Dynamics of physicochemical factors and microbial communities during ripening fermentation of Pixian Doubanjiang, a typical condiment in Chinese cuisine

Food Microbiology 86 (2020) 103342

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Dynamics of physicochemical factors and microbial communities during ripening fermentation of Pixian Doubanjiang, a typical condiment in Chinese cuisine

T

Liang Zhanga, Zhenmin Chea, Weizhen Xua, Peng Yueb, Rui Lia, Yufeng Lia, Xiaofang Peic,d, Peibin Zengc,d,∗ a

Key Lab of Food Biotechnology of Sichuan Province, College of Food & Bioengineering, Xihua University, Chengdu, 610039, China Sichuan Dandan Pixian Soybean Paste Company Limited, Chengdu, 611730, China West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 61000, China d West China School of Public Health and Healthy Food Evaluation Research Center, Sichuan University, Chengdu, 61000, China b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Doubanjiang ripening Physicochemical factors Microbial communities Flavor

As the spirit of Chinese Sichuan cuisine, Pixian Doubanjiang (DBJ) is an indispensable flavor condiment and has been widely used for centuries, which is made from red pepper (Capsicum annuum L.), meju and brine after open ripening fermentation. In this study, the physicochemical factors including pH value, titratable acidity, moisture, organic acids, free amino acids and volatile components etc., were identified; the compositions of microbial communities and representative microbiota were investigated; the correlations between physicochemical factors and representative microbial taxa were analyzed, at different ripening stages. The results indicated that the organic acids were all relatively stable starting from the 12th month; most of the free amino acids (17/20) reached the peak concentrations at the 6th month and 28 volatile components were considered as major odorant flavors in DBJ. Zygosaccharomyces rouxii could be the key microorganism associated with 10 volatile components to the maturing of DBJ flavor. The comprehensive analysis on the physicochemical changes related to the succession of microbiota is expected to help us understand the maturing of the taste and flavor in DBJ production.

1. Introduction Doubanjiang (DBJ), a traditional food fermented by red pepper (Capsicum annuum L.) and meju (Li et al., 2017), has been consumed for centuries as a flavoring ingredient and protein source in China. Pixian DBJ has been honored as the spirit of Sichuan Cuisine, which is welcomed globally with its fascinating spicy flavor (Zhu et al., 2013). Generally, there are two types of DBJ products circulating in the market according to the ripening process (Li, 2008). First, DBJ from mature stage (fermented for 12–18 months) is usually used for stir-frying dishes such as: Mapo tofu and Boiled meat, for its intense taste and bright red in appearance. Then, DBJ from deep-mature (DM) stage (over 24 months) is commonly adopted in hotpot for its mellow and harmonious tastes. Several steps are involved to produce DBJ: 1) Preparation of DBJmeju, which is also called pre-fermentation. Broad bean (Vicia faba L.) is prepared by soaking, steaming, and subsequent mixed with wheat

∗

flour (Triticum aestivum L.) and 10–12% w/v salt inoculated with Aspergillus oryzae for about 2–3 months (Fig. 1A); 2) Alike sauerkraut fermentation, red pepper is washed, cut into small pieces (approx. 1–2 cm) and placed in jars containing 10–15% w/v salt at room temperature for storage (Fig. 1B); 3) The DBJ-meju is mixed with brine (20% w/v salt) and red pepper, and then fermented for several months or years depending on the temperature, weather, environment, flavor and taste characteristics, to reach the market demands. This process is called ripening fermentation (Fig. 1C). The suites of ripening fermentation manufacturing processes and microbial consortia significantly influence the qualitative characteristics of fermented DBJ products with profound alterations in the metabolite and enzyme compositions governing their physicochemical factors such as organic acids, amino acids and volatiles, which jointly determine the taste, texture and other properties of DBJ. Previous literature describes the bacterial community in DBJ-meju where the Tetragenococcus, Lactobacillus, Staphylococcus, Acinetobacter,

Corresponding author. West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 61000, China. E-mail address: [email protected] (P. Zeng).

https://doi.org/10.1016/j.fm.2019.103342 Received 15 February 2019; Received in revised form 23 July 2019; Accepted 24 September 2019 Available online 27 September 2019 0740-0020/ © 2019 Published by Elsevier Ltd.

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Fig. 1. The process diagram for doubanjiang (DBJ) fermentation. (A) Preparation of DBJ-meju; (B) The process for preparing red pepper-Pehtze; (C) Ripening fermentation process. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

bottom of fermentation tank after the procedure of timely stirring. The obtained samples (approximate 1.0–1.5 kg in total) were mixed evenly, packed in sterile self-sealing bags, quickly transported to the laboratory (within 1 h) and then stored at −80 °C. All samples underwent triplicate testing for the physicochemical analysis.

Pseudomonas and Streptococcus were the major genera (Li et al., 2017). Lactic acid bacteria (LAB) and Enterobacteriaceae are critical within the first three months during DBJ ripening, and certain numbers of volatile components (VCs) such as phenethyl alcohol, linalool, 3-methylbutanal, 2-methylbutanal, furfural, benzaldehyde, 5-methylfurfural, benzene acetaldehyde and 4-ethyl-2-methoxyphenol are important to form the DBJ flavor (Li et al., 2016). However, little is known on the fungal community, succession of bacterial and fungal population, and changes of organic acids (OAs) and free amino acids (FAAs) during ripening, as well as the potential roles and relationships for microbiota to these physicochemical changes. In this study, we applied 16S rDNA and ITS rDNA sequencing using the Illumina MiSeq platform to describe the composition and succession of microbial communities during the DBJ ripening fermentation. The physicochemical changes associated with the DBJ taste and flavors were also investigated including OAs, FAAs and VCs. The aim of this study was to explore the succession of bacterial and fungal community, physicochemical changes, and to assess the interrelationships between microbiota and physicochemical factors, which could lead to a better understanding of the maturing of taste and flavor during DBJ ripening process.

2.1.2. Physicochemical analysis The pH level was determined by a pH meter (Thermo Fisher Scientific, Waltham, USA). Changes of moisture during fermentation were determined by the dry/wet weight measurement method at 105 °C. Total titratable acidity (TA) was measured by 0.02 M NaOH yielding a titration endpoint at pH 8.2 as stipulates by National standard of China GB/T 5009.40 (Zhao et al., 2019). The amino type nitrogen (ATN) was quantified according to the formalin titration method (Xia et al., 2014). Extraction of Aflatoxin B1 (AFB1) from DBJ was performed according to the instruction of the producer supplied with the quantitative AFB1 test kits (R-Biopharm Corp, Darmstadt, Germany). Red pigment content was determined by a method described previously with some modifications (Wang et al., 2018). Briefly, the DBJ samples were dried in a vacuum freeze drier (precooling 30 min at −50 °C, 10 Pa, drying at 65 °C of 24 h). Then, a pulverized 10.0 g sample was extracted with 10 mL of acetone. After incubation for 30 min in ice bath in the dark, the mixture was centrifuged at 10,000×g for 5 min at 4 °C, and the extract was transferred to a clean tube. Samples were re-extracted three times and mixed together. Red pigment was quantified at 460 nm using a UV spectrophotometer (Beijing Purkinje General Instrument, Beijing, China).

