Xiao Chenab,
Nghia Huynhb,
Heping Cuia,
Peng Zhoua,
Xiaoming Zhang*a and
Baoru Yang*b
aState Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Lihu Road 1800, Wuxi, Jiangsu 214122, China. E-mail: xmzhang@jiangnan.edu.cn; Tel: +86-510-85919106
bFood Chemistry and Food Development, Department of Biochemistry, University of Turku, FIN-20014 Turku, Finland. E-mail: baoru.yang@utu.fi; Tel: +358 2 3336844
First published on 31st January 2018
Supercritical fluid was applied to extract volatile compounds from Finnish wild mushrooms (Craterellus tubaeformis). The effects of extraction pressure, temperature and supercritical carbon dioxide volume on extraction yield and the content of mushroom alcohols in the extracts were investigated in the range from 80 to 95 bar, 35 to 55 °C and 30 to 70 mL, respectively. The correlation between extracted volatile compounds and supercritical fluid extraction parameters was studied and prediction models of ten extracted aroma compounds were established by partial least squares regression (PLSR). The calibrated and validated models of 2-octen-1-ol (R_cal = 0.96, R_cal2 = 0.91, R_val = 0.94, R_val2 = 0.88) and geranyl acetone (R_cal = 0.96, R_cal2 = 0.92, R_val = 0.95, R_val2 = 0.90) were satisfactory, and had the predictive capability of 88% and 92%, respectively. Moreover, the predictive equations for other extracted aroma compounds were also proved to be sufficiently accurate. Hence, the present study provides useful reference for extraction of volatile compounds from mushrooms using supercritical fluid for further industrial applications.
For many decades mushrooms have been widely utilized as popular ingredients in various cuisines around the world because of their unique aroma and taste;7 volatile compounds are the major contributor to the characteristic mushroom flavour.8 Hundreds of volatile compounds have been identified in edible mushrooms. The most important volatiles are mushroom alcohols, including 1-octen-3-ol, 2-octen-1-ol, 3-octanol, and 1-octanol, which have been identified as the main compounds responsible for the unique aroma and flavour.9 In particular, 1-octen-3-ol (unsaturated alcohol) has been found in almost all mushroom species. It is formed during the enzymatic breakdown of linoleic acid,10,11 and has been considered as the main component responsible for the characteristic flavour of most edible mushrooms.12–15 The mushroom aroma is much wanted in some applications, for example, as food ingredients to add typical mushroom flavour to different dishes. However, they can also be an obstacle in some others by introducing strong profile of mushroom aroma in food and personal care products developed from bioactive compounds in mushrooms such as polysaccharides,2,7 phenolic compounds,2,7,16 sterols and triterpenoids.2,7 For example, mushroom aroma in food without mushrooms is important for the customers, who do not accept the structure and taste of mushrooms, while for cosmetic products,16 bioactive ingredients or extracts from mushrooms shall be free of the aroma/smell of mushrooms. In both view, it is worthwhile to separate aroma compounds from mushrooms, yielding volatile compounds which could be used as food ingredients, and aroma-free residue, which can be further extracted to obtain bioactive compounds (sterols and polysaccharide) without mushroom smell.
