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Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice
Accepted Manuscript Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice Chao Ding, Qiang Liu, Peng Li, Yongsheng Pei, Tingting Tao, Yan Wang, Wei Yan, Guofeng Yang, Xiaolong Shao PII: DOI: Reference:
S0308-8146(18)31577-2 https://doi.org/10.1016/j.foodchem.2018.09.011 FOCH 23498
To appear in:
Food Chemistry
Received Date: Revised Date: Accepted Date:
13 February 2018 11 July 2018 2 September 2018
Please cite this article as: Ding, C., Liu, Q., Li, P., Pei, Y., Tao, T., Wang, Y., Yan, W., Yang, G., Shao, X., Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice, Food Chemistry (2018), doi: https://doi.org/10.1016/j.foodchem.2018.09.011
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Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice Chao Dinga, Qiang Liua, Peng Lia, Yongsheng Peia, Tingting Taob, Yan Wanga, Wei Yana, Guofeng Yanga, Xiaolong Shao a: College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation and Safety/Key Laboratory of Grains and Oils Quality Control and Processing, Nanjing University of Finance and Economics, No. 3 Wenyuan Road, Nanjing, Jiangsu 210023, China b: Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Corresponding author: Xiaolong Shao, Ph.D., College of Food Science and Engineering, Nanjing University of Finance and Economics, No. 3 Wenyuan Road, Nanjing, Jiangsu 210023, China Tel.: +86-13951895750; E-mail address: [email protected]
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1. Introduction Rice (Oryza sativa) is one of the world’s most important staple food especially in Asian countries (Ding et al., 2018). Milling process is crucial to bring rice to a state that is suitable for human consumption. After milling, the rice husk and bran fractions, accounting for 28% of total rough rice weight, were poorly processed for further utilization. However, rice husk and bran contain special phenolic compounds such as p-hydroxybenzonic acid, ferulic acid and other hydroxycinnamic acids (Adom and Liu, 2002). The phenolic compounds found in rice were reported to support reduction of risks associated with many diseases, such as in heart disease, Alzheimers’s disease and cancer (Adom and Liu, 2002). The extracts of rice husk and bran could offer extraordinary antioxidant activity, which is attributed to the high phenolic acids content (Chuah et al, 2005). Therefore, there is increasing public attention given to the functionality of rice by-products like husk and bran (Abubakar et al., 2016). Many special compounds such as phenolic acids, flavonoids, tocopherols and oryzanol extracted from rice bran were reported to be important for animal feeds (Norton, 1995; Sugano, Koba and Tsuji, 1999). Non-uniform distribution of phenolic compounds in rice grain could affect rice functional characteristics (Shen et al., 2009). Several studies not considering impact of rice varieties have reported on specific phenolic compounds in rice bran and husk. Vallic acid and p-coumaric acid were the most abundant phenolic compounds in rice husk, whereas ferulic and pcoumaric acids were the major species found in rice bran (Wanyo, Meeso and Siriamornpun, 2014). In contrast to the distribution of p-courmaric, ferulic acid is 2
more uniformly distributed throughout the whole endosperm. However, it was still not clear that the differences of the phenolic compounds distribution and corresponding antioxidant activity of husk, bran and endosperm fractions in rice subspecies or varieties. For detection and identification of complex compounds, liquid chromatographymass spectrometry (LC-MS) has been used as powerful tool in last few decades (Yang et al., 2015; Li et al., 2016). However, precise detection and identification of phenolic compounds in rice fractions has still been challenging for researchers. In recent years, high resolution mass spectrometry like Ultra Performance Liquid Chromatography coupled with Time of Flight Mass Spectrometry (UPLC/TOF-MS), allows for qualitative and quantitative structural analysis of compounds. The high resolution power and accuracy accorded by the mass detection can provide detailed information of compounds by eliminating the influence of background or impurity. Simultaneously, the full mass scan, multiple effective data mining methods, such as extracted ion chromatography (XIC), mass defect filtering (MDF) and product ion filtering (PIF), make it easy for identification of compounds (Ma et al., 2016). The objective of this study was to investigate the composition and distribution of the phenolic compounds, and total phenolic acid content in fractions of different Japonica and Indica rice varieties by UPLC analytical method. Corresponding antioxidant capacities of the identified compounds were further determined to evaluate the functionalities of different fractions of Japonica and Indica varieties. The analysis of phenolic compounds distribution may improve the utilization of these rice
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by-products.
2. Materials and Methods 2.1. Chemicals and Reagents Standards of p-hydroxybenzaldehyde (HD), p-hydroxyphenylacetaldehyde (HA), phydroxybenzoic acid (HHA), cinnamic acid (CIA), p-hydroxyphenylacetic acid (HAA), protocatechuic acid (PA), vanilla acid (VA), gallic acid (GA), caffeic acid (CA), ferulic acid (FA), syringic acid (SA) and kaempferol (KA) were bought from Sigma Chemical Co. (St. Louis, MO, USA). The compounds 2, 2-diphenylpicrylhydrazyl (DPPH), gallic acid, Folin-Ciocalteu’s reagents were purchased from Aladdin Industrial Co. (Shanghai, China). AB-8 macroporous adsorption resin was purchased from Chemical Plant of Nankai University (Tianjin, China). The formic acid, methanol and ethanol were LC grade and were purchased from Merck (Darmstadt, Germany). All chemicals and reagents were of analytical grade. Besides, Milli-Q deionized water was used throughout the study.
2.2. Preparation of Samples To determine the differences of phenolic compounds distribution in husk, bran and endosperm of rough rice, four Japonica rice samples (JH1, SX9, HD5 and NG46) and four Indica rice samples (ZX51, SLY1813, FLY886 and YLY316) from different regions in China were obtained to conduct this study. The details of rice samples were shown in Table 1. These rice varieties were collected from 6 different planting areas in China. The HD5(Japonica rice) and FLY886 (Indica rice) were both selected from 4
Yangzhou city while the NG46 (Japonica rice) and YLY316 (Japonica rice) were both selected from Suqian city. The two groups collected from same planting area was to reduce the effects of environmental aspects on the phenolic compounds distribution analysis of different rice subspecies. Rough rice grain was dehulled into brown rice and further milled into white rice and bran. The details for processing procedures as following: rice samples were dehulled two times to achieve husk and brown rice. Since the thickness were different with 2.3 mm and 1.9 - 2.0 mm for Japonica and Indica rice, the setting parameters for spacing rubber covered roller was 2.2 and 1.8 mm respectively. The brown rice samples were milled to obtain well-milled rice. The milling degree was defined by National Standard of People's Republic of China (GB 1354-2009, 2009): more than 90% of the rice embryo and surface in grain kernel were removed, and the dorsal groove in each kernel without bran. The obtained samples of each rice fraction were divided into two portions. One portion of husks, bran and milled rice collected separately were grounded with a high speed universal crusher (FE80, Tianjing Taisite Instrument Co. Ltd, Tianjin, China), and screened through 60 mesh for chemical compounds analyzing. Another portion was stored at -18°C for color measurement. The moisture content was measured by the weight loss criterion drying at 110°C for 24 h (Ding et al., 2015).
2.3. Solvent Extraction of Rice Fragments A total of 3.00 g each of rice husk, bran and endosperm fragments were extracted with 120 mL 80% (W:V) ethanol under reflux 50°C for 2 h, and the extraction was repeated twice. The optimized extracting condition by the ultrasonic wave instrument 5
(SB25-12DTDN, Ningbo Scientz Biotechnology Co., LTD, Ningbo, China) was determined pre-experiment as following: ultrasonic power of 600 W, ultrasonic treatment duration of 40 min, and the ultrasonic treatment temperature of 50°C. The extracts were collected and centrifuged at 18000 rpm for 10 min at 4°C by high-speed freezing centrifuge (Avanti J-E, Beckman Coulter Inc., CA, USA). The supernatant was then evaporated to dry under vacuum at 45°C by using Heidolph rotary evaporators (Hei-VAP Silver 1, Schwabach, Germany). After that, the extracts were re dissolved in methanol and then purified by AB-8 macroporous resin then eluted with 60% ethanol as crude solvent extraction (Hu et al., 2016; Wang et al., 2014).
2.4. Determination of Total Phenolic Content (TPC) The TPC of each fraction was determined spectrophotometrically by using FolinCiocalteu method with some modifications (Liu and Yao, 2007). Briefly, 150 μL of extract solution mixed with 500 μL distill water and 125 μL Folin-Ciocalteu and shaken for 6 min at 25°C, and then 1.25 mL Na2CO3 (7%, W/V, in water) and 1.00 mL distill water were added into mixture. After 90 min of reaction, the absorbance at 760 nm was determined to calculate the concentration using a calibration curve of gallic acid in the specific concentration range from 10 to 200 μg·mL-1. The calibration equation was y=0.0042x+0.0644 (R2 = 0.9997), where y was the absorbance and x was the concentration of gallic acid (GAE) mg·mL-1.
2.5. DPPH Radical Scavenging Activity The DPPH radical scavenging activity of each extract was evaluated according to the procedure by Hsu et al (2008) with slight modifications. An aliquot of 1.5 mL 6
extract was added into the prepared 1.5 mL of 150 μM DPPH solution. Then the mixed solution was stirred and avoided light for 30 min in 25°C. Then the absorbance was measured at 517 nm. A blank control sample was used as a reference. The results of scavenging effect was expressed by the following equation: Scavenging activity (%) = [(Acontrol - Asample) / Acontrol] × 100% where, Acontrol is the absorbance of control samples and Asample is the absorbance of test samples read at 517 nm.
