Differentiating Huangjiu with Varying Sugar Contents from Different Regions Based on Targeted Metabolomics Analyses of Volatile Carbonyl Compounds
by
Junting Yu
1, 
Zhilei Zhou
1,2,3,
Xibiao Xu
4,
Huan Ren
4,
Min Gong
5,
Zhongwei Ji
1,2,3,
Shuangping Liu
1,2,3,
Zhiming Hu
4 and
Jian Mao
1,2,3,6,* 1
National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
2
Jiangnan University (Shaoxing) Industrial Technology Research Institute, Shaoxing 312000, China
3
Jiangsu Provincial Engineering Research Center for Bioactive Product Processing, Jiangnan University, Wuxi 214122, China
4
Shaoxing Nverhong Winery Co., Ltd., Shaoxing 312000, China
5
College of Life Sciences, Linyi University, Linyi 276000, China
6
National Engineering Research Center for Huangjiu, Shaoxing 312000, China
*
Author to whom correspondence should be addressed.
Foods 2023, 12(7), 1455; https://doi.org/10.3390/foods12071455
Submission received: 3 March 2023
/
Revised: 23 March 2023
/
Accepted: 27 March 2023
/
Published: 29 March 2023
(This article belongs to the Special Issue Innovative Chromatographic and Spectroscopic Analytical Methods for Profiling Chemicals in Foods)
Abstract
:Huangjiu is one of the oldest alcoholic beverages in the world. It is usually made by fermenting grains, and Qu is used as a saccharifying and fermenting agent. In this study, we identified differential carbonyl compounds in Huangjiu with varying sugar contents from different regions. First, we developed and validated a detection method for volatile carbonyl compounds in Huangjiu, and for optimal extraction, 5 mL of Huangjiu and 1.3 g/L of O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) were incubated at 45 °C for 5 min before extracting the volatile carbonyl compounds at 45 °C for 35 min. Second, the targeted quantitative analysis of 50 carbonyl compounds in Huangjiu showed high levels of Strecker aldehydes and furans. Finally, orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to differentiate between Huangjiu with different sugar contents, raw materials, and region of origin. A total of 19 differential carbonyl compounds (VIP > 1, p < 0.05) were found in Huangjiu with different sugar contents (semidry and semisweet Huangjiu), and 20 differential carbonyl compounds (VIP > 1, p < 0.05) were found in different raw materials for Huangjiu production (rice and nonrice Huangjiu). A total of twenty-two and eight differential carbonyl compounds, with VIP > 1 and p < 0.05, were identified in semidry and semisweet Huangjiu from different regions (Zhejiang, Jiangsu, Shanghai, and Fujian), respectively.
1. Introduction
Chinese rice wine (Huangjiu), along with beer and wine, is one of the oldest alcoholic beverages in the world [1]. Huangjiu is usually made by fermenting grains, with Qu as a saccharifying and fermenting agent. The traditional process of Huangjiu production generally includes maceration, steaming of materials, cooling and addition of Qu, primary fermentation, Kaipa, post-fermentation, pressing and filtering, boiling and sterilization, storage, blending, and packaging [2], as shown in Figure 1. Owing to its specific brewing process, the flavor profile of Huangjiu differs markedly from those of beer, wine, and other alcoholic beverages [1]. Depending on the region and the primary raw materials used, Huangjiu can be divided into the following two categories: rice Huangjiu, which is typically made with glutinous rice, with japonica rice as the primary raw material, and is primarily produced in southern China, and nonrice Huangjiu, which is typically made with millet, buckwheat, and oats as the primary raw materials and is primarily produced in northern China [3]. Furthermore, depending on the total sugar contents, Huangjiu can be divided into dry Huangjiu (≤15 g/L), semidry Huangjiu (15.1–40.0 g/L), semisweet Huangjiu (40.1–100 g/L), and sweet Huangjiu (>100 g/L) [4].
Levels of carbonyl compounds are usually low in alcoholic beverages, but being the diverse and important class of flavoring substances, they are common in wine [5,6], beer [7,8,9], vodka [10], brandy [11], and Chinese baijiu [12,13]. Some carbonyl compounds are directly derived from raw materials, whereas others are produced during alcoholic fermentation and aging processes through a series of chemical reactions, such as oxidation of fatty acids and higher alcohols, Strecker degradation, aldehyde condensation, or the Maillard reactions [9,14,15,16,17,18,19]; thus, carbonyl compounds are susceptible to various factors and can be used as the key to differentiate among beverages. Carbonyl compounds are highly reactive compounds [20], which are difficult to trap by Headspace Solid-Phase Microextraction (HS-SPME) owing to their low content in Huangjiu and their volatile and reactive nature; however, the properties of these compounds can be changed by derivatization to be more favorable for SPME. In many previous studies, PFBHA was used for the detection and derivatization of carbonyl compounds in alcoholic beverages [5,8,9,21].
Metabolomics has been widely used in recent years for the identification and differentiation of compounds of food origins. Peng Q. et al. used gas chromatography (GC)-flash electronic nose in combination with chemometrics to successfully differentiate between Chinese Tongshan kaoliang spirits from different geographical origins [22]. Leborgne C. et al. reported the color of rosé wines by polyphenol-targeted metabolomics, which can also be applied to identify the varietal and geographical origin of the wines [23]. Moreira N et al. used PFBHA derivatization combined with HS-SPME-GC-MS to determine the content of carbonyl compounds in various aged port wines, and to differentiate among them [5]. However, there are no studies on targeted metabolomics using GC-MS to analyze volatile carbonyl compounds in Huangjiu.
In this study, we aimed to develop and establish a method for the analysis of volatile carbonyl compounds in Huangjiu by PFBHA derivatization combined with HS-SPME-GC-MS, and to investigate the differences in volatile carbonyl compounds contents in Huangjiu from different regions and varying sugar contents using targeted quantitative metabolomics and multivariate statistical analysis.
2. Materials and Methods
2.1. Samples
A total of 55 commercial Huangjiu samples were used in this study, which were divided into 27 semidry and 28 semisweet Huangjiu according to their sugar content, and into rice and nonrice Huangjiu according to the raw materials used. Among them, rice-semidry Huangjiu included six Huangjiu of Jiangsu origin (SDJ), nine of Zhejiang origin (SDZ), four of Shanghai origin (SDS), and eight of Fujian origin (SDF). Rice-semisweet Huangjiu included four Huangjiu of Jiangsu origin (SSJ), six of Zhejiang origin (SSZ), four of Shanghai origin (SSS), and three of Fujian origin (SSF). Nonrice-semisweet Huangjiu were 11 in number and from various origins (SSN).
2.2. Reagents and Standards
PFBHA (≥99%), hexanal (≥96%), nonanal (≥95%), decanal (≥97%), 2-methylpropanal (≥99%), (E)-2-heptenal (≥95%), glyoxal (≥40%), phenyl acetaldehyde (≥95%), furfural (≥99%), 5-methyl-2-furfural (≥95%), methional (≥95%), 1-octen-3-one (≥97%), and cyclopentanone (≥99%) were purchased from J&K Scientific (Beijing, China). Ethanal (≥99.5%), propanal (≥99%), heptanal (≥98%), and acrolein (≥99%) were purchased from Aladdin (Shanghai, China). Butanal (≥99.5%), pentanal (≥98%), undecanal (≥97%), dodecanal (≥95%), tridecanal (≥95%), (E)-2-butenal (≥98%), (E)-2-pentenal (≥95%), (E)-2-hexenal (≥98%), (E)-2-octenal (≥95%), (E)-2-nonenal (≥95%), (E)-2-decenal (≥95%), 2-pentanone (≥99%), 2-hexanone (≥99%), 4-heptanone (≥98%), 2-heptanone (≥98%), 2-nonanone (≥99%), benzaldehyde (≥99%), 2-phenyl-2-butenal (≥97%), 3-methyl-2-butanone (≥99.5%), 3-pentanone (≥99.5%), 3-penten-2-one (≥95%), and cyclohexanone (≥99.7%) were purchased from Macklin (Shanghai, China). Acetophenone (≥99.5%), 2-methylbutanal (≥98%), 3-methylbutanal (≥98%), 2-octanone (≥99%), methyl glyoxal (≥40%), 6-methyl-5-hepten-2-one (≥97%), and ethanol (≥99.8%) were obtained from Sinopharm Chemical Reagent (Shanghai, China). Octanal (≥98%), 2-decanone (≥99%), acetoin (≥98%), diacetyl (≥98%), and 3-methyl-2-butenal (≥97%) were purchased from TCI (Shanghai, China). p-fluorobenzaldehyde (internal standard, ≥98%) was purchased from Sigma-Aldrich (Shanghai, China).
