Differentiation of Aroma Characteristics of Pine ... - ACS Publications

Keywords: Pine-mushroom (Tricholoma matsutake Sing.); instrument-sensory correlations; GC-O; quantitative descriptive analysis (QDA); partial least-sq...
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J. Agric. Food Chem. 2007, 55, 2323−2328

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Differentiation of Aroma Characteristics of Pine-Mushrooms (Tricholoma matsutake Sing.) of Different Grades Using Gas Chromatography−Olfactometry and Sensory Analysis IN HEE CHO,† SOH MIN LEE,† SE YOUNG KIM,† HYUNG-KYOON CHOI,‡ KWANG-OK KIM,† AND YOUNG-SUK KIM*,† Department of Food Science and Technology, Ewha Womans University, Seoul 120-750, South Korea, and College of Pharmacy, Chung-Ang University, Seoul 156-756, South Korea

Two independent approaches, gas chromatography-olfactometry and sensory analysis, were used to evaluate and compare the aroma characteristics of pine-mushrooms (Tricholoma matsutake Sing.) of four different grades. The aroma-active compounds responsible for the sensory attributes of pinemushrooms were investigated based on the correlation between instrumental and sensory analyses through partial least-square regression. Piny, meaty, and floral attributes were strongly correlated with each other and were the most important descriptors for defining the pine-mushrooms of the highest grade, and they decreased as the grade decreased. Among 23 aroma-active compounds, (E)-2-decenal, R-terpineol, phenylethyl alcohol, and 2-methylbutanoic acid ethyl ester contributed most to these attributes. On the other hand, the major aroma characteristics of the pine-mushrooms of the lowest grade were wet soil-like, alcohol, metallic, moldy, and fermented, and they decreased as the grade increased. These aroma characteristics were strongly associated with 1-octen-3-one, 1-octen-3-ol, 3-octanol, 3-octanone, (E)-2-octen-1-ol, and methional. KEYWORDS: Pine-mushroom (Tricholoma matsutake Sing.); instrument-sensory correlations; GC-O; quantitative descriptive analysis (QDA); partial least-square regression (PLSR)

INTRODUCTION

The aroma of a foodstuff is crucially important to its perceived quality (1). In general, aroma perception is determined by the properties and amounts of volatile components and their availability to the sensory system as a function of time (2). It has been shown in many foods that only a small number of volatiles activate the odorant receptors in the human nasal cavity (3-5), thereby contributing to the aroma perception during mastication. Such aroma-active compounds can be screened from the bulk of nonactive volatiles by combining the human olfactometry system with analytical techniques (6). Gas chromatography-olfactometry (GC-O) with aroma extract dilution analysis (AEDA) is the most frequently used method to estimate the sensory contribution of single aroma compounds. In AEDA, the assessors evaluate whether or not an aroma can be perceived and describe its aroma property. The result is expressed as the flavor dilution (FD) factor that corresponds to the maximum dilution at which the aroma is detected (7). In addition, information on the sensory attributes of a foodstuff can be provided by establishing their descriptive profiles with sensory descriptive analysis, such as a quantitative descriptive analysis (QDA) technique, which discriminates and describes both * To whom correspondence should be addressed. Tel: +82 2 3277 3091. Fax: +82 2 3277 4213. E-mail: [email protected]. † Ewha Womans University. ‡ Chung-Ang University.

qualitative and quantitative aspects of a foodstuff. The qualitative component comprises the descriptive terms, called “attributes”, which define the sensory profile of the samples, and the quantitative component measures the degree or intensity of each perceived attribute (8, 9). Therefore, combining two approaches, GC-O and sensory evaluation, represents a powerful and comprehensive way to investigate the aroma characteristics of a foodstuff. Multivariate analysis can be used to extract interpretable and statistically reliable information from data sets obtained by separate approaches (10-15). In particular, partial least-square regression (PLSR) is one of the multivariate regression analysis techniques that can be used to understand the relationship between two data sets by predicting one data set (Y) from the other set (X). It not only provides solutions for both data sets but also attempts to find the best solution of one data set to explain the variation of the other data set (16). Pine-mushroom (Tricholoma matsutake Sing.) is the most valuable mushroom species worldwide, and it exhibits a characteristic and delicate flavor. Pine-mushrooms can be classified according to their appearance (17, 18), which is affected mostly by their ripening stages and cultivating conditions. The quality characteristics of pine-mushrooms, such as aroma, taste, texture, and color, vary with their grades. In particular, pine-mushrooms of higher grades have distinctive aroma characteristics as compared to those of lower grades. We recently investigated

10.1021/jf062702z CCC: $37.00 © 2007 American Chemical Society Published on Web 02/27/2007

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Cho et al.