2.6. Ferric Reducing Ability of Plasma Assay (FRAP) The FRAP assay was adopted to measure the reducing power of extracts according to the method proposed by Zhang (2009), with some modifications. Briefly, 2.5 mL of extracts was mixed with 2.5 mL phosphate buffer (0.2M, pH = 6.6) and then reacted with 2.5 mL potassium ferricyanide (1% W:V, in water) at 50°C in a dark condition for 20 min. The reaction was stopped by addition of 2.5 mL trichloroacetic acid (10%, W:V. in water), and the upper layer was collected after 15 min centrifugation at 5000 rpm. The 2.5 mL collected solution was mixed with 2.5 mL distilled water and 0.5 mL FeCl3 (0.1%, W:V, in water), and the absorbance was measured at 700 nm against blanks that were all the same, except the sample extracts.
2.7. Measurement of Sample Color The color of paddy hull and bran color was measured with a chroma meter (CR400, Konica Minolta Sensing, Tokyo, Japan). A colorimetric dish with dimensions 20 mm diameter and 10 mm height was filled with husk and rice bran, placed in colorimeter for color detection. The color values were described in terms of L*, a*, and b* color 7
space. Yellowness index (YI) was used to describe color according to Ding et al (2016); YI=142.86×b*/L*
2.8. UPLC-Triple/TOF-MS Conditions Phenolic compositions were determined by a UPLC system (LC-30A, Shimadzu, Japan) equipped with two infusion pump (LC-30AD), automatic sampler (SIL-30AC), oven (CTO-30A), system controller (CBM-20A) and a photo diode array (SPDM20A). Chromatographic separation was conducted on a column (2.0 × 150 mm i.d., 2.2μm) adapting a Shim-Pack XR-ODSIII (Shimadzu, Japan), at following condition: injection speed 0.4 mL min-1; injection volume 10 μL; column temperature 40°C; pumping mode was performed on Binary Flow; photo diode array detection at 217 nm, 280 nm and 320 nm, spectra scan from 200 nm to 700 nm, frequency 4.167 Hz. Gradient elution was performed in this experiment, one of mobile phase (solution A) was consist by formic acid with purified water (0.1%, V:V), while solution B contained by methanol. Prior to injection, the column was equilibrated for 5 min. The following gradient condition was adopt: solution B with 5% in beginning, increased to 10% in 5 min, to 80% in 10 min, holding at 80% in 3 min, back to 5% in 2 min. After then, the conditions were reestablished for 2 min. TOF-MS system was performed by a Triple-TOF-TM 5600+ (AB Sciex Pte. Ltd., Framingham, MA, USA), and operated in the ESI ion source model and negative ion scan mode. The operating conditions used were the as following: interface voltage: 3.5 kV; analysis temperature: 250°C; atomizer speed: 3.0 L·min-1; dry gas (nitrogen) 8
speed: 10 L·min-1; collision gas: argo; multiple reaction mode (MRM) scanning; 10 ms residence time and 3 ms delay time, respectively. The information dependant acquistion (IDA) criteria was adopted to obtain the MS/MS spectral. Meanwhile, the compounds were determined though the m/z values. The XIC, MDF and PIF were analyzed to describe the probable elemental composition and structural formula.
2.9. Statistical Analysis Data were expressed as mean standard deviation (SD) of triplicates. Analysis of variance (ANOVA) was carried out by JMP 10.0 software (SAS Institute Inc., Cary. NC, USA), using Duncan’s Multiple Range Test. P values <0.05 were regarded as significant and P < 0.01 were regarded as extremely significant. Principal component analysis (PCA) was performed using software (SPSS 18, Inc., Chicago, USA) to determine the characteristic for husk, bran and endosperm fractions.
3. Results and Discussion 3.1. Morphological and Physical Characteristics of Rice Fractions Morphological and color characteristics are useful for classifying paddy rice varieties (Liu et al., 2005). There are wide range of variations in the color characteristics of each rice fraction (Fig. 1a). In all the eight studied Japonica and Indica rice, the YI values of husk (70.45 ± 1.40 to 73.28 ± 1.23) were significantly higher (P < 0.05) than bran (53.42 ± 0.13 to 61.59 ± 0.40) and endosperm (27.57 ± 0.82 to 30.53 ± 0.68). For each rice variety, the L*, a*, and b* values of the husk, bran and endosperm samples were also significantly different (P < 0.05). The YI values of the husk of JH1, SX9 9
and ZX51were significantly higher than that of other five rice samples (P < 0.05). Comparing the bran and endosperm fractions of the two rice groups selected from same planting area (HD5 and FLY886, NG46 and YLY316), the YI values of Japonica rice bran and endosperm were significantly higher than that of Indica rice. The differences of YI in the same rice fraction could be due to the following reasons: The Japonica and Indica rice may have various genes, which are responsible for observed seed coloration. There are 26 genes involved in seed coloration during plant growth of which 10 genes are involved in anthocyanin coloration, and 15 genes are involved in other coloration compounds coloration, such as from proanthocyanidin (Kinoshita 1995). The Rc gene is evidenced to be responsible for the accumulation of pigments in the pericarp of seeds (Nagao et al. 1957).
3.2. Total Phenolic Content The TPC of husk, bran and endosperm of different rice varieties are shown in Fig. 1b. There were significant differences (P < 0.05) for TPC content in three fractions of rice. Rice husk, contains TPC ranging from 2.23 ± 0.13 to 3.62 ± 0.05 mg GAE·g-1; this was significantly lower than in rice bran (3.57 ± 0.28 to 6.78 ± 0.13 mg GAE·g-1) but significantly higher than in endosperm (0.43 ± 0.07 to 0.93 ± 0.07 mg GAE·g-1) (P < 0.05). Among the TPC of the eight studied varieties, the JH1 rice variety had the highest TPC in bran (6.78 ± 0.13 mg GAE·g-1) and endosperm (0.93 ± 0.07 mg GAE·g-1) fractions while the SX9 rice variety had the highest TPC in husk. For same rice variety, bran and husk fractions provided more than 90% of phenolic compounds of the whole rice. Comparing the Japonica and Indica rice planted in same area, the 10
average TPCs of husk, bran and endosperm in Japonica rice were significantly higher than that in Indica rice (P < 0.05). Rc and Rd genes in rice may affect the proanthocyanidin synthesis during growth period (Furukawa et al., 2007). Moreover, different rice varieties and soil properties at rice planting area might also influence the TPC of rice kernel. Phenolic compounds in rice could be existed in free, esterified and insoluble-bound forms, which may cause the TPC diversities of different rice species or varieties (Shen et al., 2009).
3.3. Evaluation of the Antioxidant Activity in Rice Fractions
3.3.1. DPPH Radical Scavenging Ability The antioxidant abilities of rice fractions were worthy investigating because of the significant variation phenolic acid content and type of compounds in husk, bran and endosperm. The DPPH radical scavenging ability method is widely used to evaluate the free radical scavenging activity of antioxidant (Jiao et al., 2012). The inhibition abilities of DPPH radical by different rice fractions were shown in Fig. 1c. The radical scavenging abilities of extracts from rice husk, bran and endosperm ranged from 54.34 to 59.62%, 73.09 to 78.82% and 33.48 to 38.92%, respectively. The order of the DPPH inhibition activity of rice fractions was endosperm < husk < bran, and the difference between each of the two fractions was extremely significant (P < 0.01). For same rice fractions, the DPPH inhibition abilities of Japonica and Indica rice were not significant different. It revealed that the radical scavenging activities of Japonica and Indica rice were in same level.
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3.3.2. FRAP assay FRAP method measured the ability of Fe3+ transformation to Fe2+ at low pH (Benzie and Strain, 1996). The reducing power was based on measuring the formation of Perl’s Prussian blue at 700 nm (Hu et al., 2016). The distribution of reducing power among different rice fraction from the eight varieties is shown in Fig. 1d. The reducing power of three fractions were observed as follows: endosperm (0.18 ± 0.01 to 0.22 ± 0.01 ABS) < husk (0.81 ± 0.03 to 1.18 ± 0.05 ABS) < bran (1.05 ± 0.03 to 1.64 ± 0.04 ABS). It was obviously showed that the rice bran gave higher reducing power than that of other fractions. Meanwhile, with regard to specific varieties, the reducing power of bran fraction decreased in the following order: SLY1813 < YLY316 0.05). For same rice variety, bran and husk fractions contributed to more than 90% of antioxidant ability of whole rice. Correlation analysis revealed that the antioxidant ability of husk and bran extracts under acidic condition were strongly correlated to the corresponding TPC amounts, which were in agreement with the findings proposed by Liyana-Pathirana and Shahidi (2007).