2. Materials and methods 2.1. Sample collection and physicochemical analysis 2.1.1. Sample collection The DBJ samples were manufactured in the factory of a well-known brand in China (Pidu district, Chengdu city, Sichuan). The samples during the ripening fermentation process were collected at 1, 3, 6, 12, 18, 24 and 36 months, representing three stages of DBJ fermentation: initial-mature (IM, 1–6 months), mature (12–18 months) and deepmature (DM, 24–36 months). The samples were scooped from one fermentation tank at three different sites: the top (0–20 cm bellow the upper edge), the middle (40–50 cm below the upper edge) and the

2.1.3. Organic acids profiles The contents of eight organic acids (lactic acid, formic acid, acetic acid, citric acid, malic acid, succinic acid, tartaric acid and oxalic acid) in the DBJ samples were analyzed by HPLC with UV detector. The separation was performed on a column (Phenomenex, Torrance, USA) at 35 °C. The mobile phase consisted of Ammonium phosphate ((NH4)2·HPO4, pH 2.8, A) and 95% Methanol (CH3OH, B) using a 2

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Chengdu Institute of Biology. Sequence data have been deposited in the Sequence Read Archive under BioProject accession PRJNA544161.

gradient program of 99% (A) in 0–8 min, 99-85% (A) in 8–12 min, 8580% (A) in 12–15 min, 80% (A) in 15–30 min. The mobile phase was maintained at 0.8 mL/min, and the detected wavelength of the UV detector was 220 nm.

2.3. Bioinformatic analysis on microbial communities and the correlations to physicochemical factors

2.1.4. Analysis of volatile components The profiles of volatile components during DBJ ripening were analyzed by utilizing SPME-GC/MS methods (Luo et al., 2018a, 2018b). Briefly, 5 g of each ground DBJ and 5 mL distilled water were transferred to a 15 mL vial. This vial was then tightly capped with a silicon septum and a 50/30 mm divinylbenzene/carboxen/poly (dimethylsiloxane) coated fiber (Supelco, Bellefonte, USA) was inserted into the headspace of the vial for the VCs extraction at 55 °C water bath for 30 min. GC/MS analyses were performed on a Shimadzu gas chromatograph (Shimadzu, Kyoto, Japan). Separation of VCs was performed on a DB-5MS column (Agilent, Santa Clara, USA). Helium was used as a carrier gas at a constant flow rate of 1 mL/min. Oven temperature was maintained at 40 °C for 2 min, programmed at 3 °C/min to 160 °C, thereafter programmed at 6 °C/min to 200 °C and held for 3 min. The interface temperature was set at 250 °C. The mass spectrometer was operated in electron impact mode with the electron energy set at 70 eV and a scan range of 40–600 m/z. The temperature of MS source and quadrupole was set at 230 and 150 °C, respectively. Each VC was identified using the National Institute of Standards and Technology (NIST) library. The relative percentages of the detected peaks were obtained by peak-area normalization.

The raw sequences were trimmed and filtered to remove low-quality reads using the QIIME software (Version 1.9). The high-quality reads were merged to generate the 16S rDNA V4 fragment sequences using FLASH software. Chimera sequences were filtered out using the Gold database by UCHIME (version 4.2.40). All quality filtered sequences were then clustered into operational taxonomic units (OTUs) with a threshold of 97% sequence similarity, by utilizing UPARSE software (Version 7.0). The representative sequences for each OTU was taxonomically assigned to the silva database (16S rDNA) and unite database (ITS) using the RDP classifier. Then, OTUs were processed by removing chloroplast sequences, chondriosome sequences, and unclassified sequences. The normalized OTU abundance profile was generated by utilizing a standard sequence number corresponding to the sample with the least sequences. Based on the normalized OTU abundance profile, the four alpha diversity indices (Chao1, Shannon, Observed species, and Phylogenetic distance whole tree) were calculated to estimate the species diversity and richness for each sample using QIIME software. Subsequent the differences of samples in OTU-level were evaluated through the PCoA based on Bray-Curtis by using R software. Moreover, the linear discriminant analysis (LDA) effect size (LEfSe) algorithm was performed to identify the representative bacterial and fungal taxa of each phase of bean paste. Correlations between bacteria and fungi, the physicochemical factors and significantly enriched OTUs were calculated using Spearman's rank correlation. Significant correlations are shown using Heatmap in R software.

2.1.5. The free amino acids analysis The profiles of FAAs were analyzed using an amino acid analyzer (Biochrom, Cambridge, UK) as previously reported with some modifications (Zhu et al., 2016). Briefly, 1 g of DBJ was weighed into a 10 mL plastic tube and vortex-mixed with 5 mL of 4% sulfosalicylic acid solution. Then the mixture was centrifuged at 8000 r/min for 10 min after being left at 4 °C for 24 h. FAAs were determined after filtration of the supernatant.

3. Results 3.1. Changes of physicochemical factors during ripening fermentation

2.2. Illumina Miseq sequencing on 16S rDNA and ITS region 3.1.1. Fermentation features and organic acids profiles The pH value slightly increased from the first to the 12th month (4.58–4.65) and decreased to 4.39 in the 36th months, while the TA sharply dropped from 1.6 to 0.69 g/100 g from the first to the third month and kept rising to 1.49 g/100 g in the 36th month (Fig. 2A). The moisture, AFB1 and pigment all decreased from 57.2 g/100 g, 3.46 μg/ kg and 0.7 (OD460nm) in the first month, to 42.5 g/100 g, 1.53 μg/kg and 0.45 (OD460nm) in the 36th month. Conversely, the content of ATN increased during the ripening fermentation, peaked in the 36th month on concentration of 0.36 g/100 g, which approximately doubled than that from the first month (Fig. 2B). The salt concentration slightly increased from approximate 15% w/v in the 1st month to about 20% w/v in the 36th month. Out of eight OAs, four (malic acid, tartaric acid, acetic acid, and lactic acid) displayed the consistent trends as that observed in TA, dropping within the first to third month and then increasing. Oxalic acid increased at beginning 6 months and reached a plateau until the 36th month, which is similar to the citric acid with plateau phase starting from the 12th month. Few variations were observed for fumaric acid and succinic acid during ripening fermentation. Interestingly, the contents of eight organic acids were all relatively stable between the 12th and 36th month (Fig. 2C).