Ultrapure water was obtained from a Milli-Q water purification system (Millipore, France). The divinylbenzene/carbon wide range/polydimethylsiloxane (DVB/CWR/PDMS, 80 μm) SPME fibers were purchased from Agilent Technologies (Geneva, Switzerland).
The 20 g/L PFBHA solution was prepared with ultrapure water on a daily basis. A 107 mg/L internal standard (p-fluorobenzaldehyde) solution was prepared in ethanol. Standard solutions of the other compounds were also prepared in ethanol and diluted with a Huangjiu simulant (15% ethanol, 5 g/L lactic acid, pH = 4). All solutions were stored at 4 °C.
2.3. Derivatization and HS-SPME Procedure
Based on the derivatization method of Nathalie Moreira et al. [5], HS-SPME-related experimental parameters were optimized. The experiment was performed with a DVB/CWR/PDMS (80 μm) extraction head (Agilent Technologies, Geneva, Switzerland), and the HS-SPME procedure was performed with a Combi-PAL autosampler (Varian Pal Autosampler, Geneva, Switzerland). After equilibrating the vial at the extraction temperature for 3–15 min with stirring at 250 rpm, the extraction head was exposed to HS at the same temperature, and the extraction head was desorbed at the GC injector for 5 min.
First, the effect of sample volume on the extraction efficiency was evaluated by adding 2, 3, 4, and 5 mL of Huangjiu, 5 μL of internal standard (107 mg/L), and 2 g/L of PFBHA (20 g/L) in a 20 mL vial. After incubating at 50 °C for 5 min, extraction was performed at 50 °C for 50 min. Next, using the same extraction procedures and adding 0, 1, and 2 g of NaCl to the vials containing 5 mL of Huangjiu samples, the effect of the ionic strength on the extraction efficiency was assessed.
The experimental parameters, including extraction temperature, extraction time, incubation time, and PFBHA concentration were optimized by a central composite design (CCD, α = 2.000) including a 24 factorial design with eight axial points and five replicates in the center of the design. A total of 29 experiments were generated by CCD and executed in random order. The factor levels and experimental domains are listed in Table 1. CCD experiments allowed for a reduction in the number of experiments, thereby reducing time and cost, while assessing the contribution of each parameter and the relationship among them [5,24].
2.4. GC-MS Analysis
An Agilent 8890 GC (Agilent Technologies, Shanghai, China) and a 7000D triple quadrupole MS were employed, and VF-WAXms (30 m × 0.25 mm × 0.25 μm, Agilent Technologies, Amsterdam, Netherlands) columns were used. The injection port temperature was 250 °C in a nonsplit injection mode. High-purity helium (≥99.999%) was used as the carrier gas at a constant flow rate of 1 mL/min. The initial oven temperature was held for 2 min at 40 °C, which increased up to 230 °C at a rate of 5 °C/min and was held for 10 min. Electron ionization (EI) mode was used at 70 eV ionization energy. The ion source temperature was 230 °C. The characterization was performed in full scan mode, 33–400 m/z, at a scan rate of 6 scan/s. The quantitative analysis of carbonyl compounds was performed in the selected ion monitoring mode.
2.5. Qualitative and Quantitative Analyses
After PFBHA derivatization, most carbonyl compounds generated two or more isomers [24], and the identification results are shown in Table 2. The mass spectra of PFBHA derivatives with 181 m/z as the characteristic ion were used to characterize the compounds by (1) comparing MS ion fragments with the National Institute of Standards and Technology (NIST 20) with >70% similarity; (2) comparing the retention time and mass spectra of the standard compounds under the same experimental conditions; and (3) the retention indices of each compound were calculated by n-alkanes (C7–C30) and identified by comparing the retention indices of the standard compounds with those described in the relevant literature.
The carbonyl compounds were quantified by establishing a standard curve, which was carried out in a simulant Huangjiu (15% ethanol, 5 g/L lactic acid, pH = 4). If isomers were present after PFBHA derivatization, the sum of the isomer peak areas was used for quantification.
2.6. Method Validation
The limit of detection (LOD) was defined as the minimum concentration of the substance that can be detected when the signal-to-noise ratio is 3, and the limit of quantification (LOQ) was defined as the minimum concentration of the substance that can be quantified when the signal-to-noise ratio is 10. The precision experiment included interday and intraday precision. In the intraday precision experiment, six samples of the same level were measured on the same day, whereas in the interday precision test, six samples of the same level were analyzed on different days, and the precision results are expressed as the relative standard deviation (RSD).
Referring to the method in the literature [25], the volatile compounds in Huangjiu were removed by solvent-assisted flavor evaporation. The nonvolatile matrix was adjusted to the initial volume with 15% ethanol and was extracted twice with Poly-Sery PSD cartridges (500 mg, 6 mL/30 pcs, CNW, Shanghai, China) to remove the residual volatiles until the Huangjiu was odorless. The recoveries were determined by adding standard solutions of carbonyl compounds at low, medium, and high concentrations to the odorless Huangjiu.
2.7. Statistical Analyses
All Huangjiu samples were obtained in triplicate, and results are expressed as mean ± standard deviation (Mean ± SD). The CCD design and analysis were performed using Statistica 12 (Statsoft Inc., Tulsa, OK, USA). Analysis of variance (ANOVA) was performed to analyze the data using SPSS 26 (SPSS Inc., Chicago, IL, USA). OPLS-DA was performed with SIMCA-P 13 (Umetrics, Umea, Sweden). GraphPad Prism8 (GraphPad Software, CA, USA) software was used to perform the Student’s t-test, and differences were deemed significant at p < 0.05.
3. Results and Discussion
3.1. Extraction Method Optimization
First, the effect of sample volume on the derivative extraction effect was determined, and the results showed that the volume of the sample did not significantly affect the extraction effect, which is consistent with previous findings in alcoholic beverages (Figure S1) [5]. Therefore, the sample addition volume was kept at 5 mL. Secondly, NaCl of different concentrations was used to determine the effect of ionic strength on the extraction effect, which frequently affected the extraction of volatiles because of the salt precipitation effect (Figure S2). Under the experimental conditions, the extraction efficiency of the samples with the addition of NaCl decreased significantly, which is consistent with the results of previous studies [9,21]. This indicated that the addition of NaCl increased the spatial potential resistance effect and decreased the extraction efficiency; therefore, the samples were prepared without the addition of NaCl.
HS-SPME conditions and PFBHA addition levels were optimized using a CCD. The response values were based on the total peak areas of carbonyl compound derivatives, and some substances with high contents, such as ethanal, 2-butanone, 2-methylpropanal, 3-methylbutanal, acetoin, 2-furfural, and benzaldehyde, were excluded from the total peak areas to prevent their interference with the results. Thus, a good response model was constructed. The results are shown in Table S1. ANOVA was performed to determine the importance of each experimental factor and its interactions, which yielded a coefficient of determination R2 of 0.986 and an adjusted-R2 of 0.973 for the method, indicating that the experimental data had a good fit. The experimental error was calculated using replication values of the central point with an RSD of 2.80%, indicating that the method had good reproducibility. More details of ANOVA are shown in Table S2. The multivariate quadratic corresponding surface regression model was obtained, as given:
Total area = −2.442 × 108 − 3.254 × 106 × A + 2.372 × 108 × B + 3.006 × 106 × C + 8.637 × 106 × D − 8.890 × 105 × AB − 1.226 × 105 × AC − 8.881 × 104 ×AD + 2.045 × 106× BC − 3.347 × 106 × BD + 1.065 × 105 × CD + 5.602 × 105 × A2 − 7.498 × 107 × B2 − 3.107 × 104 × C2 − 5.599× 104 × D2
To characterize the primary factors and their interactions that affect the extraction efficiency, a Pareto chart was used (Figure 2). Extraction temperature and time were found to have a strong positive effect on the results, whereas PFBHA concentration and incubation time were found to have a negative effect on the results. The extraction temperature is a crucial factor affecting the derivative extraction of carbonyl compounds, which affects the partition coefficients of volatile compounds between the sample and HS, and between HS and the extracted fiber head. The increase in extraction temperature increases the HS concentration of volatile compounds, but decreases the adsorption of top air to the fiber [21,26]. The high concentration of PFBHA saturates the extraction fiber head with PFBHA, thereby decreasing the total amount of volatile carbonyl compounds analyzed [8].
A significant interaction was observed between the experimental factors affecting the response values of carbonyl compound derivatives. The interaction between extraction time and PFBHA concentration showed that the response values were high at low PFBHA concentrations (Figure 3a). The interaction between PFBHA and extraction temperature resulted in greater response values at higher temperatures (Figure 3b). Additionally, the interaction between extraction time and extraction temperature significantly affected the extraction results, with the response values increasing significantly with the increase in temperature and time (Figure 3c).