3.4. Identification and Quantification of Phenolic Compounds in Rice Fractions 12
In total, 12 phenolic compounds were identified from the crude solvent extracts of different rice fractions of the 8 rice varieties. The details of [M-H]-, MS/MS fragments and formula of each identified phenolic compound were listed in Table 2. The formula and structure of each compound or derivative were obtained and analyzed based on the data for tR (retention time) molecular ion and fragmentations, and is listed in Fig. 2. The quantity of the identified 12 compounds were then determined from the intensity information by comparing with the literature and pure standards. The molecular mass of No.1 and No. 2 compounds were detected at m/z [M-H]121.0350 and 135.0453, respectively. This two peaks can be identified as the phydroxybenzaldehyde (HD) and p-hydroxyphenylacetaldehyde (HA) with the reference standard. Other fragments m/z [MS/MS] were at 93 also observed from No. 3 and No.9, which were identified as p-hydroxybenzoic acid (HHA) and caffeic acid (CA) (Mellegård et al., 2009). These four of compounds (HD, HA, HHA and CA) it rarely reported in rice husk, bran and endosperm previously. Compound No. 6 and 10 with [M-H]- at 153.0195 and 178.9769 m/z, were defined as protocatechuic acid (PA) and ferulic acid (FA) compounds respectively. Similar results for the fragment of ions at 109.03 and 134.04 and 133.03 m/z were reported by Wang et al (2014). Vanilla acid (VA), gallic acid (GA) and syringic acid (SA) were detected in husk, bran and endosperm fractions of the all eight rice varieties, which were widely accepted as important antioxidant substance (Ferreira, Barros and Abreu, 2009).
3.5 Distribution of Phenolic Compounds in Different Fractions of Four Rice Varieties Phenolic compounds in rice husk, bran and endosperm of Japonica rice (JH1, SX9, 13
HD5 and NG46) and Indica rice (ZX51, SLY1813, FLY886 and YLY316) were shown in Table 3. In husk fraction, the most abundant phenolic compounds were HD, GA, PA and FA, with quantity ranging 14.46 to 23.72 μg·g-1, 3.44 to 9.56 μg·g-1, 2.06 to 4.54 μg·g-1 and 1.58 to 13.97 μg·g-1, respectively. The FA, PA and SA were the most abundant three phenolic compounds in all bran fractions, with quantities ranging from 5.14 to 16.07 μg·g-1, from 5.89 to 9.03 μg·g-1 and 4.89 to 8.76 μg·g-1, respectively. The FA and PA were also the dominant phenolic compounds in endosperm, ranging from 1.35 to 2.24 μg·g-1 and 1.27 to 2.38 μg·g-1, respectively. However, the amounts were significantly lower than in bran (P < 0.05). Interestingly, KA was the only detected phenolic compounds in bran with a concentration lower than 1.00 μg·g-1. The CA was not detected in endosperm of all rice varieties. Similar result also reported by Wanyo et al (2014). The concentration of phenolic acid in rice bran are much higher than in milled rice or endosperm (Zhou et al., 2004), and phenolic acids content in rice husk were also detected and higher than that in bran and endosperm fractions (Butsat and Siriamornpun, 2010). However, there are few reports for phenolic compounds analyzing in grains, and also lack of investigation considering different rice subspecies or varieties. It was worth to notice that HD was the most dominant phenolic compounds in the husk, although this may be inconsistent with other reports (Wanyo et al., 2014; Zhou et al., 2004). In these previous studies, only one rice variety was selected for identification of the antioxidant capacities and phenolic acids in different rice fractions. Rice varieties might also contributed to this difference by specified gene
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expression (Furukawa et al., 2007). Moreover, HD with a aldehyde group might be an intermediate compounds in the phenolic compounds reactions in rice fractions. For total phenolic compounds, HA, HHA, CIA, HAA, PA and SA in husk fraction were higher than the endosperm, and lower than in bran fraction. On the other hand, total amount of FA in all fractions were much higher than other phenolic acids, which may be caused by arabinoxylan in cell walls of aleurone layer and husk (Mckeehen, Busch and Fulcher, 1999). Some phenolic compounds (PA, GA and FA) in JH1 and NG46 husk fractions were higher than other rice varieties. It means that the specified husk could be used to extract phenolic acids (Butsat and Siriamornpun, 2010). Remarkable, the HD content in rice husk (14.46 to 23.72 μg·g-1) was higher than that in bran (0.21 to 1.07 μg·g-1) and endosperm (0.33 to 0.68 μg·g-1). The phenolic compounds content in rice husk could be greater than previous research reported (Abubakaret al., 2016; Liu, 2007). Fig. 3 showed the score plot of principal component analysis (PCA) applied to rice fractions by using contents of the identified phenolic compounds. The first two principal compounds accounted for 70.35% and 18.31% of loading score, respectively. Apparently, the scores of PC1 and PC2 from husk, bran and endosperm segment were clearly separated with each other; this suggested that content of phenolic compounds are significantly different in the three fractions of rough rice (husk, bran and endosperm). Based on the Fig. 3, the scatter of the husk and bran were higher than endosperm; this may mainly be caused by the significant differences of HD content in the three fractions, which was influenced by the varieties of the rice
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(Table 3). The three different fractions can be isolated based on content of phenolic compounds. Comparing the different rice subspecies, the amount of HD and FA in husk and bran of Japonica rice were significantly higher than that of Indica rice (P < 0.05), while the amount of HA in bran of Indica rice was significantly higher than that of Japonica rice (P < 0.05). The amounts of other 9 phenolic compounds existed in same fraction of Japonica and Indica rice were in same level. However, for the endosperm fraction, limited difference in all phenolic compounds came from Japonica and Indica rice. This was mainly because phenolic compounds were abundant in husk and bran fraction, the content of each phenolic compound rarely distributed in rice endosperm.
4. Conclusion The distribution of phenolic compounds and antioxidant activity of husk, bran and endosperm in four Japonica rice and four Indica rice were investigated in this research. Highest YI value (husk 72.84 ± 0.90, bran 61.59 ± 0.40, endosperm 30.34 ± 0.44) were found in JH1 amongst the 8 studied rice varieties. Twelve phenolic compounds in rice (p-hydroxybenzaldehyde, p-hydroxyphenylacetaldehyde, phydroxybenzoic acid, cinnamic acid, p-hydroxyphenylacetic acid, protocatechuic acid, vanilla acid, gallic acid, caffeic acid, ferulic acid, syringic acid and kaempferol) were identified from the fraction extracts. Ferulic acid, gallic acid, protocatechuic acid and syringic acid were the dominant phenolic compounds in rice bran, while pHydroxybenzaldehyde was the main phenolic compounds existed in rice husk (14.4616
23.72 μg·g-1). For same rice variety, more than 90% of phenolic compounds existed in bran and husk fractions and provide strong antioxidant ability. Bran and husk fractions can also provide corresponding more than 90% of antioxidant activity of the whole rice. By contrast, Japonica rice has significant higher phenolic compounds and antioxidant activity than Indica rice (P < 0.05). Therefore, the distribution of phenolic compounds were strongly correlated with the rice varieties and fractions. The analysis of phenolic compounds distribution in rice bran and husk may give a great potential for further utilization in food and allied industries.
Acknowledgments The authors wish to acknowledge and thank the projects funding by the National Key Research and Development Program of China (2017YFD0401403), National Natural Science Foundation of China (31601402), the Natural Science Foundation of the Colleges and Universities in Jiangsu Province (16KJB550004), the Independent Innovation Fund Project for Agricultural Science and Technology of Jiangsu (CX(17)100205), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
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Liu, Q., & Yao, H. (2007). Antioxidant activities of barley seeds extracts. Food Chemistry, 102(3), 732-737. Liu, R. H. (2007). Whole grain phytochemicals and health. Journal of Cereal Science, 46(3), 207-219. Liyana-Pathirana, C. M., & Shahidi, F. (2007). Antioxidant and free radical scavenging activities of whole wheat and milling fractions. Food Chemistry, 101(3), 1151-1157. Ma, Y., Xie, W., Tian, T., Jin, Y., Xu, H., Zhang, K., & Du, Y. (2016). Identification and comparative oridonin metabolism in different species liver microsomes by using UPLC-Triple-TOF-MS/MS and PCA. Analytical Biochemistry, 511, 61-73. Mckeehen, J. D., Busch, R. H., & Fulcher, R. G. (1999). Evaluation of Wheat (Triticum aestivum L.) Phenolic acids during grain development and their contribution to fusarium resistance. Journal of Agricultural & Food Chemistry, 47(4), 1476-1482. Mellegård, H., Stalheim, T., Hormazabal, V., Granum, P. E., & Hardy, S. P. (2009). Antibacterial activity of sphagnum acid and other phenolic compounds found in Sphagnum papillosum against food-borne bacteria. Letters in Applied Microbiology, 49(1), 85-90. Nagao, S., Takahashi, M., & Miyamoto, T. (1957). Genetical studies on rice plant, XXI biochemical studies on red rice pigmentation. Japanese Journal of Genetics, 32, 124-128. Norton, R. A. (1995). Quantitation of steryl ferulate and p-coumarate esters from corn and rice. Lipids, 30(3), 269-274. Shen, Y., Jin, L., Xiao, P., Lu, Y., & Bao, J. (2009). Total phenolics, flavonoids, antioxidant capacity in rice grain and their relations to grain color, size and weight. Journal of Cereal Science, 49(1), 106-111. Yang, S., Zhang, H., Beier, R. C., Sun, F., Cao, X., Shen, J. Wang Z., & Zhang S. (2015). Comparative metabolism of Lappaconitine in rat and human liver microsomes and in vivo of rat using ultra high-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry. Journal of Pharmaceutical & Biomedical Analysis, 110, 1-11. Sugano, M., Koba, K., & Tsuji, E. (1999). Health benefits of rice bran oil. Anticancer Research, 19(5A), 3651-3657. Wang, X., Li, W., Ma, X., Chu, Y., Li, S., Guo, J., Jia, Y., Zhou, S., Zhu, Y., & Liu, C. (2014). Simultaneous determination of caffeic acid and its major pharmacologically active metabolites in rat plasma by LC-MS/MS and its application in pharmacokinetic study. Biomedical Chromatography, 29(4), 552559. Wanyo, P., Meeso, N., & Siriamornpun, S. (2014). Effects of different treatments on the antioxidant properties and phenolic compounds of rice bran and rice husk. Food Chemistry, 157(157), 457-463. Zhang, Q. F., Zhang, Z. R., & Cheung, H. (2009). Antioxidant activity of Rhizoma Smilacis Glabrae extracts and its key constituent-astilbin. Food Chemistry, 115(1), 297-303. Zhou, Z., Robards, K., Helliwell, S., & Blanchard, C. (2004). The distribution of 19
phenolic acids in rice. Food Chemistry, 87(3), 401-406.