Total DNA was extracted from 0.5 g DBJ sample using Ezup Genomic DNA Extraction Kit for Soil (Sangon Biotech, Shanghai, China) according to the instruction of manufacturer. The DNA concentration and quality were checked using a NanoDrop Spectrophotometer (NanoDrop Technologies, Montchanin, USA). Extracted DNA was diluted into 10 ng/μL as template for further amplification. The V4–V5 region of 16S rDNA genes was amplified with universal primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 909R (5′-CCCCGYCAATTCMTTTRAGT-3′). The PCR reaction (25 μl) consisted of 5 ng of total DNA, 1 Unit of EX Taq (TaKaRa, Dalian, China), 1 × Ex Taqbuffer, 0.2 mM of each dNTP and 0.4 μM of each primer. Amplification condition consisted of an initial denaturation step of 94 °C for 5 min, followed by 30 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 50 s with a final extension at 72 °C for 10 min. For fungi, the internal transcribed spacer (ITS) regions were amplified with the primers ITS4 (5′-TCCTCCGCTTATTGATATGC-3′) and ITS3_KYO2 (5′-GATGAAGAACGYAGYRAA-3′). The PCR reaction (25 μl) consisted of 10 ng of total DNA, 1 Unit of EX Taq (TaKaRa, Dalian, China), 1 × Ex Taqbuffer, 0.2 mM of each dNTP and 0.4 μM of each primer. Amplification condition consisted of an initial denaturation step of 94 °C for 3 min, followed by 30 cycles of 94 °C for 40 s, 56 °C for 60 s, and 72 °C for 60 s with a final extension at 72 °C for 10 min. The sequencing sample was prepared using a TruSeq DNA kit according to manufacture's instruction. The purified library was diluted, denatured, re-diluted, mixed with PhiX (equal to 30% of final DNA amount) as described in the Illumina library preparation protocols, and then applied to an IlluminaMiseq system for sequencing with the Reagent Kit v2 2 × 250 bp at the Environmental Genome Platform of

3.1.2. The free amino acids profiles Out of 20 FAAs identified, Glu had the highest concentration (2.36–3.44 mg/g), followed by Pro (2.1–3.04 mg/g), Asp (1.34–2.62 mg/g), Asn (1.13–2.72 mg/g) and Arg (0.77–1.45 mg/g), representing more than half of the total content (Fig. 3). Gln and Cys were scarcely detected except in the first or/and the third month, while 3

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Fig. 2. Changes in the pH value and titratable acidity (A); moisture, amino nitrogen, aflatoxin B1 and pigment (OD460nm) (B); and eight organic acids (C). Data are given as mean ± standard deviations (n = 3).

3.1.3. The profiles of volatile components More than 140 VCs were detected by GC-MS, among which a total of 80 VCs were identified at least in two samples or above the peak area percent of 0.1% were recorded (Table S1). Further, 28 VCs with high

low levels of His and Met were observed at concentration less than 0.25 mg/g in DBJ. Notably, most of the FAAs (17/20) reached the highest concentrations in the 6th month during the ripening fermentation.

Fig. 3. Changes in 20 free amino acids identified by amino acid analyzer during Doubanjiang ripening fermentation process. Data are given as mean ± standard deviations (n = 3). *Abbreviation: γ-ABA, gamma-amino butyric acid. 4

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Table 1 The 28 major volatile compounds. No

Volatile compounds

Alcohols (n = 7) 1 Ethanola 2 Isoamylola 3 Furfuryl alcohola 4 Benzyl alcohol 5 Linaloola 6 Phenyl ethyl alcohol 7 α-terpineola Aldehydes (n = 10) 8 Isobutyraldehyde 9 3-Methylbutanala

Fermentation stages (Peak area percentage, %)

Sensorial descriptor

References

Initial-mature

Mature

16.25 ± 3.85 1.71 ± 0.06 4.85 ± 0.36 0.09 1.95 ± 0.08 9.08 ± 1.13 0.99 ± 0.07

5.65 0.77 2.96 0.29 3.05 6.56 1.59

0.14 0.14 0.49 0.11 0.69 0.69 0.24

3.51 ± 1.6 0.96 ± 0.09 1.98 ± 0.33 0.05 ± 0.04 2.68 ± 0.4 8.1 ± 2.95 1.12 ± 0.17

sweet Malty, bitter, chocolate Burnt sweet, flower flower, lavender Honey-like oil, anise, mint

(Lee et al., 2010) Frauendorfer and Schieberle (2008) Flavor databaseb (Jide Adedeji et al., 1991) (Beaulieu and Stein-Chisholm, 2016) (Beaulieu and Stein-Chisholm, 2016) (Jide Adedeji et al., 1991)

0.03 0.61 ± 0.08

0.61 ± 0.08 0.52 ± 0.24

0.31 ± 0.2 1.62 ± 0.34

pungent, malty, green Chocolate, malty

(Jide Adedeji et al., 1991) (Counet et al., 2002; Frauendorfer and Schieberle, 2006) (Counet et al., 2002; Frauendorfer and Schieberle, 2006) Carrapiso et al. (2002) (Lee and Noble, 2003) (Valim et al., 2003)

± ± ± ± ± ± ±

Deep-mature

10

2-Methylbutanala

0.39 ± 0.19

0.5 ± 0.23

1.62 ± 0.54

Chocolate, malty

11 12 13

a

0.31 ± 0.17 0.45 ± 0.11 0.2 ± 0.02

1.35 ± 0.34 0.98 ± 0.09 0.37 ± 0.21

0.42 ± 0.07 1.05 ± 0.38 1.3 ± 0.91

1.24 ± 0.22 3.2 ± 0.87 0.29 ± 0.03 0.25 ± 0.04

1.56 ± 0.18 5.16 ± 0.08 0.56 ± 0.09 0.4 ± 0.16

2.96 ± 0.91 7.14 ± 1.78 0.52 1.32 ± 0.86

grass, tallow, fat bread, almond, sweet almond, caramel, burnt sugar almond, burnt sugar Fruity, rosy Soapy Roasted cocoa, sweet

0.55 0.39 2.72 0.51

0.32 0.14 1.08 2.47

0.25 ± 0.16 0.04 ± 0.01 1 ± 0.03 4.3 ± 0.82

apple peel, fruit Rosy, honey leaf Fermented Tomato Juice

(Schnermann, 1997) (Feng et al., 2015) Flavor database Liu et al., (2018)

Hexanal Furfural 5-Methyl furfural

14 Benzaldehydea 15 Benzene acetaldehydea 16 Nonanala 17 5-Methyl-2-phenyl-2-hexenal Ketones (n = 4) 18 Ethyl hexanoate 19 Ethyl phenylacetatea 20 Ethyl lauratea 21 Ethyl tridecanoatea Acids (n = 2) 22 Acetic acida 23 Isovaleric acid Phenols (n = 2) 24 4-Ethylphenol 25 4-Ethyl-2-methoxypheno Heterocyclics (n = 3) 26 2,6-Dimethylpyrazine 27 2-Acetylpyrrole 28 Tetramethylpyrazine

± ± ± ±

0.07 0.09 0.42 0.02

± ± ± ±

0.13 0.04 0.03 0.18

(Reda Triqui, 1995) (Gu et al., 2013) (Beaulieu and Stein-Chisholm, 2016) (Owusu et al., 2012)

12.37 ± 0.82 0.6 ± 0.12

27.08 ± 6.35 0.41 ± 0.07

15.67 ± 0.62 0.44 ± 0.17

sour sweat

(Valim et al., 2003) (Schnermann, 1997)

1.99 ± 0.05 10.42 ± 5.6

2.06 ± 0.78 11.25 ± 1.69

2.59 ± 1.51 10.79 ± 8.03

Spicy Burnt, spicy

Feng et al., (2014) (Feng et al., 2014)

0.15 ± 0.04 0.3 ± 0.04 0.07 ± 0.01

0.23 0.45 ± 0.2 0.34 ± 0.04

0.62 ± 0.55 2 ± 1.48 0.4 ± 0.04

Nutty, coffee, green Bread, walnut, licorice Cocoa, mocha, milk coffee

Perez-Boada et al., (2005) Perez-Boada et al., (2005) (Counet et al., 2002; Perez-Boada et al., 2005)