Incubation time has a negative effect on extraction efficiency, but according to past experience, this time cannot be ignored, and a smaller reaction time of 5 min is optional [21]. There is an interaction between extraction time, PFBHA, and extraction temperature. In order to improve experimental efficiency, the extraction time was less than 40 min. Too high a temperature can denature Huangjiu, so the temperature should not be too high, ranging from 40 to 50 °C. For the convenience of the experiment, the extraction temperature and extraction time should preferably be integers. The concentration of PFBHA is greatly affected by temperature and time, and the overall impact on extraction efficiency increases first, and then decreases. Based on the above considerations, the optimal experimental parameters can be obtained according to the corresponding optimizer, as shown in Figure S3.
Therefore, the optimal experimental conditions for the analysis of volatile carbonyl compounds in Huangjiu were as follows: PFBHA concentration of 1.3 g/L, extraction temperature of 45 °C for 35 min, and SPME fiber addition after 5 min of incubation. Comparison with the optimal parameters for carbonyl compound extraction in port wine [5] and beer [8] showed that the optimal experimental conditions for the derivative extraction of carbonyl compounds in different alcoholic beverages differed, owing to the differences in the matrix.
3.2. Method Validation
The linear range, coefficient of determination, LOD, and LOQ of the method were determined under optimal experimental conditions, and the results are shown in Table 3. A total of 49 carbonyl compounds, including 11 saturated aldehydes, 8 alkenes, 7 Strecker aldehydes, 3 dicarbonyl compounds, 9 ketones, 2 furans, and 9 other carbonyl compounds were included, with good linearity (r2 ≥ 0.996). The LOD of the compounds ranged from 0.002 to 0.105 μg/L, whereas the LOQ of the compound ranged from 0.007 to 0.317 μg/L. As shown in Table S3, the developed method had a good precision with RSD < 10% for both interday and intraday precision. Furthermore, the recoveries obtained by the method ranged from 91% to 109%, indicating the high accuracy of the method. Therefore, the developed method is suitable for the determination of carbonyl compounds in Huangjiu.
3.3. Quantification of Volatile Carbonyl Compounds in Huangjiu
The volatile carbonyl compounds in Huangjiu were qualitatively analyzed, and the results are shown in Table 2. A total of 53 carbonyl compounds were identified, including 12 alkanals, 8 alkenals, 7 Strecker aldehydes, 3 dicarbonyl compounds, 11 ketones, 3 furans, and 9 other carbonyl compounds, among which glyoxal and methyl glyoxal have not been reported in previous studies on Huangjiu. No significant difference was found in the number of carbonyl compounds found in Huangjiu of different origins and with sugar content.
The 50 carbonyl compounds of semidry Huangjiu (Table S4) and semisweet Huangjiu (Table S5) were quantitatively analyzed. The results showed that Huangjiu contained high levels of propanal, pentanal, hexanal, (E)-2-butenal, 2-methylpropanal, 2-methylbutanal, 3-methylbutanal, benzaldehyde, phenyl acetaldehyde, diacetyl, glyoxal, methyl glyoxal, 2-butanone, 2-furfural, 5-methyl-2-furfural, 3-penten-2-one, acetoin, and 2-phenyl-2-butenal. Among them, alkanals might be obtained from the oxidative degradation of fatty acids, such as enzymatic oxidation of linoleic/linolenic acid, and hexanal is the main product of linoleic acid oxidation [27]. Valine, isoleucine, and leucine yielded 2-methylpropanal, 2-methylbutanal, and 3-methylbutanal, respectively, through Strecker degradation [20]. The oxidation of benzyl alcohol and the action of microbes on aromatic amino acids, phenylacetic acid, and p-hydroxybenzoic acid can all result in the production of benzaldehyde [28], and its concentration can increase with the aging process [29]. Diacetyl can be produced by thermal degradation of the Maillard reactions [20], and a significant difference was found between fresh and aged Huangjiu [30]. Furans (2-furfural, 5-methyl-2-furfural) have a typical caramel aroma, which can be used to distinguish between fresh and aged Huangjiu [30,31], as its content increases during the aging process [1]. Furans are the thermal degradation product of the Maillard reaction [20]. The compound 2-Phenyl-2-butenal is produced during the aging process of Huangjiu and is a key substance [32,33]. Acetoin has a milky aroma and is a crucial component of Huangjiu [34].
The differences in the contents of carbonyl compounds in semidry and semisweet Huangjiu from different origins were analyzed. The contents of propanal, pentanal, heptanal, undecanal, methyl glyoxal, and 2-cyclohexen-1-one in semidry Huangjiu from the Fujian region were significantly higher than those in the other three regions, probably because it is HongquHuangjiu, and the saccharifying ferments used are different from those in other regions [35,36]. The contents of dodecanal, butenal, 3-methyl-2-butenal, glyoxal, 2-pentanone, and cyclopentanone in Huangjiu from the Shanghai region were significantly higher than those from other regions. Shanghai Huangjiu has the same root as Zhejiang Huangjiu, but Shanghai Huangjiu introduced filtration and canning processes in the brewing process, and also added honey and wolfberry, which improved the bitterness of traditional Zhejiang Huangjiu and made the flavor composition very different. The content of 2-heptanone in Huangjiu from the Jiangsu region is significantly lower than that of Huangjiu from other regions, and the content of methional and acetoin is significantly higher than that of Huangjiu from other regions, probably due to the fact that Huangjiu from other regions mainly uses glutinous rice as raw material, while Huangjiu from Jiangsu uses japonica rice instead of glutinous rice [37]. Glutinous rice is the best rice for making Huangjiu [38]; glutinous rice has a higher content of branched chain starch, which is more easily pasted and digested by enzymes [39], and is the main reason for the mellow and pleasant taste of Huangjiu. Compared to glutinous rice, japonica rice has a higher protein content and produces a more nutritious Huangjiu with a higher amino acid content [40]. Among them, Yangzhou rice (japonica rice) is considered to be a good substitute for glutinous rice in the Huangjiu brewing process [41]. The content of 2-phenyl-2-butenal in Huangjiu from the Zhejiang region was significantly higher than that of other regions, in agreement with the results of Xiao et al. [33] when they studied the classification of Huangjiu by region.
Nonrice-semisweet Huangjiu contained significantly higher levels of (E)-2-heptenal and significantly lower levels of 3-methylbutanal than rice Huangjiu. The main raw materials of rice Huangjiu are glutinous rice and japonica rice, which are produced in Jiangsu, Zhejiang, Shanghai, Fujian, and other southern regions of China, while the main raw materials of nonrice Huangjiu are millet, corn, and other coarse grains, produced in Shandong, Shanxi, and other northern regions of China [42]. Because there is a big difference in the nutritional composition of millet and rice, the quality and flavor of the Huangjiu produced also differs greatly [40].
3.4. OPLS-DA Distinguishes between Carbonyl Compounds in Different Huangjiu
The content of carbonyl compounds in Huangjiu from different regions and with different sugar contents varies, which may be because of raw materials [39,41], ferments [36], brewing processes, and aging time [43,44]; however, Huangjiu has strong regional characteristics in terms of flavor composition.
3.4.1. OPLS-DA of Semidry and Semisweet Huangjiu
Data on carbonyl compounds in two sweet types of Huangjiu, semidry and semisweet, were modeled and analyzed (Figure 4) using rice Huangjiu samples. Figure 4 shows clear separation (R2Y = 0.885), and the model exhibited good predictive power (Q2 = 0.813). Based on the OPLS-DA, a total of 19 volatile carbonyl compounds with VIP > 1 and p < 0.05 were screened, and the results are shown in Table 4. The difference between semidry Huangjiu and semisweet Huangjiu lies firstly in the brewing process. Semidry Huangjiu is brewed with water, whereas semisweet Huangjiu is brewed with finished Huangjiu instead of water, thus causing differences in sugars and flavors between the two types of Huangjiu, which may also be the reason for the different contents of carbonyl compounds. The generally higher concentration of carbonyl compounds in semidry Huangjiu, particularly with more benzaldehyde, 2-phenyl-2-butenal, 3-methylbutanal, 2-methylbutanal, and 2-furfural, may be the cause of the stronger and more complex aroma [4].
