Anhydrous ethanol (chromatographic grade, ≥99.97%) was purchased from Tianjin kemiou Chemical Reagent Co., Ltd. (Tianjin, China); 2-methyl-2-butanol (≥99.5%) was chromatographic grade standards and purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Alkane standard solutions (C7-C30) were from Sigma-Aldrich (Beijing, China).

Samples were collected from the most famous region of SSAB production (Renhuai, Guizhou Province, China; 27°33′30″ ~ 28°10′19″N and 105°59′49″ ~ 106°35′50″E). The samples are the base liquor and distilled from the 3rd RF to the 5th RF of jiupei. There were four grades base liquor in each RF, namely superior, first, second, and third-grade base liquor. The ethanol contents of the liquor samples are shown in Supplementary Table S1. Six parallel samples of each grade were collected under the same production conditions. In this way, a total of 72 samples were collected. All samples were stored, sealed and protected from light at room temperature.

Ten panelists with excellent professional qualifications were organized to conduct the sensory evaluation of aromas strictly following the Baijiu flavor wheel of SSAB according to GB/T 33405–2016. The aroma-related indicators and corresponding reference standards include sauce (soybean paste-like aroma), Qu (daqu-like aroma), flower and fruit (fresh flower and fruit-like aroma), distilled grain (steamed sorghum-like aroma), roast (2-ethyl-3, 5-dimethyl pyrazine-like aroma), fermented (ethyl hexanoate-like aroma), grain (sorghum-like aroma), herb (hexanal-like aroma), baked (baked grain cereals-like aroma) and sour (acetic acid-like aroma). The taste indicators include softness, fullness, harmony, purity and persistence. The sensory evaluation was conducted on a five-point scale. The closer the score is to five, the more pronounced the corresponding flavor profile is. The sensory evaluation of each sample was visualized in the radar chart.

E-nose analysis was performed with a PEN3 E-nose (Airsense Analytics GmbH, Schwerin, Germany), referring to Zhang et al. (25), with slight modifications. There were ten metal-oxide gas sensors, each of which could reflect different sensory properties depending on its sensitivity to compounds. According to the performance of E-nose, W1C, W5S, W3C, W6S, W5C, W1S, W1W, W2S, W2W, and W3S are sensitive to aromatic compounds; nitrogen oxides; ammonia and aromatic compounds; hydrogen; alkanes and aromatics; methane and a broad range of compounds; sulfur compounds and terpenes; alcohols, aldehydes and ketones; aromatics and organic sulfur compounds; long-chain alkanes, in sequence (9). The 1 ml sample was transferred into a 20 ml headspace vial, capped and allowed to stand at room temperature for 30 min. The equipment must be preheated for more than 30 min before testing and cleared and standardized after each testing. The testing parameters are set as follows: the temperature was 20 ± 2°C; the sample preparation time was 5 s. The measurement time was 45 s, the measurement interval was 1 s, the measurement count was 1 s, the sensor cleaning time was 60 s, and the auto-zero time was 1 s; the intake flow rate was 600 ml/min. Each sample was measured in triplicate.

Following Wang’s (19) method with slight modifications, samples were diluted to 10% (v/v) of ethanol content using redistilled water. 10 mL of diluted liquor, 3.0 g NaCl and 10 μl of 2-methyl-2-butanol (as the internal standard at final content of 8.09 mg/L) were transferred into a 20 mL headspace vial were shocked at 50°C and 280 r/min for 5 min. Then, the volatiles was extracted with an automatic sampler (Supelco, Bellefonte, PA, United States) combined with SPME fiber (DVB/CAR/PDC, divinylbenzene/carboxen/polydimethylsiloxane, 2 cm, 50/30 μm, Supelco Inc., Bellefone, PA, United States) at 50°C for 45 min.

Volatile compounds were analyzed by GC–MS (GC–MS-TQ 8040, Shimadzu Co., Kyoto, Japan) equipped with SH-Rtx-Wax capillary column (30 m × 0.25 mm × 0.25 μm, Shimadzu Co., Kyoto, Japan). The SPME fiber was desorbed for 5 min at an inlet temperature of 250°C. The initial temperature of the column was maintained at 37°C for 5 min, then raised to 45°C at 3°C/min for 5 min, increased to 100°C at 10°C/min for 4 min, warming up to 180°C at 5°C/min for 3 min, and finally raised to 220°C at 10°C/min for 4 min. The injection was set to split mode with a split ratio of 50:1. Helium (purity ≥99.999%) was used as the carrier gas at a 1.0 ml/min flow rate. The ion source adopted an electron ionization source with 70 eV of electron energy. MS transmission line and ion source temperature were 250°C and 230°C, respectively. The mass spectrometry data was collected using full-scan mode (m/z 35–550), and the solvent delay time was 5 min.