Data analysis was performed using Graphpad Prism 7 software, and the results of this set of data were expressed as mean ± standard deviation (SD). a Using one-way ANOVA, a value of P < 0.05 is considered significant. b Odour descriptions are based on Flavor database (http://www.flavornet.org/flavornet.html).

samples (each two from the 24th and 36th month) from DM stage seemed more close to each other in fungi. In addition, the samples belonging to IM stage distributed more widely both in bacteria and fungi, indicating the possible higher variations of microbiota on IM stage than the other two stages. The alpha diversities of the microbial community during DBJ ripening were evaluated by the indices including Observed species, Chao1, and Shannon (Table S2). The index of observed species was selected to be visualized. As shown in Fig. 4B, the observed species for bacteria responding to the IM, mature and DM were 176, 342.5 and 141, respectively in median numbers, indicating a rising bacterial diversity on the stage of mature and then going down on the stage of DM. Similar trend was also observed in the fungi diversity with observed species on stages of IM, mature and DM as 239.5, 443.5 and 235, respectively (Fig. 4F). To identify the compositions of microbial communities, the OTUs reads from 16s rDNA and ITS sequencing were annotated and classified at phylum and genus levels. For bacteria at the phylum level, Firmicutes and Proteobacteria were predominant, combined with ratio of abundances as high as 87.1%–94%, followed by Bacteroidetes (3.2–4.1%), Actinobacteria (1–2.3%) and Acidobacteria (0.2–2.7%), during the three stages of ripening fermentation (Fig. 4C). The ratio of Proteobacteria increased from 49.9% to 61.7%, accompanied with Firmicutes decreased from 44.1% on IM to 25.5% on DM, respectively. The abundances of Bacteroidetes were relatively stable in the whole process and expanding

relative contents (peak area percentage > 0.3% on either stage) and described flavors, were selected for further substantial analysis (Table 1). The 28 VCs were consisted by 7 alcohols, 10 aldehydes, 4 esters, 2 acids, 2 phenols, and 3 heterocyclics. The variations of these selected VCs during the ripening showed different patterns: ethanol, furfuryl alcohol and ethyl laurate kept decreasing; hexanal, and acetic acid peaked on mature stage; phenyl ethyl alcohol, 4-ethylphenol and 4-ethyl-2-methoxyphenol were relatively stable in the whole process; and the highest relative amounts of 3-methylbutanal, 2-methylbutanal, 5-methyl furfural, benzaldehyde and benzene acetaldehyde were identified on DM stage. 3.2. Microbial community profiles and succession 3.2.1. The changes of microbial diversity and compositions The number of effective tags ranged from 17,764 to 54,686 per sample from bacterial analysis, and 9807 to 45,237 for fungi. The amount of bacterial OTUs each sample were between 205 and 616; While fungal OTUs of each sample were between 167 and 425. The overall sequencing features for all the samples analyzed for microbial diversity and compositions were displayed in Table S2. In this study, PCoA score plot was performed to visualize the differences among these different stage samples in bacteria (Fig. 4A) and fungi (Fig. 4E). It was shown that the samples from the same stage reflected the better convergence in fungi than in bacteria. The 4 5

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Fig. 4. Bacterial and fungal biodiversity and compositions on three stages during DBJ ripening fermentation. Principal coordinate analysis of Bray–Curtis distance with each sample colored according to the fermentation stages in bacteria (A) and fungi (E). Observed species number describing the alpha diversity of the bacterial (B) and fungi (G). The composition of bacterial microbiota at the phyla and genus levels (C and D) and fungal mycobiota at the phyla and genus levels (G and H). *p < 0.05. 6

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Fig. 5. Heatmap showing the correlation between physicochemical factors and representative microbial taxa on three ripening stages. Only significant correlations (p value < 0.05 after false discovery rate correction) are displayed.

Aureobasidium, constituting the top 10 genera during DBJ ripening fermentation. The abundance of Zygosaccharomyces on DM (69.9%) was significantly higher than IM (23.6%) and mature (17.1%). Conversely, the Aspergillus decreased to 5.8% on DM, comparing to 23.2% and 29.3% on IM and mature. Continuing decreasing of Penicillium was also observed from 8.8% on IM, to 2.2% and 0.5% on mature and DM, as well as increasing of Wickerhamomyces from 0.4% on IM to 2.9% on mature and 8.6% on DM. Millerozyma, Alternaria and Mucor exhibited relative high abundance on IM as: 4.3%, 3.2% and 3.7%, and then significantly decreased on later two stages with abundance less than 0.5%.

abundance of Actinobacteria was observed on mature and DM stages. At genus level of bacterial, an overview of the top 15 genera at three stages was displayed in Fig. 4D. The compositions of bacteria varied in different stages: 1) On IM stage, the predominant populations were Lactobacillus (14.5%), Pantoea (10.8%), Escherichia-Shigella (5.7%), Halomonas (5.3%), Leuconostoc (5%) and Weissella (3.7%); 2) For mature stage, the main genus were Bacillus (7.5%), Pantoea (7%), Halomonas (6.4%), Lactobacillus (5.5%), Sphingomonas (5.4%) and Staphylococcus (5%); 3) The major bacterial genera observed at DM stage were Pantoea (21.8%), Sphingomonas (12.9%), Escherichia-Shigella (6.4%), Clostridium (5.9%) and Bacillus (5.3%). It was noteworthy that the abundance of Lactobacillus (14.5%) on IM decreased to 3.5% on DM, while Sphingomonas increased from 2.6% to 12.9%, becoming one of the major genera on DM. Low abundance of Pseudomonas was identified on IM (0.8%), then increased to 3% on DM, and the Leuconostoc, one of the major species on IM (5%) decreased on mature (0.7%) and DM (0.4%) stage. For fungi, top four taxa at phylum level were identified to be Ascomycota, Basidiomycota, Zygomycota and Rozellomycota (Fig. 4G). The major populations at phylum levels were Ascomycota with expanding abundance from IM (73.1%) to mature (87%), and up to 92.1% at DM. The highest abundance of basidiomycota was observed at mature (2.5%), compared to 1.2% at IM and 0.2% at DM. Zygomycota kept decreasing from 3.8% on IM, to 0.3% on mature and then to 0.04% on DM. At genus level, the compositions of mycobiota represented large fluctuations (Fig. 4H). Zygosaccharomyces and Aspergillus were the predominant fungi, followed by Penicillium, Wickerhamomyces, Cladosporium, Millerozyma, Alternaria, Mucor, Yamadazyma and

3.2.2. Representative bacteria and fungi on three stages The specific bacterial and fungal taxa within each stage during ripening fermentation were identified by the LEfSe analysis 3.0 and the threshold on the LDA score for discriminative features was adopted. The overall comparison including the relative abundance of these representatives bacterial and fungi taxa from each time-point during three ripening fermentation stages were conducted by heatmap plots (Figs. S1A and B). In the comparison of the bacterial populations among three stages (n = 37), 22 bacterial genus and species from IM, 13 from mature and 2 from DM exhibit differentially abundant in each stage (Fig. S1A). On the IM stage, Weissella ghanensis had the highest LDA score of 4.24, followed by Leuconostoc lactis (4.14), Halomonas jeotgali (4.1), and Leuconostoc pseudomesenteroides (4.03), all greater than the score of 4.0. On the mature stage, Bacteroides fragilis (2.89), Alishewanella (2.88), Brevundimonas Nasdae (2.84), Variibacter (2.82) and Chthonomonas (2.81) were the top 5 representative taxa, as well as on 7