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Figure legends:
Fig. 1. Descriptive statistics for yellowness index (a), total phenolic compounds (b), DPPH radical scavenging ability (c) and FRAP assay (d) of three fractions (husk, bran and endosperm) in four Japonica rice (JH1, SX9, HD5 and NG46) and four Indica rice (ZX51, SLY1813, FLY886 and YLY316). Vertical line on the top of columns represented error bars, different letters upon each column identified statistically different (P < 0.05) data; TPC means total phenolic compounds. Fig. 2. Extraction ion chromatograms for 12 sub-fraction of bran from ZX51 by UPLC-Triple/TOF - MS chromatograms. No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). Fig. 3. Principal component analysis of phenolic compounds contents in different rice fractions of eight rice varieties. (husk-green (■); bran-red (◆); endosperm-black (●)). Table legends: Table 1. Details of eight rice samples used in experiment. Table 2. Phenolic compounds in rice fractions identified by UPLC-Triple/TOF-MS.
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Table 3. Distribution (μg·g-1) of phenolic compounds in different fractions of eight rice varieties. Nd means not detected; Tr means trace amount (lower than 0.01μg·g-1). Different letters behind numbers in same column were mean significantly different (P < 0.05) No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). subsp. Japonica rice (JH1, SX9, HD5 and NG46); subsp. Indica rice (ZX51, SLY1813, FLY886 and YLY316) Table 1 Details of eight rice samples used in experiment Variety
Type
Sites Location
Size (length × wideth ×
Thousand
thickness)
weight
content
(mm)
(g)
(% w.b.)
subsp.
32°65’N,
7.9(±0.3) × 3.4(±0.1) ×
Japonica
119°07’E
2.3( ± 0.1)
subsp.
32°30’N,
7.4(±0.4) × 3.3(±0.3) ×
Japonica
118°47’E
2.3( ± 0.1)
subsp.
32°35’N,
7.7(±0.2) × 3.3(±0.2) ×
Japonica
118°83’E
2.3( ± 0.1)
subsp.
33°60’N,
7.3(±0.4) × 3.3(±0.1) ×
Japonica
119°02’E
2.3( ± 0.1)
subsp.
28°96’N,
9.2(±0.5) ×2.2(±0.1) ×
rice)
Indica
111°98’E
1.9 ( ± 0.1)
SLY1813 (white
subsp.
30°55’N,
8.7(±0.6) ×2.4(±0.1) ×
rice)
Indica
116°94’E
2.0 (±0.1)
FLY886 (white
subsp.
32°35’N,
9.1(±0.6) ×2.2(±0.1) ×
rice)
Indica
118°83’E
1.9 ( ± 0.1)
YLY316 (white
subsp.
33°60’N,
9.2(±0.6) ×2.3(±0.1) ×
rice)
Indica
119°02’E
1.9 (±0.1)
JH1 (white rice)
SX9 (white rice) HD5
(white
rice) NG46
(white
rice) ZX51
(white
25.8 ± 0.3
25.0 ± 0.1
25.1 ± 0.2
25.0 ± 0.2
21.4 ± 0.2
25.3 ± 0.3
24.8 ± 0.2
25.0 ± 0.3
grain
Moisture
14.0
±
0.2% 14.0
±
0.3% 14.0
±
0.3% 14.0
±
0.3% 13.5
±
0.4% 13.5
±
0.3% 13.5
±
0.3% 13.5
±
0.3%
22
`
23
Table 2 Phenolic compounds in rice fractions identified by UPLC-Triple/TOF-MS Number
Identification
Formula
tR
[M-H]-
Error
MS/MS
min
m/z
ppm
m/z
1
HD
C7H6O2
3.81
121.0305
3.3
93.0366; 92.0281
2
HA
C8H8O2
4.41
135.0453
8.2
93.0370; 92.0277; 91.7364
3
HHA
C7H6O3
3.35
137.0252
2.2
93.0369; 65.0420
4
CIA
C9H8O2
5.35
147.0454
9.3
129.0286; 119.0515; 117.0326; 61.9900;
Structural formula
58.9805 5
HAA
C8H8O3
4.29
151.0402
9.8
136.0155; 122.0374; 108.0215; 92.0267
6
PA
C7H6O4
3.49
153.0195
8.4
135.0087; 109.0316; 65.0395; 67.0194
7
VA
C8H8O4
3.90
167.0344
10.8
152.0098
8
GA
C7H6O5
12.94
169.0870
7.9
123.0837; 83.0513
9
CA
C9H8O4
5.37
178.9769
10.1
136.0175;135.0468; 34.9920; 93.0378; 92.0254; 91.0001; 84.9913
10
FA
C10H10O
5.46
193.0507
2.7
178.0268; 149.0571; 134.0357; 133.0292
4
11
SA
C9H10O5
1.14
197.8086
1.3
162.8394; 160.8421
12
KA
C15H10O
4.43
285.0604
13.2
217.1021; 197.0443; 182.0222; 150.0366; 123.0095; 121.0286
tR means retention time; No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA).
24
Table 3 Distribution (μg·g-1) of phenolic compounds in different fractions of eight rice varieties. Variety JH1
SX9
HD5
NG46
ZX51
SLY1813
FLY886
YLY316
Rice
HD
HA
HHA
CIA
HAA
PA
VA
GA
Husk
23.72±2.62a
0.13±0.01a
0.19±0.05a
0.88±0.06a
0.28±0.02a
3.16±0.58cd
3.71±0.34a
5.26
Bran
1.07±1.07c
0.75±0.03c
3.33±0.29d
2.53±0.17c
1.65±0.12d
8.86±0.84a
3.07±0.02b
14.7
Endosperm
0.39±0.22c
Nd
0.13±0.07a
Tr
Nd
1.28±0.02e
0.82±0.03c
1.35
Husk
18.06±0.53b
0.12±0.01a
0.09±0.02a
0.84±0.03a
0.28±0.01a
4.54±0.90bc
3.06±0.39b
7.56
Bran
0.61±0.06c
0.59±0.01b
1.59±0.10b
2.49±0.20c
0.70±0.04b
5.89±0.78b
2.74±0.07b
9.81
Endosperm
0.70±0.11c
Nd
Nd
Tr
Nd
2.38±0.01e
0.80±0.01c
0.98
Husk
19.03±0.78b
0.1±0.02a
0.23±0.06a
1.00±0.59ab
0.20±0.05a
3.78±1.03cd
3.12±0.55ab
7.71
Bran
0.51±0.10c
0.55±0.10b
2.58±0.47c
2.48±0.23c
0.64±0.10b
8.02±0.56a
3.09±0.22b
13.3
Endosperm
0.40±0.08c
Nd
Nd
Nd
Nd
1.77±0.70e
0.81±0.04c
1.20
Husk
18.94±1.89b
0.10±0.05a
0.15±0.05a
0.99±0.23a
0.18±0.04a
3.23±0.66cd
3.66±0.10a
6.98
Bran
0.37±0.08c
0.42±0.09b
2.30±0.67c
2.52±0.44c
1.03±0.45c
7.95±0.39a
3.11±0.10b
15.6
Endosperm
0.77±0.12c
Nd
Nd
Nd
Nd
2.77±0.50d
0.83±0.01c
1.00
Husk
14.46±0.11b
0.19±0.02a
0.13±0.01a
1.22±0.16ab
0.24±0.03
2.22±0.03de
3.12±0.20b
3.69
Bran
0.31±0.04c
1.64±0.04d
2.28±0.09c
2.08±0.23c
0.83±0.09b
8.75±0.40a
3.09±0.11b
14.5
Endosperm
0.68±0.42c
Tr
Tr
Nd
Nd
1.27±0.01e
0.82±0.02c
2.59
Husk
15.28±0.48b
0.16±0.01a
0.11±0.04a
0.98±0.06a
0.19±0.02a
2.06±0.04de
3.75±0.02a
3.44
Bran
0.21±0.05c
2.24±0.09e
2.35±0.15c
1.88±0.47c
1.10±0.07c
8.98±0.72a
3.05±0.03b
14.9
Endosperm
0.33±0.02c
0.08±0.04a
Tr
Nd
Nd
1.27±0.01e
0.80±0.02c
3.48
Husk
14.78±0.15b
0.20±0.06a
0.13±0.05a
1.16±0.25ab
0.14±0.10a
2.23±0.20de
3.32±0.22b
4.23
Bran
0.48±0.22c
1.87±0.32de
2.45±0.78c
2.22±0.13c
1.23±0.44c
9.03±0.23a
3.45±0.38ab
13.5
Endosperm
0.78±0.12c
Nd
Nd
Nd
Nd
1.44±0.24e
0.77±0.04c
3.56
Husk
16.34±0.21b
0.42±0.06b
0.24±0.14a
1.34±0.32ab
Tr
2.55±0.77de
3.88±0.12a
3.89
Bran
0.65±0.34c
1.42±0.67d
1.49±0.54b
2.56±0.45c
1.03±0.21c
8.01±0.77a
3.00±0.11b
15.8
Endosperm
0.37±0.15c
Nd
Nd
Nd
Nd
1.33±0.09e
0.82±0.04c
4.01
fraction
Nd means not detected; Tr means trace amount (lower than 0.01
μg·g-1).
