Comparison of Volatiles in Cooked Rice with Various Amylose Contents

Abstract

Gas chromatography-mass spectrometry (GC-MS) was employed to analyze the volatiles in thirty-five samples of cooked rice (Oryza sativa L.) including the low-amylose rice cv. ‘Oborozuki’, normal-amylose rice, and glutinous rice. A distinct flavor is exhibited in cooked glutinous rice (containing no amylose) because of the high amount of unsaturated aldehydes; therefore, low-amylose rice might also have a glutinous-like flavor due to the decrease in amylose. Thus, volatile profiles were analyzed to determine the relationships with amylose content. The profiles of 42 volatiles in three types of cooked rice were compared. There were significant differences between glutinous and non-glutinous rice samples. Several volatiles detected at significant levels in the glutinous samples were characterized as glutinous-rich volatiles. These volatiles were predicted to be negatively correlated with amylose content. However, of the 22 glutinous-rich volatiles, only indole had significant negative relationship with amylose content. These results suggest that glutinous-rich volatiles are not affected by decreases in amylose content.

Introduction

Rice (Oryza sativa L.) is one of the most important grains throughout the world, with the third-highest production after maize and wheat, and is a staple food in many countries, including Japan. Because of high consumer demand, rice breeding in Japan has focused mainly on improvements in eating quality. Japanese rice has recently experienced an increase in popularity, especially in Asia, due to its high eating quality. Moreover, the amount of exported rice has increased two-fold in 5 years(i). Texture is important for the eating quality of cooked rice; therefore, the properties of starches in the rice endosperm have been extensively studied (Biliaderis et al., 1986; Lii et al., 1996; Takeda et al., 1986; Villareal et al., 1994; Williams et al., 1958). Juliano and collaborators reported that low level amylose content contributes to the good eating quality of cooked rice (Cagampan et al., 1973; Juliano, 1981; Perez et al., 1979). Several mutations of the WX1 locus were found to affect amylose synthesis and reduced amylose concentrations to less than 20% (Sano, 1984; Yano et al., 1988). As a result, a number of low-amylose rice cultivars have been developed over the past decade in Japan (Higashi et al., 1999; Okamoto et al., 2001; Tanno et al., 1997; Uehara et al., 1995).

Flavor also plays a key role in consumer acceptability of rice. Fragrant rice such as Jasmine or Basmati is popular in Asia. Cooked rice flavor has been extensively studied and more than 100 flavor volatiles have been identified (Champagne, 2008; Maraval and others, 2008; Tsugita, 1986). According to previous reports, glutinous rice (waxy rice; containing no starch amylose) has a distinctive aroma due to the high amount of volatiles such as unsaturated aldehydes (Grimm et al., 2002). Furthermore, low-amylose cooked rice might also exhibit a glutinous-like flavor due to the low amylose content compared to normal-amylose rice. While the composition of flavor volatiles in cooked rice of varying amylose content has not yet been investigated, we expect there to be negative relationships between amylose content and volatile profiles.

This paper describes the differences in volatile profiles of low-amylose rice, normal-amylose rice, and glutinous rice in an effort to characterize the volatile profiles in low-amylose rice. In this study, we analyzed the following rice varieties: Oborozuki, a popular low-amylose variety developed in Hokkaido (Ando et al., 2007); four normal-amylose varieties, Kirara397, Hoshinoyume, Nanatsuboshi, and Fukkurinko; and four glutinous varieties, Hakuchoumochi, Kitayukimochi, Kazenokomochi, and Shirokumamochi.

Solid-phase microextraction (SPME) is a well-established technique for the extraction and concentration of volatiles, and has been employed in investigations of cooked rice (Zeng et al., 2007, 2008). Headspace sorptive extraction (HSSE) can also be employed in headspace analysis of samples in the same way as SPME. Its absorption capacity is nearly 50-fold greater than SPME, allowing for a more sensitive analysis. HSSE has been successfully applied to the analysis of several matrices (Kreck et al., 2002; Lorenzo et al., 2006; Weldegergis et al., 2007); however, the quantification of 2-acetyl-1-pyrroline (2AP), one of the most important volatiles in rice flavor, was inadequate (Grimm et al., 2011). Notably, this technique has been optimized for analyzing volatiles in wine vinegar (Callejón et al., 2008). In this study we employed HSSE to compare the volatile profiles of rice samples with varying amylose content. The interaction between food matrix components and volatiles was also discussed.

