3.1. Microbial community changes during stacking fermentation
The changes in microbiota structure during cigar stacking fermentation were analyzed by 16S and ITS amplion sequencing, and the bacterial and fungal genera with relative abundances in the top 20 were selected for subsequent analysis, as shown in . The results showed that the compositions of the dominant bacterial genera in the different varieties of CTLs were similar. The three dominant bacterial genera, Staphylococcus, Corynebacterium 1 and Aerococcus, were the main components of the bacterial communities in different CTL varieties. The total relative abundance of all samples was between 67.15 % and 99.10 %; however, the relative abundance changes during stacking fermentation differed. The relative abundances of Corynebacterium 1 and Aerococcus gradually increased from the CX14, BESUKI, and MATA FINA CTLs, while the sum of the relative abundances of Corynebacterium 1 and Aerococcus at the end of fermentation were 79.59 %, 67.68 %, and 72.30 %, respectively. The CTLs from DX4 and N-Jalap HABANA had Staphylococcus as the dominant bacteria in the stacking fermentation process, with its relative abundance exceeding 90 % at the end of fermentation. Furthermore, the CTLs from CRIOLLO 98, HVA, and E-HABANO 2000 showed Staphylococcus as the main dominant bacteria, although the relative abundance of Staphylococcus gradually decreased, whilst the relative abundances of Halomonas, Atopostipes, Corynebacterium 1, and other genera showed a slight increase. During stacking fermentation, the fungal community with Aspergillus as the dominant fungal genus showed the highest proportion of relative abundance among different varieties of CTL fungi, whilst the relative abundance of Aspergillus in different CTLs varied greatly. Among them, CX14, CRIOLLO 98, HVA, BESUKI, and E-HABANO 2000 CTLs Aspergillus decreased during the fermentation process, with the community composition being richer at the end of fermentation. While Aspergillus was the most dominant fungus in the CTLs from DX4, N-Jalap HABANA, and MATA during stacking fermentation, at the end of fermentation, the relative abundances of Aspergillus were 73.98 %, 97.83 %, and 88.88 %, respectively.
Figure 1.
Microbial community changes of CTLs from different varieties. (A: Composition of bacterial community during stacking fermentation; B: Composition of fungal community during stacking fermentation)
Figure 1.
Microbial community changes of CTLs from different varieties. (A: Composition of bacterial community during stacking fermentation; B: Composition of fungal community during stacking fermentation)
3.3. Interaction relationship between microbial community
Using Spearman to analyze the interaction relationship between CTL microbial communities, ρ < 0.05, r > 0.6 were defined as significant positive correlations, whilst ρ < 0.05, r < -0.6 were defined as significant negative correlations, with the results being shown in . During stacking fermentation, among the dominant bacteria,
Staphylococcus were negatively correlated with
Corynebacterium 1 and
Aerococcus, whilst
Corynebacterium 1 and
Aerococcus interacted positively. Dominant bacterial genera from different CTL varieties were significantly related to characteristic microorganisms, for example,
Corynebacterium 1 was positively correlated with
Facklamia,
Jeotgalicoccus,
Brachybacterium,
Geomicrobium,
Glutamicibacter,
Yaniella,
Salinicoccus,
Solibacillus, and
Natribacillus. Additionally,
Aerococcus was positively correlated with
Carnimonas,
Facklamia,
Yaniella, whilst
Staphylococcus was shown to have been positively correlated with
Halomonas and
Solitalea. During stacking fermentation, the dominant bacterial genera were found to have affected the growth of the corresponding characteristic bacterial genera, such as
Aerococcus and
Corynebacterium 1, which in turn increased in the pre-fermentation period. This promoted the proliferation of
Sphingobium,
Aquabacterium,
Halomonas, etc., and decreased when
Staphylococcus increased during the middle and late fermentation stages. Characteristic bacteria such as
Aquabacterium,
Brachybacterium,
Tetragenococcus,
Ralstonia,
Enteractinococcus,
Jeotgalicoccus,
Lactobacillus,
Bacillus, and
Yaniella all interacted in a positive direction, whilst characteristic fungi such as
Sampaiozyma,
Wallemia,
Penicillium,
Trichosporon,
Nigrospora,
Septoria, and
Plectosphaerella also all interacted in a positive direction. These positive interactions between the characteristic microorganisms greatly influenced the evolution of the microbiota structure during the stacking fermentation process.
Aspergillus, the dominant fungi of CTLs, was negatively correlated with characteristic fungal genera, including
Alternaria,
Curvularia,
Fusarium,
Gibberella,
Mycosphaerella,
Plectosphaerella,
Pseudeurotium,
Penicillium,
Sampaiozyma,
Septoria, and
Trichothecium. During stacking fermentation,
Aspergillus inhibits the growth of characteristic fungi, such as
Alternaria,
Trichosporon, and
Mycosphaerella which was opposite to the change observed in
Aspergillus. The abundance of
Aspergillus was found to have been higher during the early stage of fermentation, whilst the characteristic fungus was then inhibited from growing and increased during the middle and late stages of fermentation with a decrease in
Aspergillus. The above results showed that the abundance and interactions of dominant microbes during stacking fermentation affected the changes in characteristic microorganisms in the microbial community and subsequently influenced the microbiota structure of CTLs during the stacking fermentation process.