On the other hand, hydrodistillation (HD) and organic solvent extraction, such as simultaneous distillation extraction (SDE) using a Likens–Nickerson instrument,17 are traditional processes used for the extraction of essential oils from aroma-active and medicinal plants.9,15,18 Nevertheless, these extraction methods are time consuming, and some compounds are susceptible to chemical changes under high temperatures.19 Additionally, some volatile compounds could also be lost during the solvent removal.20 Supercritical fluid extraction (SFE) is a suitable method to extract valuable components from natural raw materials. SFE offers features that overcome many limitations of conventional extraction methods, thus, being a suitable alternative to conventional processes such as HD, SDE, and organic solvent extraction.21 Furthermore, high extraction yield and extract quality could be achieved using optimized supercritical fluid extraction parameters.22,23 Supercritical carbon dioxide (SC-CO2) is the most preferred and commonly used supercritical fluid because it is non-toxic, chemically stable, environmental friendly, and easy to be removed from the extract yielding a solvent-free extract.21,23 It also has the potential for selective and efficient extraction by controlling the pressure and temperature, which regulate the density and solvating power of CO2.24–27 Thus, volatiles can be selectively extracted from mushrooms, and other compounds, such as protein, polysaccharides and sterols can be well protected in the residue and have the possibility for further application. Many researchers have reported the extraction of mushroom aroma compounds based on HD or SDE.9,13–15,20,28,29 Previous works related to supercritical fluid extraction of mushrooms focused on biologically active compounds including fatty acids and sterols as targets of extraction;30–32 the characteristic of extracts and the effect of extraction parameters on the total extraction yield was further studied. However, there are very limited publication on the SFE of volatile compounds from mushrooms and the impact of SFE parameters on the yield and composition of extracted volatile compounds.
Partial least-squares regression (PLSR) has been effectively used to explain the correlation of variables by obtaining information from raw data and focusing on a comprehensive evaluation of the obtained information.33,34 PLSR analysis method facilitates to create models for accurate prediction of the chemical characteristics of unknown food samples.35 The aroma compounds or/and bioactive components can be selectively extracted by supercritical fluid extraction for further characterization. Combining extraction parameters with GC-FID results in PLSR analysis, prediction models can be built up based on the correlation between SFE parameters and the yield of volatile compounds in the extracts. Such models could be an effective tool for ensuring efficient selective extraction of typical volatile compounds from Craterellus tubaeformis and other mushrooms.
This study determined the optimal range of parameters for extracting volatiles from dried Finnish wild mushrooms (Craterellus tubaeformis) and studied the composition of the extracts and the content of each extracted volatile compound under different extraction parameters. The effect of extraction parameters on extraction yield and the content of mushroom alcohols were also evaluated to assess the supercritical fluid's potential for selective and efficient extractions of major aroma components. Additionally, the correlation between chemical profiles and supercritical fluid extraction parameters were analysed with PLSR to design models for the prediction of volatile contents in mushroom extracts under different SFE operating parameters. The proposed prediction models will be helpful to optimize the processing conditions of SFE for extracting aroma compounds from Finnish wild mushrooms as well as other wild mushrooms. This study provides guidance and theoretical reference for commercial-scale supercritical fluid extraction to collect target volatile compounds from mushrooms as ingredients for food flavouring and fragrance, meanwhile yielding aroma-free residues for special purpose.
No. | Factors | ||
---|---|---|---|
Temperature/°C | Pressure/bar | SC-CO2 volume/mL | |
1 | 40 | 85 | 30 |
2 | 40 | 90 | 50 |
3 | 40 | 95 | 70 |
4 | 45 | 90 | 70 |
5 | 45 | 95 | 30 |
6 | 45 | 85 | 50 |
7 | 50 | 95 | 50 |
8 | 50 | 85 | 70 |
9 | 50 | 90 | 30 |
(1) |
A series of n-alkanes (C8–C40) was analysed under the same conditions to obtain the linear retention index (RI). The RI was calculated according to the following equation:
(2) |
The quantities of volatiles were calculated by comparison of their peak areas with that of the internal standard. The peaks of the volatile compounds were identified by both mass spectrum and retention index; also, some authentic compounds were used for the volatiles identification.