Materials and Methods

Rice samples    Thirty-five rice samples were obtained from Hokkaido, Japan during 2010 (Table 1). The rice samples were transplanted on May 24 (± 4 days), then harvested on September 20 (± 2 days) and dehulled where they were grown. They were immediately transported to the laboratory as brown rice, and stored at 2°C for about 60 days until the experiments were performed. The water content of rice samples was 14.95 ± 0.35%. The rice samples were milled using a milling machine (Yamamoto, Tendo, Japan) to a 90.0 ± 0.1% milling yield (brown rice basis) to give white rice, which was used for the experiments. The amylose content was measured colorimetrically at pH 4.5 and 620 nm using an autoanalyzer (BL TEC K.K., Osaka, Japan). Glutinous rice starch was used as a standard.

Table 1. Rice sample information.

Type	Varieties		Amylose content (%)	Latitude of production area	Amount of precipitation (mm)a	Day length (h)a	Average temperature(°C)a
Glutinous	Hakuchoumochi	1	0.0	44.2	623	579	19.4
		2	0.0	43.5	400	612	20.0
	Kitayukimochi	1	0.0	44.2	623	579	19.4
		2	0.0	43.5	400	612	20.0
		3	0.0	44.0	574	597	19.8
		4	0.0	42.4	743	517	19.4
	Kazenokomochi	1	0.0	44.2	623	579	19.4
		2	0.0	44.0	574	597	19.8
	Shirokumamochi	1	0.0	44.2	623	579	19.4
		2	0.0	44.3	623	645	18.9
Low-amylose	Oborozuki	1	10.1	41.5	563	618	20.7
		2	10.9	42.5	523	559	19.3
		3	11.2	42.3	577	559	19.0
		4	11.6	42.6	471	563	19.4
		5	11.8	43.1	477	608	19.7
		6	11.9	43.0	619	629	20.4
		7	11.9	43.5	576	614	20.3
		8	12.0	42.6	495	601	20.4
		9	12.3	42.1	569	533	18.7
		10	12.4	43.8	441	607	20.8
		11	12.6	43.7	548	642	20.2
		12	12.7	42.5	554	623	20.1
		13	12.9	44.4	554	664	19.8
		14	12.9	44.3	553	644	19.7
		15	13.0	43.7	480	637	20.1
Normal-amylose	Kirara397	1	19.8	43.8	441	607	20.8
		2	19.7	43.4	584	631	19.9
		3	18.7	43.2	636	617	20.2
	Hoshinoyume	1	20.3	43.8	441	607	20.8
		2	17.8	41.5	563	618	20.7
	Nanatsuboshi	1	18.8	44.1	420	624	19.7
		2	18.6	42.3	577	559	19.0
		3	18.0	43.7	548	642	20.2
	Fukkurinko	1	18.9	41.5	563	618	20.7
		2	19.8	43.7	548	642	20.2

a  Weather data were collected between May 24th and September 20th in 2010 during field cultivation.

Chemicals    All private standards used for volatile identification were supplied by TCI Tokyo (Tokyo, Japan), Wako Pure Chemical Industries (Osaka, Japan), and Sigma Aldrich (St. Louis, MO, USA) Sample preparation The rice was cooked according to the traditional Japanese method. White rice (400 g) was washed using tap water to prepare cooked rice as ordinarily consumed. The washed rice sample, benzyl alcohol as an internal standard (920 µL; 0.10 mg mL-1 water), and about 520 mL of tap water were combined for a total amount of 920 g in an automatic electric rice cooker (Panasonic, Kadoma, Japan). The mixture was heated for 48 min and kept warm for another 30 min to ensure it was completely cooked.