Different letters behind numbers in same column were mean significantly different (P < 0.05) No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: p-Hydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). subsp. Japonica rice (JH1, SX9, HD5 and NG46); subsp. Indica rice (ZX51, SLY1813, FLY886 and YLY316)
Highlights:
Twelve main phenolic compounds (PC) were identified in different rice varieties. Bran and husk provide more than 90% of PC and antioxidant activity of whole rice. Ferulic acid, gallic acid and protocatechuic acid were the highest 3 PCs in rice bran. P-Hydroxybenzaldehyde was the main PC existed in rice husk (14.46-23.72 μg·g-1). Japonica rice has significant higher PC and antioxidant activity than Indica rice.
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S0308-8146(18)31577-2 https://doi.org/10.1016/j.foodchem.2018.09.011 FOCH 23498
To appear in:
Food Chemistry
Received Date: Revised Date: Accepted Date:
13 February 2018 11 July 2018 2 September 2018
Please cite this article as: Ding, C., Liu, Q., Li, P., Pei, Y., Tao, T., Wang, Y., Yan, W., Yang, G., Shao, X., Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice, Food Chemistry (2018), doi: https://doi.org/10.1016/j.foodchem.2018.09.011
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Distribution and quantitative analysis of phenolic compounds in fractions of Japonica and Indica rice Chao Dinga, Qiang Liua, Peng Lia, Yongsheng Peia, Tingting Taob, Yan Wanga, Wei Yana, Guofeng Yanga, Xiaolong Shao a: College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation and Safety/Key Laboratory of Grains and Oils Quality Control and Processing, Nanjing University of Finance and Economics, No. 3 Wenyuan Road, Nanjing, Jiangsu 210023, China b: Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Corresponding author: Xiaolong Shao, Ph.D., College of Food Science and Engineering, Nanjing University of Finance and Economics, No. 3 Wenyuan Road, Nanjing, Jiangsu 210023, China Tel.: +86-13951895750; E-mail address: [email protected]
1
1. Introduction Rice (Oryza sativa) is one of the world’s most important staple food especially in Asian countries (Ding et al., 2018). Milling process is crucial to bring rice to a state that is suitable for human consumption. After milling, the rice husk and bran fractions, accounting for 28% of total rough rice weight, were poorly processed for further utilization. However, rice husk and bran contain special phenolic compounds such as p-hydroxybenzonic acid, ferulic acid and other hydroxycinnamic acids (Adom and Liu, 2002). The phenolic compounds found in rice were reported to support reduction of risks associated with many diseases, such as in heart disease, Alzheimers’s disease and cancer (Adom and Liu, 2002). The extracts of rice husk and bran could offer extraordinary antioxidant activity, which is attributed to the high phenolic acids content (Chuah et al, 2005). Therefore, there is increasing public attention given to the functionality of rice by-products like husk and bran (Abubakar et al., 2016). Many special compounds such as phenolic acids, flavonoids, tocopherols and oryzanol extracted from rice bran were reported to be important for animal feeds (Norton, 1995; Sugano, Koba and Tsuji, 1999). Non-uniform distribution of phenolic compounds in rice grain could affect rice functional characteristics (Shen et al., 2009). Several studies not considering impact of rice varieties have reported on specific phenolic compounds in rice bran and husk. Vallic acid and p-coumaric acid were the most abundant phenolic compounds in rice husk, whereas ferulic and pcoumaric acids were the major species found in rice bran (Wanyo, Meeso and Siriamornpun, 2014). In contrast to the distribution of p-courmaric, ferulic acid is 2
more uniformly distributed throughout the whole endosperm. However, it was still not clear that the differences of the phenolic compounds distribution and corresponding antioxidant activity of husk, bran and endosperm fractions in rice subspecies or varieties. For detection and identification of complex compounds, liquid chromatographymass spectrometry (LC-MS) has been used as powerful tool in last few decades (Yang et al., 2015; Li et al., 2016). However, precise detection and identification of phenolic compounds in rice fractions has still been challenging for researchers. In recent years, high resolution mass spectrometry like Ultra Performance Liquid Chromatography coupled with Time of Flight Mass Spectrometry (UPLC/TOF-MS), allows for qualitative and quantitative structural analysis of compounds. The high resolution power and accuracy accorded by the mass detection can provide detailed information of compounds by eliminating the influence of background or impurity. Simultaneously, the full mass scan, multiple effective data mining methods, such as extracted ion chromatography (XIC), mass defect filtering (MDF) and product ion filtering (PIF), make it easy for identification of compounds (Ma et al., 2016). The objective of this study was to investigate the composition and distribution of the phenolic compounds, and total phenolic acid content in fractions of different Japonica and Indica rice varieties by UPLC analytical method. Corresponding antioxidant capacities of the identified compounds were further determined to evaluate the functionalities of different fractions of Japonica and Indica varieties. The analysis of phenolic compounds distribution may improve the utilization of these rice
3
by-products.
2. Materials and Methods 2.1. Chemicals and Reagents Standards of p-hydroxybenzaldehyde (HD), p-hydroxyphenylacetaldehyde (HA), phydroxybenzoic acid (HHA), cinnamic acid (CIA), p-hydroxyphenylacetic acid (HAA), protocatechuic acid (PA), vanilla acid (VA), gallic acid (GA), caffeic acid (CA), ferulic acid (FA), syringic acid (SA) and kaempferol (KA) were bought from Sigma Chemical Co. (St. Louis, MO, USA). The compounds 2, 2-diphenylpicrylhydrazyl (DPPH), gallic acid, Folin-Ciocalteu’s reagents were purchased from Aladdin Industrial Co. (Shanghai, China). AB-8 macroporous adsorption resin was purchased from Chemical Plant of Nankai University (Tianjin, China). The formic acid, methanol and ethanol were LC grade and were purchased from Merck (Darmstadt, Germany). All chemicals and reagents were of analytical grade. Besides, Milli-Q deionized water was used throughout the study.
2.2. Preparation of Samples To determine the differences of phenolic compounds distribution in husk, bran and endosperm of rough rice, four Japonica rice samples (JH1, SX9, HD5 and NG46) and four Indica rice samples (ZX51, SLY1813, FLY886 and YLY316) from different regions in China were obtained to conduct this study. The details of rice samples were shown in Table 1. These rice varieties were collected from 6 different planting areas in China. The HD5(Japonica rice) and FLY886 (Indica rice) were both selected from 4
Yangzhou city while the NG46 (Japonica rice) and YLY316 (Japonica rice) were both selected from Suqian city. The two groups collected from same planting area was to reduce the effects of environmental aspects on the phenolic compounds distribution analysis of different rice subspecies. Rough rice grain was dehulled into brown rice and further milled into white rice and bran. The details for processing procedures as following: rice samples were dehulled two times to achieve husk and brown rice. Since the thickness were different with 2.3 mm and 1.9 - 2.0 mm for Japonica and Indica rice, the setting parameters for spacing rubber covered roller was 2.2 and 1.8 mm respectively. The brown rice samples were milled to obtain well-milled rice. The milling degree was defined by National Standard of People's Republic of China (GB 1354-2009, 2009): more than 90% of the rice embryo and surface in grain kernel were removed, and the dorsal groove in each kernel without bran. The obtained samples of each rice fraction were divided into two portions. One portion of husks, bran and milled rice collected separately were grounded with a high speed universal crusher (FE80, Tianjing Taisite Instrument Co. Ltd, Tianjin, China), and screened through 60 mesh for chemical compounds analyzing. Another portion was stored at -18°C for color measurement. The moisture content was measured by the weight loss criterion drying at 110°C for 24 h (Ding et al., 2015).
2.3. Solvent Extraction of Rice Fragments A total of 3.00 g each of rice husk, bran and endosperm fragments were extracted with 120 mL 80% (W:V) ethanol under reflux 50°C for 2 h, and the extraction was repeated twice. The optimized extracting condition by the ultrasonic wave instrument 5
(SB25-12DTDN, Ningbo Scientz Biotechnology Co., LTD, Ningbo, China) was determined pre-experiment as following: ultrasonic power of 600 W, ultrasonic treatment duration of 40 min, and the ultrasonic treatment temperature of 50°C. The extracts were collected and centrifuged at 18000 rpm for 10 min at 4°C by high-speed freezing centrifuge (Avanti J-E, Beckman Coulter Inc., CA, USA). The supernatant was then evaporated to dry under vacuum at 45°C by using Heidolph rotary evaporators (Hei-VAP Silver 1, Schwabach, Germany). After that, the extracts were re dissolved in methanol and then purified by AB-8 macroporous resin then eluted with 60% ethanol as crude solvent extraction (Hu et al., 2016; Wang et al., 2014).