Figure 3.
Microbial community interaction networks. (A: Interaction network between CTLs bacterial communities; B: Interaction network between CTLs fungal communities. Red represents positive correlation and blue represents negative correlation)
Figure 3.
Microbial community interaction networks. (A: Interaction network between CTLs bacterial communities; B: Interaction network between CTLs fungal communities. Red represents positive correlation and blue represents negative correlation)
3.4. Changes of volatiles in the stacking fermentation
The results showed that the types of volatiles increased during stacking fermentation with the volatiles detected including 2-undecanone, 6,10-dimethyl-, geranyl acetone, β-ionone, phytone, farnesyl acetone, ethanone, 1-(3-pyridinyl)-, myosmine, and nicotyrine [
7]. However, the transformation mechanism of stacking fermentation on CTL aroma and sensory quality remained unclear. The results are shown in , with the volatiles at the end of fermentation for different CTLs and the volatiles of CTLs between raw materials and the end of fermentation being found to have been quite different. During stacking fermentation, carotenoid degradation products, Maillard reaction products, and nicotinic degradation products increased, which was consistent with the past results found by Liu’s study, indicating that these three types of substances were the key volatiles for the quality improvement of CTLs [
7].
Figure 4.
Cluster analysis of volatiles from different varieties of CTLs between raw materials and the end of fermentation.
Figure 4.
Cluster analysis of volatiles from different varieties of CTLs between raw materials and the end of fermentation.
In addition to β-ionone, dihydroactinidiolide, 6-methyl-3,5-heptadien-2-one, geranyl acetone, and isophorone, the carotenoid degradation products in different varieties of CTLs also contained β-ionone-5,6-epoxide, menthol, and α-terpineol, among other aroma intermediates. Carotenoid degradation products are important components of tobacco aroma, the threshold is low, and their type and content both have an important impact on improving tobacco aroma and mellowness [
22,
23]. For example, β-ionone is an aroma ingredient of CTLs flowery and woody aroma; dihydroactinidiolide has a sweet and woody aroma, which could mellow the smoke gas; 6-methyl-3,5-heptadien-2-one and geranyl acetone have a rosy, leafy, and fruity aroma [
23]. The content of Maillard reaction products, such as pyrazine, 2,5-dimethyl-, pyrazine, 2,6-dimethyl-, pyrazine, tetramethyl-, furfural, 2-propanone, 1-hydroxy-, ethanone, 1-(3-pyridinyl)-, and indole, all increased during stacking fermentation. Maillard reaction products are mainly generated by carbohydrates and amino acids via the production of dicarbonyl compounds and amino ketones, primarily creating nutty, roasted, chocolate, and other aromas for CTLs [
24]. Nicotine, the most abundant and important alkaloid in CTLs, is irritating and bitter when its content is too high, whilst there is insufficient smoke and a bland flavor when its content is too low. CTLs can reduce irritation and increase mellowness through degrading nicotine to produce myosmine and nicotine during stacking fermentation [
25]. Therefore, in stacking fermentation, the transformation of carotenoid degradation and Maillard reaction products alongside the degradation of nicotine played a role in mellowing smoke gas and enhancing the aroma of CTLs.
Figure 5.
Effects from volatiles of stacked fermented CTLs on the aroma and quality.
Figure 5.
Effects from volatiles of stacked fermented CTLs on the aroma and quality.
3.6. Correlation analysis between microorganisms-volatiles and volatiles-aroma
The interaction between CTLs microorganisms and volatiles during stacking fermentation was analyzed by Spearman correlation analysis, with ρ < 0.05 and r greater than 0.6 being defined as significant positive correlations, and ρ < 0.05 and r less than -0.6 being defined as significant negative correlations, as shown in . The correlation between bacteria and volatiles during stacking fermentation was more complex than that between fungi and volatiles whilst also being mainly positively correlated. Characteristic volatiles of different varieties of CTLs were also positively correlated with characteristic microorganisms, such as in CX14 CTLs, Penicillium was positively correlated with dimethyl phthalate, whilst Diaporthe, Trichothecium were positively correlated with ethanone, 1-(2-pyridinyl)-, tigelic acid, megastigmatrienone 4, and bourgeonal. This provides CTLs with a fresh flowery and light sweet aroma. In DX4 CTLs, Chloroplast was positively correlated with ethanone, 1-(1-cyclohexen-1-yl)-, and Trichosporon was positively correlated with pyrazine, tetramethyl-, which could increase the roasted and burnt sweet aroma of CTLs. Among N-Jalap HABANA CTLs, Thioalkalicoccus was positively correlated with geranyl Acetone and α-curcumene, and Solitalea was positively correlated with acetic acid, which could increase the light sweet and flowery aroma of CTLs. Furthermore, Enteractinococcus, Jeotgalicoccus, and Talaromyces in the HVA CTLs were positively correlated with 2-undecanone, 6,10-dimethyl-, and Lactobacillus, whilst Atopococcus was positively correlated with butanoic acid and isophorone, which could increase the fruity and mint aroma. Carnimonas and Debaryomyces in BESUKI CTLs were also positively correlated with 1-dodecanol, 3,7,11-trimethyl- and dihydro-beta-ionone, which could increase the flowery and hay aroma. Additionally, Yaniella in MATA FINA CTLs was positively correlated with nicotine, when Salinicoccus, Nocardiopsis, Natribacillus, Solibacillus, Geomicrobium, Salinicoccus and Glutamicibacter were positively correlated with 4-oxoisophorone and 1,4-cyclohexanedione, 2,2,6-trimethyl-, which could increase the sweet, hay, nutty, and woody aroma.
