherrima* FLAVIA, 1 <sup>×</sup> 10<sup>6</sup> cfu/mL of *T. delbrueckii* BIODIVA and 1 <sup>×</sup> 10<sup>4</sup> cfu/mL of *S. cerevisiae* strains (DV10 or I6). Each fermentation experiment was carried out by performing three simultaneous independent repetitions. With these four biotypes, 14 different combinations of strains were carried out (Table 1). Fermentative kinetics from grape must were monitored daily by gravimetric determinations for seven days. With this purpose, samples were weighed daily to follow the weight loss caused by CO2 production.


**Table 1.** Microorganisms employed in different grape must/juice fermentations (trials 1–15).

*2.3. Samples Preparation and PTR-ToF-MS (Proton Transfer Reaction-Time of Flight-Mass Spectrometry) Analysis*

Nano-vinifications were performed in the vials using the above yeast combinations (Table 1) in commercial red grape juice and fresh red grape must. Nitrogen flux in the vial headspace assured maintaining the conditions comparable with those present in vinification. While the manufacturer sterilized the commercial grape juice, the must was not treated to reduce microbial presence. When present in the same trial, yeasts were co-inoculated in the juice/must. The resulting AF was monitored for three days. The whole experiment was performed in five replicates. For the measurements, a commercial PTR-ToF-MS 8000 apparatus from Ionicon Analytik GmbH (Innsbruck, Austria) was used in its standard configuration (V mode). The air associated with the headspace of the sample was directly injected in the PTR-MS drift tube. An argon dilution system was applied after headspace sampling. The dilution ratio was one part of headspace to three parts of argon. The argon flow rate was 120 sccm and was controlled by a multigas controller (MKS Instruments, Inc, Andover, MA, USA). Ionization conditions were as follows: 110 ◦C drift tube temperature, 2.30 mbar drift pressure, and 550 V drift voltage. These conditions led to an E/N ratio of about 140 Td (1 Townsend = 10–17 cm<sup>2</sup> V−<sup>1</sup> s<sup>−</sup>1). The inlet line was a PEEK capillary tube (internal diameter 0.04 in.) heated at 110 ◦C, with a flow set at 40 sccm. The acquisition rate of the instrument was one spectrum per second.

#### *2.4. Data Analysis*

Deadtime correction, internal calibration of mass spectral data, and peak extraction were performed according to the procedure described by Cappellin et al. [44,45]. Peak intensity in ppbv was estimated using the formula described by Lindinger et al. [46] using a constant value for the reaction rate coefficient (k = 2.10−<sup>9</sup> cm<sup>3</sup> s−1). This approach introduces a systematic error for the absolute concentration for each compound that is, in most cases, below 30% and could be accounted for if the actual rate constant coefficient is available [45]. All data detected and recorded by the PTR-ToFMS were processed and analyzed using MATLAB R2017a (MathWorks Inc., Natick, MA, USA) and R (R Foundation for Statistical Computing, Vienna, Austria). Principal component analysis, analysis of variance, and Tukey's post-hoc test were performed to spot the differences in the volatile aroma compounds emitted by the 28 grape must and juice fermentations used in this study.

#### **3. Results**

#### *3.1. Alcoholic Fermentation Kinetics and Yeast Dynamics*

The kinetics of the 14 fermentations in red grape must were monitored daily for seven days, evaluating the loss of weight due to the production of CO2 (data not shown). All fermentations were completed in four days except for sample 3 (inoculated with a single culture of *M. pulcherrima* FLAVIA), which was not able to complete the AF. The interactions between *Saccharomyces* spp. and both non-*Saccharomyces* spp. of enological interest, *M. pulcherrima* FLAVIA and *T. delbrueckii* BIODIVA, were investigated in terms of cell density. The differential morphology of the colonies on WL medium allowed us to calculate the proportion of each yeast species in different phases of AF (Figure 1). Only when both *S. cerevisiae* strains were co-inoculated the viable cell count was considered as total *S. cerevisiae* viable cells without distinguishing between DV10 and I6 strains.

Results from plate counting revealed that the maximum cell density of the single cultures was obtained after 48–72 h of the grape must inoculation both for *S. cerevisiae* (with an initial cell population of 1 <sup>×</sup> 104 cfu/mL) and non-*Saccharomyces* yeasts (with an initial cell population of 1 <sup>×</sup> 10<sup>6</sup> cfu/mL) (Figure 1, Experiments 1–4). In terms of single cultures studied, *M. pulcherrima* FLAVIA reached the lowest cell concentration (slightly more than 1 <sup>×</sup> 10<sup>7</sup> cfu/mL) after 72 h of inoculation (Figure 1, Experiment 3). Conversely, *T. delbrueckii* BIODIVA, even if with a different profile, achieved a biomass concentration comparable to those of the two *S. cerevisiae* strains. Considering the strain combinations, when two *S. cerevisiae* strains (DV10 and I6) were inoculated simultaneously, the growth behavior was the same as when they were inoculated in a single form and reached the maximum yeast population after 48 h of the inoculation (Figure 1, Experiment 5). Results from the co-inoculation of one strain of *S. cerevisiae* with *M. pulcherrima* FLAVIA (Figure 1 Experiments 6 and 8) showed that in 24 h, the *S. cerevisiae* strains were able to overtake the non-*Saccharomyces* yeast concentration, and in 48–72 h

achieved the maximum yeast population. On the other hand, the *M. pulcherrima* FLAVIA population decreased drastically after 72 h of inoculation. Contrary to *M. pulcherrima* FLAVIA, yeast *T. delbrueckii* BIODIVA presented a high cell density when it was co-inoculated with one of the *S. cerevisiae* strains, and with similar cell concentration levels to *S. cerevisiae* (Figure 1, Experiments 7 and 9). In the same way, when the two *S. cerevisiae* strains, DV10 and I6, were co-inoculated with *M. pulcherrima* FLAVIA or with *T. delbrueckii* BIODIVA strains, the growth behavior of the non-*Saccharomyces* strains was the same than when they were inoculated with only one *S. cerevisiae* strain (Figure 1, Experiments 10 and 11). The simultaneous inoculation of one *S. cerevisiae* strain with both, *T. delbrueckii* BIODIVA and *M. pulcherrima* FLAVIA (Figure 1, Experiments 12 and 13), revealed that *S. cerevisiae* strains needed more time to reach the maximum cell concentration than when co-inoculated with only one non-*Saccharomyces* strain, and *T. delbrueckii* BIODIVA presented a higher population than *S. cerevisiae* strains for 48 h.

**Figure 1.** Viable cell count (cfu/mL) of different yeast single or mixed culture (Table 1) inoculated. The cell enumeration was performed on Wallerstein Laboratory agar medium that discriminates *S. cerevisiae* (large white colonies) from non-*Saccharomyces* yeasts (green colonies).

Inoculating the four starter cultures simultaneously (Figure 1, Experiment 14) triggered, as in the previous cases, that *S. cerevisiae* strains required more time to reach the maximum cell population and, the maximum cell concentration was lower than when they were inoculated in a single culture form. Furthermore, the population of *S. cerevisiae* and *T. delbrueckii* BIODIVA presented similar population levels after 48 h of inoculation. Otherwise, the *M. pulcherrima* FLAVIA population decreased from the inoculation time. Overall, biological interactions influenced single yeast growth behavior. Nevertheless, in all of the studied experimental modes, the most significant changes related to yeast population occurred during the first 72 h, which led us to focus on this temporal interval for the online monitoring of VOCs associated with the considered experimental modes using the PTR-ToF-MS technology.

#### *3.2. Automated Monitoring Volatile Organic Compound (VOC) Evolution in Red Grape Must and Juice Fermentation by Di*ff*erent Yeast Mixed Cultures*

A preliminary data exploration has been made to visualize the results of the PTR-ToF-MS grape must and juice analysis through a principal component analysis (PCA). The first and second PCA components (Figure 2) accounted for 84% of total variability and showed that the two matrices (grape juice and must) used in this study led to clear changes of VOC release. Differences in the distribution of variances were also observed concerning single yeasts or yeast combinations. It is easy to follow a time-dependent dimension of the phenomena, observing the increasing dimensions of the symbols in Figure 2.

**Figure 2.** Score plot of the principal component analysis of volatile organic compound (VOC) emission evolution associated with the first three days of AF for each trial tested in this study. Data were logarithmically transformed and centered. Different colors indicate the different yeast managements, medium, and blank samples. The size of the points grew with the time of measurements. For a detailed view of the figure, the original image is included in the Supplementary Materials (Figure S1).

Separations and different evolutions were evident by comparing the matrices 'grape must' and 'grape juice'. In the 'must' assays, it was clear the partition between the trials with only *S. cerevisiae* strains inoculated (sample codes 1, 2, and 5; Table 1) and those that included, in the starter cultures, non-*Saccharomyces* strains (sample codes 3, and 4; Table 1) (Figure 2). Additionally, a diverse behavior was noticeable for the fermentations inoculated with pure cultures of *M. pulcherrima* FLAVIA and *T. delbrueckii* BIODIVA strains, respectively. All the experiments that included both *S. cerevisiae* and non-*Saccharomyces* strains (sample codes 6–14; Table 1) followed a trend that appeared more similar to the non-*Saccharomyces* pure cultures. Concerning the 'juice' experimental plan, an uniform trend was confirmed for the samples inoculated with the *S. cerevisiae* strains (Figure 2). In contrast, the behavior observed for the pure inoculation of *M. pulcherrima* FLAVIA strain (sample code 3; Table 1) was radically different. The pure culture of *T. delbrueckii* BIODIVA strain (sample code 4; Table 1) and all the combinations of *S. cerevisiae*–*T. delbrueckii* (sample codes 7, 9, and 11; Table 1) followed trajectories closer to those of *S. cerevisiae* strains than to the *M. pulcherrima* one. In contrast, all the other trials (sample codes 6, 8, 10, and 12–14; Table 1) observed patterns of evolution similar to *M. pulcherrima*. Concerning these last trials, some samples also included *T. delbrueckii* BIODIVA among the inoculated strains. In the case of PCA, the loading plot (Figure 3) indicates the mass peaks related to the observed evolution of the VOC profile in Figure 2.

**Figure 3.** Loading plot of principal component analysis of the mass peaks (ms) related to the observed evolution of VOCs profile in Figure 2. For a detailed view of the figure, the original image is included in the Supplementary Materials (Figure S2).