3.4.2. OPLS-DA of Rice Huangjiu and Nonrice Huangjiu
The OPLS-DA based on carbonyl compounds in different raw Huangjiu showed significant differences between rice Huangjiu and nonrice Huangjiu with clear separation and good predictive power (R2Y = 0.958, Q2 = 0.811, Figure 5), and a total of 20 carbonyl compounds with VIP > 1 and p < 0.05 were identified (Table 5). Rice Huangjiu contained higher levels of Strecker aldehydes (3-methylbutanal, benzaldehyde, 2-methylpropanal, and 2-methylbutanal) than nonrice Huangjiu. The content of Strecker aldehydes is strongly correlated to the aging time [29]. Thus, the higher content of Strecker aldehydes in rice Huangjiu may be because of different raw materials, or because of a longer aging time than that of nonrice Huangjiu.
3.4.3. OPLS-DA of Huangjiu from Different Regions
Different rice Huangjiu from different regions were distinguished by OPLS-DA (Figure 6). In semidry rice Huangjiu (Figure 6a R2Y = 0.936, Q2 = 0.752), a total of 22 carbonyl compounds with VIP > 1 and p < 0.05 were detected (Table 6). As shown in Figure 6a, the Huangjiu from the Fujian region was located in the negative half-axis, while the Huangjiu from the Zhejiang, Jiangsu, and Shanghai regions was located in the positive half-axis, indicating that the characteristics of carbonyl compounds in Huangjiu from the Fujian region were significantly different from those from other regions This might be due to the fact that the Fujian region used Hongqu as the saccharifying fermenter, while the other regions used wheat Qu, and the difference in microorganisms may lead to the difference in carbonyl compounds. As shown in Figure S4A, highly significant positive correlations existed between methyl glyoxal, (E)-2-butenal, and phenyl acetaldehyde, and semidry Huangjiu from the Fujian, Shanghai, and Zhejiang regions, respectively, whereas significant positive correlations existed between methional and semidry Huangjiu from the Jiangsu region.
Semisweet rice Huangjiu (Figure 6b; R2Y = 0.99, Q2 = 0.587) contained eight substances with VIP > 1 and p < 0.05 (Table 7). As shown in Figure S4B, highly significant positive correlations existed between phenyl acetaldehyde and semisweet Huangjiu from the Fujian region, as well as between 2-methylpropanal, 2-methylbutanal, 3-methylbutanal, and semisweet Huangjiu from the Jiangsu region. The compounds 2-pentanone and 4-heptanone were correlated with semisweet Huangjiu from the Shanghai region, whereas no carbonyl compounds correlating to semisweet Huangjiu from the Zhejiang region were discovered.
4. Conclusions
In the present study, a method for identifying carbonyl compounds in Huangjiu was developed by combining HS-SPME-GC-MS and PFBHA derivatization, and was applied to the targeted analysis of volatile carbonyl compounds in Huangjiu. The contents of most of the differential carbonyl compounds, such as benzaldehyde, 2-phenyl-2-butenal, 3-methylbutanal, 2-methylbutanal, and 2-furfural, were higher in semidry Huangjiu than in semisweet Huangjiu. The content of Strecker aldehydes (3-methylbutanal, benzaldehyde, 2-methylpropanal, and 2-methylbutanal) was higher in rice Huangjiu than in nonrice Huangjiu. Methyl glyoxal, (E)-2-butenal, and phenyl acetaldehyde could be used as representative carbonyl compounds in semidry rice Huangjiu from the Fujian, Shanghai, Zhejiang, and Jiangsu regions. In semisweet Huangjiu, the representative carbonyl compounds were phenylglyoxal from the Fujian region, 2-pentanone and 4-heptanone from the Shanghai region, and 2-methylpropanal, 2-methylbutanal, and 3-methylbutanal from the Jiangsu region. No representative carbonyl compounds were found in Huangjiu from the Zhejiang region.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods12071455/s1, Figure S1: Effect of sample volume on extraction efficiency; Figure S2: Effect of ionic strength on extraction efficiency; Figure S3: The result of the corresponding optimizer; Figure S4: The OPLS-DA biplot of Huangjiu from different regions; Table S1: Experimental conditions and response values (total area) of the CCD used to optimize the derivatization conditions of volatile compounds in Huangjiu; Table S2: ANOVA study for responses; Table S3: Precision and accuracy of the proposed method; Table S4: The range of volatile carbonyl compounds in semi-dry Huangjiu from different production areas; Table S5: The range of volatile carbonyl compounds in semi-sweet Huangjiu from different production areas.
Author Contributions
J.Y.: methodology, software, investigation, and writing—original draft; Z.Z.: supervision, writing—review; X.X.: sampling; H.R.: sampling; M.G.: writing—editing; Z.J.: formal analysis, validation; S.L.: writing—editing; Z.H.: sampling; J.M.: project administration, funding acquisition, conceptualization. All authors have read and agreed to the published version of the manuscript.
Funding
The work is supported by the National Key Research and Development Program of China (No. 2021YFD2100102-4) and the National Natural Science Foundation of China (22138004 and 32001828).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data are available from the corresponding author.
Conflicts of Interest
Authors Xibiao Xu, Huan Ren, Zhiming Hu were employed by the company Shaoxing Nverhong Winery Co., Ltd. The company was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
- Wang, J.; Yu, Y.; Gao, X.; Jiang, X.; Huang, M.; Ye, H.; Wu, J.; Zhang, J.; Sun, X.; Wu, Q. Succession patterns of aroma components during brewing process of broomcorn millet (Panicum miliaceum L.) Huangjiu. Food Res. Int. 2022, 154, 110982. [Google Scholar] [CrossRef]
- Xie, G.; Zheng, H.; Qiu, Z.; Lin, Z.; Peng, Q.; Bealu, G.D.; Elsheery, N.I.; Lu, Y.; Shen, C.; Fu, J.; et al. Study on relationship between bacterial diversity and quality of Huangjiu (Chinese Rice Wine) fermentation. Food Sci. Nutr. 2021, 9, 3885–3892. [Google Scholar] [CrossRef]
- Yan, Y.; Chen, H.; Sun, L.; Zhang, W.; Lu, X.; Li, Z.; Xu, J.; Ren, Q. The changes of microbial diversity and flavor compounds during the fermentation of millet Huangjiu, a traditional Chinese beverage. PLoS ONE 2022, 17, e0262353. [Google Scholar] [CrossRef]
- Yu, H.; Xie, T.; Xie, J.; Ai, L.; Tian, H. Characterization of key aroma compounds in Chinese rice wine using gas chromatography-mass spectrometry and gas chromatography-olfactometry. Food Chem. 2019, 293, 8–14. [Google Scholar] [CrossRef]
- Moreira, N.; Araújo, A.M.; Rogerson, F.; Vasconcelos, I.; De Freitas, V.; de Pinho, P.G. Development and optimization of a HS-SPME-GC-MS methodology to quantify volatile carbonyl compounds in Port wines. Food Chem. 2019, 270, 518–526. [Google Scholar] [CrossRef]
- Culleré, L.; Cacho, J.; Ferreira, V. Analysis for wine C5–C8 aldehydes through the determination of their O-(2,3,4,5,6-pentafluorobenzyl)oximes formed directly in the solid phase extraction cartridge. Anal. Chim. Acta 2004, 524, 201–206. [Google Scholar] [CrossRef]
- Wu, Q.J.; Chen, H.L.; Yang, Z. Determination of aging aldehydes in beer by automated Headspace Derivatization Solid Phase Microextraction. Chin. J. Anal. Lab. 2007, 4, 38–41. [Google Scholar]
- Moreira, N.; Meireles, S.; Brandão, T.; de Pinho, P.G. Optimization of the HS-SPME–GC–IT/MS method using a central composite design for volatile carbonyl compounds determination in beers. Talanta 2013, 117, 523–531. [Google Scholar] [CrossRef]
- Saison, D.; De Schutter, D.P.; Delvaux, F.; Delvaux, F.R. Determination of carbonyl compounds in beer by derivatisation and headspace solid-phase microextraction in combination with gas chromatography and mass spectrometry. J. Chromatogr. A 2009, 1216, 5061–5068. [Google Scholar] [CrossRef]
- Sowiński, P.; Wardencki, W.; Partyka, M. Development and evaluation of headspace gas chromatography method for the analysis of carbonyl compounds in spirits and vodkas. Anal. Chim. Acta 2005, 539, 17–22. [Google Scholar] [CrossRef]
- Ledauphin, J.; Barillier, D.; Beljean-Leymarie, M. Gas chromatographic quantification of aliphatic aldehydes in freshly distilled Calvados and Cognac using 3-methylbenzothiazolin-2-one hydrazone as derivative agent. J. Chromatogr. A 2006, 1115, 225–232. [Google Scholar] [CrossRef] [PubMed]