After the raw peaks are extracted and processed, the peaks are qualified by matching the mass spectra and retention indexes in NIST17 (United States National Institute of Standards and Technology) database. The retention indexes were calculated by running C7-C30 n-alkanes under the same chromatographic conditions referring to the improved Kovats’s method (26). The identified compounds with match scores above 80 were retained for further analysis. At last, the relative content of each compound was calculated by dividing the isolated compound’s peak area by the internal standard’s peak area (9, 27). Each sample was measured in a sextuplicate.

Radar charts and principal component analysis (PCA) score plots were drawn by OriginPro 9.0 (MicroCal Inc., MA, United States). Heatmaps were plotted by R 4.2.1 software (Auckland University, Auckland, New Zealand). SIMCA 17.0 (Umetricus Inc., Sweden) calculated the variable importance projection (VIP) values. Compounds with VIP values >1 were identified as differential compounds. Correlation analysis between the sensors’ response values and the differential compounds was calculated according to spearman’s correlation coefficient with R software. When the absolute value of |ρ| > 0.6 was considered as a robust correlation (28). The correlative network was visualized with Gephi 0.9.3 (Web Atlas, Paris, France).

The aroma profiles of the different quality grades of base liquor of three RFs are shown in Figures 2A,C,E. The significant aroma-related indicators are sauce, floral and fruity, fermented and baked aromas. Among them, the sauce, floral and fruity, fermented aromas are positively correlated with the quality grade of the base liquor, while the baked aroma is reversed. A baked aroma gives a unique flavor to SSAB, but too much baked aroma will cause an imbalance of flavors. Moreover, the sauce and fermented aromas of 4th RF base liquor are the most outstanding, suggesting the quality of 4th RF base liquor is the best of the three RFs. The taste evaluation of the different quality grades of base liquor of three RFs is shown in Figures 2B,D,F. It showed a trend with the taste indicators in the base liquor of quality grades. The scores of taste indicators are positively correlated with the quality grades of base liquor. The superior-grade base liquor has a full taste with persistence, harmony, softness and purity. On the contrary, the third-grade base liquor has a light taste, a weak aroma and disharmony.

The flavor profiles exhibited by the base liquor from the 3rd RF, 4th RF, and 5th RF are closely related to the process. With the rounds of fermentation and repeated high-temperature cooking of jiupei increased, the intensity of floral and fruity aromas gradually decreased. In contrast, the baked aroma in the liquor became more prominent.

The response intensities of sensors are closely related to the content of corresponding compounds in samples. As shown in Figure 3, W1C, W5S, W1W, and W2S sensors have high reaction intensities, which indicates that the samples have high levels of aromatics, nitrogen oxides, sulfur compounds, alcohols, aldehydes and ketones. The response intensities of W1C, W1S, W1W and W2S in the 1st-grade base liquor of 3rd RF and 5th RF is higher than other grade base liquor. Moreover, in the 4th RF base liquor, the response intensity of the W1C, W1S, W1W, and W2S sensors are positively correlated with the quality grade of the base liquor. It is suggested that better quality base liquor has a higher abundance of aromatics, methane, sulfur compounds, alcohols, aldehydes and ketones. Besides, with the number of RF increased, the intensities of W1W and W2S sensor responses gradually increased.

PCA is a statistical tool used to extract information from variables and explain the differentiation in samples (29). PCA score chart of response intensities is shown in Figure 4. The two principal components can explain 89.9% of the total variance, indicating that E-nose can distinguish the different quality grades of base liquor well. The 3rd and 4th RF samples are close together, while the 5th RF is farther away from the other samples. It indicates that the aroma profile is more similar between the 3rd and 4th RF samples compared to the 5th RF. The 5th RF sample has a distinctive style due to its noticeable baked aroma.