2.4. Determination of Total Phenolic Content (TPC) The TPC of each fraction was determined spectrophotometrically by using FolinCiocalteu method with some modifications (Liu and Yao, 2007). Briefly, 150 μL of extract solution mixed with 500 μL distill water and 125 μL Folin-Ciocalteu and shaken for 6 min at 25°C, and then 1.25 mL Na2CO3 (7%, W/V, in water) and 1.00 mL distill water were added into mixture. After 90 min of reaction, the absorbance at 760 nm was determined to calculate the concentration using a calibration curve of gallic acid in the specific concentration range from 10 to 200 μg·mL-1. The calibration equation was y=0.0042x+0.0644 (R2 = 0.9997), where y was the absorbance and x was the concentration of gallic acid (GAE) mg·mL-1.
2.5. DPPH Radical Scavenging Activity The DPPH radical scavenging activity of each extract was evaluated according to the procedure by Hsu et al (2008) with slight modifications. An aliquot of 1.5 mL 6
extract was added into the prepared 1.5 mL of 150 μM DPPH solution. Then the mixed solution was stirred and avoided light for 30 min in 25°C. Then the absorbance was measured at 517 nm. A blank control sample was used as a reference. The results of scavenging effect was expressed by the following equation: Scavenging activity (%) = [(Acontrol - Asample) / Acontrol] × 100% where, Acontrol is the absorbance of control samples and Asample is the absorbance of test samples read at 517 nm.
2.6. Ferric Reducing Ability of Plasma Assay (FRAP) The FRAP assay was adopted to measure the reducing power of extracts according to the method proposed by Zhang (2009), with some modifications. Briefly, 2.5 mL of extracts was mixed with 2.5 mL phosphate buffer (0.2M, pH = 6.6) and then reacted with 2.5 mL potassium ferricyanide (1% W:V, in water) at 50°C in a dark condition for 20 min. The reaction was stopped by addition of 2.5 mL trichloroacetic acid (10%, W:V. in water), and the upper layer was collected after 15 min centrifugation at 5000 rpm. The 2.5 mL collected solution was mixed with 2.5 mL distilled water and 0.5 mL FeCl3 (0.1%, W:V, in water), and the absorbance was measured at 700 nm against blanks that were all the same, except the sample extracts.
2.7. Measurement of Sample Color The color of paddy hull and bran color was measured with a chroma meter (CR400, Konica Minolta Sensing, Tokyo, Japan). A colorimetric dish with dimensions 20 mm diameter and 10 mm height was filled with husk and rice bran, placed in colorimeter for color detection. The color values were described in terms of L*, a*, and b* color 7
space. Yellowness index (YI) was used to describe color according to Ding et al (2016); YI=142.86×b*/L*
2.8. UPLC-Triple/TOF-MS Conditions Phenolic compositions were determined by a UPLC system (LC-30A, Shimadzu, Japan) equipped with two infusion pump (LC-30AD), automatic sampler (SIL-30AC), oven (CTO-30A), system controller (CBM-20A) and a photo diode array (SPDM20A). Chromatographic separation was conducted on a column (2.0 × 150 mm i.d., 2.2μm) adapting a Shim-Pack XR-ODSIII (Shimadzu, Japan), at following condition: injection speed 0.4 mL min-1; injection volume 10 μL; column temperature 40°C; pumping mode was performed on Binary Flow; photo diode array detection at 217 nm, 280 nm and 320 nm, spectra scan from 200 nm to 700 nm, frequency 4.167 Hz. Gradient elution was performed in this experiment, one of mobile phase (solution A) was consist by formic acid with purified water (0.1%, V:V), while solution B contained by methanol. Prior to injection, the column was equilibrated for 5 min. The following gradient condition was adopt: solution B with 5% in beginning, increased to 10% in 5 min, to 80% in 10 min, holding at 80% in 3 min, back to 5% in 2 min. After then, the conditions were reestablished for 2 min. TOF-MS system was performed by a Triple-TOF-TM 5600+ (AB Sciex Pte. Ltd., Framingham, MA, USA), and operated in the ESI ion source model and negative ion scan mode. The operating conditions used were the as following: interface voltage: 3.5 kV; analysis temperature: 250°C; atomizer speed: 3.0 L·min-1; dry gas (nitrogen) 8
speed: 10 L·min-1; collision gas: argo; multiple reaction mode (MRM) scanning; 10 ms residence time and 3 ms delay time, respectively. The information dependant acquistion (IDA) criteria was adopted to obtain the MS/MS spectral. Meanwhile, the compounds were determined though the m/z values. The XIC, MDF and PIF were analyzed to describe the probable elemental composition and structural formula.
2.9. Statistical Analysis Data were expressed as mean standard deviation (SD) of triplicates. Analysis of variance (ANOVA) was carried out by JMP 10.0 software (SAS Institute Inc., Cary. NC, USA), using Duncan’s Multiple Range Test. P values <0.05 were regarded as significant and P < 0.01 were regarded as extremely significant. Principal component analysis (PCA) was performed using software (SPSS 18, Inc., Chicago, USA) to determine the characteristic for husk, bran and endosperm fractions.
3. Results and Discussion 3.1. Morphological and Physical Characteristics of Rice Fractions Morphological and color characteristics are useful for classifying paddy rice varieties (Liu et al., 2005). There are wide range of variations in the color characteristics of each rice fraction (Fig. 1a). In all the eight studied Japonica and Indica rice, the YI values of husk (70.45 ± 1.40 to 73.28 ± 1.23) were significantly higher (P < 0.05) than bran (53.42 ± 0.13 to 61.59 ± 0.40) and endosperm (27.57 ± 0.82 to 30.53 ± 0.68). For each rice variety, the L*, a*, and b* values of the husk, bran and endosperm samples were also significantly different (P < 0.05). The YI values of the husk of JH1, SX9 9
and ZX51were significantly higher than that of other five rice samples (P < 0.05). Comparing the bran and endosperm fractions of the two rice groups selected from same planting area (HD5 and FLY886, NG46 and YLY316), the YI values of Japonica rice bran and endosperm were significantly higher than that of Indica rice. The differences of YI in the same rice fraction could be due to the following reasons: The Japonica and Indica rice may have various genes, which are responsible for observed seed coloration. There are 26 genes involved in seed coloration during plant growth of which 10 genes are involved in anthocyanin coloration, and 15 genes are involved in other coloration compounds coloration, such as from proanthocyanidin (Kinoshita 1995). The Rc gene is evidenced to be responsible for the accumulation of pigments in the pericarp of seeds (Nagao et al. 1957).
3.2. Total Phenolic Content The TPC of husk, bran and endosperm of different rice varieties are shown in Fig. 1b. There were significant differences (P < 0.05) for TPC content in three fractions of rice. Rice husk, contains TPC ranging from 2.23 ± 0.13 to 3.62 ± 0.05 mg GAE·g-1; this was significantly lower than in rice bran (3.57 ± 0.28 to 6.78 ± 0.13 mg GAE·g-1) but significantly higher than in endosperm (0.43 ± 0.07 to 0.93 ± 0.07 mg GAE·g-1) (P < 0.05). Among the TPC of the eight studied varieties, the JH1 rice variety had the highest TPC in bran (6.78 ± 0.13 mg GAE·g-1) and endosperm (0.93 ± 0.07 mg GAE·g-1) fractions while the SX9 rice variety had the highest TPC in husk. For same rice variety, bran and husk fractions provided more than 90% of phenolic compounds of the whole rice. Comparing the Japonica and Indica rice planted in same area, the 10
average TPCs of husk, bran and endosperm in Japonica rice were significantly higher than that in Indica rice (P < 0.05). Rc and Rd genes in rice may affect the proanthocyanidin synthesis during growth period (Furukawa et al., 2007). Moreover, different rice varieties and soil properties at rice planting area might also influence the TPC of rice kernel. Phenolic compounds in rice could be existed in free, esterified and insoluble-bound forms, which may cause the TPC diversities of different rice species or varieties (Shen et al., 2009).
3.3. Evaluation of the Antioxidant Activity in Rice Fractions
3.3.1. DPPH Radical Scavenging Ability The antioxidant abilities of rice fractions were worthy investigating because of the significant variation phenolic acid content and type of compounds in husk, bran and endosperm. The DPPH radical scavenging ability method is widely used to evaluate the free radical scavenging activity of antioxidant (Jiao et al., 2012). The inhibition abilities of DPPH radical by different rice fractions were shown in Fig. 1c. The radical scavenging abilities of extracts from rice husk, bran and endosperm ranged from 54.34 to 59.62%, 73.09 to 78.82% and 33.48 to 38.92%, respectively. The order of the DPPH inhibition activity of rice fractions was endosperm < husk < bran, and the difference between each of the two fractions was extremely significant (P < 0.01). For same rice fractions, the DPPH inhibition abilities of Japonica and Indica rice were not significant different. It revealed that the radical scavenging activities of Japonica and Indica rice were in same level.