Table 1. Definitions and References of the Descriptive Attributes for Pine-Mushrooms attribute sweet salty sour bitter umami

definition

reference

piny

fundamental taste elicited by sugars fundamental taste elicited by salts fundamental taste elicited by acids fundamental taste elicited by caffeine fundamental meaty taste elicited by monosodium glutamate (MSG) aroma associated with pine needle

floral

aroma associated with chrysanthemum

alcohol meaty moldy wet soil-like fishy fermented

aroma associated with rum aroma associated with cooked meat aroma associated with typical mushroom aroma associated with damp soil aroma associated with fermented anchovy aroma associated with Sikhye (a traditional Korean fermented rice beverage) aroma associated with metals mouth feeling associated with tannins

metallic astringent

how the volatile compositions of pine-mushrooms vary with their grades by applying multivariate statistical methods to gas chromatography-mass spectrometry (GC-MS) data sets (18). We also revealed that 23 aroma-active compounds were key odorants of pine-mushrooms of the highest grade (19). The aims of the present study were to (i) characterize and quantify the potent odorants in pine-mushrooms of different grades, (ii) describe and measure the intensity of each sensory attribute in pine-mushrooms according to their grades, (iii) ascertain how the results of instrumental and sensory analyses of pine-mushrooms vary with their grades, and (iv) identify the odorants responsible for aroma attributes of pine-mushrooms by correlating the GC-O and sensory data sets using PLSR. MATERIALS AND METHODS Chemicals. Dichloromethane (g99.9% purity) was obtained from Fisher Scientific (Seoul, Korea). Sodium sulfate and n-alkane standards (C8-C22) were purchased from Sigma-Aldrich (St. Louis, MO). Stock solutions of 23 authentic standard compounds were prepared in dichloromethane. Standards 1-9, 11-15, 17-21, and 23 were obtained from Sigma-Aldrich, while standards 10, 16, and 22 were purchased from Wako Pure Chemical Industries (Osaka, Japan). Sample Materials. Pine-mushrooms of four grades cultivated in Injeeup, Gangwon-do, South Korea, in 2004 were used. Raw pinemushrooms were wrapped in low-density polyethylene film and stored at -70 °C until used. Extraction of Volatiles. Frozen mushrooms were thawed at 4 °C for 3 h and then sliced using a cutter (Shinomura, Sanjoˇ, Niigata, Japan). The sliced mushrooms were transferred into a stainless steel container, frozen in liquid nitrogen, and then ground in a blender (Hanil Electric, Seoul, Korea). The ground mushrooms (100 g) were extracted with 200 mL of dichloromethane that was redistilled before use. The ground sample suspended in dichloromethane was magnetically stirred at 400 rpm for 30 min and then filtered through Whatman no. 41 filter paper (Maidstone, United Kingdom) under vacuum. Volatile components were then separated from the nonvolatiles using high vacuum sublimation (HVS) (18). The extract was dehydrated over anhydrous sodium sulfate, evaporated on a Vigreux column (50 cm length × 3 cm i.d.) in a water bath at 45 °C, and then concentrated under a slow stream of nitrogen gas to obtain a final volume of 0.1 (for GC-MS and GC-O) or 1.0 mL (for fractionation by column chromatography). Fractionation by Column Chromatography. To identify odorants not detected by GC-MS, the HVS extracts (1.0 mL) were subjected to silica gel column chromatography. The mushroom extracts were loaded onto a cooled column (45 cm length × 20 mm i.d.) filled with silica gel (35-70 mesh, 40 Å, Sigma-Aldrich). The concentrated volatile