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Zygosaccharomyces (Baruzzi et al., 2012) and Aspergillus during DBJ ripening process. The varied pH values are likely due to the changes of TA and OAs, as the inverse correlation between pH and TA were observed during DBJ ripening (Fig. 5). The fluctuation of pH value and TA between 1st and 6th month may probably due to the production or consumption of OAs (eg. Lactic and acetic acids) by multiple bacterial and fungal genera during IM ripening (Lee et al., 2014; Li et al., 2017). The decline of TA and four OAs (malic acid, tartaric acid, acetic acid, and lactic acid) was estimated to be driver by the consumption of negatively related fungi on IM, such as Zygosaccharomyces, with supporting evidence using OAs as a carbon source when lack of glucose (Vermeulen et al., 2012). Lactobacillus and Leuconostoc with strong capability to produce OAs, were likely to be related to the raise of the TA starting from the 3rd month, since high abundance of both bacteria were observed on IM. Further, this process might be caused by other acids producing bacteria such as: Fructobacillus (Endo et al., 2011) and A. cibinongensis (Lisdiyanti et al., 2001). OAs were usually considered to be the flavoring agents that with an impact on the taste of food (Neta et al., 2009). In our study, it could be estimated that the typical taste of DBJ had been initially formed since the 12th month, on the aspect of OAs, due to the stable concentrations of eight OAs from then on. Lactic acid and citric acid were reported to modify the tastes of divalent salts (Delay et al., 2019), while malic acid was aware to be related to the sweet taste in apple (Aprea et al., 2017). The increasing of these OAs might be the reason of the taste of DBJ changed from plain, flat and salty to intense, mellow and harmonious following the ripening. It was understandable that the variation of OAs on IM stage might be resulted from multiple microorganisms as mentioned above. However, several strains from bacteria and fungi were identified to be positively related to most OAs on mature and DM stage (Fig. 5), and some of these might directly contribute to the maintenance of OAs concentration, such as: Aureobasidium, with ability to enhance the production of malic acid (Feng et al., 2018). The moisture plays an important role in determining the concentration of chemical indices. It should be noted that OAs at all concentrations barely changed after the 12th month, which was possible due to the synchronous stability of the moisture. Also, the succession of microbial compositions may be strongly influenced by the moisture (Bal et al., 2017). Several bacteria and fungi with reported resistance on the low moisture became major or/and representative microbial population in the end of DBJ ripening, such as: Z. rouxii (Vermeulen et al., 2015), Wickerhamomyces (Rodriguez-Gomez et al., 2013) and Flavobacterium (Luo et al., 2018a, 2018b). Interestingly, negatively correlations between Z. rouxii and Wickerhamomyces with moisture on DM stage were observed (Fig. 5), implying the continuous consumption of moisture by these two fungi to maintain the balance of moisture on later stage of ripening. AFB1, one of well recognized human carcinogens and problematic toxic secondary metabolites produced by the genus Aspergillus (Li et al., 2018), was commonly found in grain, spice and nuts. In our study, the AFB1 observed in DBJ was lower than that permitted from DBJ National standard of China (≤5 μg/kg). A. flavus was identified as a representative fungus on IM and then demised on mature and DM (Fig. 5), which might be the reason for the decline of AFB1 during the ripening. Further, several bacteria observed in DBJ with potential function to degrade the AFB1 may also contribute to this process, such as Lactobacillus (Brana et al., 2017), and Pantoea (Xie et al., 2019). The taste of DBJ may also be affected by the FAAs. Glu, Pro, Asp, Asn and Arg were the major FAAs identified in DBJ (Fig. 3), which might contribute to the flavors such as: umami, sweetness and bitterness (Bassoli et al., 2014; Poojary et al., 2017). The variations of FAAs in DBJ were similar to dongchimi (Jeong et al., 2013) and saeu-jeot (Jeong et al., 2013; Jung et al., 2013), where FAAs increased on early stages and then kept stable or decreased. The proteolysis process was reported to be critical to enhance the amino acid compounds in fermented broad bean products

DM stage were only Chryseobacterium (2.61) and Flavobacterium (2.57). For fungal LDA analysis, 8, 10 and 3 fungal genus or species were found to be enriched on IM, mature and DM stages, respectively. Cladosporium (4.31), Mucor racemosus (4.25) and Z. rouxii_OTU13 (4.10) on IM stage, Cladosporium sphaerospermum (4.31) and Aureobasidium (4.19) on mature, and Z. rouxii_OTU2 (5.44) and Wickerhamomyces subpelliculosus (4.56) on DM stage, were verified to the specific enriched on each stage (Fig. S1B). 3.3. Correlation analysis between physicochemical factors and representative microbiota on three stages The relationship between the Ⅰ) 27 major VCs (acetic acid was included in organic acids), Ⅱ) 20 FAAs, Ⅲ) 6 fermentation features, Ⅳ) 8 OAs, and all representative Ⅴ) bacteria (n = 37) and Ⅵ) fungi (n = 21) on three stages were analyzed by Spearman's rank correlation and visualized by using R software. The associations among the six data panels were shown in Fig. 5, with a correlation cut-off of 0.5. For the major VCs, it showed that ethanol, isoamylol, furfuryl alcohol, ethyl hexanoate, ethyl phenylacetate and ethyl laurate were positively correlated to most of representative bacteria and fungi on stage of IM, and linalool, α-terpineol, isobutyraldehyde and hexanal were positively correlated to most of representative taxa on stage of mature. Z._rouxii (OTU_2) was positively related to 10 major VCs with relative contents peaked on DM. As shown in Fig. 5, for 20 FAAs, His was identified to have positively correlated to half of representative bacteria (11/22) and more than half of fungi (5/8) on stage of IM. Most of representative fungi on IM (7/8) were positively correlated to Asn, compared to 7 out of 22 bacterial on IM. The Glu was positively correlated to IM representative bacteria: W. ghanensis and Proteus; and IM representative fungi: Cladosporium and Z. rouxii. Also, four IM representative bacteria: Halomonas elongata, Proteus, Acetobacter cibinongensis and Vitreoscilla; and four IM representative fungi: Cladosporium, Z. rouxii, Penicillium and Aspergillus flavus, were verified to be positively correlated to Pro. The correlations between general fermentation physicochemical indices and microbiota diversified. For example, most of representative microbiota positively correlated to pH value was found on IM stage, such as: W. ghanensis, L.lactis, L. pseudomesenteroides, Penicillium and A. flavus, which were also (or from) the major genus identified on IM stage by OTU abundance. Fructobacillus, Proteus and A. cibinongensis, of these representative bacteria on IM were negatively correlated to the amount of TA. Similar patterns of correlations between the features of moisture, pigment and AFB1, and the microbiota were also observed. Six OAs were found to be negatively correlated to most of representative bacteria and fungi on IM stage. 4. Discussion DBJ National standard of China (“Product of geographical indication – Pixian douban”, GB/T 20560-2006) stipulates that the ATN should be ≥ 1.8 g/kg (Premium ≥2.5, First-class ≥2.0 and Qualified ≥1.8 g/ kg) and the TA content should be ≤ 20 g/kg. According to this standard, the ATN and TA of DBJ are Qualified since the 1st month and reach the standard of Premium at the 6th month during the ripening fermentation. In general, the content of ATN of DBJ were comparable to Shuidouchi (Cai et al., 2018), Miso (Jayachandran and Xu, 2019), but lower than Cheonggukjang (Cho et al., 2017) and Myeolchi-Aekjeot (Lee et al., 2015). The pH value of DBJ in the first month was 4.58, similar to that observed in the end of DBJ-meju fermentation with pH around 4.5 (Li et al., 2017). The pH gradually changed far away from the optimum growing region for some strains, accordingly, the abundance of whom, such as: Lactobacillus and Leuconostoc were significantly decreased on DM stage compared to IM (Fig. 2). In addition, fungal genera with tolerance to low pH were the major population, such as 8