This research is part of a larger project aimed for comprehensive utilization of the wild mushroom (Craterellus tubaeformis) resource by multi-stage extraction and separation. Extracting volatile compounds and further correlating SFE parameters with the yield of volatiles is the first step of the whole project and the focus of the current manuscript. The aim is to selectively extract volatile compounds as flavour-enhancing food ingredients, whereas the aroma-free residues can be further extracted by SFE or other extraction methods to obtain fatty acids, polysaccharides and protein for the study of functional properties or the development of novel products. The latter part was not the focus of the present work. Sample pre-tests were performed to determine the optimal range of extraction parameters for increasing the yield of volatile compounds from mushrooms, meantime avoiding co-extraction of fatty components. During the pre-tests, maintaining the SC-CO2 density between 0.205 and 0.657 g mL−1 (pressure from 80 to 95 bar, temperature from 35 to 55 °C) was sufficient for the extraction of desirable volatile compounds, such as 1-octen-3-ol, limonene, 2-octen-1-ol and nonanal, from mushrooms without fatty acids. Thus, single factor experiments were done based on parameters within these ranges. Similar findings were reported by Bocevska et al.37 who found that the moderate extraction conditions (SC-CO2 density of 0.290 g mL−1 under the pressure of 100 bar and the temperature of 60 °C) were the most selective for limonene extraction from yarrow flowers with respect to unwanted waxes.
The influence of pressure was studied from 80 bar to 95 bar, with the temperature set at 40 °C and the SC-CO2 volume at 50 mL. Results showed that the total extraction yield was enhanced as the extraction pressure increased from 85 to 95 bar with the highest yield of extract reaching 0.76% (Fig. 2a). This was because the elevation of pressure at fixed temperature resulted in an increase of the density of SC-CO2 from 0.278 to 0.557 g mL−1, which led to the enhancement of the solvent power of SC-CO2. Additionally, the increased density of SC-CO2 might also have accelerated the mass transfer between the analytes and solvent during extraction process, therefore, improving the total extraction yield.22,23 These findings were in accordance with previously reported studies on the SFE of substances from mint leaves (Mentha spicata),38 Bulgarian Achillea millefolium,39 quinoa (Chenopodium quinoa willd) seeds,40 Zingiber officinale var. Amarum,41 coriander (Coriandrum sativum L., Apiaceae) seeds,26 and common carp (Cyprinus carpio L.).42 As shown in Fig. 2b, the content of mushroom alcohols decreased from 15% to 3% with the increase of pressure. This might be due to the higher solvating power of SC-CO2, which decreased the extraction selectivity and increased the co-extraction of non-volatile compounds.22 Thus, the presence of co-extracted solutes under higher pressure reduced the extraction efficiency of the mushroom-alcohol compounds. Similar observations were reported by Hamburger et al.,43 that at higher pressure some non-volatile lipophilic compounds were co-extracted with target substances. Hence, taking these two figures (Fig. 2a and b) into account, 85 bar might be the best pressure for extracting mushroom alcohols because of its satisfied total extraction yield and relatively desirable extract.
Fig. 2 Influence of pressure on total extraction yield (a) and the content of mushroom alcohols (b) at 80–95 bar, 40 °C, 50 mL SC-CO2. |
Moreover, the effect of temperature has been also evaluated in the range between 35 to 55 °C while the pressure and SC-CO2 was kept at 85 bar and 50 mL, respectively. As shown in Fig. 3, the temperature influenced both the total extraction yield and the mushroom alcohols content. With the increase of temperature, the density of CO2 and the corresponding solvent strength decreased, which had a negative effect on the total extraction yield. On the other hand, the elevated temperature also increased vapor pressure of the volatile compounds, facilitating the extraction of these compounds. For extracting aroma compounds under different temperatures, there is a competition between the solubility of SC-CO2 (which decreases with increasing temperature) and the vapor pressure of extracted compounds (which rises with increasing temperature).22,42 As shown in Fig. 3a, the increasing temperature from 35 to 55 °C decreased the total extraction yield from 0.6% to 0.32%, which was mostly due to the weak solubility of SC-CO2 at lower density despite the enhanced solute sublimation at higher temperature. Similar findings were reported by Zeković et al.26 and Salea et al.41 using supercritical fluid to extract substances from coriander seeds and Zingiber officinale var. Amarum, respectively. Moreover, for the content of mushroom alcohol compounds, there was a sharp increase from 35 °C to 40 °C (Fig. 3b) and followed by a slight increase from 40 to 55 °C. The decreased solvent strength of SC-CO2 increased the extraction selectivity, avoiding undesired co-extraction of non-volatile compounds, such as fatty acids and other lipids. In addition, the volatile compounds were extracted more easily because of their enhanced vapor pressure, therefore, the content of mushroom alcohol compounds in the extracts increased. Thus, 40 °C was selected as the optimum temperature for extracting mushroom alcohols, providing acceptable total extraction yield and higher content of the target compounds.