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3.3.2. FRAP assay FRAP method measured the ability of Fe3+ transformation to Fe2+ at low pH (Benzie and Strain, 1996). The reducing power was based on measuring the formation of Perl’s Prussian blue at 700 nm (Hu et al., 2016). The distribution of reducing power among different rice fraction from the eight varieties is shown in Fig. 1d. The reducing power of three fractions were observed as follows: endosperm (0.18 ± 0.01 to 0.22 ± 0.01 ABS) < husk (0.81 ± 0.03 to 1.18 ± 0.05 ABS) < bran (1.05 ± 0.03 to 1.64 ± 0.04 ABS). It was obviously showed that the rice bran gave higher reducing power than that of other fractions. Meanwhile, with regard to specific varieties, the reducing power of bran fraction decreased in the following order: SLY1813 < YLY316
3.4. Identification and Quantification of Phenolic Compounds in Rice Fractions 12
In total, 12 phenolic compounds were identified from the crude solvent extracts of different rice fractions of the 8 rice varieties. The details of [M-H]-, MS/MS fragments and formula of each identified phenolic compound were listed in Table 2. The formula and structure of each compound or derivative were obtained and analyzed based on the data for tR (retention time) molecular ion and fragmentations, and is listed in Fig. 2. The quantity of the identified 12 compounds were then determined from the intensity information by comparing with the literature and pure standards. The molecular mass of No.1 and No. 2 compounds were detected at m/z [M-H]121.0350 and 135.0453, respectively. This two peaks can be identified as the phydroxybenzaldehyde (HD) and p-hydroxyphenylacetaldehyde (HA) with the reference standard. Other fragments m/z [MS/MS] were at 93 also observed from No. 3 and No.9, which were identified as p-hydroxybenzoic acid (HHA) and caffeic acid (CA) (Mellegård et al., 2009). These four of compounds (HD, HA, HHA and CA) it rarely reported in rice husk, bran and endosperm previously. Compound No. 6 and 10 with [M-H]- at 153.0195 and 178.9769 m/z, were defined as protocatechuic acid (PA) and ferulic acid (FA) compounds respectively. Similar results for the fragment of ions at 109.03 and 134.04 and 133.03 m/z were reported by Wang et al (2014). Vanilla acid (VA), gallic acid (GA) and syringic acid (SA) were detected in husk, bran and endosperm fractions of the all eight rice varieties, which were widely accepted as important antioxidant substance (Ferreira, Barros and Abreu, 2009).
3.5 Distribution of Phenolic Compounds in Different Fractions of Four Rice Varieties Phenolic compounds in rice husk, bran and endosperm of Japonica rice (JH1, SX9, 13
HD5 and NG46) and Indica rice (ZX51, SLY1813, FLY886 and YLY316) were shown in Table 3. In husk fraction, the most abundant phenolic compounds were HD, GA, PA and FA, with quantity ranging 14.46 to 23.72 μg·g-1, 3.44 to 9.56 μg·g-1, 2.06 to 4.54 μg·g-1 and 1.58 to 13.97 μg·g-1, respectively. The FA, PA and SA were the most abundant three phenolic compounds in all bran fractions, with quantities ranging from 5.14 to 16.07 μg·g-1, from 5.89 to 9.03 μg·g-1 and 4.89 to 8.76 μg·g-1, respectively. The FA and PA were also the dominant phenolic compounds in endosperm, ranging from 1.35 to 2.24 μg·g-1 and 1.27 to 2.38 μg·g-1, respectively. However, the amounts were significantly lower than in bran (P < 0.05). Interestingly, KA was the only detected phenolic compounds in bran with a concentration lower than 1.00 μg·g-1. The CA was not detected in endosperm of all rice varieties. Similar result also reported by Wanyo et al (2014). The concentration of phenolic acid in rice bran are much higher than in milled rice or endosperm (Zhou et al., 2004), and phenolic acids content in rice husk were also detected and higher than that in bran and endosperm fractions (Butsat and Siriamornpun, 2010). However, there are few reports for phenolic compounds analyzing in grains, and also lack of investigation considering different rice subspecies or varieties. It was worth to notice that HD was the most dominant phenolic compounds in the husk, although this may be inconsistent with other reports (Wanyo et al., 2014; Zhou et al., 2004). In these previous studies, only one rice variety was selected for identification of the antioxidant capacities and phenolic acids in different rice fractions. Rice varieties might also contributed to this difference by specified gene
14
expression (Furukawa et al., 2007). Moreover, HD with a aldehyde group might be an intermediate compounds in the phenolic compounds reactions in rice fractions. For total phenolic compounds, HA, HHA, CIA, HAA, PA and SA in husk fraction were higher than the endosperm, and lower than in bran fraction. On the other hand, total amount of FA in all fractions were much higher than other phenolic acids, which may be caused by arabinoxylan in cell walls of aleurone layer and husk (Mckeehen, Busch and Fulcher, 1999). Some phenolic compounds (PA, GA and FA) in JH1 and NG46 husk fractions were higher than other rice varieties. It means that the specified husk could be used to extract phenolic acids (Butsat and Siriamornpun, 2010). Remarkable, the HD content in rice husk (14.46 to 23.72 μg·g-1) was higher than that in bran (0.21 to 1.07 μg·g-1) and endosperm (0.33 to 0.68 μg·g-1). The phenolic compounds content in rice husk could be greater than previous research reported (Abubakaret al., 2016; Liu, 2007). Fig. 3 showed the score plot of principal component analysis (PCA) applied to rice fractions by using contents of the identified phenolic compounds. The first two principal compounds accounted for 70.35% and 18.31% of loading score, respectively. Apparently, the scores of PC1 and PC2 from husk, bran and endosperm segment were clearly separated with each other; this suggested that content of phenolic compounds are significantly different in the three fractions of rough rice (husk, bran and endosperm). Based on the Fig. 3, the scatter of the husk and bran were higher than endosperm; this may mainly be caused by the significant differences of HD content in the three fractions, which was influenced by the varieties of the rice
15
(Table 3). The three different fractions can be isolated based on content of phenolic compounds. Comparing the different rice subspecies, the amount of HD and FA in husk and bran of Japonica rice were significantly higher than that of Indica rice (P < 0.05), while the amount of HA in bran of Indica rice was significantly higher than that of Japonica rice (P < 0.05). The amounts of other 9 phenolic compounds existed in same fraction of Japonica and Indica rice were in same level. However, for the endosperm fraction, limited difference in all phenolic compounds came from Japonica and Indica rice. This was mainly because phenolic compounds were abundant in husk and bran fraction, the content of each phenolic compound rarely distributed in rice endosperm.
4. Conclusion The distribution of phenolic compounds and antioxidant activity of husk, bran and endosperm in four Japonica rice and four Indica rice were investigated in this research. Highest YI value (husk 72.84 ± 0.90, bran 61.59 ± 0.40, endosperm 30.34 ± 0.44) were found in JH1 amongst the 8 studied rice varieties. Twelve phenolic compounds in rice (p-hydroxybenzaldehyde, p-hydroxyphenylacetaldehyde, phydroxybenzoic acid, cinnamic acid, p-hydroxyphenylacetic acid, protocatechuic acid, vanilla acid, gallic acid, caffeic acid, ferulic acid, syringic acid and kaempferol) were identified from the fraction extracts. Ferulic acid, gallic acid, protocatechuic acid and syringic acid were the dominant phenolic compounds in rice bran, while pHydroxybenzaldehyde was the main phenolic compounds existed in rice husk (14.4616
23.72 μg·g-1). For same rice variety, more than 90% of phenolic compounds existed in bran and husk fractions and provide strong antioxidant ability. Bran and husk fractions can also provide corresponding more than 90% of antioxidant activity of the whole rice. By contrast, Japonica rice has significant higher phenolic compounds and antioxidant activity than Indica rice (P < 0.05). Therefore, the distribution of phenolic compounds were strongly correlated with the rice varieties and fractions. The analysis of phenolic compounds distribution in rice bran and husk may give a great potential for further utilization in food and allied industries.
Acknowledgments The authors wish to acknowledge and thank the projects funding by the National Key Research and Development Program of China (2017YFD0401403), National Natural Science Foundation of China (31601402), the Natural Science Foundation of the Colleges and Universities in Jiangsu Province (16KJB550004), the Independent Innovation Fund Project for Agricultural Science and Technology of Jiangsu (CX(17)100205), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
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Figure legends:
Fig. 1. Descriptive statistics for yellowness index (a), total phenolic compounds (b), DPPH radical scavenging ability (c) and FRAP assay (d) of three fractions (husk, bran and endosperm) in four Japonica rice (JH1, SX9, HD5 and NG46) and four Indica rice (ZX51, SLY1813, FLY886 and YLY316). Vertical line on the top of columns represented error bars, different letters upon each column identified statistically different (P < 0.05) data; TPC means total phenolic compounds. Fig. 2. Extraction ion chromatograms for 12 sub-fraction of bran from ZX51 by UPLC-Triple/TOF - MS chromatograms. No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). Fig. 3. Principal component analysis of phenolic compounds contents in different rice fractions of eight rice varieties. (husk-green (■); bran-red (◆); endosperm-black (●)). Table legends: Table 1. Details of eight rice samples used in experiment. Table 2. Phenolic compounds in rice fractions identified by UPLC-Triple/TOF-MS.