More than 70 mass peaks were identified among the four yeast commercial starters during online monitoring throughout the three days of fermentation. For each of these mass peaks, it was possible to perform a tentative identification (allowing a possible link of the ion with a given molecule/molecular fragment) and to follow the evolution of the intensity in the time, allowing a direct analytic determination to evaluate the yeast metabolic activity during the progress of AF.

More specifically, differences between the matrices used were observed when the score plot of the PCA analysis on the distribution of variances associated with VOC emission during the first three days of AF was represented separately for each trial (Figure 4). Negligible VOC evolution was evident in uninoculated grape juice and slow evolution in grape must as revealed by the first PCA dimension, which is related to the increase of volatile concentration in the sample headspace (Figure 4, uninoculated trial, experiment 15). Regarding the inoculated yeasts, differences in the VOC emissions were also found. For example, *M. pulcherrima* and *T. delbrueckii* in single culture (Figure 4, experiments

3 and 4) tended to reach a lesser concentration of VOCs in juice, while both *S. cerevisiae* kept producing more volatile compounds with time (Figure 4, experiments 1 and 2). Moreover, this graph confirmed that there were differences between the different yeast combinations inoculated, as they were arranged in the graph according to different patterns. This effect is of particular interest, if we consider that together with the effect of different strains/species combinations we also tested the impact of the increasing microbial diversity of the starter cultures inoculated.

**Figure 4.** Score plot of principal component analysis of VOC emission evolution associated with the first three days of AF, separately represented for each trial (Table 1). Continuous lines indicate grape must and broken lines indicate grape juice. For a detailed view of the figure, the original image is included in the Supplementary Materials (Figure S3).

#### **4. Discussion**

Wine is a peculiar commodity in the agrifood sector in terms of business opportunities and innovative trends [47]. The management of AF deeply affects the optimization of the product quality and the improvement of process sustainability [48–52]. Several variables can influence the performance of AF such as grape variety, yeast species, yeast strain, nutrient availability for the yeasts, temperature of the process, addition of chemical compounds, and technological regimen [49,53–55]. The fact that these variables are often intimately connected leads to a huge 'oenological space' that needs to be explored. This observation explains the high interest in approaches tested to monitor this bioprocess [53,56] including those using VOCs as target molecules [57–61]. Furthermore, it is important to underline that the study of VOC diversity has a dual significance; on one hand, VOC variability is the effect of yeast metabolism, on the other, VOCs represent the molecular basis of the sensory perception of wine tasting [1,62,63]. Among the DIMS techniques, no study has delved into the survey of the untargeted diversity of volatiles associated with the wine headspace in order to (i) monitor online the progress of AF, and (ii) evaluate the impact of the different variables of wine quality [4].

As a case study, the assessment of VOCs variability associated with different combinations of *Saccharomyces*/non-*Saccharomyces* was selected. In fermented beverages such as wine, a relevant field of study deals with the contribution of microbiological resources to the organoleptic and sensory properties of the final product [64,65]. In the winemaking process, some of the most characteristic flavor and aroma components are synthesized by yeasts during the AF [66]. *S. cerevisiae* is the main responsible microorganism of the AF in wine, but nowadays, non-*Saccharomyces* yeasts are used in industry to improve flavor, aroma, and stability [16,22,64,65]. This heterogeneous class of eukaryotic microorganisms detains a wide enzymatic diversity [67–69]. In this light, it appears comprehensible the interest in the formation of volatile compounds by both *Saccharomyces* and non-*Saccharomyces* yeasts, which are important to maximize the sensorial quality of the final products. The present study, in particular, tested the PTR-ToF-MS-based approach recently optimized to compare the performance of different yeasts in cultural media [35]. This technology has been successfully employed in fermented foods and beverages to monitor the effect of different microorganisms responsible for the fermentative process, for instance, to discriminate wines inoculated with different malolactic starters [39], monitor lactic fermentation driven by different yoghurt commercial starter cultures [33], and characterize single commercial yeast starters in bread productions [36]. This study proposed the first application of PTR-ToF-MS for the AF monitoring in wine, demonstrating the high potential of this analytical approach to explore the huge number of variables influencing this bioprocess crucial in winemaking.

Concerning the yeast population kinetics, the respective inoculation of non-*Saccaromyces* and *Saccharomyces* strains to promote/drive alcoholic fermentation in wine were generally performed (i) by inoculating together the strains (generally with a ratio 100:1 in favor of the non-*Saccharomyces* strain) (simultaneous inoculation) or (ii) inoculating the *Saccharomyces* strain with a delay of 24–48 h compared to the non-*Saccharomyces* inoculation (sequential inoculation) [70–72]. Both approaches aimed to maximize the development of non-*Saccharomyces*, concretizing an advantage for these yeasts [73]. The oenological objective is to counteract the fermentative advantage of *S. cerevisiae*, allowing non-*Saccharomyces* yeasts to influence wine quality [74]. The findings reported in the present article suggest that simultaneous inoculation led to good growth/survival for the tested non-*Saccharomyces* in combination with the selected *S. cerevisiae* strain. Cell concentration remained particularly high for *T. delbrueckii,* confirming the ability of this non-*Saccharomyces* yeast to survive at high ethanol concentrations [75]. For *M. pulcherrima*, the evidence was only partially in accordance to that reported by Dutraive et al. [17], who observed an initial decline of this yeast between the second and the third day after the inoculation, but followed by the complete annulment of the population.

The analysis included both commercial grape juice and fresh grape must to test the efficacy of the technique both in model conditions and in the real winemaking conditions. In fact, commercial grape juice, together with synthetic grape must [76] represents a common model medium for the fermentative studies in oenology (e.g., [77,78]). We found an evolution of volatiles during the three days of the study, which was in accordance with the evolution of yeast cell counts carried out during the AF. The results reported from the analysis of 'volatomes' associated with the development of single yeast species depicted different trends that could be coherent with different claimed aromatic properties for three commercialized strains, which received a considerable interest in the scientific literature (*S. cerevisiae* DV10, e.g., [79–83]; *M. pulcherrima* FLAVIA, e.g., [17,19,84–87]; *T. delbrueckii* BIODIVA, e.g., [17,84–88]). The study highlighted a global separation of VOC variability associated with the headspaces of the two tested matrices that can be ascribable to the chemical differences and/or to variable microbiological properties of the two media. Interesting, the behavior VOCs released by *M. pulcherrima* FLAVIA radically changed, shifting from fresh must to commercial juice, meaning that chemical/microbiological determinants of these media can directly or indirectly modulate VOC production by the yeasts. Even if the effect of abiotic and biotic interaction in the wine environment have been extensively investigated [89–91], further studies are needed to understand the biology affecting this phenotype, particularly in light of the huge intraspecific variability in terms of oenological properties within the species *M. pulcherrima* [92]. Intriguingly, variable patterns in must versus juice have also been observed in the trials where *M. pulcherrima* was co-inoculated with *S. cerevisiae* and with *T. delbrueckii*. A few studies have delved into the compatibility of *S. cerevisiae* combined in the same vinification with more than one non-*Saccharomyces* species [69,93]. Except for the coupled *Lachancea thermotolerans* and *Schizosaccharomyces pombe* that (used both in combination but not with also *S. cerevisiae*) has been extensively explored [94–96], only one study has tested the sensory impact (but not the VOC analysis) of this non-*Saccharomyces* multiple inoculation in wine [69]. In fact, usually, the articles considered the impact on volatile diversity of single strains or mixed starters composed of one *S. cerevisiae* strain and one non-*Saccharomyces* species. While the effect of multiple *Saccharomyces* yeast co-inoculations on volatile wine composition has been assessed (yeast inocula differed substantially in volatile thiols and other flavor compounds) [97,98], the interactions among different non-*Saccharomyces* wine yeast species need to be further elucidated [69]. The present findings suggest that the addition of *M. pulcherrima* to the coupled (in the case of the strains we tested) *S. cerevisiae*/*T. delbrueckii* can modify the global release of volatiles during the AF in wine as a function of the fermented matrix.

The different behaviors of the 'volatomes' associated with the single and mixed cultures showed promising results in terms of variability of the single mass peaks. The study of individual peak mass profiles during the three first days of AF in association with the tested yeast combinations will be the natural follow-up of the present communication. The objective will be focused to elucidate the single mass peaks/molecules responsible for the strain/species-specific differences and the specific yeast interactions/combinations, but also for the selection of candidate 'volatile' markers for the rapid screening of new microbial resources for 'flavoring' starter culture design in wine fermentations. Some findings have corroborated the evidence that the complexity of the microbial starter cultures inoculated can be among the levers capable of improving sensory wine complexity, assuring the safety of the productions (also for the possible exploitation in terms of biocontrol activity) [12,99–101]. It is interesting to underline that the tested strategy could find an application also in testing the interaction of yeast with malolactic bacteria [102–105]. Furthermore, it is important to stress how the proposed exploration of the phenotypic space of yeast activity in oenology can open new research lines for fundamental research in the field of yeast biology [106–108].

#### **5. Conclusions**

PTR-ToF-MS, combining high sensitivity/accuracy without neither sample preparation nor sample destruction, allows rapid real-time determination of volatile organic compounds (VOCs). In this paper, preliminary findings on the application of this analytical approach for the online monitoring of alcoholic fermentation in wine is proposed. The study explored different single and multiple inoculation of diverse oenological yeasts both in commercial grape juice and fresh must. The experiment highlighted a variability of the global volatiles in association with (i) the different yeast species, (ii) the different yeast combinations, and (iii) the different fermenting matrices. The evidence demonstrates the potential

of PTR-ToF-MS in monitoring experimental variables associated with alcoholic fermentation in wine, opening new opportunities to manage this crucial phase, thus improving the quality of the final products and optimizing the processes.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2311-5637/6/2/55/s1, Figure S1: source file for Figure 2. Figure S2: source file for Figure 3. Figure S3: source file for Figure 4.