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sequencing data and statistical analysis. Whether the physicochemical properties of DBJ is a function of microbiota or adaptation of microbiota should be further explored. Moreover, addressing correlation between representative microbiota and a few physicochemical factors with variation on each stage is not enough to reveal the complex interweaving relationships of microorganisms and the interactions between physicochemical conditions and microbiota in DBJ fermentation. Future study may expand samples and employ tools of metagenomics and metabolomics analyses, accompanied by culture-dependent methods to further identify the key microorganisms and explore the functions of these strains associated with the succession of microbial structure and physicochemical variations during DBJ ripening. Our findings shed light on drawing a more comprehensive picture on the physicochemical changes related to the succession of microbial communities during DBJ ripening, which is expected to provide substantial data to better understand the maturing of the taste and flavor in production of DBJ.

(Zofia et al., 2007). It could be estimated that high level of proteolysis occurred during the IM stage of ripening since the concentrations for most the FAAs (17/20) were peaked on the 6th month. Few significant relations between FAAs and representative microbial taxa on each stage were observed, especially for those major FAAs (Fig. 5), suggesting the changes of FAAs might be involved with a large population of microorganisms not only these representative microorganisms on each stage. Lactobacillus with high abundance on IM was reported to promote the proteolysis (Chaves-Lopez et al., 2014), which could attribute to the raise of FAAs within the IM stage. Further, the protein from the strains may probably be another important factor that leads to the variation of FAAs. For example, Zygosaccharomyces, which was identified to be abundance in DBJ, was described to release FAAs by autolysis (Guo et al., 2016). The decline of FAAs was probably due to the consumption by multiple microorganisms via Maillard reaction and enzymatic conversions (Zhao et al., 2016). Our findings agreed with the previous studies that phenethyl alcohol, linalool, ethanol, furfuryl alcohol with honey-like, floral, sweet, and burnt odour were the major alcohols during DBJ ripening (Li et al., 2016). On mature and DM stage, isoamylol and α-terpineol were both with relatively high contents, described as representative VCs from cocoa beans and hog plums (Frauendorfer and Schieberle, 2008; Jide Adedeji et al., 1991). Aldehydes are important in contributing to various odors and are associated with flavor production as substrates in food (Moon et al., 2006). Among 10 major aldehydes identified, eight were commonly found in DBJ ripening and fermented soybean food (Lee, 2009; Li et al., 2016), except isobutyraldehyde and hexanal. Isobutyraldehyde was reported as one of the major aldehydes from hog plum peaked at mature and decreased on DM stage (Jide Adedeji et al., 1991). Hexanal with odour of grass and fat (Carrapiso et al., 2002), also declined on DM stage. Compared with the mature stage, 5 aldehydes (3Methylbutanal, 2-methylbutanal, 5-methyl furfural, benzaldehyde and 5-methyl-2-phenyl-2-hexenal), mostly with aroma Chocolate, almond and roasted cocoa, largely increased on DM stage. Four major ketones were identified during DBJ ripening. The most abundance of ketones identified on mature and DM stage of DBJ was ethyl tridecanoate with significantly higher amount compared to IM stage (p < 0.5). Ethyl tridecanoate was reported as one of major VCs in fermented tomato juice (Liu et al., 2018), which was likely to contribute the intensity of favor in DBJ products. Ethyl hexanoate, ethyl phenylacetate and ethyl laurate with odour of fruity, honey and leaf decreased on mature and DM stages. 4-Ethylphenol and 4-ethyl-2-methoxypheno, two major odour contributors to the flavor of spicy, were commonly observed in fermented red pepper pasted such as gochujang (Kang and Baek, 2014) and DBJ (Li et al., 2016). They are also reported to potentially enhance the flavor quality of soy sauce (Feng et al., 2014). 2-Acetylpyrrole with aroma of licorice and 2,6-dimethylpyrazine with nutty-like flavor (Perez-Boada et al., 2005), both with the highest relative abundance on DM stage, might help on forming the flavor of mellow and harmonious during DBJ ripening. Though the variations of these major VCs could be involved with a large microbial population, Z. rouxi could be the key microorganism to distinct the flavor during the DBJ ripening, especially in the later stage. Z. rouxii was predominant during DBJ ripening (69.9% in abundance on DM stage), in accordance with that observed in soy sauce and miso fermentation (Devanthi et al., 2018; Sujaya et al., 2003). Z. rouxii was previously reported with its capability to enhance VCs using the Maillard intermediates as precursors (Hayashida et al., 1999) and widely applied in the Japanese soy sauce industry (Wah et al., 2013). Here we found Z. rouxii was positively related to 10 VCs that were all peaked on DM stage (Fig. 5), indicating the critical role of Z. rouxii to contribute to synthesize the typical odorant flavor of DBJ on DM stage. There were several limitations should be addressed in our study. The small sample size may limit the accurate understanding of microbial compositions. Our analysis on the microbial communities and correlations to physicochemical factors are mainly based on the OTUs