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Table 3. Distribution (μg·g-1) of phenolic compounds in different fractions of eight rice varieties. Nd means not detected; Tr means trace amount (lower than 0.01μg·g-1). Different letters behind numbers in same column were mean significantly different (P < 0.05) No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). subsp. Japonica rice (JH1, SX9, HD5 and NG46); subsp. Indica rice (ZX51, SLY1813, FLY886 and YLY316) Table 1 Details of eight rice samples used in experiment Variety
Type
Sites Location
Size (length × wideth ×
Thousand
thickness)
weight
content
(mm)
(g)
(% w.b.)
subsp.
32°65’N,
7.9(±0.3) × 3.4(±0.1) ×
Japonica
119°07’E
2.3( ± 0.1)
subsp.
32°30’N,
7.4(±0.4) × 3.3(±0.3) ×
Japonica
118°47’E
2.3( ± 0.1)
subsp.
32°35’N,
7.7(±0.2) × 3.3(±0.2) ×
Japonica
118°83’E
2.3( ± 0.1)
subsp.
33°60’N,
7.3(±0.4) × 3.3(±0.1) ×
Japonica
119°02’E
2.3( ± 0.1)
subsp.
28°96’N,
9.2(±0.5) ×2.2(±0.1) ×
rice)
Indica
111°98’E
1.9 ( ± 0.1)
SLY1813 (white
subsp.
30°55’N,
8.7(±0.6) ×2.4(±0.1) ×
rice)
Indica
116°94’E
2.0 (±0.1)
FLY886 (white
subsp.
32°35’N,
9.1(±0.6) ×2.2(±0.1) ×
rice)
Indica
118°83’E
1.9 ( ± 0.1)
YLY316 (white
subsp.
33°60’N,
9.2(±0.6) ×2.3(±0.1) ×
rice)
Indica
119°02’E
1.9 (±0.1)
JH1 (white rice)
SX9 (white rice) HD5
(white
rice) NG46
(white
rice) ZX51
(white
25.8 ± 0.3
25.0 ± 0.1
25.1 ± 0.2
25.0 ± 0.2
21.4 ± 0.2
25.3 ± 0.3
24.8 ± 0.2
25.0 ± 0.3
grain
Moisture
14.0
±
0.2% 14.0
±
0.3% 14.0
±
0.3% 14.0
±
0.3% 13.5
±
0.4% 13.5
±
0.3% 13.5
±
0.3% 13.5
±
0.3%
22
`
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Table 2 Phenolic compounds in rice fractions identified by UPLC-Triple/TOF-MS Number
Identification
Formula
tR
[M-H]-
Error
MS/MS
min
m/z
ppm
m/z
1
HD
C7H6O2
3.81
121.0305
3.3
93.0366; 92.0281
2
HA
C8H8O2
4.41
135.0453
8.2
93.0370; 92.0277; 91.7364
3
HHA
C7H6O3
3.35
137.0252
2.2
93.0369; 65.0420
4
CIA
C9H8O2
5.35
147.0454
9.3
129.0286; 119.0515; 117.0326; 61.9900;
Structural formula
58.9805 5
HAA
C8H8O3
4.29
151.0402
9.8
136.0155; 122.0374; 108.0215; 92.0267
6
PA
C7H6O4
3.49
153.0195
8.4
135.0087; 109.0316; 65.0395; 67.0194
7
VA
C8H8O4
3.90
167.0344
10.8
152.0098
8
GA
C7H6O5
12.94
169.0870
7.9
123.0837; 83.0513
9
CA
C9H8O4
5.37
178.9769
10.1
136.0175;135.0468; 34.9920; 93.0378; 92.0254; 91.0001; 84.9913
10
FA
C10H10O
5.46
193.0507
2.7
178.0268; 149.0571; 134.0357; 133.0292
4
11
SA
C9H10O5
1.14
197.8086
1.3
162.8394; 160.8421
12
KA
C15H10O
4.43
285.0604
13.2
217.1021; 197.0443; 182.0222; 150.0366; 123.0095; 121.0286
tR means retention time; No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: pHydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA).
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Table 3 Distribution (μg·g-1) of phenolic compounds in different fractions of eight rice varieties. Variety JH1
SX9
HD5
NG46
ZX51
SLY1813
FLY886
YLY316
Rice
HD
HA
HHA
CIA
HAA
PA
VA
GA
Husk
23.72±2.62a
0.13±0.01a
0.19±0.05a
0.88±0.06a
0.28±0.02a
3.16±0.58cd
3.71±0.34a
5.26
Bran
1.07±1.07c
0.75±0.03c
3.33±0.29d
2.53±0.17c
1.65±0.12d
8.86±0.84a
3.07±0.02b
14.7
Endosperm
0.39±0.22c
Nd
0.13±0.07a
Tr
Nd
1.28±0.02e
0.82±0.03c
1.35
Husk
18.06±0.53b
0.12±0.01a
0.09±0.02a
0.84±0.03a
0.28±0.01a
4.54±0.90bc
3.06±0.39b
7.56
Bran
0.61±0.06c
0.59±0.01b
1.59±0.10b
2.49±0.20c
0.70±0.04b
5.89±0.78b
2.74±0.07b
9.81
Endosperm
0.70±0.11c
Nd
Nd
Tr
Nd
2.38±0.01e
0.80±0.01c
0.98
Husk
19.03±0.78b
0.1±0.02a
0.23±0.06a
1.00±0.59ab
0.20±0.05a
3.78±1.03cd
3.12±0.55ab
7.71
Bran
0.51±0.10c
0.55±0.10b
2.58±0.47c
2.48±0.23c
0.64±0.10b
8.02±0.56a
3.09±0.22b
13.3
Endosperm
0.40±0.08c
Nd
Nd
Nd
Nd
1.77±0.70e
0.81±0.04c
1.20
Husk
18.94±1.89b
0.10±0.05a
0.15±0.05a
0.99±0.23a
0.18±0.04a
3.23±0.66cd
3.66±0.10a
6.98
Bran
0.37±0.08c
0.42±0.09b
2.30±0.67c
2.52±0.44c
1.03±0.45c
7.95±0.39a
3.11±0.10b
15.6
Endosperm
0.77±0.12c
Nd
Nd
Nd
Nd
2.77±0.50d
0.83±0.01c
1.00
Husk
14.46±0.11b
0.19±0.02a
0.13±0.01a
1.22±0.16ab
0.24±0.03
2.22±0.03de
3.12±0.20b
3.69
Bran
0.31±0.04c
1.64±0.04d
2.28±0.09c
2.08±0.23c
0.83±0.09b
8.75±0.40a
3.09±0.11b
14.5
Endosperm
0.68±0.42c
Tr
Tr
Nd
Nd
1.27±0.01e
0.82±0.02c
2.59
Husk
15.28±0.48b
0.16±0.01a
0.11±0.04a
0.98±0.06a
0.19±0.02a
2.06±0.04de
3.75±0.02a
3.44
Bran
0.21±0.05c
2.24±0.09e
2.35±0.15c
1.88±0.47c
1.10±0.07c
8.98±0.72a
3.05±0.03b
14.9
Endosperm
0.33±0.02c
0.08±0.04a
Tr
Nd
Nd
1.27±0.01e
0.80±0.02c
3.48
Husk
14.78±0.15b
0.20±0.06a
0.13±0.05a
1.16±0.25ab
0.14±0.10a
2.23±0.20de
3.32±0.22b
4.23
Bran
0.48±0.22c
1.87±0.32de
2.45±0.78c
2.22±0.13c
1.23±0.44c
9.03±0.23a
3.45±0.38ab
13.5
Endosperm
0.78±0.12c
Nd
Nd
Nd
Nd
1.44±0.24e
0.77±0.04c
3.56
Husk
16.34±0.21b
0.42±0.06b
0.24±0.14a
1.34±0.32ab
Tr
2.55±0.77de
3.88±0.12a
3.89
Bran
0.65±0.34c
1.42±0.67d
1.49±0.54b
2.56±0.45c
1.03±0.21c
8.01±0.77a
3.00±0.11b
15.8
Endosperm
0.37±0.15c
Nd
Nd
Nd
Nd
1.33±0.09e
0.82±0.04c
4.01
fraction
Nd means not detected; Tr means trace amount (lower than 0.01
μg·g-1).
Different letters behind numbers in same column were mean significantly different (P < 0.05) No.1: p-Hydroxybenzaldehyde (HD); No.2: p-Hydroxyphenylacetaldehyde (HA); No.3: p-Hydroxybenzoic acid (HHA); No.4: Cinnamic acid (CIA); No.5: p-Hydroxyphenylacetic acid (HAA); N0. 6: Protocatechuic acid (PA); No.7: Vanillic acid (VA); No.8: Gallic acid (GA); No.9: Caffeic acid (CA); No.10: Ferulic acid (FA); No.11: Syringic acid (SA); No.12: Kaempferol (KA). subsp. Japonica rice (JH1, SX9, HD5 and NG46); subsp. Indica rice (ZX51, SLY1813, FLY886 and YLY316)
Highlights:
Twelve main phenolic compounds (PC) were identified in different rice varieties. Bran and husk provide more than 90% of PC and antioxidant activity of whole rice. Ferulic acid, gallic acid and protocatechuic acid were the highest 3 PCs in rice bran. P-Hydroxybenzaldehyde was the main PC existed in rice husk (14.46-23.72 μg·g-1). Japonica rice has significant higher PC and antioxidant activity than Indica rice.
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