Headspace extraction sampling    Since cooked rice is so sticky that most commercial headspace vials are too small for use in HSSE extraction, we employed an ordinary glass beaker for headspace volatile extraction. One hundred grams of cooked rice were transferred to a 500 mL beaker. A Twister® stir bar (10 mm, Gerstel, Müllheim, Germany), consisting of a magnetic core sealed in a glass tube coated with 24 µL of PDMS, was hung in the headspace, and the beaker was covered with ordinary clear film (polyvinylidene chloride) for 30 min. HSSE extraction was performed at room temperature (25°C). The temperature in the HSSE headspace was changed from 40.0 ± 1.0°C to 32.2 ± 1.6°C during extraction. Artificial volatiles from the HSSE sampling system detected in a blank run are listed in Table 2. These volatiles were removed from further analyses. After sampling, the stir bar was removed, washed and dried gently, and placed in the original glass vial. The stir bar was then removed from the vial, rinsed with distilled water, and dried with cellulose tissue before being placed in an empty pre-conditioned glass thermal desorption tube (187 mm length, 6 mm OD, and 4 mm ID). The stir bar was desorbed using a TDS-3 (Gerstel) thermodesorption system.

Table 2. Levels of 81 volatiles in 3 rice types.^a

Compound	m/zd	RI	Glutinous	Low-amylose	Normal-amylose
Hexanal	56	1072	3.87 ± 1.04a	0.63 ± 0.20b	0.46 ± 0.11b
Butan-1-ol	56	1073	0.29 ± 0.15a	0.04 ± 0.01b	0.05 ± 0.03b
Heptanal	70	1164	0.15 ± 0.08a	0.05 ± 0.01b	0.05 ± 0.01b
Heptan-2-one	43	1172	0.88 ± 0.28a	0.09 ± 0.03b	0.08 ± 0.02b
Benzene, 1-ethyl-3-methylbc		1207
2-Pentylfuran	81	1230	6.12 ± 2.62a	0.9 6 ± 0.34b	1.07 ± 0.27b
Octan-3-one	99	1232	0.02 ± 0.01	tre	tr
Pentan-1-ol	55	1277	0.11 ± 0.05a	0.02 ± 0.01b	0.03 ± 0.00b
1,2,4-Trimethylbenzenebc		1281
Octan-2-one	128	1282	0.01 ± 0.00	tr	tr
Octanal	84	1289	0.13 ± 0.08a	0.04 ± 0.01b	0.04 ± 0.01b
(E)-Hept-2-enal	83	1332	0.25 ± 0.11a	0.07 ± 0.01b	0.07 ± 0.01b
2-Hexylfuran	152	1333	0.01 ± 0.00	ndf	nd
6-Methylhept-5-en-2-one	43	1341	0.07 ± 0.04a	0.04 ± 0.01b	0.05 ± 0.02 ab
Cyclohexasiloxane, dodecamethylbc		1356
Hexan-1-ol	56	1363	0.14 ± 0.04	0.08 ± 0.09	0.08 ± 0.02
Dimethylsiloxane cyclic trimerbc		1368
Nonan-2-one	142	1387	0.01 ± 0.00	tr	tr
2-Ethyl-1-hexanol acetateb	70	1388	0.18 ± 0.14a	0.03 ± 0.01b	0.03 ± 0.04b
Nonanal	95	1394	0.12 ± 0.05a	0.07 ± 0.01b	0.06 ± 0.03b
(E)-Oct-2-enal	70	1432	0.19 ± 0.07a	0.06 ± 0.01b	0.05 ± 0.01b
Oct-1-en-3-ol	57	1455	1.05 ± 0.38a	0.15 ± 0.03b	0.13 ± 0.03b
2-Propenoic acid, 2-ethylhexyl esterbc		1462
Heptan-1-ol	70	1465	0.09 ± 0.04a	0.01 ± 0.01b	0.01 ± 0.00b
Octamethylcyclotetrasiloxanebc		1469
Acetic acid	43	1470	0.14 ± 0.10a	0.03 ± 0.02b	0.02 ± 0.01b