- Changjiang, C. Flavor Compounds of Chinese Kongfujia Liquor. Master’s Thesis, Jiangnan University, Wuxi, China, 2014. [Google Scholar]
- Fan, W.; Qian, M.C. Characterization of Aroma Compounds of Chinese “Wuliangye” and “Jiannanchun” Liquors by Aroma Extract Dilution Analysis. J. Agric. Food Chem. 2006, 54, 2695–2704. [Google Scholar] [CrossRef] [PubMed]
- Martínez-García, R.; García-Martínez, T.; Puig-Pujol, A.; Mauricio, J.C.; Moreno, J. Changes in sparkling wine aroma during the second fermentation under CO2 pressure in sealed bottle. Food Chem. 2017, 237, 1030–1040. [Google Scholar] [CrossRef] [PubMed]
- Saison, D.; De Schutter, D.P.; Delvaux, F.; Delvaux, F.R. Optimisation of a complete method for the analysis of volatiles involved in the flavour stability of beer by solid-phase microextraction in combination with gas chromatography and mass spectrometry. J. Chromatogr. A 2008, 1190, 342–349. [Google Scholar] [CrossRef]
- Ferreira, A.C.D.S.; Reis, S.; Rodrigues, C.; Oliveira, C.; de Pinho, P.G. Simultaneous Determination of Ketoacids and Dicarbonyl Compounds, Key Maillard Intermediates on the Generation of Aged Wine Aroma. J. Food Sci. 2007, 72, S314–S318. [Google Scholar] [CrossRef] [PubMed]
- Baert, J.J.; De Clippeleer, J.; Hughes, P.S.; De Cooman, L.; Aerts, G. On the Origin of Free and Bound Staling Aldehydes in Beer. J. Agric. Food Chem. 2012, 60, 11449–11472. [Google Scholar] [CrossRef]
- Saison, D.; De Schutter, D.P.; Uyttenhove, B.; Delvaux, F.; Delvaux, F.R. Contribution of staling compounds to the aged flavour of lager beer by studying their flavour thresholds. Food Chem. 2009, 114, 1206–1215. [Google Scholar] [CrossRef]
- da Costa, M.S.; Gonçalves, C.; Ferreira, A.; Ibsen, C.; de Pinho, P.G. Further Insights into the Role of Methional and Phenylacetaldehyde in Lager Beer Flavor Stability. J. Agric. Food Chem. 2004, 52, 7911–7917. [Google Scholar] [CrossRef]
- Moreira, N.; Lopes, P.; Cabral, M.; de Pinho, P.G. HS-SPME/GC-MS methodologies for the analysis of volatile compounds in cork material. Eur. Food Res. Technol. 2016, 242, 457–466. [Google Scholar] [CrossRef]
- López-Vázquez, C.; Orriols, I.; Perelló, M.-C.; de Revel, G. Determination of aldehydes as pentafluorobenzyl derivatives in grape pomace distillates by HS-SPME-GC/MS. Food Chem. 2011, 130, 1127–1133. [Google Scholar] [CrossRef]
- Peng, Q.; Tian, R.; Chen, F.; Li, B.; Gao, H. Discrimination of producing area of Chinese Tongshan kaoliang spirit using electronic nose sensing characteristics combined with the chemometrics methods. Food Chem. 2015, 178, 301–305. [Google Scholar] [CrossRef] [PubMed]
- Leborgne, C.; Lambert, M.; Ducasse, M.-A.; Meudec, E.; Verbaere, A.; Sommerer, N.; Boulet, J.-C.; Masson, G.; Mouret, J.-R.; Cheynier, V. Elucidating the Color of Rosé Wines Using Polyphenol-Targeted Metabolomics. Molecules 2022, 27, 1359. [Google Scholar] [CrossRef]
- Schmarr, H.-G.; Potouridis, T.; Ganß, S.; Sang, W.; Köpp, B.; Bokuz, U.; Fischer, U. Analysis of carbonyl compounds via headspace solid-phase microextraction with on-fiber derivatization and gas chromatographic–ion trap tandem mass spectrometric determination of their O-(2,3,4,5,6-pentafluorobenzyl)oxime derivatives. Anal. Chim. Acta 2008, 617, 119–131. [Google Scholar] [CrossRef] [PubMed]
- Zhou, Z.; Jian, D.; Gong, M.; Zhu, S.; Li, G.; Zhang, S.; Zhong, F.; Mao, J. Characterization of the key aroma compounds in aged Zhenjiang aromatic vinegar by gas chromatography-olfactometry-mass spectrometry, quantitative measurements, aroma recombination and omission experiments. Food Res. Int. 2020, 136, 109434. [Google Scholar] [CrossRef] [PubMed]
- Pellati, F.; Benvenuti, S.; Yoshizaki, F.; Bertelli, D.; Rossi, M.C. Headspace solid-phase microextraction-gas chromatography–mass spectrometry analysis of the volatile compounds of Evodia species fruits. J. Chromatogr. A 2005, 1087, 265–273. [Google Scholar] [CrossRef]
- Rocha, S.; Delgadillo, I.; Correia, A.J.F. GC−MS Study of Volatiles of Normal and Microbiologically Attacked Cork from Quercus suber L. J. Agric. Food Chem. 1996, 44, 865–871. [Google Scholar] [CrossRef]
- Genovese, A.; Gambuti, A.; Piombino, P.; Moio, L. Sensory properties and aroma compounds of sweet Fiano wine. Food Chem. 2007, 103, 1228–1236. [Google Scholar] [CrossRef]
- Feng, T.; Hu, Z.; Chen, L.; Chen, D.; Wang, X.; Yao, L.; Sun, M.; Song, S.; Wang, H. Quantitative structure-activity relationships (QSAR) of aroma compounds in different aged Huangjiu. J. Food Sci. 2020, 85, 3273–3281. [Google Scholar] [CrossRef]
- Chen, S.; Wang, C.; Qian, M.C.; Li, Z.; Xu, Y. Characterization of the Key Aroma Compounds in Aged Chinese Rice Wine by Comparative Aroma Extract Dilution Analysis, Quantitative Measurements, Aroma Recombination, and Omission Studies. J. Agric. Food Chem. 2019, 67, 4876–4884. [Google Scholar] [CrossRef]
- Chen, S.; Xu, Y.; Qian, M.C. Comparison of the aromatic profile of traditional and modern types of Huang Jiu (Chinese rice wine) by aroma extract dilution analysis and chemical analysis. Flavour Fragr. J. 2018, 33, 263–271. [Google Scholar] [CrossRef]
- Wang, N.; Chen, S.; Zhou, Z. Age-dependent characterization of volatile organic compounds and age discrimination in Chinese rice wine using an untargeted GC/MS-based metabolomic approach. Food Chem. 2020, 325, 126900. [Google Scholar] [CrossRef] [PubMed]
- Xiao, Z.; Dai, X.; Zhu, J.; Yu, H. Classification of Chinese Rice Wine According to Geographic Origin and Wine Age Based on Chemometric Methods and SBSE-TD-GC-MS Analysis of Volatile Compounds. Food Sci. Technol. Res. 2015, 21, 371–380. [Google Scholar] [CrossRef] [Green Version]
- Ren, Q.; Sun, L.; Sun, Z.; Liu, Q.; Lu, X.; Li, Z.; Xu, J. Bacterial succession and the dynamics of flavor compounds in the Huangjiu fermented from corn. Arch. Microbiol. 2019, 202, 299–308. [Google Scholar] [CrossRef] [PubMed]
- Chen, G.-M.; Li, W.-L.; Tong, S.-G.; Qiu, Y.-T.; Han, J.-Z.; Lv, X.-C.; Ai, L.-Z.; Sun, J.-Y.; Sun, B.-G.; Ni, L. Effects of the microbial community on the formation of volatile compounds and biogenic amines during the traditional brewing of Hongqu rice wine. Curr. Res. Food Sci. 2022, 5, 1433–1444. [Google Scholar] [CrossRef] [PubMed]
- Yang, Y.; Xia, Y.; Wang, G.; Zhang, H.; Xiong, Z.; Yu, J.; Yu, H.; Ai, L. Comparison of oenological property, volatile profile, and sensory characteristic of Chinese rice wine fermented by different starters during brewing. Int. J. Food Prop. 2017, 20, S3195–S3211. [Google Scholar] [CrossRef] [Green Version]
- Gong, M.; Zhou, Z.; Jin, J.; Yu, Y.; Liu, S.; Han, X.; Zhong, F.; Mao, J. Effects of soaking on physicochemical properties of four kinds of rice used in Huangjiu brewing. J. Cereal Sci. 2020, 91, 102855. [Google Scholar] [CrossRef]
- Ji, Z.W.; Huang, G.D.; Mao, J.; JW, F. Effect of socking time of rice on the quality of Chinese rice wine. Food Mach. 2013, 29, 49–52. [Google Scholar]
- Chen, T.; Wu, F.; Guo, J.; Ye, M.; Hu, H.; Guo, J.; Liu, X. Effects of glutinous rice protein components on the volatile substances and sensory properties of Chinese rice wine. J. Sci. Food Agric. 2020, 100, 3297–3307. [Google Scholar] [CrossRef]
- Cai, Q.Y.; Zhou, J.; Miao, L.H.; Chen, X. Reasearch progress of specific rice for Huangjiu production. China Brew. 2018, 37, 1–5. [Google Scholar]
- Yang, Y.; Hu, W.; Xia, Y.; Mu, Z.; Tao, L.; Song, X.; Zhang, H.; Ni, B.; Ai, L. Flavor Formation in Chinese Rice Wine (Huangjiu): Impacts of the Flavor-Active Microorganisms, Raw Materials, and Fermentation Technology. Front. Microbiol. 2020, 11, 580247. [Google Scholar] [CrossRef]
- Wang, J.; Zhang, B.; Wu, Q.; Jiang, X.Y.; Liu, H.J.; Wang, C.Z.; Huang, M.Q.; Wu, J.H.; Zhang, J.L.; Yu, Y.G. Sensomics-assisted flavor decoding of coarse cereal Huangjiu. Food Chem. 2022, 381, 132296. [Google Scholar] [CrossRef] [PubMed]
- Chen, C.; Liu, Y.; Tian, H.; Ai, L.; Yu, H. Metagenomic analysis reveals the impact of JIUYAO microbial diversity on fermentation and the volatile profile of Shaoxing-jiu. Food Microbiol. 2019, 86, 103326. [Google Scholar] [CrossRef] [PubMed]
- Xu, J.; Wu, H.; Wang, Z.; Zheng, F.; Lu, X.; Li, Z.; Ren, Q. Microbial dynamics and metabolite changes in Chinese Rice Wine fermentation from sorghum with different tannin content. Sci. Rep. 2018, 8, 4639. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1.