Declaration of competing interest The authors have no conflict of interest. Acknowledgements The study was supported by the Science and Technology Agency of Sichuan Province (No. 2015GZX0021 and 2018NZZJ018), “The Fundamental Research Funds for the Central Universities” and the Science and Technology Bureau of Chengdu (No. 2015NY0100001NC) and. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.fm.2019.103342. References Aprea, E., Charles, M., Endrizzi, I., Laura Corollaro, M., Betta, E., Biasioli, F., Gasperi, F., 2017. Sweet taste in apple: the role of sorbitol, individual sugars, organic acids and volatile compounds. Sci. Rep. 7, 44950. Bal, J., Yun, S.H., Yeo, S.H., Kim, J.M., Kim, B.T., Kim, D.H., 2017. Effects of initial moisture content of Korean traditional wheat-based fermentation starter nuruk on microbial abundance and diversity. Appl. Microbiol. Biotechnol. 101, 2093–2106. Baruzzi, F., Lagonigro, R., Quintieri, L., Morea, M., Caputo, L., 2012. Occurrence of nonlactic acid bacteria populations involved in protein hydrolysis of cold-stored high moisture Mozzarella cheese. Food Microbiol. 30, 37–44. Bassoli, A., Borgonovo, G., Caremoli, F., Mancuso, G., 2014. The taste of D- and L-amino acids: in vitro binding assays with cloned human bitter (TAS2Rs) and sweet (TAS1R2/TAS1R3) receptors. Food Chem. 150, 27–33. Beaulieu, J.C., Stein-Chisholm, R.E., 2016. HS-GC-MS volatile compounds recovered in freshly pressed ‘Wonderful’ cultivar and commercial pomegranate juices. Food Chem 190, 643–656. Brana, M.T., Cimmarusti, M.T., Haidukowski, M., Logrieco, A.F., Altomare, C., 2017. Bioremediation of aflatoxin B1-contaminated maize by king oyster mushroom (Pleurotus eryngii). PLoS One 12, e0182574. Cai, H., Zhang, T., Zhang, Q., Luo, J., Cai, C., Mao, J., 2018. Microbial diversity and chemical analysis of the starters used in traditional Chinese sweet rice wine. Food Microbiol. 73, 319–326. Carrapiso, A.I., Jurado, A., Timon, M.L., Garcia, C., 2002. Odor-active compounds of Iberian hams with different aroma characteristics. J. Agric. Food Chem. 50, 6453–6458. Chaves-Lopez, C., Serio, A., Paparella, A., Martuscelli, M., Corsetti, A., Tofalo, R., Suzzi, G., 2014. Impact of microbial cultures on proteolysis and release of bioactive peptides in fermented milk. Food Microbiol. 42, 117–121. Cho, K.M., Lim, H.J., Kim, M.S., Kim, D.S., Hwang, C.E., Nam, S.H., Joo, O.S., Lee, B.W., Kim, J.K., Shin, E.C., 2017. Time course effects of fermentation on fatty acid and volatile compound profiles of Cheonggukjang using new soybean cultivars. J. Food Drug Anal. 25, 637–653. Counet, C., Callemien, D., Ouwerx, C., Collin, S., 2002. Use of gas chromatography-olfactometry to identify key odorant compounds in dark chocolate. Comparison of samples before and after conching. J Agric Food Chem 50, 2385–2391. Delay, E.R., Weaver, B., Lane, D.R., Kondoh, T., 2019. Dried bonito dashi: contributions of mineral salts and organic acids to the taste of dashi. Physiol. Behav. 199, 127–136.

9

Food Microbiology 86 (2020) 103342

L. Zhang, et al.

antioxidation, antimicrobial effect, and volatile profiles. Molecules 23. Luo, J., Zhao, H., Xu, W., Yang, G., Yue, P., Zhang, L., 2018a. Analysis of volatile compounds in Pixian Soybean Paste during post-fermentation by SPME-GC-MS combined with PCA. Food Sci 39, 209–216. Luo, Y., Wu, Y., Wang, H., Xing, R., Zheng, Z., Qiu, J., Yang, L., 2018b. Bacterial community structure and diversity responses to the direct revegetation of an artisanal zinc smelting slag after 5 years. Environ. Sci. Pollut. Res. Int. 25, 14773–14788. Moon, S.Y., Cliff, M.A., Li-Chan, E.C.Y., 2006. Odour- active components of simulated beef flavour analysed by solid phase microextraction and gas chromatography-mass spectrometry and-olfactometry. Food Res. Int. 39, 294–308. Neta, E.R., Johanningsmeier, S.D., Drake, M.A., McFeeters, R.F., 2009. Effects of pH adjustment and sodium ions on sour taste intensity of organic acids. J. Food Sci. 74, S165–S169. Owusu, M., Heimdal, H., 2012. Effect of fermentation method, roasting and conching conditions on the aroma volatiles of dark chocolate. J Food Process Preserv 446, 456. Perez-Boada, M., Ruiz-Duenas, F.J., Pogni, R., Basosi, R., Choinowski, T., Martinez, M.J., Piontek, K., Martinez, A.T., 2005. Versatile peroxidase oxidation of high redox potential aromatic compounds: site-directed mutagenesis, spectroscopic and crystallographic investigation of three long-range electron transfer pathways. J. Mol. Biol. 354, 385–402. Poojary, M.M., Orlien, V., Passamonti, P., Olsen, K., 2017. Enzyme-assisted extraction enhancing the umami taste amino acids recovery from several cultivated mushrooms. Food Chem. 234, 236–244. Reda Triqui, G.A.R., 1995. Changes in Flavor Profiles with Ripening of Anchovy (Engraulis encrasicholus). J Agric Food Chem 7, 1883–1889. Rodriguez-Gomez, F., Bautista-Gallego, J., Romero-Gil, V., Arroyo-Lopez, F.N., GarridoFernandez, A., 2013. Influence of yeasts on the oil quality indexes of table olives. J. Food Sci. 78, M1208–M1217. Schnermann, P., 1997. Evaluation of key odorants in milk chocolate and cocoa mass by aroma extract dilution analyses. J Agric Food Chem 45, 867–872. Sujaya, I.N., Tamura, Y., Tanaka, T., Yamaki, T., Ikeda, T., Kikushima, N., Yata, H., Yokota, A., Asano, K., Tomita, F., 2003. Development of internal transcribed spacer regions amplification restriction fragment length polymorphism method and its application in monitoring the population of Zygosaccharomyces rouxii M2 in miso fermentation. J. Biosci. Bioeng. 96, 438–447. Valim, M.F., Rouseff, R.L., Lin, J., 2003. Gas chromatographic-olfactometric characterization of aroma compounds in two types of cashew apple nectar. J Agric Food Chem 51, 1010–1015. Vermeulen, A., Daelman, J., Van Steenkiste, J., Devlieghere, F., 2012. Screening of different stress factors and development of growth/no growth models for Zygosaccharomyces rouxii in modified Sabouraud medium, mimicking intermediate moisture foods (IMF). Food Microbiol. 32, 389–396. Vermeulen, A., Marvig, C.L., Daelman, J., Xhaferi, R., Nielsen, D.S., Devlieghere, F., 2015. Strategies to increase the stability of intermediate moisture foods towards Zygosaccharomyces rouxii: the effect of temperature, ethanol, pH and water activity, with or without the influence of organic acids. Food Microbiol. 45, 119–125. Wah, T.T., Walaisri, S., Assavanig, A., Niamsiri, N., Lertsiri, S., 2013. Co-culturing of Pichia guilliermondii enhanced volatile flavor compound formation by Zygosaccharomyces rouxii in the model system of Thai soy sauce fermentation. Int. J. Food Microbiol. 160, 282–289. Wang, J., Yang, X.H., Mujumdar, A.S., Fang, X.M., Zhang, Q., Zheng, Z.A., Gao, Z.J., Xiao, H.W., 2018. Effects of high-humidity hot air impingement blanching (HHAIB) pretreatment on the change of antioxidant capacity, the degradation kinetics of red pigment, ascorbic acid in dehydrated red peppers during storage. Food Chem. 259, 65–72. Xia, X., Li, G., Zheng, J., Ran, C., Kan, J., 2014. Biochemical, textural and microstructural changes in whole-soya bean cotyledon sufu during fermentation. Int. J. Food Sci. Technol. 49, 1834–1841. Xie, Y., Wang, W., Zhang, S., 2019. Purification and identification of an aflatoxin B1 degradation enzyme from Pantoea sp. T6. Toxicon 157, 35–42. Zhao, C.J., Schieber, A., Ganzle, M.G., 2016. Formation of taste-active amino acids, amino acid derivatives and peptides in food fermentations - a review. Food Res. Int. 89, 39–47. Zhao, Z., Mu, T., Sun, H., 2019. Microbial characterization of five Chinese traditional sourdoughs by high-throughput sequencing and their impact on the quality of potato steamed bread. Food Chem. 274, 710–717. Zhu, Y., Luo, Y., Wang, P., Zhao, M., Li, L., Hu, X., Chen, F., 2016. Simultaneous determination of free amino acids in Pu-erh tea and their changes during fermentation. Food Chem. 194, 643–649. Zhu, Y.X., Huang, J., Zhang, Z.K., Zhang, Q.M., Zhou, T., Ahn, Y.Y., 2013. Geography and similarity of regional cuisines in China. PLoS One 8, e79161. Zofia, L., Kmiecik, W., Jacek, S., 2007. Content of amino acids in raw and frozen broad beans (Vicia faba var. major) seeds at milk maturity stage, depending on the processing method. Food Chem. 105, 1468–1473.