2-Ethylhexyl acrylatebc		1489
(E,E)-Hepta-2,4-dienal	110	1490	0.01 ± 0.00	nd	nd
Decanal	68	1503	0.13 ± 0.09a	0.05 ± 0.02b	0.04 ± 0.02b
Phenyl-pentamethyl-disiloxanebc		1516
Cycloheptasiloxane, tetradecamethylbc		1520
Benzaldehyde	106	1522	0.27 ± 0.11a	0.17 ± 0.04b	0.19 ± 0.04b
Unknownc		1537
Decan-2-one	156	1541	0.01 ± 0.00	tr	tr
(E)-Non-2-enal	70	1541	0.05 ± 0.02a	0.02 ± 0.00b	0.02 ± 0.01b
Pyrrole, 2-methylbc		1560
2-Fenchanolbc		1561
Longifolenebc		1565
Octan-1-ol	56	1566	0.08 ± 0.03a	0.02 ± 0.01b	0.01 ± 0.00b
Undecan-2-one	170	1578	tr	nd	nd
Cyclohexasiloxane, dodecamethylbc		1581
Octa-3,5-dien-2-oneb	95	1584	0.10 ± 0.06a	0.01 ± 0.00b	0.01 ± 0.01b
Undecanal	126	1587	tr	nd	nd
Camphor	108	1628	0.02 ± 0.02	0.02 ± 0.01	0.02 ± 0.01
Carbitolbc		1631
Naphthalene, 1,2,3,4-tetrahydro-5-methylbc		1638
Menthol	71	1648	0.02 ± 0.01a	0.01 ± 0.00b	0.01 ± 0.00b
(E)-Dec-2-enal	83	1650	0.02 ± 0.00	nd	nd
Nonan-1-ol	70	1672	0.02 ± 0.01a	0.01 ± 0.00b	0.01 ± 0.00b
(E,E)-Nona-2,4-dienal	81	1708	0.06 ± 0.01a	0.01 ± 0.01b	0.01 ± 0.00b
Cyclooctasiloxane, hexadecamethylbc		1710
Dibutyl carbitolbc		1742
Benzene, 3-cyclohexen-1-ylbc		1750
Pentanoic acidb	60	1759	0.01 ± 0.01a	0.01 ± 0.00b	0.01 ± 0.00b
Heptadecane, 3-methylbc		1764
N,N-Dibutylformamidebc		1784
(E,E)-Deca-2,4-dienal	81	1819	0.19 ± 0.04	0.16 ± 0.03	0.16 ± 0.05
Benzaldehyde, 2,4-dichlorobc		1850
Unknownc		1856
Hexanoic acid	60	1858	0.03 ± 0.02a	0.02 ± 0.01 ab	0.02 ± 0.01b
Geranyl acetone	69	1862	0.05 ± 0.01	tr	tr
Unknownc		1877
Unknownc		1889
Butylated hydroxytoluenebc		1916
Dodecan-1-olb	69	1979	0.11 ± 0.05	0.09 ± 0.02	0.09 ± 0.02
Diethylene glycolbc		1986
Unknownc		1997
Phenol	94	2006	0.03 ± 0.01	0.02 ± 0.01	0.02 ± 0.01
Lilialbc		2045
Unknownc		2053
Octanoic acidb	60	2069	0.02 ± 0.01	0.02 ± 0.01	0.02 ± 0.02
Unknownc		2099
Hexanedioic acid, bis(2-methylpropyl) esterbc		2148
Nonanoic acidb	60	2179	0.01 ± 0.01	0.02 ± 0.01	0.02 ± 0.02
2-Methoxy-4-vinylphenolb	135	2204	0.04 ± 0.02a	0.06 ± 0.01b	0.10 ± 0.02 c
Isopropyl palmitatebc		2249
Phenol, 2,4-bis(1,1-dimethylethyl)bc		2323
Diethyl phthalatebc		2380
2,4-Diphenyl-4-methyl-1-pentenebc		2381
Indole	117	2458	0.16 ± 0.05a	0.11 ± 0.04b	0.06 ± 0.03b
Benzophenonebc		2493
Diisobutyl phthalatebc		2544
Methanone, (4-methylphenyl)phenylbc		2662
Total			15.27 ± 4.23a	3.10 ± 0.63b	3.20 ± 0.67b

Values are mean ± standard deviation.

a  Means with different letters in the same row are significantly different (p < 0.05).

b  Tentatively identified.

c  Detected in blank run. These were regarded as artificial peaks and omitted from further analysis.

d  m/z used for area measurement

e  Trace with a peak area (mean level < 0.01).

f  Not detected.