**Author Contributions:** Conceptualization, C.B., I.K., P.R., G.S., M.F., F.B., and V.C.; Methodology, C.B., I.K., P.R., G.S., M.F., F.B., and V.C.; Investigation, C.B., I.K., P.R., M.F., F.B., and V.C.; Resources, G.S., F.B., and V.C.; Data curation, C.B., I.K., F.B., and V.C.; Writing—original draft preparation, C.B., I.K., and V.C.; Writing—review and editing, P.R., G.S., M.F., and F.B.; Supervision, G.S. and F.B.; Project administration, F.B. and V.C.; Funding acquisition, F.B. and V.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** Pasquale Russo is the beneficiary of a grant by MIUR in the framework of 'AIM: Attraction and International Mobility' (PON R&I 2014–2020) (practice code D74I18000190001). The work has been partially supported by the Autonomous Province of Trento (ADP 2020).

**Acknowledgments:** We would like to thank (i) the three anonymous reviewers for their suggestions and comments, (ii) Francesco De Marzo and Massimo Franchi of the Institute of Sciences of Food Production—CNR for their skilled technical support provided during the realization of this work, and (iii) Sergio Pelosi of the Institute of Sciences of Food Production—CNR for their critical reading of the manuscript.

**Conflicts of Interest:** The authors declare no conflicts of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Antioxidant Properties of Fermented Green Co**ff**ee Beans with** *Wickerhamomyces anomalus* **(Strain KNU18Y3)**

#### **Mesfin Haile <sup>1</sup> and Won Hee Kang 1,2,\***


Received: 20 November 2019; Accepted: 27 January 2020; Published: 28 January 2020

**Abstract:** A few yeast species have been tested frequently to improve the tastes, flavors, and other important quality parameters of coffee. However, continuing evaluations of different yeast species for fermenting green coffee beans will have a significant positive contribution to the coffee industry. This experiment was conducted to evaluate the antioxidant properties, total phenol content (TPC), total flavonoid content (TFC), total tannin content (TTC), and the consumer acceptability of fermented green coffee beans with *Wickerhamomyces anomalu*. The coffee beans were roasted at different roasting conditions (light, medium, and dark). There was no significant (*p* > 0.05) difference between the yeast-fermented and non-fermented coffee with regard to the oxygen radical absorbance capacity (ORAC) values in medium and dark roasted coffee. Similarly, the superoxide dismutase-like (SOD)-like activity did not significantly differ in all roasting conditions. However, the SOD-like activity was significantly different (*p* < 0.05), particularly within light roasted and medium roasted, and between light roasted and dark roasted in both the control and fermented coffee extracts. The 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and ferric reducing antioxidant power (FRAP) were improved in fermented coffee beans. There was a significant (*p* ≤ 0.05) difference between the yeast-fermented and non-fermented coffee with respect to the TPC and TFC in all roasting types and the TTC in the light and dark roasting conditions. The fermentation of green coffee beans with *W. anomalus* increased the TPC and TFC. However, the TTC was lower in the fermented coffee beans compared to the non-fermented coffee beans in medium and dark roasted coffee. In general, fermentation of green coffee beans with *W. anomalus* has the potential to improve the functionality of coffee beans.

**Keywords:** antioxidant; coffee; fermentation; *W. anomalus*

#### **1. Introduction**

Fermentation has the potential to improve the functionality of foods. Fermentation is primarily relied upon during the wet processing of coffee to remove mucilage. However, it is also improves coffee's sensory quality attributes [1]. Fermentation has been extensively applied in the food, chemical, and pharmaceutical industries to aid in the manufacturing, extraction, and modification of bioactive compounds [2,3]. Microbial fermentation is an interesting biotechnological processing system that can improve the total phenolic content of foods and herbs by liberating their insolubly bound phenolics and hence boost their nutritional value [4,5]. Numerous research papers provide a comparison of the antioxidant properties of popular drinks such as coffee, tea, and cocoa [6–8]. Phenolic compounds are found in a broad range of regularly consumed plant foods, such as vegetables, fruits, legumes, and cereals, and in beverages of plant origin, such as coffee, tea, and wine [9,10]. Flavonoids naturally exist in plants with a variable phenolic structure. Functional hydroxyl groups in flavonoids mediate their antioxidant effects by chelating metal ions and scavenging free radicals [11,12]. Flavonoids in food are commonly responsible for the color, the taste, the prevention of fat oxidation, and the protection of enzymes and vitamins [13].

*Wickerhamomyces anomalus* (formerly *Pichia anomala*) is an ascomycetous heterothallic yeast of the family *Wickerhamomycetaceae* that propagates sexually through the development of hat-shaped ascospores and asexually by budding [14]. *W. anomalus* strains are found in several environments and have been isolated from cereal grains, fruits, maize silage, wine, and high-sugar food products [14]. *W. anomalus* is categorized as a biosafety level-one organism; it is deemed harmless for healthy individuals and can grow under severe environmental stress conditions, such as high and low pH, high osmotic pressure, anaerobic conditions, and low water activity [15]. As mentioned by Comitini et al. [16], *W. anomalus* toxins have been examined as antimicrobial agents against some spoilage yeasts such as *Dekkera*/*Brettanomyces*. Some researchers have reported that the wild species of *W. anomalus* strains have the potential to use maltose and grow better than other commercial brewing yeasts [17]. However, other studies have referred to its clear inability to metabolize maltose [18]. Considering these findings, *W. anomalus* is preferred as a good starter culture in sequence or inoculated together with other yeasts in winemaking [19]. *p. anomala*-mixed starters have been evaluated to improve the final quality of cider [18]. Due to its positive effect on sensory quality, a mixed starter of *W. anomalus* and *Saccharomyces cerevisiae* has been proposed for making Chinese baijiu [20].

Recently, studies have been conducted to improve the functionality of coffee through green bean fermentation with selected microorganisms. In these studies, the *Saccharomyces* species [21,22], *Saccharomycopsis fibuligera* [22], *Rhizopus oligosporus* [23], and *Yarrowia lipolytica* [24], have been used to ferment green coffee beans. The fermentation of green coffee beans with *R. oligosporus* significantly enhanced the compositions of aroma precursors [23]. As reported by Kwak et al. [21] and Mesfin and Kang [22], the fermentation of green coffee beans improves antioxidant activity, total phenol content (TPC), and total flavonoid content (TFC), and it reduces the total tannin content (TTC), which is mostly responsible for coffee's astringency. *W. anomalus* strain KNU18Y3 has the ability to produce a pectinase enzyme, it was selected as a starter culture for coffee fermentation in the wet processing method [25]. Since this yeast has not been tested previously to ferment green coffee beans, this study was conducted to evaluate the antioxidant activities of fermented coffee beans with *W. anomalus* (strain KNU18Y3).

#### **2. Materials and Methods**

#### *2.1. Chemicals*

Disodium phosphate (Na2HPO4), aluminium chloride (AlCl3·6H2O), monosodium phosphate (NaH2PO4), sodium carbonate (Na2CO3), D-glucose, and sodium nitrite (NaNO2) were supplied by Dae-Jung Chemicals & Metals Co., Ltd., (Jeongwang-dong, Shiheung-city, Gyeonggi-do, Republic of Korea). Pyrogallol, 2,2'-azobis (2-amidinopropane) dihydrochloride (AAPH), and fluorescein sodium were purchased from Santa Cruz Biotechnology, Inc. (Dallas, Texas, USA). NaCl, ethylenediaminetetraacetic acid, yeast peptone dextrose, gallic acid, Folin-Ciocalteu's phenol reagent, quercetin, Trolox, 2,2-diphenyl-1-picrylhydrazyl, potassium ferricyanide(C6N6FeK3), trichloroacetic acid (C2HCl3O2), and ferric chloride (FeCl3) were purchased from Sigma Aldrich LLC (St. Louis, MO, USA). Methanol was supplied by Merck KGaA (Darmstadt, Germany), and HCl was purchased from Junsei Chemical Co., Ltd. (4-4-16 Nihonbashi-honcho, Chuo-ku, Tokyo, Japan).

#### *2.2. Fermentation of Green Co*ff*ee Beans*

A freeze-dried *W. anomalus* (strain KNU18Y3) yeast cells were cultivated in a sterile yeast peptone dextrose broth (0.5% *w*/*v* yeast extract, 2 % *w*/*v* dextrose and 1% *w*/*v* casein peptone) for 48 h at 30 ◦C. The pH of the media was calibrated to 5.0 with 1 M HCl. Then, the yeast cells were collected via

centrifugation at 8000× *g*. Finally, the collected yeast cells were washed twice using the deionized distilled water (ddH2O) and mixed in a similar volume of 100 mM phosphate-buffered saline solution.

The green coffee beans (*Co*ff*ea arabica* L.) that imported from Kenya were used for this study. The coffee beans (600 g) saturated in ddH2O at 4 ◦C for 24 h and then steamed at 80 ◦C for 40 min to kill native yeasts that exist on the coffee beans. Next, the steamed coffee beans then allowed to cool at 20–23 ◦C. The heat-treated green coffee beans were divided into two lots: fermented through inoculation (1.0 <sup>×</sup> <sup>10</sup><sup>4</sup> colony-forming unit (CFU)/g of coffee beans) and non-inoculated (control). Then, each lot was divided into three parts and underwent a different roasting treatment. Fermentation of green coffee beans and roasting were done in three replications. The fermentation was carried out for 24 h at 30 ◦C. After that, the coffee beans were washed thoroughly using a ddH2O. The fermented coffee beans were dried using oven at 45 ◦C until the moisture content reached between 10% and 12%.

The pH of the fermented solution (the water that used to ferment the coffee beans) was recorded using a pH meter at 0 h and 24 h. A sample solution was taken after 24 h fermentation and serially diluted and plated onto yeast peptone dextrose agar (YPDA) plates. The plates were incubated for 24 h at 30 ◦C to estimate the growth of yeast cells. The pH measurements and microbial counts were made in five replications.

#### *2.3. Co*ff*ee Roasting, Grinding, Extraction*

The green coffee beans were roasted at 245 ◦C for 11.5 (light roast), 13.5 (medium roast) and 16 (dark roast) min using a coffee roaster (GeneCafe CR-100 coffee roaster, Genesis, Ansan, Korea) to ensure uniform roasting conditions. Each roasting was done in triplicate. After roasting, the beans were allowed to cool for 30 min and then ground by adjusting in a medium level on a coffee grinder (Latina 600N electric grinder). Hot brew extraction made using a coffee maker (HD7450, Philips, Nanjing, China) by mixing 36 g of coffee powder with 500 mL of water. A filter paper was used during brewing. After each brewing, the coffee machine was cleaned prior to brewing the next sample. The extraction was made in three replications. The analysis of antioxidant activities, TPC, TFC, and TTC were measured from this extract.