The traditional production process of Huangjiu.
Figure 2.
Pareto chart for the total area of all volatile carbonyl compounds of the GC–MS analysis of the HS-SPME of Huangjiu.
Figure 2.
Pareto chart for the total area of all volatile carbonyl compounds of the GC–MS analysis of the HS-SPME of Huangjiu.
Figure 3.
Response surface model for the total area of all volatile compounds vs. (a) extraction time (tex) and PFBHA content (incubation time = 9 min, temperature = 50 °C), (b) extraction temperature (Tex) and PFBHA content (incubation time = 9 min, extraction time = 40 min), and (c) extraction temperature (Tex) and extraction time (tex) (incubation time = 9 min, PFBHA = 1.5 g/L).
Figure 3.
Response surface model for the total area of all volatile compounds vs. (a) extraction time (tex) and PFBHA content (incubation time = 9 min, temperature = 50 °C), (b) extraction temperature (Tex) and PFBHA content (incubation time = 9 min, extraction time = 40 min), and (c) extraction temperature (Tex) and extraction time (tex) (incubation time = 9 min, PFBHA = 1.5 g/L).
Figure 4.
OPLS-DA of semidry Huangjiu and semisweet Huangjiu.
Figure 5.
OPLS-DA of rice Huangjiu and nonrice Huangjiu.
Figure 6.
OPLS-DA of different regions of rice Huangjiu, (a) semidry Huangjiu, and (b) semisweet Huangjiu.
Figure 6.
OPLS-DA of different regions of rice Huangjiu, (a) semidry Huangjiu, and (b) semisweet Huangjiu.
Table 1.
Factor levels and experimental domain applied to optimize the HS-SPME experimental conditions.
Table 1.
Factor levels and experimental domain applied to optimize the HS-SPME experimental conditions.
| Factor | Experimental Domain | ||||
|---|---|---|---|---|---|
| −α a | −1 | 0 | +1 | +α a | |
| PFBHA (g/L) | 0.5 | 1 | 1.5 | 2 | 2.5 |
| Extraction temperature (Tex-°C) | 30 | 40 | 50 | 60 | 70 |
| Extraction time (tex-min) | 20 | 30 | 40 | 50 | 60 |
| Incubation time (tinc-min) | 3 | 6 | 9 | 12 | 15 |
a α = 2.000.
Table 2.
Compounds identified in Huangjiu: retention time (RT), retention index (RI), m/z quantitative ion, identification method (ID).
Table 2.
Compounds identified in Huangjiu: retention time (RT), retention index (RI), m/z quantitative ion, identification method (ID).
| RT (min) | RIcalc a | RIlit b | Compounds | Ions (m/z) | ID |
|---|---|---|---|---|---|
| Alkanals | |||||
| 15.53/15.69 | 1447/1453 | 1451/1457 | Ethanal | 181/209/239 | STD/MS |
| 16.87/17.10 | 1495/1504 | 1502/1509 | Propanal | 181/236/253 | STD/MS |
| 18.70/18.75 | 1558/1560 | 1572/1585 | Butanal | 181/239 | STD/MS |
| 21.01/21.28 | 1655/1666 | 1664/1675 | Pentanal | 181/239 | STD/MS |
| 22.90/23.08 | 1745/1754 | 1755/1765 | Hexanal | 181/239 | STD/MS |
| 24.89/25.06 | 1827/1833 | 1852/1861 | Heptanal | 181/239 | STD/MS |
| 26.89/27.03 | 1928/1935 | 1943/1950 | Octanal | 181/239 | STD/MS |
| 28.85/28.95 | 2027/2038 | 2041/2047 | Nonanal | 181/239 | STD/MS |
| 30.72/30.80 | 2127/2131 | 2138/2143 | Decanal | 181/239 | STD/MS |
| 32.55/32.62 | 2227/2231 | 2239/2243 | Undecanal | 181/239 | STD/MS |
| 34.30/34.35 | 2327/2329 | 2337/2340 | Dodecanal | 181/239 | STD/MS |
| 35.99 | 2426 | 2443 | Tridecanal | 181/239 | STD/MS |
| Alkenals | |||||
| 18.37/19.20 | 1544/1578 | 1566/1594 | 2-Propenal | 181/251 | STD/MS |
| 22.19/23.20 | 1713/1759 | 1728/1763 | (E)-2-Butenal | 181/250 | STD/MS |
| 24.14/24.49 | 1801/1813 | 1808/1825 | (E)-2-Pentenal | 181/250 | STD/MS |
| 26.04/26.27 | 1886/1897 | 1898/1910 | (E)-2-Hexenal | 181/250 | STD/MS |
| 28.14/28.26 | 1987/1995 | 2009/2016 | (E)-2-Heptenal | 181/250 | STD/MS |
| 30.09 | 2093 | 2109 | (E)-2-Octenal | 181/250 | STD/MS |
| 31.92 | 2192 | - | (E)-2-Nonenal | 181/250 | STD/MS |
| 33.65/33.74 | 2290/2294 | 2307/2309 | (E)-2-Decenal | 181/250 | STD/MS |
| Strecker aldehydes | |||||
| 16.82/16.89 | 1493/1496 | – | 2-Methylpropanal | 181/250 | STD/MS |
| 18.77/18.92 | 1561/1567 | – | 2-Methylbutanal | 181/239 | STD/MS |
| 19.60/20.00 | 1594/1611 | 1599/1618 | 3-Methylbutanal | 181/239 | STD/MS |
| 24.85/25.69 | 1928/1969 | – | 3-Methyl-2-butenal | 181/264 | STD/MS |
| 30.77/30.83 | 2129/2133 | 2147/2150 | Methional | 181/299 | STD/MS |
| 33.20/33.26 | 2264/2267 | – | Benzaldehyde | 181/301 | STD/MS |
| 33.90/33.99 | 2303/2309 | 2326/2329 | Phenyl acetaldehyde | 181/91 | STD/MS |
| Dicarbonyl | |||||
| 32.97/34.26/35.67 | 2251/2324/2407 | – | Diacetyl | 181/279 | STD/MS |
| 35.74/36.17/36.32 | 2411/2437/2447 | – | Methyl glyoxal | 181/265 | STD/MS |
| 36.69/36.88 | 2469/2480 | – | Glyoxal | 181/251 | STD/MS |
| Ketones | |||||
| 15.98 | 1463 | 1466 | Acetone | 181/253 | MS |
| 17.20/17.26 | 1508/1511 | 1521/1521 | 2-Butanone | 181/253 | MS |
| 17.55/18.04 | 1511/1531 | – | 3-Methyl-2-butanone | 181/253 | STD/MS |
| 17.54/18.90 | 1511/1566 | – | 2-Pentanone | 181/253 | STD/MS |
| 18.1192 | 1534 | – | 3-Pentanone | 181/253 | STD/MS |
| 20.90/21.11 | 1650/1659 | – | 2-Hexanone | 181/253 | STD/MS |
| 20.94 | 1651 | – | 4-Heptanone | 181/253 | STD/MS |
| 22.46/22.73 | 1725/1738 | – | 2-Heptanone | 181/253 | STD/MS |
| 24.33/24.67 | 1803/1819 | 1818/1833 | 2-Octanone | 181/253 | STD/MS |
| 26.25/26.60 | 1895/1913 | 1925/1943 | 2-Nonanone | 181/253 | STD/MS |
| 28.14/28.52 | 1986/2010 | – | 2-Decanone | 181/253 | STD/MS |
| Furans | |||||
| 29.22/30.52 | 2047/2116 | 2056/2126 | 2-Furfural | 181/291 | STD/MS |
| 30.64/31.65 | 2122/2177 | – | 5-Methyl-2-furfural | 181/305 | STD/MS |
| 46.81/48.18 | 3158/3266 | – | 5-(Hydroxymethyl)furfural | 181/321 | STD/MS |
| Others | |||||
| 23.12 | 1755 | – | 3-Penten-2-one | 181/264 | STD/MS |
| 24.55/25.39 | 1813/1854 | 1838/1880 | 1-Octen-3- one | 181/140 | STD/MS |
| 24.83 | 1825 | – | Cyclopentanone | 181/279 | STD/MS |
| 25.86 | 1862 | – | Cyclohexanone | 181/293 | STD/MS |
| 25.26/25.67 | 1841/1855 | 1864/1883 | 6-Methyl-5-hepten-2-one | 181/253 | STD/MS |
| 28.36 | 1803 | – | 2-Cyclohexen-1-one | 181/291 | STD/MS |
| 29.49/30.50 | 2061/2115 | 2092/2146 | Acetoin | 181/240 | STD/MS |
| 33.50/31.32 | 2159/2281 | 2171/2295 | Acetophenone | 181/315 | STD/MS |
| 35.03 | 2369 | – | 2-Phenyl-2-butenal | 181/341 | STD/MS |
| Internal standard | |||||
| 33.33/33.39 | 2271/2274 | – | p-Fluorobenzaldehyde | 181/319 | STD/MS |
a RIcalc: retention indices calculated from C7 to C30 n-linear alkanes with VF-WAXms capillary column; b RIlit: retention indices reported in the literature for VF-WAXms capillary column or equivalent.–: retention indices reported in no-literature.