Instrumentation Conditions    GC-MS analysis was carried out using a gas chromatograph (Agilent 6890; Agilent Technologies, Palo alto, CA) coupled to a mass spectrometer (5973MSD; Agilent Technologies), equipped with a capillary column (DB-WAX, 30 m × 0.25 mm, ID × 0.25 µm film thickness; Agilent Technologies). The GC oven was kept at 40°C for 5 min, increased to 220°C at a rate of 8°C/min, and then kept at this temperature for 10 min. Helium was used as the carrier gas at a flow rate of 1.0 mL/min (linear velocity: 36 cm/sec). The MS was operated in scan mode at 2.02 scans/s between m/z 29 and 450. The MS transfer line, ion source, and quadrupole temperatures were 280°C, 230°C and 150°C, respectively, and spectra were recorded in the electron impact mode at 70 eV (Soria et al., 2008).

The TDS-3 (Gerstel) temperature program, operating in splitless mode, began at 20°C for 1 min, was then raised to 220°C at a rate of 60°C/min, and was finally kept at 220°C for 10 min. The transfer line was kept at 240°C. The desorbed compounds were cryofocused in the CIS-4 injector (Gerstel), with a programmed temperature vaporizing injector (PTV) at −150°C using liquid nitrogen. The injector temperature was increased to 220°C at a rate of 12°C/s, and then maintained for 10 min.

Volatile identification and peak determination    Volatiles were identified using the NIST 08 library and retention index (RI) with a mixture of n-alkanes determined by AMDIS software (http://chemdata.nist.gov/mass-spc/amdis/) based on private standards. The identified volatiles were determined using Chemstation software (Agilent technologies). Volatile levels (semiquantification) were calculated from the GC-peak area relating to the GC-peak area of benzyl alcohol (internal standard) prior to statistical analysis. All experiments were performed in duplicate.

Statistical analysis    After normalizing against the peak area of benzyl alcohol (internal standard), principal component analysis (PCA) was carried out using JMP 8.0 (SAS Institute, Cary, NC). Analysis of variance (ANOVA) was also performed (JMP 8.0).

Results and Discussion

Flavor volatiles in cooked rice of varying amylose content    The flavor volatiles in the headspace of cooked rice were directly extracted using a PDMS-coated Twister® stir bar and analyzed by GC-MS; 81 volatiles were detected (Table 2). To distinguish the artificial volatiles from the HSSE sampling system, a blank extract (ordinary film over 520 mL of hot water in the beaker; the same as volatile sampling conditions) was performed. Thirty-nine volatiles were detected from the blank measurement (Table 2), which were then omitted from further analysis. The other 42 peaks extracted from cooked rice using HSSE were compared to the NIST library and authentic private standards for the identification of volatiles.

The volatiles detected in the cooked rice consisted of aldehydes, ketones, alcohols, heterocyclic volatiles, fatty acids, fatty esters, and phenolic volatiles (Table 2). The results are consistent with previously reported rice volatiles extracted by different methods (Buttery et al., 1988; Jezussek et al., 2002; Widjaja et al., 1996; Yang et al., 2008a, 2008b). One target m/z ion for each volatile was calculated as the method commonly used for metabolite profiling (Ochi et al., 2012), which provided relative levels of the volatiles, and not absolute quantities (Table 2). The most abundant volatile was nonanal (data not shown), which is consistent with a previous study where SPME was used to analyze Japanese cooked rice (Zeng et al., 2007). HSSE contains only a PDMS phase, whereas SPME contains DVB/CAR/PDMS; thus, there might be differences in the application of HSSE and SPME for volatile determinations. Although the glutinous rice aroma components γ-nonalactone and vanillin were detected by SPME as markers of the rice cooking method (Zeng et al., 2009), these volatile levels were below the detection limit of this study. In addition, 2-acetyl-1-pyrroline (2AP) was not detected in the three rice types. Though only 2-methoxy-4-vinylphenol was detected at high levels in the non-glutinous rice, 23 volatiles showed significantly high levels (p < 0.05) in the glutinous rice samples (Table 2). The total amount of volatiles in non-glutinous rice was about 5-fold less than that of glutinous rice. In particular, the concentrations of odor-active volatiles in glutinous rice previously reported, such as 2-pentylfuran, 3-octenol, 2,4-nonadienal(E,E), indole, and hexanal (Zeng et al., 2009), were at least 3-fold higher than those in Oborozuki samples. Furthermore, the levels of some aldehydes and ketones approached the detection limit in non-glutinous samples. These data imply noticeable differences in the flavor characteristics of the different types of rice.