sucrose (1.5% in water) sodium chloride (0.4% in water) citric acid (0.05% in water) caffeine (0.07% in water) monosodium glutamate (0.15% in water) pine needle tea (one tea bag infused in 100 mL of boiling water for 2 min) chrysanthemum tea (one tea bag infused in 200 mL of boiling water for 2 min) white rum (0.125% in water) boiled beef 1-octen-3-one (1000 ppm in dichloromethane) damp soil fermented anchovy sauce (0.025% in water) Sikhye drink (50% in water) stainless steel spoon tannic acid (0.1% in water)

extracts were separated into six fractions using a pentane/diethyl ether gradient (F1 extracts ) 50/0 mL, F2 extracts ) 40/10 mL, F3 extracts ) 30/20 mL, F4 extracts ) 20/30 mL, F5 extracts ) 10/40 mL, and F6 extracts ) 0/50 mL, respectively). Each fraction was further concentrated under a slow stream of nitrogen gas until it could be analyzed for the identification of unknowns in GC-MS anaylsis. GC-MS. GC-MS analysis was performed using an HP 6890N gas chromatography-5973N mass selective detector (GC-MSD) (HewlettPackard, Palo Alto, CA) equipped with a DB-wax column (60 m length × 0.25 mm i.d. × 0.25 mm film thickness, J&W Scientific, Folsom, CA) and an HP 5890 series II GC/5972 MSD equipped with a DB5ms column (30 m length × 0.25 mm i.d. × 0.25 mm film thickness). The carrier gas was helium at a constant flow rate of 0.8 mL/min. One microliter of mushroom extract was injected into the column using the splitless injection mode. The oven temperature was initially held at 40 °C for 1 min, then raised to 200 °C at a rate of 4 °C/min, and finally held at 200 °C for 10 min. The temperatures of injector and detector were 200 and 250 °C, respectively. The mass detector was operated in electron impact mode with an ionization energy of 70 eV, a scanning range of 33-550 amu, and a scan rate of 1.4 scans/s. GC-O. GC-O was conducted on a Varian CP-3800 GC (Varian, Walnut Creek, CA) equipped with a flame ionization detector (FID) and a sniffing port (ODO II, SGE, Ringwood, Australia) using a DBwax column and a DB-5ms column. Effluent collected from the end of GC column was split equally between the FID and the sniffing port. The HVS extract was diluted stepwise with dichloromethane (1 + 1 by volume). An aliquot (1 µL) was injected into the capillary column. The oven temperature program was the same as that used for GC-MS. The temperatures of injector and detector were 200 and 250 °C, respectively. FD factors of the volatile components were determined by AEDA; the FD factor corresponded to the maximum dilution at which each component could be detected (20). Two experienced sniffers, each with >30 h training on GC-O, participated in AEDA. Then, the maximum value of them was provided as the FD factor of that compound. Identification of Aroma-Active Compounds. For positive identifications, mass spectra, linear retention indices (RIs), and aroma properties of unknowns were compared with those of authentic standards. Tentative identifications were based on matching RIs and aroma properties of unknowns with those in the literature (21) or comparing the RIs and aroma properties of unknowns to those of authentic standards. Aroma properties of all authentic standards were determined by GC-O. The RI of each compound was calculated using n-alkanes C8-C22 as external references (22). Panel Selection and Training for Sensory Evaluation. Eight subjects (female, 21-25 years of age), who previously participated in more than four descriptive analyses in the Department of Food Science and Technology at Ewha Womans University, were selected as the

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Table 2. Aroma-Active Compounds of Pine-Mushrooms of Four Different Grades FD factorc no.

RIa on DB-wax DB-5ms

DB-wax second third

aroma-active compound

aroma propertyb

first

herbaceous floral and sweet

1 32

1 4

2 1 2

DB-5ms second third

fourth

IDd

fourth

first

1 4

0 16

2 64

2 8

1 8

0 16

MS/RI/odor RI/odor

2 1 1

1 2 4

2 1 4

2 2 4

2 1 4

1 2 4

2 1 8

MS/RI/odor MS/RI/odor MS/RI/odor

1 256 1

4 256 0

2 512 1

4 1024 1

1 256 1

4 256 0

1 1024 2

4 4096 2

1 2

1031 1073