Devanthi, P.V.P., Linforth, R., Onyeaka, H., Gkatzionis, K., 2018. Effects of co-inoculation and sequential inoculation of Tetragenococcus halophilus and Zygosaccharomyces rouxii on soy sauce fermentation. Food Chem. 240, 1–8. Endo, A., Irisawa, T., Futagawa-Endo, Y., Sonomoto, K., Itoh, K., Takano, K., Okada, S., Dicks, L.M., 2011. Fructobacillus tropaeoli sp. nov., a fructophilic lactic acid bacterium isolated from a flower. Int. J. Syst. Evol. Microbiol. 61, 898–902. Feng, Y., Cai, Y., Sun-Waterhouse, D., Cui, C., Su, G., Lin, L., Zhao, M., 2015. Approaches of aroma extraction dilution analysis (AEDA) for headspace solid phase microextraction and gas chromatography-olfactometry (HS-SPME-GC-O): Altering sample amount, diluting the sample or adjusting split ratio? Food Chem 187, 44–52. Feng, J., Yang, J., Yang, W., Chen, J., Jiang, M., Zou, X., 2018. Metabolome- and genomescale model analyses for engineering of Aureobasidium pullulans to enhance polymalic acid and malic acid production from sugarcane molasses. Biotechnol. Biofuels 11, 94. Feng, Y., Cai, Y., Su, G., Zhao, H., Wang, C., Zhao, M., 2014. Evaluation of aroma differences between high-salt liquid-state fermentation and low-salt solid-state fermentation soy sauces from China. Food Chem. 145, 126–134. Frauendorfer, F., Schieberle, P., 2006. Identification of the key aroma compounds in cocoa powder based on molecular sensory correlations. J Agric Food Chem 54, 5521–5529. Frauendorfer, F., Schieberle, P., 2008. Changes in key aroma compounds of Criollo cocoa beans during roasting. J. Agric. Food Chem. 56, 10244–10251. Gu, S.Q., Wang, X.C., Tao, N.P., Wu, N., 2013. Characterization of volatile compounds in different edible parts of steamed Chinese mitten crab (Eriocheir sinensis). Food Res Int 54, 81–92. Guo, H., Niu, C., Liu, B., Wei, J., Wang, H., Yuan, Y., Yue, T., 2016. Protein abundance changes of Zygosaccharomyces rouxii in different sugar concentrations. Int. J. Food Sci. Technol. 233, 44–51. Hayashida, Y., Kuriyama, H., Nishimura, K., Slaughter, J.C., 1999. Production of 4-hydroxyfuranones in simple media by fermentation. Biotechnol. Lett. 21, 505–509. Jayachandran, M., Xu, B., 2019. An insight into the health benefits of fermented soy products. Food Chem. 271, 362–371. Jeong, S.H., Jung, J.Y., Lee, S.H., Jin, H.M., Jeon, C.O., 2013. Microbial succession and metabolite changes during fermentation of dongchimi, traditional Korean watery kimchi. Int. J. Food Microbiol. 164, 46–53. Jide Adedeji, T.G.H., Rosen, Robert T., Ho, Chi Tang, 1991. Free and glycosidically bound aroma compounds in hog plum (Spondias mombins L.). J. Agric. Food Chem. 8, 1494–1497. Jung, J.Y., Lee, S.H., Lee, H.J., Jeon, C.O., 2013. Microbial succession and metabolite changes during fermentation of saeu-jeot: traditional Korean salted seafood. Food Microbiol. 34, 360–368. Kang, K.M., Baek, H.H., 2014. Aroma quality assessment of Korean fermented red pepper paste (gochujang) by aroma extract dilution analysis and headspace solid-phase microextraction-gas chromatography-olfactometry. Food Chem. 145, 488–495. Lee, S.A.,B., 2009. Comparison of volatile components in fermented soybean pastes using simultaneous distillation and extraction (SDE) with sensory characterisation. Food Chem. 114, 600–609. Lee, S.H., Jung, J.Y., Jeon, C.O., 2014. Effects of temperature on microbial succession and metabolite change during saeu-jeot fermentation. Food Microbiol. 38, 16–25. Lee, S.H., Jung, J.Y., Jeon, C.O., 2015. Bacterial community dynamics and metabolite changes in myeolchi-aekjeot, a Korean traditional fermented fish sauce, during fermentation. Int. J. Food Microbiol. 203, 15–22. Li, J., Huang, J., Jin, Y., Wu, C., Shen, D., Zhang, S., Zhou, R., 2018. Aflatoxin B1 degradation by salt tolerant Tetragenococcus halophilus CGMCC 3792. Food Chem. Toxicol. 121, 430–436. Lee, S.J., Moon, T.W., Lee, J., 2010. Increases of 2-furanmethanol and maltol in Korean red ginseng during explosive puffing process. J Food Sci 75, C147–151. Lee, S.J., Noble, A.C., 2003. Characterization of odor-active compounds in Californian chardonnay wines using GC-olfactometry and GC-mass spectrometry. J Agric Food Chem 51, 8036–8044. Li, Y.J., 2008. Analysis of Pixian-douban paste. China Brew. 11, 83–86. Li, Z., Dong, L., Huang, Q., Wang, X., 2016. Bacterial communities and volatile compounds in Doubanjiang, a Chinese traditional red pepper paste. J. Appl. Microbiol. 120, 1585–1594. Li, Z., Rui, J., Li, X., Li, J., Dong, L., Huang, Q., Huang, C., Wang, Z., Li, L., Xuan, P., Tang, Y., Chen, F., 2017. Bacterial community succession and metabolite changes during doubanjiang-meju fermentation, a Chinese traditional fermented broad bean (Vicia faba L.) paste. Food Chem. 218, 534–542. Lisdiyanti, P., Kawasaki, H., Seki, T., Yamada, Y., Uchimura, T., Komagata, K., 2001. Identification of Acetobacter strains isolated from Indonesian sources, and proposals of Acetobacter syzygii sp. nov., Acetobacter cibinongensis sp. nov., and Acetobacter orientalis sp. nov. J. Gen. Appl. Microbiol. 47, 119–131. Liu, Y., Chen, H., Chen, W., Zhong, Q., Zhang, G., Chen, W., 2018. Beneficial effects of tomato juice fermented by Lactobacillus Plantarum and Lactobacillus casei:

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