Relationship between aroma volatiles and amylose content in cooked low-amylose rice    Volatile components are of interest because they are emitted from the food structure matrix, and thus interactions between volatiles and other ingredients, such as starch, are important (Jouquand et al., 2006). The linear amylose in starch was able to form complexes with volatiles, and consequently the retention of the volatiles increased with the amylose content (Arvisenet et al., 2002). Glutinous rice has a distinctive aroma because of the high amount of unsaturated aldehydes (Grimm et al., 2002). Additionally, cooked low-amylose rice might also have a glutinous-like flavor due to the low amylose content. However, while these observations imply a relationship between amylose content and cooked rice flavor, such a relation is not well understood (Champagne et al., 2004).

In this study, we employed three different types of rice according to amylose content (Table 1). We proposed that if a relationship exists between amylose content and the amount of volatiles in cooked rice, the level of volatiles, being higher in glutinous rice, might increase as the amylose content decreases. Table 3 shows the volatiles that were significantly increased in glutinous rice compared to normal-amylose rice. To investigate the correlation between amylose content and cooked rice volatile levels, we defined 22 volatiles as glutinous-rich volatiles, which were present at significantly higher levels (p < 0.01) in the glutinous rice (Table 3). The volatiles showing a particularly low p value were expected to be significantly associated with the flavor of glutinous rice. The concentration of these 22 volatiles was predicted to be negatively correlated with the amylose content. Although 16 of the glutinous-rich volatiles were negatively correlated with the amylose content, a significant correlation (p<0.05) was detected only with indole (Table 4). These results suggest that the glutinous-rich volatiles in cooked rice are not affected by the decrease in amylose content.

Table 3. Ratios of the volatile levels in glutinous rice samples to that of normal-amylose rice

Compound	Level	p value
2-Methoxy-4-vinylphenol	0.42	0.000
Heptan-2-one	10.32	0.000
Hexanal	8.49	0.000
(E,E)-Nona-2,4-dienal	5.06	0.000
Oct-1-en-3-ol	7.97	0.000
(E)-Non-2-enal	2.75	0.000
Octan-1-ol	5.60	0.000
Heptan-1-ol	7.45	0.000
Pentan-1-ol	4.51	0.000
2-Pentylfuran	5.74	0.000
(E)-Oct-2-enal	3.77	0.000
(E)-Hept-2-enal	3.64	0.000
Butan-1-ol	6.16	0.000
Octa-3,5-dien-2-one	7.68	0.000
Indole	2.75	0.001
Heptanal	3.09	0.001
Nonan-1-ol	2.30	0.001
Octanal	3.51	0.002
Acetic acid	5.60	0.003
Nonanal	2.01	0.004
Decanal	3.11	0.005
2-Ethyl-hexan-1-ol acetate	5.70	0.006
Pentanoic acid	2.15	0.008
Hexanoic acid	2.10	0.013
Menthol	1.77	0.026
Benzaldehyde	1.43	0.035
Hexan-1-ol	1.65	0.133
6-Methylhept-5-en-2-one	1.34	0.163
Nonanoic acid	0.41	0.217
(E,E)-Deca-2,4-dienal	1.14	0.292
Dodecan-1-ol	1.17	0.375
Camphor	1.28	0.509
Octanoic acid	1.25	0.535
Phenol	1.06	0.721

Volatiles indicated in bold were particularly elevated in glutinous rice (p < 0.01), and were defined as glutinous-rich volatiles. The p value was determined using one-way analysis of variance (ANOVA).