#### *2.4. Color Parameters*

Chroma Meter (CR-400 Chroma Meter, Tokyo, Japan) was used to estimate the color of the roasted coffee powder. A small coffee powder (5 g) was kept into a Petri dish for reading, and a\* (redness), b\* (yellowness) and L\* (lightness) were assessed. The color reading was made in triplicate.

#### *2.5. Antioxidant Activity*

#### 2.5.1. Oxygen Radical Absorbance Capacity

The oxygen radical absorbance capacity (ORAC) was estimated with some modifications using the protocol described by Ou et al. [26]. Fluorescein powder was dissolved using a phosphate buffer (NaH2PO4-Na2HPO4, 10 mM, pH 7.0). The coffee extract (50 μL) was mixed with 25 mM of the fluorescein solution (150 μL) and incubated in a dark environment for about 10 min. Then, 25 μL of 120 mM AAPH solution was mixed to the coffee extract and fluorescein mixture. Meanwhile, 10 mM phosphate buffer was substituted instead of coffee extract and used as a control. The absorbance was measured using a UV/visible spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan). The readings were recorded at one minute interval for 30 min (excitation wavelength: 485 nm; emission wavelength: 535 nm). The absorbance readings for ORAC estimation were made in triplicate and expressed as a μM Trolox equivalent/mL of coffee (μM TE/mL). The ORAC estimated using the formula stated below;

$$\text{ORAC} \left( \mu \text{M TE/g} \right) = \left( \text{C}\_{\text{Trolox}} \times \left( \text{AUC}\_{\text{Sample}} - \text{AUC}\_{\text{Blank}} \right) \times \text{k} \right) \text{AUC}\_{\text{Trolox}} - \text{AUC}\_{\text{Blank}} \tag{1}$$

where CTrolox, k, and AUC were the concentrations of Trolox (5 μM), the sample dilution factor, and the area under the curve, respectively. AUC was computed according to the formula presented below;

$$\text{AUC} = 1 + \sum\_{n=1}^{30} \frac{fn}{f0} \tag{2}$$

where fn was the fluorescence at time n (min).

#### 2.5.2. Superoxide Dismutase-Like Activity

The protocol suggested by Marklund and Marklund [27] used with some modifications to estimate the SOD-like activity. Coffee extract (400 μL), Tris-HCl buffer (600 μL, 50 mM tris (hydroxymethyl) aminomethane and 10 mM ethylenediaminetetraacetic acid, pH 8.0), and 7.2 mM pyrogallol (40 μL) were mixed together and kept at 25 ◦C for 10 min. The reaction was terminated by mixing 0.1N HCl (20 μL). Absorbance readings were done at 420 nm using a UV/visible spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan). The absorbance readings for the estimation of the SOD-like activity were performed in triplicate. SOD-like activity was computed with the formula presented below:

$$\text{SOD-like activity (\%)} = (1 - \text{A/B}) \times 100\tag{3}$$

where A indicates the sample absorbance and B indicates the absorbance of the blank (control).

#### 2.5.3. 2.,2-diphenyl-1-picrylhydrazyl (DPPH) Radical Scavenging Assay

The DPPH activity was measured using the protocol described by Pataro et al. [28], with some modifications. DPPH was dissolved in methanol (0.1 mM) and 3.9 mL of it transferred into a cuvette, then immediately the absorbance was measured at 515 nm (used as a control). The coffee extracts (800 μL) from each sample were mixed with 3.2 mL of methanol-DPPH solution and placed in a dark condition for 30 min. Then the absorbance was recorded. Methanol was used as a blank. The DPPH assay was done in three replications. The DPPH inhibition percentage was calculated using the following formula;

$$\text{DPPH} \text{ inhibition (\%)} = (\text{A}\_{\text{control}} - \text{A}\_{\text{sample}}) / \text{A}\_{\text{control}} \times 100 \tag{4}$$

where Acontrol is the absorbance of control reaction (DPPH and Methanol), and Asample is the absorbance in the presence of coffee extract.

#### 2.5.4. Ferric Reducing Antioxidant Power (FRAP)

FRAP of the coffee extract was assessed using the method described by Oyaizu [29]. A 2.5 mL of coffee extract was mixed with 2.5 mL of 200 mM sodium phosphate buffer (pH 6.6) 2.5 mL of 1% potassium ferricyanide. The mixture was incubated for 20 min at 50 ◦C following 2.5 mL of 10% trichloroacetic acid was added. Then, this mixture was centrifuged (2000× *g* for 10 min) and 5 mL of the supernatant was taken and mixed with 5 mL of water and finally added 1 mL of 0.1% ferric chloride. The absorbance was measured at 700 nm using a spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan) and the FRAP was subsequently determined using ascorbic acid as standard. The FRAP analysis was done in three replications.

#### *2.6. Total Phenol Content, Flavonoid Content, and Tannin Content*

The total phenol content of the coffee extract was measured using a protocol described by Singleton's method [30], with some adjustments. The coffee extract (20 μL) was diluted with 1580 μL ddH2O. Diluted coffee extract (160 μL) and Ciocalteu's phenol reagent (10 μL) were mixed and kept for 8 min. Then, 30 μL of 20% Na2CO3 solution was mixed and incubated in a dark environment

for 2 h. The coffee extract was substituted with distilled water and used as a blank. The absorbance readings were determined at 765 nm using a UV/visible spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan). Gallic acid solutions (0–1 mg/mL) were used to generate a standard curve (r2 = 0.997). The estimation of the TPC was done in triplicate. Results were expressed as mg gallic acid equivalent/mL (mg GAE/mL) of coffee extract.

A protocol stated by Dewanto [31], applied with some modification to estimate the total flavonoid content of the coffee extract. The mixture was prepared using 250 μL coffee extract, 1 mL of distilled water and 75 μL of 5% NaNO2. The 5 min later, 10% AlCl3 6H2O solution (150 μL) was mixed and incubated for 6 min. Finally, 1N NaOH (500 μL) was added and incubated for 11 min. The ddH2O used as a blank sample. The absorbance was measured at 510 nm using a UV/visible spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan). The standard solution was prepared using a quercetin solution (0–1 mg/mL) to make a standard curve (r2 = 0.999). The estimation of the TFC was done in triplicate. The total flavonoids in the coffee were expressed as mg quercetin equivalent/mL of coffee extract.

The total tannin content (TTC) was measured using the Folin-Ciocalteu method, with some modifications [32]. About 100 μL of the coffee extract was added to a tube (10 mL) containing 7500 μL of distilled water, 500 μL of Folin-Ciocalteu phenol reagent, and 1000 μL of 35% sodium carbonate solution and was then diluted to 10,000 μL with distilled water. The mixture was well-mixed and placed at room temperature for 30 min. A set of standard solutions of tannic acid (20, 40, 60, 80, 100 μg/mL) were made as a reference. Absorbance for the test and standard solutions was measured with a UV/Visible spectrophotometer (U-2900, Hitachi High-Tech Corporation, Tokyo, Japan) against the blank (distilled water) at 700 nm. The estimation of the TTC was done in triplicate. The tannin content was expressed in mg/mL of tannic acid in the coffee extracts.

#### *2.7. Sensory Evaluation*

The consumer responses of the coffee made from fermented and non-fermented coffee beans were evaluated with 50 people (students and staff members of the horticulture department) at Kangwon National University, Republic of Korea. The medium roasted coffee beans were selected for testing the consumer acceptability since the Korean people widely used the medium roasted coffee. The coffee was brewed using a coffee maker (HD7450, Philips, Nanjing, China) using 36 g of coffee powder with 500 mL of water. The prepared coffee was poured into a thermos to maintain the temperature. Each consumer was provided with coffee sample (20 mL, 60 ± 2 ◦C) in a paper cup (150 mL) and a glass of water (24 ± 2 ◦C) for cleansing palate after each taste. The scale was 1 to 7 and labeled as 1 = dislike very much, 2 = dislike moderately, 3 = dislike slightly, 4= neither like nor dislike, 5 = like slightly, 6 = like moderately, 7 = like very much.

#### *2.8. Statistical Analysis*

The results were compiled using Microsoft Excel 2013. Analysis of variance (ANOVA) was performed using SAS 9.4 software (SAS Institute, 100 Campus Drive, Cary, Raleigh, North Carolina, USA), to classify significant variations among samples.

#### **3. Results and Discussion**

#### *3.1. pH and Colony Count (log CFU*/*mL)*

The pH of the solution (the water that was used to ferment the coffee beans) was measured right after the inoculation of the yeast (0 h) and after 24 h of fermentation. A pH reduction was observed in both the yeast-inoculated and non-yeast-inoculated (control) treatments. However, the pH reduction rate was higher in the yeast-inoculated sample. The pH in the control treatment was 6.02 at 0 h and 5.78 after 24 h (Figure 1A). In the fermented treatment, the pH was reduced from 6.05 to 5.46 within 24 h of fermentation (Figure 1A). The pH of the yeast-inoculated solution showed a higher reduction compared to the non-yeast-inoculated solution. The alkalinity and acidity of the solution are expressed based on the pH values. The pH continues to decrease while fermentation takes place for various reasons. Fermentation is responsible for the production of organic acids and the absorption of basic amino acids, which substantially reduces the pH [33]. However, a small pH reduction was found in the non-yeast-inoculated treatment. This reduction was expected because the water-soluble organic acids leaked from the coffee beans into the water [21,34] and/or because of bacteria that naturally exist on the coffee beans [21]. The yeast populations were measured; initially, they were 7.66 log CFU/mL, and after 24 h, they reached 9.62 log CFU/mL (Figure 1B).

**Figure 1.** The pH in yeast inoculated and non-inoculated treatments (**A**) and yeast population (**B**).

#### *3.2. Colorimeter Data*

The fermented and non-fermented ground coffee after roasting is shown in Figure 2. A significant (*p* < 0.05) differences were observed between the yeast-fermented and non-fermented treatments of ground roasted (light roasting level) coffee with respect to the colorimetric parameter (L\* and a\*) (Figure 3A,B). The L*\** and a*\** of ground roasted coffee did not significantly differ between the fermented and control treatment in both medium and dark roasting condition. However, we observed that the L*\** value increased and the *a*\* value decreased as the roasting time increased. The b\* value was significantly higher in the fermented treatment at the light, medium and dark roasting level (Figure 3C). Supporting reports showed that fermentation of green coffee beans with *S. cerevisiae* strains [21,22], and *S. fibuligera* [22] resulted in high L\*, a\*, and b\* values compared to non-fermented coffee beans. During cocoa fermentation, gradually, a color change was observed as a result of a high amount of phenolic compounds and flavonoids, which act as a substrate of polyphenol oxidase in the presence of oxygen [35].