Fig. 3 Influence of temperature on total extraction yield (a) and the content of mushroom alcohols (b) at 85 bar, 35–55 °C, 50 mL SC-CO2. |
The larger amount of fluid volume means longer extraction time and likely more sufficient contact between the supercritical fluid and the material samples. Fig. 4 shows the effect of SC-CO2 volume on total extraction yield and content of mushroom alcohols. From Fig. 4a it was observed that the total extraction yield increased from 0.43% to 0.60% with increasing SC-CO2 volume from 30 to 60 mL, and after 60 mL the yield increase tended to be gentle, which indicated that 60 mL was enough for volatiles extraction at 85 bar and 40 °C. Moreover, a decrease trend of mushroom alcohols content was seen from 30 to 60 mL SC-CO2 (Fig. 4b), and a relative low content was obtained at 60 mL SC-CO2; these results suggested that with prolonged extraction time, the co-extraction of unwanted compounds occurred, which reduced alcohols content (eight carbon alcohols). Similar findings were reported by Kitzberger et al.30 who found that the extraction time affected the extract composition when extracting oil from shiitake; moreover, low molecular weight compounds tended to be extracted in the beginning of extraction process, followed by more polar compounds. Finally, taking the extraction yield and the content of mushroom alcohols into account, 50 mL SC-CO2 was the optimal fluid volume.
Fig. 4 Influence of SC-CO2 volume on total extraction yield (a) and the content of mushroom alcohols (b) at 85 bar, 40 °C, 30–70 mL SC-CO2. |
RIa | KIb | IDc | Compound | Content in sampled (μg/100 g dried mushrooms) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ||||
a RI means the Kovats index which were determined by a series of hydrocarbons (C8–C40) on the column of DB-1 described in Section 2.4.b KI denotes the Kovats index reference from NIST standard reference database, by which the compositions were determined on a non-polar (HP/DB-5 or HP/DB-1) column run under similar GC-FID conditions.c The identification was indicated by the following symbols: (A) mass spectrum; (B) comparison between RI and KI; (C) authentic compounds.d All GC peak areas were quantified as the internal standard (p-xylene) and approximate concentrations (mean ± standard deviation, average of triple samples) for the individual volatile compounds were shown in the table. | ||||||||||||
738 | 757 | AB | 3-Hexanone | 29 ± 2 | 33 ± 8 | 27 ± 1 | 36 ± 8 | 29 ± 3 | 40 ± 3 | 43 ± 7 | 47 ± 4 | 40 ± 1 |
765 | 785 | AB | 1-Octene | 36 ± 5 | 54 ± 6 | 117 ± 8 | 97 ± 7 | 60 ± 8 | 56 ± 4 | 87 ± 2 | 68 ± 5 | 32 ± 2 |