Table 4. Correlation between the level of glutinous-rich volatiles and amylose content in low-amylose and normal-amylose rice samples.

Glutinous-rich factors	Correlation values	p value
Indole	−0.40a	0.046
Oct-1-en-3-ol	−0.38	0.059
Hexanal	−0.35	0.085
(E,E)-Nona-2,4-dienal	−0.31	0.131
(E)-Oct-2-enal	−0.26	0.202
Nonanal	−0.21	0.315
Nonan-1-ol	−0.20	0.346
Octan-1-ol	−0.18	0.401
2-Ethyl-hexan-1-ol acetate	−0.17	0.403
(E)-Non-2-enal	−0.16	0.455
Decanal	−0.16	0.457
Heptan-2-one	−0.15	0.490
Octanal	−0.13	0.545
Heptan-1-ol	−0.11	0.593
Octa-3,5-dien-2-one	−0.09	0.670
Pentanoic acid	−0.03	0.893
Heptanal	0.01	0.959
Butan-1-ol	0.02	0.907
Acetic acid	0.04	0.851
(E)-Hept-2-enal	0.04	0.838
2-Pentylfuran	0.07	0.729
Pentan-1-ol	0.21	0.312

a  Significant R > (± 0.400) at the 5% level.

Our results revealed that the reduction in amylose content did not significantly influence the increase in all glutinous-rich volatiles in cooked rice, although it has been reported that a glutinous-like flavor was detected in cooked low-amylose rice. Principal component analysis (PCA) was conducted using 32 volatiles (Fig. 1); 10 volatiles were omitted because they were below the quantification limit (tr or nd in Table 2) in any of three rice types. With respect to the volatile levels in the 15 Oborozuki samples, which accounted for 35.2% as the first principal component (PC1) and 16.4% as the second principal component (PC2) of the total variance, Oborozuki 6 was distinct from the other Oborozuki samples, indicating that it has a unique volatile profile (Fig. 1A). Figure 1B shows PCA using the volatiles data from all 35 rice samples. The correlation of PC1 with total volatile level (R = 0.974; p < 0.01) separated the glutinous and the low-amylose rice. Furthermore, Oborozuki 6 was located near the glutinous samples, indicating the similarity of its volatile profile to glutinous rice. Although 5 of the 15 Oborozuki samples had low amylose content (10.1 − 11.8%), only Oborozuki 6 (11.9% amylose content) had a glutinous-like flavor (data not shown). These observations also indicate that amylase content was not correlated with glutinous-like flavor in cooked low-amylose Oborozuki.

Fig. 1.

Sample scores for the principal component analysis of the 32 volatiles determined in cooked rice. Numbers correspond to the Oborozuki samples listed in Table 1. A) Scores from PC1 and PC2 using the 15 Oborozuki samples. B) Scores from PC1 and PC3 using all 35 samples.

A homogenous genetic background was necessary to characterize the volatile profiles of low-amylose rice, thus only the Oborozuki variety was used. In contrast, a number of different varieties would have provided a wider range of amylose content. Oborozuki has a 37-bp deletion in intron 10 in the WX1 locus (Ando et al., 2010). WX1 plays a central role in glutinous characteristics (Olsen and Purugganan 2002) such as sticky and glossy texture, and is influenced by the environmental temperature during grain filling (Sano et al., 1985). However, the main conditions responsible for altering volatile profiles, such as in Oborozuki 6, of cooked rice are unclear. Therefore, further study is required to demonstrate the relationship between volatile profiles, environmental conditions, and cooked low-amylose rice flavor.

Acknowledgments    We would like to thank Dr. Fukuyo Tanaka (NARO) for useful suggestions regarding GC-MS and statistical analysis. We would also like to thank Dr. Shuji Shibata for critical discussions and Ms. Masami Terauchi for assistance in performing experiments.

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