**Figure 2.** The fermented and non-fermented ground coffee that roasted at a different level.

**Figure 3.** Colorimeter (L\*, a\* and b\*) values of fermented roasted and ground coffee (**A**–**C**). Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

#### *3.3. Antioxidant Activity*

#### 3.3.1. SOD-Like and ORAC

The antioxidants of fermented and non-fermented coffee extract were evaluated in terms of the oxygen radical absorbance capacity (ORAC) and superoxide dismutase (SOD)-like activity. The peroxyl radical scavenging potentials of aqueous soluble components present in the coffee could be estimated more accurately with a modified ORAC assay [36,37]. There was no significant (*p* > 0.05) difference between the yeast-fermented and non-fermented coffee extracts with respect to the ORAC value in medium (Figure 4A) and dark roasted coffee. The SOD-like activity was not significantly differed between fermented and non-fermented coffee in all roasting conditions (Figure 4B). However, both ORAC and SOD-like activity were significantly lower in both treatments in the light roasting condition. The means of ORAC value for the yeast-fermented coffee extracts was 28.33, 46.08, and 47.82 μ MTE/mL in the light, medium and dark roasted coffee, respectively (Figure 4A). The means of the SOD-like activity of yeast-fermented coffee extracts was 59.56, 87.31, and 89.05% at the light, medium and dark roasting levels, respectively (Figure 4B). The ORAC value was higher by 3.96 μ MTE/mL in fermented coffee compared to non-fermented coffee in the light roasting condition (Figure 4A). We found a significant improvement in the ORAC value and SOD-like activity in the medium and dark conditions compared to the light roasted coffee regardless of the fermentation. The medium and dark roasting conditions improved the ORAC by 21.93 and 23.94 μ MTE/mL in the control treatment. However, it was increased by 17.75 and 19.49 μ MTE/mL in the fermented coffee extracts compared to light roasted coffee, respectively. This is in agreement with previous reports on the influence of roasting on antioxidant activity. Nicoli et al. [38] reported higher antioxidant activity for medium and dark roast brews. Similarly, the elevated antioxidant activity for higher degrees of roasting has been confirmed in studies [39–41]. As the roasting temperature increased the antioxidant activities of the kernel, cashew nut and testa extracts increased [42]. Several publications have described variations in coffee antioxidant contents as a cause of roasting conditions [43,44]. Del Castillo et al. [43] noticed a higher antioxidant activity in the medium roasted coffee brew. However, Perrone et al. [45]

found a greater antioxidant activity for light roast brews. The results from various investigations regarding the antioxidant activity of coffee have been considerably diverse. The causes of such variable research results can be associated with the development of melanoidin compounds, which increase the antioxidant capacity despite the reductions in the polyphenol content. Nevertheless, other studies have not detected any significant effects of roasting on antioxidant activity [46], nor any indications that roasting for a longer duration at high temperature reduce antioxidant activity [44,47,48] when polyphenol degradation is not compensated by melanoidin formation [49,50]. However, amongst other coffees, this phenomenon was noticed for dark roasted Robusta coffee [40].

**Figure 4.** The oxygen radical absorbance capacity (ORAC) and superoxide dismutase-like (SOD)-like activity of fermented coffee at different degrees of roast (**A** and **B**, respectively). Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

#### 3.3.2. DPPH and FRAP

DPPH and FRAP are among the various methods of evaluating the antioxidant properties of foods and drinks. The percentage of DPPH inhibition was higher in the fermented coffee than the non-fermented coffee in all roasting conditions (Figure 5A). Like the DPPH, the FRAP was improved in the fermented coffee in the light, medium, and dark roast types (Figure 5B). The maximum DPPH inhibition resulted from the fermented treatment in the light roasting condition (46.31%). The highest FRAP was found in the fermented coffee in the dark roasting condition (176.11 AAE μg/mL of coffee extract). In general, fermentation of green coffee beans using *W. anomalus* improved the DPPH and FRAP. Adetuyi and Ibrahim [51] reported that fermentation enhanced the DPPH radical-scavenging ability and FRAP of okra seeds. The increase in DPPH capacity after the fermentation process shows that fermentation likely has great potential in generating some metabolites with superior radical scavenging activity [52]. The percentage of DPPH inhibition dropped as the roasting time increased (from the light to dark roasting condition). The result is in agreement with Jung et al. [53], who reported that lightly roasted coffee extract has the highest antioxidant activity with a low roasting temperature and that the DPPH decreases in the dark roasted extract. However, the FRAP improved as the roasting time increased. A supporting result published by Song et al. [54] showed that as the roasting time increased from 11 to 13 min (medium-light to medium-dark) the FRAP increased as well.

**Figure 5.** The DPPH inhibition (%) and Ferric reducing antioxidant power (AAE μg/mL of coffee extract) of fermented coffee. (**A** and **B**, respectively). Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

#### *3.4. Total Phenol, Flavonoid and Tannin Content*

The TPC of yeast-fermented coffee extracts had significant differences (*p* < 0.05) compared to the non-fermented coffee in all roasting types (Figure 6). During the medium roasting condition, the highest TPC difference was observed between the fermented and non-fermented coffee. The TPC in the control treatment showed a decreasing trend as the roasting time increased (light to medium to dark). The TPC in the fermented treatment was 0.98, 1.29 and 0.91 GAEmg/mL of coffee extract

in the light, medium and dark roasting condition, respectively (Figure 6). The fermentation of green coffee beans with *W. anomalus* increased the TPC of the coffee extract by 0.09, 0.46, and 0.21 GAE mg/mL of coffee extract compared to non-fermented coffee at each degree of roasting (light, medium and dark roast, respectively) (Figure 6). Generally, fermentation improved the TPC compared to non-fermented coffee. These results are in agreement with several reports on fermented seeds, where fermentation induced an improvement in the phenolic content of seeds, such as legumes [55–59], okra seeds [51], soybeans [60], and coffee [21,22]. Similarly, fermentation elevated the phenolic and flavonoid contents and improved the antioxidant properties of the following plant seeds: chestnut, adlay, walnut, and lotus seed [61]. This might be associated with, proteolytic enzymes from the starter organism that hydrolyze the complexes of phenolics into simple, soluble-free phenols and biologically more active forms during fermentation, which are readily absorbed by organisms [56,62]. However, other researchers' findings indicate the proteolytic activities alone did not show a significant TPC increase; rather, when it was combined with a pectinase enzyme, the olive oil polyphenol content showed a significantly high increment [63]. These findings lead us to conclude *W. anomalus's* ability to produce pectinase enzymes linked with the increased TPC content in this experiment. In our experiment, the TPC was decreased as the roasting time increased, except the fermented coffee in the medium roast condition which significantly increased the TPC, regardless of the fermentation. A supporting result was published by Odžakovi´c, B., et al. [64], the TPC decreased as the roasting temperature increased. During coffee roasting the degradation of polyphenols [36,44–46], which are sensitive to heat, are affected by roasting temperature. The reduction in the polyphenol content which is linked to the extended roasting is due to the heat-sensitive nature of such compounds and the lengthened roasting duration, as well as the high processing temperature. Phenol reductions or losses during the processing steps are undesirable because of their profound effects on human health.

**Figure 6.** Total phenol contents (GAE mg/mL of coffee extract) of fermented coffee. Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

Fermentation of green coffee beans with *W. anomalous* significantly (*p* < 0.05) increased the TFC compared to non-fermented coffee in all roasting conditions (light, medium and dark) (Figure 7). TFC was approximately consistent in the control treatment in all roasting conditions. However, in the fermented coffee, the TFC was significantly higher in the light roasting compared to medium and dark roasting conditions. As shown in Figure 7, the TFC in the control treatment was 0.64, 0.67, and 0.64. The TFC in the fermented coffee at different roasting levels was 0.86 (light), 0.74 (medium), and 0.72 (dark) QE mg/mL of coffee extract. Fermentation improves the TFC content by 0.22, 0.07, and 0.08 QE mg/mL of coffee extract in the light, medium, and dark roasting conditions, respectively (Figure 7). These findings agree with several published papers on different fermented seeds, where

fermentation significantly enhanced the TFC compared to the TFC in unfermented seeds, such as in soybeans [60], legumes [45,55,56], coffee beans [21,22], and okra seeds [51]. The increase in the flavonoid content might be linked to the rise in acidic values during fermentation, which releases bound flavonoid components and makes them more bioavailable [51].

**Figure 7.** Total flavonoid contents (QE mg/mL of coffee extract) of fermented coffee. Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

Regardless of the fermentation, the average TFC from both treatments at each roasting condition was 0.75 ± 0.11, 0.71 ± 0.03, and 0.68 ± 0.04 QE mg/mL of coffee extract at the light, medium, and dark roasting levels, respectively. The average TFC value showed a decreasing trend as the roasting time increased, regardless of the fermentation. The result in our study coincides with Tiwari, B. K., et al. [65], who found that the TFC was reduced significantly as the roasting temperature increased from 80 ◦C to 120 ◦C and roasting duration proceeded from 20 min to 40 min. The cause for the reduction in the TFC at a higher temperature might be associated with the degradation of flavonoids. The preparation and processing of food may reduce the flavonoid contents depending on the techniques used [66].