Figure 7.
Interaction network between CTLs microorganisms and volatiles. (A: Interaction network between bacteria and volatiles; B: Interaction network between fungi and volatiles. Red represents positive correlation and blue represents negative correlation).
Figure 7.
Interaction network between CTLs microorganisms and volatiles. (A: Interaction network between bacteria and volatiles; B: Interaction network between fungi and volatiles. Red represents positive correlation and blue represents negative correlation).
Figure 8.
Aroma composition of CTLs and interaction network between volatiles and aroma. (A: Radar chart of the aroma from different varieties of CTLs; B: Interaction network between the volatiles and aroma. Red represents positive correlation and blue represents negative correlation).
Figure 8.
Aroma composition of CTLs and interaction network between volatiles and aroma. (A: Radar chart of the aroma from different varieties of CTLs; B: Interaction network between the volatiles and aroma. Red represents positive correlation and blue represents negative correlation).
Radar charts were used to identify the aroma of different CTL varieties at the end of stacking fermentation. The results are shown in , where the woody aroma was found to be the most prominent among the different CTL varieties, with each sample being supplemented with another aroma.
Using Spearman correlation analysis, the interaction network between volatile aroma was established; ρ < 0.05 and r greater than 0.6 were defined as significant positive correlations, whilst ρ < 0.05 and r less than -0.6 were defined as significant negative correlations, with the results being shown in B. The characteristic volatiles of CTLs showed a stronger positive correlation with many aromas, such as bean aroma, which was positively related to nonanal, decanal, pyrazine, 2,5-dimethyl-, furfural, pyrazine, 2,6-dimethyl-, and α-terpineol. Meanwhile, the coffee aroma was positively correlated with farnesyl acetone C and propanoic acid, 2-methyl-, whilst the flowery aroma was positively correlated with geranyl acetone, benzophenone, benzonitrile, and α-curcumene. Hay aroma was positively correlated with dihydro-beta-ionone; Honey sweet aroma was positively correlated with benzophenone; Mellow sweet aroma was positively correlated with megastigmatrienone, pyrazine, tetramethyl-, and furfural; Pepper aroma was positively correlated with 1-dodecanol, 3,7,11-trimethyl-, 2,6,6-trimethyl-2-cyclohexenone and ethanone, 1-(2-furanyl)-. The resin aroma was positively correlated with dimethyl phthalate and dihydro-beta-ionone.
The characteristic volatiles of different CTLs varieties were positively correlated with the aroma of CTLs, such as the characteristic volatiles of DX4 CTLs, including nonanal and pyrazine, tetramethyl, which corresponded to sweet, roasted, and nutty honey aromas, respectively. In N-Jalap HABANA CTLs, geranyl acetone and α-curcumene were positively correlated with the honey sweet aroma. The characteristic volatiles farnesyl acetone C and propanoic acid, 2-methyl-, were positively correlated with coffee and roasted aroma in HVA CTLs. In BESUKI CTLs, dihydro-beta-ionone was positively correlated with hay aroma; In MATA FINA CTLs, acetaldehyde and 4-oxoisophorone were positively correlated with honey sweet and roasted aroma, respectively. In CX14 CTLs, characteristic volatiles were not strongly correlated with the aroma, but the volatiles with a pleasant aroma, such as the characteristic volatiles ethanone, 1-(2-pyridinyl)-, tigelic acid, benzoic acid, 2-methoxy-, methyl ester, and bourgeonal, corresponded to the burn sweet, roasted and hay aromas, respectively. Furthermore, the higher contents of ethanone, 1-(3-pyridinyl)-and pentanoic acid, 3-methyl- in E-HABANO 2000 CTLs were positively correlated with featured roasted and resin aromas, respectively. The above results showed that the characteristic volatiles of CTLs had an important contribution to the aroma.