791 | 819 | AB | 1,3-Octadiene | 230 ± 20 | 190 ± 10 | 190 ± 10 | 187 ± 6 | 180 ± 10 | 210 ± 20 | 203 ± 3 | 230 ± 10 | 190 ± 20 |
898 | 926 | ABC | Benzaldehyde | 24 ± 1 | 34 ± 2 | 42 ± 2 | 42 ± 4 | 38 ± 7 | 36 ± 6 | 45 ± 0 | 46 ± 4 | 34 ± 4 |
952 | 966 | AB | 6-Methyl-5-hepten-2-one | 42 ± 4 | 33 ± 3 | 36 ± 3 | 53 ± 7 | 50 ± 8 | 50 ± 10 | 56 ± 3 | 65 ± 5 | 53 ± 8 |
954 | 961 | ABC | 1-Octen-3-ol | 290 ± 10 | 318 ± 6 | 350 ± 10 | 350 ± 20 | 280 ± 10 | 318 ± 6 | 298 ± 8 | 360 ± 10 | 260 ± 10 |
975 | 980 | AB | 2-Pentylfuran | 74 ± 4 | 154 ± 3 | 236 ± 5 | 190 ± 20 | 120 ± 20 | 106 ± 2 | 140 ± 10 | 150 ± 10 | 64 ± 3 |
994 | 1020 | AB | Limonene | 29 ± 2 | 32 ± 2 | 35 ± 3 | 36 ± 2 | 28 ± 3 | 31 ± 0 | 30 ± 4 | 35 ± 5 | 27 ± 1 |
1027 | 1039 | ABC | 2-Octen-1-ol | 90 ± 10 | 180 ± 4 | 290 ± 10 | 180 ± 2 | 120 ± 20 | 120 ± 10 | 140 ± 20 | 130 ± 10 | 56 ± 4 |
1050 | 1082 | ABC | Nonanal | 43 ± 3 | 61 ± 3 | 80 ± 3 | 54 ± 2 | 45 ± 4 | 34 ± 5 | 41 ± 3 | 34 ± 4 | 20 ± 4 |
1062 | 1086 | ABC | Linalool | 110 ± 10 | 235 ± 4 | 290 ± 20 | 210 ± 20 | 140 ± 10 | 111 ± 7 | 140 ± 10 | 127 ± 4 | 60 ± 6 |
1071 | — | AB | N-(3-Methylbutyl)acetamide | 620 ± 90 | 1000 ± 20 | 1590 ± 40 | 1010 ± 20 | 750 ± 40 | 370 ± 20 | 480 ± 20 | 240 ± 50 | 154 ± 6 |
1095 | 1088 | AB | 6-Methyl-3,5-heptadien-2-one | 65 ± 2 | 161 ± 6 | 179 ± 6 | 170 ± 20 | 120 ± 10 | 122 ± 5 | 150 ± 20 | 170 ± 20 | 110 ± 20 |
1197 | 1193 | AB | 2,4-Nonadienal | 160 ± 30 | 240 ± 30 | 260 ± 10 | 250 ± 10 | 180 ± 20 | 180 ± 10 | 230 ± 30 | 200 ± 20 | 130 ± 10 |
1265 | 1273 | AB | Bornyl acetate | 44 ± 2 | 100 ± 10 | 128 ± 2 | 86 ± 5 | 72 ± 6 | 50 ± 6 | 73 ± 9 | 55 ± 6 | 33 ± 4 |
1284 | 1280 | AB | 2,4-Decadienal | 29 ± 3 | 106 ± 0 | 148 ± 3 | 88 ± 9 | 66 ± 7 | 33 ± 2 | 68 ± 8 | 41 ± 5 | 23 ± 4 |
1405 | 1428 | AB | Geranyl acetone | 53 ± 4 | 139 ± 3 | 174 ± 4 | 127 ± 8 | 109 ± 8 | 68 ± 7 | 116 ± 5 | 74 ± 5 | 54 ± 1 |
As shown in Table 2, 1-octen-3-ol and 2-octen-1-ol were the only two mushroom-alcohol compounds extracted from the samples. The highest yield of 1-octen-3-ol (360 μg/100 g) was found in experiment 8 (85 bar, 50 °C, 70 mL SC-CO2), while the highest amount of 2-octen-1-ol (290 μg/100 g) was obtained in experiment 3 (95 bar, 40 °C, 70 mL SC-CO2). A similar yield of 1-octen-3-ol as in experiment 8 was also obtained in experiment 3 (95 bar, 40 °C, 70 mL SC-CO2) and experiment 4 (90 bar, 45 °C, 70 mL SC-CO2). Moreover, the highest yields of linalool (290 μg/100 g), geranyl acetone (174 μg/100 g), and bornyl acetate (128 μg/100 g) were all obtained in experiment 3 (95 bar, 40 °C, 70 mL SC-CO2). N-(3-Methylbutyl)acetamide, which was synthesized by Maillard reaction during the drying process,45 also showed the highest yield (1590 μg/100 g) in experiment 3.