The yeast-fermented coffee extracts had a significant difference (*p* < 0.05) compared to non-fermented coffee with regard to TTC in the light and dark roasting conditions (Figure 8). The TTC of non-fermented coffee was 0.53, 0.33, and 0.21 mg tannic acid/mL of coffee extract in light, medium and dark roasting conditions, respectively. In the fermented coffee, the TTC was 0.73, 0.28, and 0.15 mg tannic acid/mL coffee extract in the light, medium, and dark roasting conditions, respectively. In the light roasting condition, the tannin content was higher in fermented coffee than the control and it was lower than the control in the medium and dark roasting conditions (Figure 8). It has been reported that fermentation significantly decreased the tannin content of fermented sorghum cultivars [67], and in fermentation of *Xuan mugua* fruit with lactic acid bacteria, where it caused a significant decrease in the tannin content [68]. We have also found a supporting result in our previous experiment that indicates the fermentation of green coffee beans with *S. cerevisiae* and *S. fibuligera* strains reduced the TTC compared to non-fermented coffee [22]. Regardless of the fermentation, the TTC was reduced as the roasting time increased. The average TTC in each roasting condition was 0.63, 0.31 and 0.19 mg tannic acid mg/mL coffee extract in the light, medium, and dark roasting condition (Figure 8). Likewise, the tannin content was decreased in soya bean flour (0.01–0.30 g/100 g dry weight) [69], and 22% in maize [70]; because of soaking in water for 48 h and roasting. Tannin content has an astringent characteristic that contributes to the bitterness of coffee, so the reduction in tannins can be viewed as a positive aspect.

**Figure 8.** Total tannin contents (tannic acid mg/mL of coffee extract) of fermented coffee. Bars with different letters indicate a significant difference (*p* < 0.5) among treatments.

#### *3.5. Sensory Evaluation*

Based on the results of consumer acceptance ratings, the non-fermented coffee received a higher score than the fermented coffee in terms of its color, sourness, mouthfeel, acidity, and overall quality. However, the fermented coffee received the highest rating with respect to aroma, bitterness, and astringency. The average score for the overall quality of the coffee was 5.22 and 4.51 for non-fermented and fermented coffee, respectively (Figure 9). The average score for acidity was 3.75 for the fermented coffee and 4.15 for the non-fermented coffee. Kwak et al. [21] have evaluated the consumer acceptability of fermented green coffee beans with different yeasts, noting that one of their fermented coffee treatment acceptability ratings was lower but insignificant when compared to the control treatment. In addition, they mentioned that all the fermented coffee received lower ratings when compared to the control. Fermentation has both positive and negative influences on the flavor and aroma characteristics of coffee. Based on the overall quality rating, we have categorized the consumer responses into two groups: people who preferred the non-fermented coffee over the fermented coffee (55.48%) and people who preferred the fermented coffee over the non-fermented coffee (44.52%). A supporting result was published by Kwak et al. [21], who found that 39.4% of consumers preferred fermented coffee while 60.6% preferred non-fermented coffee by disliking the control (non-fermented) treatments based on the overall quality ratings. However, consumer acceptance evaluations are very subjective to the individual.

**Figure 9.** The consumer acceptability ratings of fermented and non-fermented coffee.

#### **4. Conclusions**

This study showed the responses of the coffee beans fermented with *W. anomalus* strain KNU18Y3. The fermentation of green coffee beans with *W. anomalus* for 24 h increased the DPPH, FRAP, TPC, and TFC when compared to non-fermented coffee, whereas the SOD-like and ORAC did not significantly differ between the fermented and non-fermented coffee beans. We have also found that the fermentation of coffee beans for 24 h is enough to modify the functionality of coffee beans. The extent of roasting had both negative and positive effects on the overall antioxidants, TPC, TFC, and TTC. The degradation of the TPC, TFC, and TTC was observed as the roasting time increased from 11.5 to 16 min, regardless of the fermentation. The fermented coffee received better ratings in terms of its aroma, bitterness, and astringency parameters. Moreover, 44.52% of participants chose the fermented coffee over the non-fermented one based on the overall quality ratings. This result shows that fermented coffee is also preferred by consumers. Since the consumer evaluation experiment was conducted blind (the participants were not informed of the coffee types), the increased antioxidants and phenolic and flavonoid compounds will probably attract more consumers when they are informed of these positive aspects of fermented coffee. While the *W. anomalus* yeast has the potential to be used for green coffee bean fermentation, further selection and evaluation of microorganisms should be continued to maximize the functionality of the coffee bean and its health benefits.

**Author Contributions:** Conceptualization, W.H.K., M.H.; methodology, M.H.; Data curation, M.H.; validation, W.H.K.; formal analysis, M.H.; software, M.H.; investigation, W.H.K.; resources, W.H.K.; funding acquisition, W.H.K.; writing—original draft preparation, M.H.; writing—review and editing, W.H.K., M.H.; supervision, W.H.K.; project administration, W.H.K. All authors have read and agreed to the published version of the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

## **E**ff**ect of Co-Inoculation with** *Pichia fermentans* **and** *Pediococcus acidilactici* **on Metabolite Produced During Fermentation and Volatile Composition of Co**ff**ee Beans**

**Alexander da Silva Vale 1, Gilberto Vinícius de Melo Pereira 1,\*, Dão Pedro de Carvalho Neto 1, Cristine Rodrigues 1, Maria Giovana B. Pagnoncelli <sup>2</sup> and Carlos Ricardo Soccol 1,\***


Received: 2 July 2019; Accepted: 19 July 2019; Published: 22 July 2019

**Abstract:** Removal of the mucilage layer of coffee fruits by a fermentation process has became an interesting strategy to improve coffee quality, which is able to assist the formation of flavored molecules. In this study, four sets of inoculation protocols were evaluated using ripe and immature coffee fruits, respectively, including (i) pure culture fermentation with *Pichia fermentans*, (ii) pure culture fermentation with *Pediococcus acidilactici*, (ii) combined fermentation with *P. fermentans* and *P. acidilactici*, and (iv) spontaneous, non-inoculated control. The initial pulp sugar concentration of ripe coffee fruits (0.57 and 1.13 g/L glucose and fructose content, respectively) was significantly higher than immature coffee pulp (0.13 and 0.26 g/L glucose and fructose content, respectively). Combined inoculation with *P. fermentans* and *P. acidilactici* of ripe coffee beans increased pulp sugar consumption and production of metabolites (lactic acid, ethanol, and ethyl acetate), evidencing a positive synergic interaction between these two microbial groups. On the other hand, when immature coffee fruits were used, only pure culture inoculation with *P. fermentans* was able to improve metabolite formation during fermentation, while combined treatment showed no significant effect. Altogether, 30 volatile compounds were identified and semi-quantified with HS- solid phase microextraction (SPME)-gas chromatography coupled to mass spectrophotometry (GC/MS) in fermented coffee beans. In comparison with pure cultures and spontaneous process, combined treatment prominently enhanced the aroma complexity of ripe coffee beans, with a sharp increase in benzeneacetaldehyde, 2-heptanol, and benzylalcohol. Consistent with the monitoring of the fermentation process, only *P. fermentans* treatment was able to impact the volatile composition of immature coffee beans. The major impacted compounds were 2-hexanol, nonanal, and D-limonene. In summary, this study demonstrated the great potential of the combined use of yeast and lactic acid bacteria to improve fermentation efficiency and to positively influence the chemical composition of coffee beans. Further studies are still required to investigate the mechanisms of synergism between these two microbial groups during the fermentation process and influence the sensory properties of coffee products.

**Keywords:** coffee processing; coffee fermentation; starter culture; coffee beverage; yeast

#### **1. Introduction**

Coffee plants are cultivated in more than 80 countries around the world, providing raw materials for a global industry valued at an excess of 10 billion US\$ [1]. Production conditions and post-harvest

operations, such as fruit harvesting, depulping, drying, and storage, have a direct impact on the quality of coffee products. Fruit harvesting is the first step in postharvest coffee processing. The heterogeneous development of coffee fruits leads to a simultaneous presence of different maturation stages in the same coffee tree, namely: (i) Green (immature) coffee fruits, presenting incomplete endosperm development and low reducing sugars content in the mucilaginous layer; (ii) cherry (ripe) fruits, presenting mucilage rich in reducing sugars, complete development of the endosperm and red or yellow exocarp color; and (iii) raisin (overripe), which are fruits showing the initial characteristics of the senescence cycle with metabolic pathway deviation for the catabolism of the nutrients accumulated in the beans [2]. In Brazil, the largest coffee producer in the world, it is estimated that 31% of the coffee fruits are harvested in the immature stage [3]. Immature coffee beans have a high content of chlorogenic acids (caffeine, trigonelline) and lower sugar content due to incomplete cycle of maturation, attributing astringency and depreciating the quality of coffee products [4,5].

After harvesting, coffee processing must begin as quickly as possible to prevent fruit spoilage by unfavorable fermentation or mold formation [6,7]. The outer layers of the coffee fruit (skin and pulp) are easily removed, while the mucilage, parchment, and silver skin are firmly attached to the beans [8]. The way that coffee growers use to remove the mucilage layer attached to the fruits classifies coffee in the international market: 'Natural coffee', where mucilage is removed by a simple method of sun-drying, known as dry processing; 'washed coffee', produced from coffee beans that undergo a relatively complex series of steps, including depulping, fermentation, and sun-drying known as wet processing; and "pulped natural coffee", which the fruits are mechanically husked and the mucilage is removed by a sun-drying process, known as semi-dry processing [9].

In the wet processing, coffee beans are submitted to underwater tank fermentation for mucilage breakdown and removal. The sugars present in the mucilage support microbial, especially yeasts and lactic acid bacteria [10]. Recent studies have been dedicated to the use of yeast and lactic acid bacteria (LAB) as pure starter cultures in post-harvest processing, in order to reduce the time required for fermentation and modulate the chemical and sensory characteristics of coffee beans [11–14]. Among the selected microorganisms, it is possible to highlight the yeast *Pichia fermentans* YC5.2 and the lactic acid bacteria *Pediococcus acidilactici* LPBC161*,* which are cultures with characteristics of efficient consumption of coffee pulp-sugars and adaptability to the stress factors of coffee processing [15,16]. Despite that the use of pure cultures offers advantages, recent studies in wine, meat, and dairy fermentations demonstrate that mixed starters are able to improve the sensorial and safety proprieties of the final product [17,18]. In this regard, the aim of this study was to evaluate the effects of co-inoculation with *Pichia fermentans* YC5.2 and *Pediococcus acidilactici* LPBC161 on metabolites produced during fermentation and the volatile composition of coffee beans.