Table 3.
Linear range, determination coefficient, limit of detection (LOD), and limit of quantitation (LOQ) of the proposed method.
Table 3.
Linear range, determination coefficient, limit of detection (LOD), and limit of quantitation (LOQ) of the proposed method.
| Compounds | Linear Range (μg/L) | Determination Coefficient (r2) | LOD (μg/L) | LOQ (μg/L) |
|---|---|---|---|---|
| Propanal | 0.785–785 | 0.9995 | 0.017 | 0.055 |
| Butanal | 0.074–74.2 | 0.9993 | 0.004 | 0.011 |
| Pentanal | 0.084–83.9 | 0.9999 | 0.016 | 0.059 |
| Hexanal | 0.081–81.1 | 0.9999 | 0.026 | 0.079 |
| Heptanal | 0.079–79.2 | 0.9999 | 0.011 | 0.038 |
| Octanal | 0.083–83.1 | 0.9999 | 0.006 | 0.023 |
| Nonanal | 0.242–121 | 0.9993 | 0.010 | 0.033 |
| Decanal | 0.026–26.4 | 0.9976 | 0.007 | 0.025 |
| Undecanal | 0.046–23.1 | 0.9997 | 0.004 | 0.015 |
| Dodecanal | 0.034–33.7 | 0.9980 | 0.007 | 0.026 |
| Tridecanal | 0.078–77.5 | 0.9994 | 0.006 | 0.021 |
| 2-Propenal | 0.112–122 | 0.9999 | 0.029 | 0.098 |
| (E)-2-Butenal | 0.837–4185 | 0.9963 | 0.017 | 0.058 |
| (E)-2-Pentenal | 0.421–84.1 | 0.9997 | 0.021 | 0.065 |
| (E)-2-Hexenal | 0.082–81.8 | 0.9996 | 0.019 | 0.065 |
| (E)-2-Heptenal | 0.083–83.3 | 0.9998 | 0.024 | 0.075 |
| (E)-2-Octenal | 0.412–41.2 | 0.9992 | 0.061 | 0.194 |
| (E)-2-Nonenal | 0.419–41.9 | 0.9974 | 0.072 | 0.219 |
| (E)-2-Decenal | 0.176–44.0 | 0.9989 | 0.008 | 0.022 |
| 2-Methylpropanal | 1.170–5825 | 0.9999 | 0.016 | 0.052 |
| 2-Methylbutanal | 0.754–3770 | 0.9999 | 0.008 | 0.025 |
| 3-Methylbutanal | 1.380–13,800 | 0.9999 | 0.043 | 0.135 |
| 3-Methyl-2-butenal | 0.856–85.6 | 0.9997 | 0.008 | 0.035 |
| Methional | 0.500–500 | 0.9999 | 0.068 | 0.206 |
| Benzaldehyde | 2.350–11,750 | 0.9990 | 0.082 | 0.248 |
| Phenyl acetaldehyde | 0.923–46.2 | 0.9994 | 0.012 | 0.038 |
| Diacetyl | 1.042–1042 | 0.9994 | 0.085 | 0.265 |
| Methyl glyoxal | 0.450–2248 | 0.9994 | 0.022 | 0.068 |
| Glyoxal | 0.511–2556 | 0.9993 | 0.044 | 0.134 |
| 3-Methyl-2-butanone | 0.567–56.7 | 0.9990 | 0.012 | 0.038 |
| 2-Pentanone | 0.078–78.4 | 0.9996 | 0.012 | 0.029 |
| 3-Pentanone | 0.312–156 | 0.9995 | 0.017 | 0.05 |
| 2-Hexanone | 0.369–73.8 | 0.9999 | 0.002 | 0.007 |
| 4-Heptanone | 0.059–59.0 | 0.9992 | 0.012 | 0.029 |
| 2-Heptanone | 0.377–75.5 | 0.9999 | 0.062 | 0.187 |
| 2-Octanone | 0.405–81.10 | 0.9999 | 0.022 | 0.066 |
| 2-Nonanone | 0.170–85.0 | 0.9977 | 0.019 | 0.059 |
| 2-Decanone | 0.152–76.0 | 0.9983 | 0.012 | 0.035 |
| 2-Furfural | 4.647–46,470 | 0.9992 | 0.066 | 0.201 |
| 5-Methyl-2-furfural | 0.113–5635 | 0.9993 | 0.012 | 0.046 |
| 3-Penten -2-one | 1.608–8040 | 0.9998 | 0.080 | 0.243 |
| 1-Octen-3- one | 0.042–84.0 | 0.9999 | 0.003 | 0.014 |
| 6-Methyl-5-hepten-2-one | 0.069–69.0 | 0.9998 | 0.002 | 0.007 |
| Cyclopentanone | 0.084–4185 | 0.9962 | 0.004 | 0.017 |
| Cyclohexanone | 0.091–91.4 | 0.9990 | 0.009 | 0.029 |
| 2-Cyclohexen-1-one | 0.448–89.6 | 0.9987 | 0.047 | 0.143 |
| Acetoin | 41.760–208,800 | 0.9988 | 0.053 | 0.162 |
| Acetophenone | 0.103–103 | 0.9992 | 0.011 | 0.027 |
| 2-Phenyl-2-butenal | 0.750–3750 | 0.9998 | 0.105 | 0.317 |
Table 4.
List of volatile carbonyl compounds significantly altered in semidry Huangjiu compared to semisweet Huangjiu (only signals p < 0.05 and VIP > 1 are presented).
Table 4.