The E-nose is sensitive to the flavors in the sample, and the intensity of sensor response intensity is positively correlated with the relevant volatile compound content in the sample (30). The high-intensity response of most sensors suggests that the composition of SSAB is complex. Sun et al. observed that the unique “sauce” flavor of SSAB was a combination of flavors (31). In similarity to other Chinese baijiu, alcohols and aldehydes are crucial flavors with high content in SSAB (32). In contrast, nitrogen oxides and sulfur compounds are present in small concentrations in SSAB, but they are essential contributors to the distinctive aromas of the liquor. Among the nitrogen oxides, pyrazines are one of the essential Maillard reaction products (33), contributing unique aromas such as baked and nutty aromas (34). Sulfur compounds, a class of compounds with high odor activity at low sensory thresholds, also contribute to SSAB (35). As a result, the W5S sensor exhibits different response intensities in the different grades of the base liquor.

A total of 179 compounds were identified in samples by HS-SPME-GC-MS, including 85 esters, 18 alcohols, 7 acids, 11 aldehydes, 16 ketones, 13 alkanes, 4 pyrazines, and 25 others (Supplementary Table S2). VIP values are usually a criterion for screening the differential compounds (28). This study calculated VIP values by the partial least squares-discrimination analysis (PLS-DA) model. The discriminative model was evaluated by a permutation test (n = 200). As shown in Supplementary Figures S1A–C, in the three permutation tests, the slope of R² in the 3rd, 4th, and 5th RF was 0.0847, 0.304 and 0.0273 (>0), respectively. The intercept of Q² on the y-axis in 3rd, 4th, and 5th RF was –0.535, −0.634 and –0.544 (<0.05), respectively. The permutation tests indicated that the PLS-DA model is not overfitting to the data. According to VIP values >1, 30, 30, 28 differential compounds (Supplementary Table S3) in the different quality grades of 3rd RF, 4th RF, and 5th RF base liquor were identified, respectively. As shown in Figure 5 and Table 1, 16 common differential compounds are shared in the base liquor of three RFs, including 11 esters, 2 aldehydes, 1 alcohol, 2 ketones. In order to further observe the performance of differential compounds in the different quality grades of base liquor, Figures 6B, 7B, 8B show the PCA score plots of the differential compounds in the different quality grades of base liquor of 3rd RF, 4th RF and 5th RF, respectively. The PCA biplots explain 96.43, 97.94, and 97.89% of the total variance in the first two principal components, respectively.

Figure 9 established a correlation network of 10 E-nose sensors with the differential compounds. 66 pairs of significant relationships were screened based on |ρ| > 0.6, including 50 positive and 16 negative correlations. The compounds closely related to the sensor response intensity are 11 esters, 3 alcohols, 3 acids, 2 aldehydes, 3 ketones, and 2 others. The highest number of compounds is associated with the W5C sensor (14 compounds), followed by the W3S sensor (12 compounds), and are related to the wide range-aromatic property sensors. The compounds of highest correlation with W5C, W3C, W1C, W6S, W2S, W1W, W5S, W2W, W3S, and W1S sensors are furfuryl ethyl ether (ρ = 0.879), butanoic acid ethyl ester (ρ = 0.882), isopentyl hexanoate (ρ = 0.751), nonanoic acid ethyl ester (ρ = 0.684), isopentyl hexanoate (ρ = 0.753), nonanoic acid ethyl ester (ρ = 0.722), 3-methyl-1-butanol (ρ = −0.688), octanoic acid (ρ = −0.659), 2-undecanone (ρ = 0.685), octanoic acid (ρ = −0.679), respectively.

The W5C, W3C, W1C, and W2S sensors are all positively correlated with hexanoic acid ethyl ester (fruity aroma), nonanoic acid ethyl ester (fruity aroma), furfuryl ethyl ether (aging aroma) and isopentyl hexanoate (fruity aroma). W5C and W3C sensors are positively correlated with butanoic acid ethyl ester (pineapple aroma), benzeneacetic acid ethyl ester (honey aroma) and furfural (almondy aroma), suggesting that these compounds have a significant impact on the flavor of SSAB. In addition, W5C, W1C, W6S, W1W, W2S, and W3S sensors are positively correlated with 2-undecanone (fruit aroma) and isopentyl hexanoate (apple aroma). However, the W5C and W3C sensors are negatively correlated with acetic acid. It can be seen that most sensors are highly correlated with esters, especially W5C and W3C sensors. These esters were related to the floral and fruity aromas, suggesting that W5C and W3C sensors are susceptible to the floral and fruity aromas.