The structural characteristics of the compounds influence their solubility in supercritical CO2, resulting in different content for each compound under different extraction conditions.46 As reported by Zeković et al.26 about monoterpenes extraction from coriander seeds. Although limonene and terpinene possess the same chemical formula (C10H16), the different position of the double bond in the molecule resulted in different solubility under the same extraction conditions.26 On the other hand, branching structures help to increase the solubility of alcohols, thus, secondary and tertiary alcohols have better solubility than primary alcohol.46 In this study, the two mushroom alcohols, 1-octen-3-ol and 2-octen-1-ol, possess the same chemical formula (C8H16O) but differ in position of their hydroxyl group and double bond resulting in different solubility in SC-CO2. During the extraction, the density of SC-CO2 was ranged from 0.252 to 0.557 g mL−1 (calculated based on the temperature and pressure applied). However, the content of extracted 1-octen-3-ol did not show significant changes and this probably due to its high solubility in SC-CO2. As a secondary alcohol, 1-octen-3-ol was more efficiently extracted compared with 2-octen-1-ol (primary alcohol), and the relative poor solubility of 2-octen-1-ol required higher density SC-CO2 (95 bar, 40 °C, 70 mL SC-CO2) to reach its highest yield.
Mushroom volatiles (Y-variable) | Regression coefficients of the parameters (X-variable) | |||
---|---|---|---|---|
N1 | N2 | N3 | B0 | |
a The values marked with “*” denote that the SFE parameters were significant as a level of p < 0.05. | ||||
1-Octene | 2.827* | −0.727 | 1.502* | −226.291 |
1-Octen-3-ol | −1.329* | −1.694* | 1.831* | 421.447 |
2-Pentylfuran | 5.267* | −2.753* | 2.700* | −351.193 |
2-Octen-1-ol | 6.680* | −8.376* | 2.777* | −218.794 |
Linalool | 7.212* | −10.345* | 2.808* | −170.586 |
Nonanal | 1.722* | −2.609* | 0.476* | −17.597 |
N-(3-Methylbutyl)acetamide | 53.368* | −81.657* | 11.470* | −1004.286 |
Bornyl acetate | 3.855* | −3.621* | 1.042* | −167.499 |
2,4-Decadienal | 6.047* | −3.723* | 1.371* | −383.743 |
Geranyl acetone | 7.463* | −2.870* | 1.376* | −515.41 |
The predictive performance of these equations was estimated via the parameters of the fitted linear calibration and validated models (Table 4). Fitted linear calibration models showed that the correlation coefficient (R_cal), represented by the regression model and the mean data, were greater than 0.90, and the regression coefficients of the linear calibration models (R_cal2) were greater than 0.82 for all the typical volatiles (except 1-octen-3-ol), indicating a good fit to the calibration model. The calibrated parameters for geranyl acetone (R_cal = 0.96 R_cal2 = 0.92) and 2-octen-1-ol (R_cal = 0.96 R_cal2 = 0.91) indicated that the mean data was excellent fitted to calibration model. However, the values of R_cal = 0.89 and R_cal2 = 0.79 for 1-octen-3-ol suggested a slightly weaker fit compared with other compounds. The linear validated models were well fitted for 1-octene, 2-pentylfuran, 2-octen-1-ol, bornyl acetate, 2,4-decadienal and geranyl acetone with correlation coefficients (R_val) greater than 0.91, which means that the extraction yield of these compounds can be projected by the SFE parameters. On the other hand, regression coefficient of the linear validated equation (R_val2) used to check the adequacy of the model represents how successfully the cross-validated regression line approximates raw data points.47 As for most extracted typical volatiles, the R_val2 were greater than 0.80 (except linalool and 1-octen-3-ol), which suggested good predictive performance of the derived models.