#### **2. Material and Methods**

#### *2.1. Microorganism and Inoculum Preparation*

The selected yeast (*Pichia fermentans* YC5.2) and lactic acid bacteria (*Pediococcus acidilactici* LPBC161) strains used in this study were previously isolated and selected from spontaneous coffee fermentations, as detailed in Muynarsk et al. [15] and Pereira et al. [16]. The *P. fermentans* YC5.2 and *P. acidilactici* LPBC161 were reactivated in MRS (Merck Millipore, Burlington, MA) and YEPG broth (Himedia, Marg, India), respectively, at 28 ◦C during 24 h. Each microorganism was then grown up to a concentration of 10<sup>9</sup> CFU/mL. To reach this concentration, *P. acidilactici* LPBC161 was cultivated in Erlenmeyer containing 4 L of sugar cane molasses 3% (w/v) medium, enriched with yeast extract 0.5% (w/v), ammonium citrate 0.5% (w/v), ammonium phosphate 0.5% (w/v), sodium acetate 0.5% (w/v), Tween 80 0.1% (v/v), and manganese sulfate 0.005% (w/v) [19], and *P. fermentans* YC5.2 was grown in Erlenmeyer containing 4 L of sugar cane molasses 3% (w/v) medium enriched with yeast extract 0.5% (w/v). After incubation, the yeast and lactic acid bacteria (LAB) cells were separated from the medium by centrifugation at 5000 × *g* during 5 min, washed twice with sterile saline-peptone solution (0.1% [w/v]

bacteriological peptone (Himedia), 0.8% (w/v; NaCl (Merck)), and resuspended in sterile saline solution (0.9% (w/v) NaCl).

#### *2.2. Farm Experiments*

The field experiments were conducted at the Fazenda Baobá (21◦42 42.8 ' S, 46◦49 42.2 ' W; 1400 m above sea level) situated in São Sebastião da Grama, São Paulo state, Brazil. Ripe and immature coffee fruits (10 kg) were, respectively, deposited in 20-L plastic buckets with 5 L of water. Four sets of inoculation protocols were performed in triplicate: (i) Pure culture fermentation with *P. fermentans*, (ii) pure culture fermentation with *P. acidilactici*, (ii) combined fermentation with *P. fermentans* and *P. acidilactici*, and (iv) spontaneous, non-inoculated control. Prior to inoculation, yeast and LAB cells were counted by a Thoma hemocytometer chamber using methylene blue dye as a marker of cell viability. Then, appropriate amounts of inoculum were used to reach an initial cell population of about 7 log CFU/mL. At the end of fermentation, coffee beans were sun dried until the value of 12% of moisture was reached.

#### *2.3. Sampling and pH Measurement*

Samples (50 mL) of the liquid fraction of the fermenting coffee pulp were collected in triplicate at intervals of 12 h to monitor sugars consumption and organic acids, ethanol, and volatile compounds production. At each sampling point, the pH was measured using a digital pH meter (Requipal, Curitiba, Brazil).

#### *2.4. HPLC Analysis of Fermenting Co*ff*ee Pulp*

The concentration of reducing sugars (glucose and fructose), organic acids (citric, succinic, lactic, acetic, and propionic acids), and ethanol in coffee pulp (liquid fraction) was determined in intervals of 12 h. Aliquots of 2 mL were centrifuged at 6000 × g for 15 min and filtered through 0.22 μm pore size filter (Millipore Corp., Billerica, MA, USA). Analysis parameters were performed according to Carvalho Neto et al. [20]. The filtered samples were injected into high-performance liquid chromatograph (HPLC) system equipped with an Aminex HPX 87 H column (300 × 7.8 mm; Bio-Rad, Richmond, CA, USA) and a refractive index (RI) detector (HPG1362A; Hewlett–Packard Company, Palo Alto, CA, USA). The column was eluted in an isocratic mode with a mobile phase of 5 mM H2SO4 at 60 ◦C and a flow rate of 0.6 mL/min.

#### *2.5. GC Analysis of Fermenting Co*ff*ee Pulp*

The formation of major volatile compounds was determined in intervals of 12 h by gas chromatography. For sample preparation, aliquots (4 mL) from the liquid fraction of the fermenting coffee pulp were placed in 20 mL hermetically sealed flasks containing NaCl 5% (w/v), followed by heating during 10 min at 60 ◦C. The headspace was then collected using a glass syringe (Hamilton, Bonaduz, Switzerland) and injected into a gas chromatograph (model 17A; Shimadzu, Kyoto, Japan) equipped with a flame ionization detector at 230 ◦C. The operation conditions were as follows: A 30 m × 0.32 mm HP-5 capillary column, column temperature of 40 to 150 ◦C at a rate of 20 ◦C/min [13]. A standard curve was constructed using authentic analytical standards purchased from Sigma and concentration of the compounds was expressed as μmol/L of headspace

#### *2.6. GC*/*MS Analysis of Fermented Co*ff*ee Beans*

The volatile aroma compound composition of spontaneous and inoculated coffee beans was determined by gas chromatography coupled to mass spectrophotometry (GC-MS) according to Carvalho Neto et al. [20]. The extraction of volatile compounds from the beans samples (2 g) was performed using a headspace vial coupled to a solid phase microextraction (SPME) fiber DVB/CAR/PDMS fiber (Supelco Co., Bellefonte, PA, USA). The flasks were heated at 70 ◦C for 10 min without agitation, followed by 15 min of exposition of the fiber in a COMBI-PAL system. The compounds were desorbed into the gas chromatograph injection system gas phase (CGMS-gun TQ Series 8040 and 2010 Plus GC-MS; Shimadzu, Tokyo, Japan) at 260 ◦C. The column oven temperature was maintained at 60 ◦C during 10 min, followed by two heating ramps of 4 and 10 ◦C /min until reaching the temperatures of 100 and 200 ◦C, respectively. The compounds were separated on a column 95% PDMS/5% PHENYL (30 m × 0.25 mm × 0.25 mm film thickness). The GC was equipped with an HP 5972 mass selective detector (Hewlett Packard, Palo Alto, CA, USA). Helium was used as carrier gas at a rate of 1.0 mL/min. Mass spectra were obtained by electron impact at 70 eV and a start and end mass-to-charge ratio (m/z) of 30 and 200, respectively. The compounds were identified by comparison to the mass spectra from library databases (Nist'98 and Wiley7N).

#### *2.7. Statistical Analysis*

The data obtained of target metabolite analysis were analyzed by post-hoc comparison of means by Duncan's test and a principal component analysis (PCA). Statistical analyses were performed using the SAS program (Statistical Analysis System Cary, NC, USA). Level of significance was established in a two-sided *p*-value <0.05.

#### **3. Results and Discussion**

#### *3.1. Field Experiment*

The use of mixed fermentation instead a single culture is a practice widely applied in winemaking in order to improve the aroma complexity or mouth-feel of wines [21,22]. It offers a number of advantages over conventional single-culture fermentations, including higher microbial growth rate and metabolite yield, better utilization of the substrate, and complex formation of aromatic compounds [23]. This work represents the first study on a mixed culture in the coffee beans fermentation process. We experimentally tested the impact of the combination of two selected cultures (*P. fermentans* YC5.2 and *P. acidilactici* LPBC161) in terms of the fermentation efficiency and volatile composition of coffee beans. The experiments were performed with individual and combined inoculations in ripe and immature coffee beans, compared to a spontaneous process. The changes in major non-volatiles (sugars, organic acids, and ethanol) and volatiles metabolites were quantified in the course of the fermentation time. The initial pulp sugar concentration of ripe coffee fruits (0.57 and 1.13 g/L glucose and fructose content, respectively) was significantly higher than immature coffee pulp (0.13 and 0.26 g/L glucose and fructose content, respectively; Figure 1). The low levels of sugars in the case of immature coffee are the consequence of incomplete maturation cycle fruits [24]. In all fermentation processes, the sugar concentration showed an increase during the initial 12 h. This phenomenon can be associated with the hydrolysis of pectin, cellulose, sucrose, and other coffee pulp complexes carbohydrates, into monomers of glucose and fructose [25,26]. After this increase, both glucose and fructose were partially consumed, resulting in a residual concentration of around 0.37 and 1.51 g/L (ripe coffee pulp) and 0.19 and 0.74 g/L (immature coffee pulp) of glucose and fructose, respectively. Residual pulp sugars are generally observed after the coffee fermentation process, mainly associated with the short fermentation cycle [14,27,28]. However, fructose consumption was more efficient in the treatments that the yeast was used (i.e., *P. fermentans*-pure culture and combined treatment with *P. fermentans* and *P. acidilactici*) than *P. acidilactici* pure culture and spontaneous assay (Figure 1). The yeast's ability to withstand stress tolerance factors and the production of pectinolytic enzymes confer advantages in comparison to lactic acid bacteria [16,29]. In addition, the low availability of initially willing nutrients in immature coffee pulp [24] may have restricted the development of *P. acidilactici*, showing poor sugar consumption (Figure 1B). Lactic acid bacteria are further distinguished by their limited biosynthetic abilities, being unable to synthesize multiple cofactors, vitamins, purines, pyrimidines, and other nutrients [30].

**Figure 1.** Pulp sugar consumption, organic acid production, and pH monitoring of inoculated (pure culture with *Pichia fermentans*, pure culture with *Pediococcus acidilactici*, and combined fermentation with *P. fermentans* and *P. acidilactici*) and spontaneous fermentation of ripe (**A**) and immature (**B**) coffee fruits. The significance of the results was assessed using an ANOVA with Duncan's post-hoc test at *p* < 0.05. Different lowercase letters (a, b, c, d, e, f) indicate significant differences within the same process (ripe and immature coffee beans) over fermentation time.

Lactic acid showed a significant increase through fermentative processes, reaching maximum concentration of ≥1.45 and ≥0.53 g/L in the ripe and immature treatments, respectively (Figure 1). Basal concentrations of acetic acid (≤0.01 g/L) were detected in all the processes, which can be associated with yeast metabolism or the heterofermentative nature of *P. acidilactici* [31,32]. Overfermentation acids, such as propionic and butyric acids, were not detected in both ripe and immature treatments. In this sense, the acidification of fermenting coffee pulp can be attributed mainly to lactic acid content. As expected, while the lactic acid concentration increased, the pH decreased progressively during all fermentation processes (Figure 1). Lactic acid is an important end-metabolite associated with coffee fermentation, which assists in the coffee-pulp acidification process without interference in the final product (Figure 1). The pH monitoring is a crucial parameter, since pH values below 4.5 are used as to indicate the end of the coffee fermentation process [33–35]. In immature coffee treatments, a pH higher than 4.5 was reported, which may be attributed to the insufficient development of *P. acidilactici*.