List of volatile carbonyl compounds significantly altered in semidry Huangjiu compared to semisweet Huangjiu (only signals p < 0.05 and VIP > 1 are presented).
| Compound | VIP a | p-Value b | Semidry vs. Semisweet c |
|---|---|---|---|
| 2-Octanone | 1.8062 | <0.0001 (****) | ⬆ |
| (E)-2-Pentenal | 1.7468 | <0.0001 (****) | ⬆ |
| 2-Hexanone | 1.6892 | <0.0001 (****) | ⬆ |
| 2-Propenal | 1.6827 | <0.0001 (****) | ⬇ |
| 2-Heptanone | 1.5018 | <0.0001 (****) | ⬆ |
| 3-Pentanone | 1.4325 | 0.0003 (***) | ⬆ |
| 2-Phenyl-2-butenal | 1.3881 | 0.0005 (***) | ⬆ |
| (E)-2-Nonenal | 1.3733 | 0.0008 (***) | ⬆ |
| (E)-2-Heptenal | 1.3592 | <0.0001 (****) | ⬆ |
| Benzaldehyde | 1.2966 | 0.0013 (**) | ⬆ |
| 2-Furfural | 1.2883 | 0.0005 (***) | ⬆ |
| 3-Methyl-2-butanone | 1.2679 | 0.0003 (***) | ⬆ |
| 2-Methylbutanal | 1.2543 | 0.0011 (**) | ⬆ |
| 2-Cyclohexen-1-one | 1.2394 | 0.0004 (***) | ⬆ |
| 3-Methylbutanal | 1.1973 | 0.0033 (**) | ⬆ |
| Dodecanal | 1.1845 | 0.0037 (**) | ⬆ |
| 4-Heptanone | 1.1236 | 0.0061 (**) | ⬆ |
| Decanal | 1.1213 | 0.0062 (**) | ⬇ |
| Glyoxal | 1.0612 | 0.0100 (**) | ⬇ |
a VIP: variable importance in the projection; b p-value: significances between date; ** p < 0.01, *** p < 0.001, **** p < 0.0001; c “⬆/⬇” means increase/decrease of the compounds.
Table 5.
List of volatile carbonyl compounds significantly altered in rice Huangjiu compared to nonrice Huangjiu (only signals p < 0.05 and VIP > 1 are presented).
Table 5.
List of volatile carbonyl compounds significantly altered in rice Huangjiu compared to nonrice Huangjiu (only signals p < 0.05 and VIP > 1 are presented).
| Compound | VIP a | p-Value b | Rice vs. Nonrice c |
|---|---|---|---|
| (E)-2-Hexenal | 1.8955 | 0.0002 (***) | ⬇ |
| 3-Methylbutanal | 1.7378 | <0.0001 (****) | ⬆ |
| Benzaldehyde | 1.6881 | <0.0001 (****) | ⬆ |
| 2-Nonanone | 1.6221 | <0.0001 (****) | ⬆ |
| Cyclopentanone | 1.5839 | 0.0041 (**) | ⬇ |
| 2-Decanone | 1.5299 | 0.0066 (**) | ⬆ |
| 2-Methylpropanal | 1.5233 | <0.0001 (****) | ⬆ |
| (E)-2-Heptenal | 1.5024 | 0.0077 (**) | ⬇ |
| 2-Methylbutanal | 1.4562 | 0.0001 (***) | ⬆ |
| 3-Methyl-2-butanone | 1.3595 | 0.0004 (***) | ⬆ |
| (E)-2-Butenal | 1.2837 | 0.0008 (***) | ⬆ |
| 2-Butanone | 1.2357 | 0.0013 (**) | ⬆ |
| Butanal | 1.2134 | 0.0056 (**) | ⬆ |
| Methyl glyoxal | 1.1814 | 0.0072 (**) | ⬇ |
| 2-Hexanone | 1.0771 | 0.0157 (*) | ⬆ |
| 2-Phenyl-2-butenal | 1.0529 | 0.0083 (**) | ⬆ |
| 2-Propenal | 1.0508 | 0.0187 (*) | ⬇ |
| 2-Heptanone | 1.0428 | 0.0198 (*) | ⬆ |
| (E)-2-Octenal | 1.0178 | 0.0232 (*) | ⬇ |
| Diacetyl | 1.0071 | 0.0249 (*) | ⬇ |
a VIP: variable importance in the projection; b p-value: significances between date; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001; c “⬆/⬇” means increase/decrease of the compounds.
Table 6.
OPLS-DA results showing the critical volatile carbonyl compounds (variable importance in projection VIP > 1.0, p < 0.05) present across semidry Huangjiu samples of different regions (Zhejiang, Jiangsu, Shanghai, Fujian).
Table 6.
OPLS-DA results showing the critical volatile carbonyl compounds (variable importance in projection VIP > 1.0, p < 0.05) present across semidry Huangjiu samples of different regions (Zhejiang, Jiangsu, Shanghai, Fujian).
| Compound | VIP a | p-Value b |
|---|---|---|
| 2-Phenyl-2-butenal | 1.7335 | <0.0001 (****) |
| Cyclopentanone | 1.5191 | <0.0001 (****) |
| Glyoxal | 1.3979 | 0.0003 (***) |
| 2-Decanone | 1.3123 | <0.0001 (****) |
| Benzaldehyde | 1.3065 | 0.0006 (***) |
| 2-Cyclohexene-1-one | 1.2443 | <0.0001 (****) |
| (E)-2-Butenal | 1.2438 | <0.0001 (****) |
| Dodecanal | 1.2284 | 0.0023 (**) |
| Heptanal | 1.2206 | <0.0001 (****) |
| Decanal | 1.2165 | 0.0048 (**) |
| Pentanal | 1.1786 | <0.0001 (****) |
| Methional | 1.1758 | 0.0023 (**) |
| Undecanal | 1.1545 | 0.0048 (**) |
| 2-Pentanone | 1.1265 | 0.046 (*) |
| 6-Methyl-5-hepten-2-one | 1.1235 | 0.0094 (**) |
| 3-Methyl-2-butenal | 1.121 | 0.0069 (**) |
| Methyl glyoxal | 1.1079 | <0.0001 (****) |
| 3-Methyl-2-butanone | 1.0926 | 0.001 (***) |
| Phenyl acetaldehyde | 1.0685 | <0.0001 (****) |
| 2-Heptanone | 1.0438 | 0.0023 (**) |
| Propanal | 1.0069 | 0.0004 (***) |
| Hexanal | 1.0064 | 0.0033 (**) |
a VIP: variable importance in the projection; b p-value: significances between date; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Table 7.
OPLS-DA results showing the critical volatile carbonyl compounds (variable importance in projection VIP > 1.0, p < 0.05) present across semisweet Huangjiu samples of different regions (Zhejiang, Jiangsu, Shanghai, Fujian).
Table 7.
OPLS-DA results showing the critical volatile carbonyl compounds (variable importance in projection VIP > 1.0, p < 0.05) present across semisweet Huangjiu samples of different regions (Zhejiang, Jiangsu, Shanghai, Fujian).
| Compound | VIP a | p-Value b |
|---|---|---|
| Phenyl acetaldehyde | 1.5676 | 0.0002 (***) |
| 2-Pentanone | 1.5134 | 0.0009 (***) |
| 2-Methylbutanal | 1.4287 | 0.0064 (**) |
| 2-Octanone | 1.3833 | 0.0445 (*) |
| 2-Methylpropanal | 1.3766 | 0.0102 (*) |
| 4-Heptanone | 1.2948 | 0.0178 (*) |
| 3-Methyl-2-butenal | 1.2901 | 0.0375 (*) |
| 3-Methylbutanal | 1.2514 | 0.0375 (*) |
a VIP: variable importance in the projection; b p-value: significances between date; * p < 0.05, ** p < 0.01, *** p < 0.001.
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MDPI and ACS Style
Yu, J.; Zhou, Z.; Xu, X.; Ren, H.; Gong, M.; Ji, Z.; Liu, S.; Hu, Z.; Mao, J. Differentiating Huangjiu with Varying Sugar Contents from Different Regions Based on Targeted Metabolomics Analyses of Volatile Carbonyl Compounds. Foods 2023, 12, 1455. https://doi.org/10.3390/foods12071455
AMA Style
Yu J, Zhou Z, Xu X, Ren H, Gong M, Ji Z, Liu S, Hu Z, Mao J. Differentiating Huangjiu with Varying Sugar Contents from Different Regions Based on Targeted Metabolomics Analyses of Volatile Carbonyl Compounds. Foods. 2023; 12(7):1455. https://doi.org/10.3390/foods12071455
Chicago/Turabian StyleYu, Junting, Zhilei Zhou, Xibiao Xu, Huan Ren, Min Gong, Zhongwei Ji, Shuangping Liu, Zhiming Hu, and Jian Mao. 2023. "Differentiating Huangjiu with Varying Sugar Contents from Different Regions Based on Targeted Metabolomics Analyses of Volatile Carbonyl Compounds" Foods 12, no. 7: 1455. https://doi.org/10.3390/foods12071455
APA StyleYu, J., Zhou, Z., Xu, X., Ren, H., Gong, M., Ji, Z., Liu, S., Hu, Z., & Mao, J. (2023). Differentiating Huangjiu with Varying Sugar Contents from Different Regions Based on Targeted Metabolomics Analyses of Volatile Carbonyl Compounds. Foods, 12(7), 1455. https://doi.org/10.3390/foods12071455
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