Mushroom volatiles | Statistical parameters | |||
---|---|---|---|---|
R_cala | R_cal2b | R_valc | R_val2d | |
a R_cal denotes the correlation coefficient of the data fit with the calibration model.b R_cal2 is the raw regression coefficient (R2) of the calibration model.c R_val denotes the correlation coefficients of the data fit with the validation model.d R_val2 is the adjusted regression coefficients (R2) of the validation model. | ||||
1-Octene | 0.95 | 0.90 | 0.93 | 0.87 |
1-Octen-3-ol | 0.89 | 0.79 | 0.86 | 0.74 |
2-Pentylfuran | 0.94 | 0.88 | 0.92 | 0.85 |
2-Octen-1-ol | 0.96 | 0.91 | 0.94 | 0.88 |
Linalool | 0.90 | 0.82 | 0.89 | 0.78 |
Nonanal | 0.93 | 0.86 | 0.90 | 0.80 |
N-(3-Methylbutyl)acetamide | 0.92 | 0.85 | 0.90 | 0.81 |
Bornyl acetate | 0.97 | 0.94 | 0.95 | 0.91 |
2,4-Decadienal | 0.95 | 0.90 | 0.93 | 0.86 |
Geranyl acetone | 0.96 | 0.92 | 0.95 | 0.90 |
The root mean square error of prediction (RMSEP) represents the accuracy of a prediction model and indicates the average difference between predicted values and reference values.47 A satisfied model should have a high value of R2 and a low value of RMSEP. As shown in Fig. 6, it was observed that the reference data points for geranyl acetone were closer to the regression line, which indicated that the reference values and predicted values for geranyl acetone were in good agreement. The correlation coefficient (R = 0.97), regression coefficient (R2 = 0.93) and RMSEP (1.10) for geranyl acetone were quite satisfactory for the validation of the model. Furthermore, the model validation for 1-octene, 2-octen-1-ol, 2-pentylfuran, linalool, bornyl acetate and nonanal showed a high correlation coefficient (R > 0.92) and regression coefficient (R2 > 0.84) (Fig. 6). These results indicated the established prediction models were suitable for performing prediction and provided predictability levels of 82% for 1-octene, 88% for 2-pentylfuran, 88% for 2-octen-1-ol, 87% for linalool, 84% for nonanal, 87% for bornyl acetone, 84% for 2,4-decadienal and 92% for geranyl acetate. For n-(3-methylbutyl)acetamide, the correlation coefficient (R = 0.89) and regression coefficient (R2 = 0.78) were considered to be satisfactory, however, its RMSEP (about 22.87) was relatively poor. This might be due to the formation of n-(3-methylbutyl)acetamide related to the Maillard reaction during the drying process,45 which was impossible to be totally controlled, resulting in the nonlinear relationship under different SFE parameters.
The relationship between supercritical fluid parameters and the extraction yield of typical mushroom volatiles was studied using PLSR to point out the significant factors correlated to the yield of each aroma compound. Prediction models were established to estimate the yield of volatiles under varying parameters of SFE, and satisfactory results were obtained for 1-octene, 1-octen-3-ol, 2-pentylfuran, 2-octen-1-ol, linalool, nonanal, bornyl acetate, 2,4-decadiena, n-(3-methylbutyl)acetamide, and geranyl acetone. Furthermore, another independent data set was applied to validate the prediction models. A good prediction ability was obtained for most of the volatile compounds including 1-octene, 1-octen-3-ol, 2-pentylfuran, 2-octen-1-ol, linalool, nonanal, bornyl acetate, 2,4-decadienal, and geranyl acetone. The predictable equation could be a promising tool to predict the yield of extracted volatile compounds from mushrooms. In addition, the developed models can be applied to facilitate the selectivity of supercritical fluid extraction of target compounds from the wild Finnish mushroom Craterellus tubaeformis by adjusting favourable parameters. This is the first study focusing on the supercritical fluid extraction of volatile compounds from the wild Finnish mushroom species Craterellus tubaeformis.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c7ra12472d |
This journal is © The Royal Society of Chemistry 2018 |