Ethanol and ethyl acetate were the major volatile compounds detected during fermentation processes (Figure 2). Interestingly, combined inoculations with *P. acidilactici* and *P. fermentans* resulted in a significant increase in the production of these metabolites when compared to pure cultures and a spontaneous process. The higher values of ethanol (27.04 and 14.8 μmol/L) and ethyl acetate (1.63 and 1.21 μmol/L) were reached after 24 h of ripe and immature combined fermentations, respectively. This agrees with the findings of Sun et al. [36] and Cañas et al. [37] that demonstrated an increase of ethyl- and acetate esters as a result of the co-inoculation of LAB and yeasts in wine fermentation. The significant sugar consumption and lactic acid, ethyl acetate, and ethanol production in treatments with combined inoculations indicated an ecological interaction between these two microbial groups. The complex nature of this interaction is highlighted by the observations that (i)the autolysis of yeasts release nutrients, such as amino acids, polysaccharides and riboflavin, favorable for bacterial growth, and that (ii) the acidification of the fermentation media by LAB creates a prone environment for yeast development [9,38,39]. These positive interactions have been shown to promote desired sensory attributes in wine, sourdough, and yogurt. However, information about these mechanisms in coffee fermentation is scarce [40].

**Figure 2.** Concentration of volatile compounds produced in the course inoculated (pure culture with *P. fermentans*, pure culture with *P. acidilactici*, and combined fermentation with *P. fermentans* and *P. acidilactici*) and spontaneous fermentation of ripe (**A**) and immature (**B**) coffee fruits. The significance of the results was assessed using an ANOVA with Duncan's post-hoc test at *p* < 0.05. Different lowercase letters (a, b, c, d, e, f) indicate significant differences within the same process (ripe and immature coffee beans) over fermentation time.

Other minor volatile compounds that increased during the fermentation processes were 1-decanol, ethyl-acetaldehyde, and hexyl acetate (Figure 2). Yeast and lactic acid bacteria generate ethyl-acetaldehyde by a condensation reaction between fatty acids and an alcohol molecule [41], while 1-decanol can be derived from amino acid catabolism via the Ehrlich pathway [16,42]. The presence of higher concentrations of linalool using immature fruits can be associated with the inferior maturation stage of the coffee beans, since this compound has been considered a volatile marker of coffee beverages produced from immature fruits [43].

#### *3.2. Co*ff*ee Beans Chemical Composition*

Over 900 volatile compounds have already been identified in green and roasted coffee beans [27,44]. Among the major volatiles found, pyrazines, furans, ketones, aldehydes, higher alcohols, esters, and sulphur compounds can be highlighted [45–47]. Although some of these flavor-active compounds originate from the beans itself, recent studies have revealed that microbial-derived metabolites can also diffuse into the beans [11,14,27,33,48–50]. Upon characterization of the volatile composition of fermented coffee beans, it was observed that inoculation of *P. fermentans* and *P. acidilactici*, both in pure and combined treatments, resulted in the modulation of the volatile constitution of coffee beans. A total of 30 compounds were identified in fermented ripe coffee beans, including higher alcohols (seven compounds), aldehydes (six compounds), and terpenes (three compounds; Table 1). Among these, 1-hexanol, 2-heptanol, phenylethyl alcohol, and benzeneacetaldehyde were the major volatiles found. Single inoculation of *P. fermentans* and *P. acidilactici* resulted in the formation and diffusion of some volatile compounds, such as 3-octanol, 2-heptenal, benzaldehyde, dodecanal, and D-limonene, that were not detected in a spontaneous process. These compounds are strictly related to both yeast and LAB metabolism, such as aldehydes and higher alcohols formed from the catabolism of coffee pulp amino acids, and terpenes through mevalonic acid pathway or released from glycoside precursors during fermentation [10,51,52].

**Table 1.** Concentration of volatile compounds (Area\*105) in ripe coffee beans after single cultures, a combined treatment, and a spontaneous assay. Means of triplicatein each row bearing the same lowercase letters (a, b) are not significantly different (*<sup>p</sup>* > 0.05) from one another using Duncan's Test (mean ± standard variation).




Interestingly, coffee beans generated from combined treatments showed significantly increased (*p* < 0.05) of specific volatile compounds, such as benzeneacetaldehyde, 2-heptanol, and benzylalcohol. These findings are in accordance with Englezos et al. [18] and Plessas et al. [53], which evidences that mixed treatments of yeast and LAB starter cultures enable higher production of esters, aldehydes, and higher alcohols in sourdough and wine fermentations when compared to single inoculations. However, further studies are required to evidence the metabolic pathways associated with the positive interaction between these microorganisms in coffee products.

Chemical analysis of immature coffee beans revealed a composition with lower diversity and concentration of volatile compounds (Table 2). A total of 19 compounds were detected, including higher alcohols (four compounds), organic acids (three compounds), and aldehydes (three compounds). *P. fermentans*-single inoculation resulted in coffee beans with significantly higher concentrations (*p* < 0.05) of 2-hexanol, nonanal, and D-limonene when compared to the spontaneous process. These compounds are commonly attributed to *Pichia* metabolism [10,54,55]. This corroborates with results from fermentation process monitoring, which demonstrated intense microbial activity of *P. fermentans* in immature coffee pulp. On the other hand, coffee beans derived from *P. acidilactici-*pure culture and combined treatment showed no significant increase (*p* > 0.05) in the volatile constituents when compared to the control (spontaneous process). This fact can be correlated to the insufficient growth of the LAB starter culture in the nutrient-scarce environment from the pulp of immature coffee beans. The auxotrophism of several amino acids turns LAB directly dependent on a rich growth medium for its full development [31].

**Table 2.** Concentration of volatile compounds (Area\*105) in immature coffee beans after single cultures, a combined treatment, and a spontaneous assay. Meansof triplicate in each row bearing the same lowercase letters (a, b, c) are not significantly different (*<sup>p</sup>* > 0.05) from one another using Duncan's Test (mean standard variation).


±



In order to explain the chemical characteristics and grouping of the samples, the parameters in Tables 1 and 2 were analyzed by a PCA (Figure 3). The first and second principal components explained, together, 73.66% of the total variability within the data. The samples were categorized into two clusters, *viz.,* ripe and immature coffee beans. This distinction was mainly related to the richer constitution of volatiles of ripe coffee beans relative to immature treatments. In addition, the presence of specific compounds (benzyl alcohol, phenylethyl alcohol, benzeneacetaldehyde, decanal, and D-limonene in ripe coffee beans, and furan-2-pentyl, 2-methyl-butanoic acid, and pyrazine, 2-methoxy-3-(2-methylpropyl) in immature coffee beans) also contributed to the separation of ripe and immature coffee beans in the PCA analysis. Interestingly, only the treatment with *P. fermentans* grouped immature coffee beans in the positive axis, which corroborates with the better yeast' adaptation and generation of volatiles in immature coffee pulp.

**Figure 3.** Principal component analysis (PCA) of volatile compounds (lozenges) identified in the different treatments of ripe (open circles) and immature (closed circles) coffee beans. Abbreviations: *SR—*spontaneous, ripe control; *PiR—Pichia* inoculation in ripe coffee beans; *PeR—Pediococcus* inoculation in ripe coffee beans; *MR*—mixed (*Pichia* plus *Pediococcus*) inoculation in ripe coffee beans; *SI—*spontaneous, immature control; *PiI—Pichia* inoculation in immature coffee beans; *PeI—Pediococcus* inoculation in immature coffee beans; *MI—*mixed (*Pichia* plus *Pediococcus*) inoculation in immature coffee beans. 1—butanoic acid, 3-methyl; 2—butanoic acid, 2-methyl; 3—hexanoic acid; 4—1-hexanol; 5—2-heptanol; 6—5-methyl-2-hexanol; 7—2-hexanol; 8—1-octen-3-ol; 9—3-octanol; 10—benzylalcohol; 11—phenylethyl alcohol; 12—butanoic acid, 2-methyl, ethyl ester; 13 - butanoic acid, 2-methyl, ethyl ester; 14—methyl salicylate; 15—2-heptenal; 16—benzaldehyde; 17—dodecanal; 18—nonanal; 19—benzeneacetaldehyde; 20—decanal; 21—2-heptanone; 22—pyridine, 2,3-dimethyl; 23—pyridine, 2,6-lutidine; 24—butyrolactone; 25—linalool; 26—D-limonene; 27—anethole; 28—furan-2-pentyl; 29—styrene; 30—tetradecane; 31—2(3)-furanone, dihydro-5-methyl; 32—pyrazine, 2-methoxy-3-(2-methylpropyl); 33—hexadecane.

#### **4. Conclusions**

This is the first study investigating the impact of co-inoculation with yeast and LAB on the fermentation of ripe and immature coffee fruits. Among the different treatments, combined inoculations with *Pichia fermentans* YC5.2 and *Pediococcus acidilactici* LPBC161 in ripe coffee fruits showed interesting features. It was possible to reach increased coffee pulp-sugar consumption and production of metabolites (lactic acid, ethanol, and ethyl acetate), evidencing a positive synergic interaction between these two microbial groups. On the other hand, when using immature coffee fruits, only *Pichia fermentans* was able to improve metabolite formation during fermentation and impact volatile composition of resulting coffee beans. This may be due to the high nutritional requirement of LAB species and poor adaptability in immature coffee pulp. Howsoever, since immature coffee beans usually have a low quality because the formation of flavored precursors is incomplete, yeast metabolism has great potential to add flavor quality to these beans.

Chemical analysis revealed a more complex volatile composition of fermented coffee beans from combined treatment in relation to pure inoculations and spontaneous process. The major compounds impacted were benzeneacetaldehyde, 1-hexanol, benzylalcohol, 2-heptanol, and phenylethyl alcohol, which are reported as important aroma-impacting compounds. Thus, this study shows the great potential of combined inoculation for the formation of desirable aroma compounds and production of specialty coffees. Further studies are still required to investigate the mechanisms of synergism between yeast and LAB and influence on sensory properties of coffee products.

**Author Contributions:** C.R.S. and G.V.d.M.P. designed the experiments. C.R. conducted the physicochemical characterization of fermenting coffee pulp. A.d.S.V. and D.P.d.C.N. performed the experiments and wrote the manuscript. C.R.S., G.V.d.M.P., and M.G.B.P., reviewed and edited the manuscript. All authors read and approved the final manuscript.

**Funding:** This work was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (project number 429560/2018-4).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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