ISSN : 2287-5174(Online)
DOI : https://doi.org/10.9787/KJBS.2012.44.4.444
Determination of Cyanidin-3-Glucoside Content using Visible/Near Infrared Reflectance Spectroscopy (VIS/NIRS) in Black Rice
Rice (Oryza sativa L.) has variation seed coat colors, such as white, brown, red, and blackish purple. The pigments of colored rice are found in the bran or hull in grain (Shibuya 1990). The edible natural pigments extracted from plant organs become steadily popular to consumer because of those physiological functions desirable for food preservation and human health. So, the natural pigments from colored rice is widely used as food colorants in the processing of wine, bread, ice creams, cakes, and so on (Araceli 2009; Cho et al. 1996; Yoshinaga 1986).
The pigments extracted from colored rice can be largely divided into two types such as anthocyanins or tannins. Anthocyanin pigments are mainly contained in black rice while tannin pigments are mainly contained in red rice (Choi & Oh 1996; Reddy 1995). The anthocyanin pigments contained in black rice was over 80% of cyaniding-3-glucoside. The other minor pigments were peonidin-3-glucoside, malvidin -3-glucoside, and cyaniding-3-ramnoglucoside (Lee 2010; Nagai et al. 1960; Ryu et al. 1998). Anthocyanin in 10 Korean black rice varieties showed significant differences and Cyaniding-3-glucoside content exhibited 52～1,601 ㎍/g (Lee 2010). Cyaniding-3-glucoside is associated with healthy effects such as anti-oxidant, anti-allergy, anti-inflammatory and anti-cancer function (Lim et al. 2011; Min et al. 2010; Park et al. 2008; Tsude et al. 1994).
The VIS/NIRS is a multi-trait technique that fulfills most of the requirements for rapid, accurate, and cost-effective mass screening technique for high quality breeding in many crops. In the case of milled rice, the NIRS technique has been shown to produce accurate and reliable results to determine the contents of amylose, protein, amino acid, lipid, moisture and the degree of starch gelatinization (Hwang et al. 1994; Kawamura et al. 1997; Barton et al. 1998; Delwiche et al. 1996; Windharm et al. 1997; Zhang et al. 2011). Also, Delwiche et al. (1996) reported the application of NIRS reflectance analysis of whole-grain rice to predict amylose, protein, whiteness, transparency, milling degree, and paste viscosity characteristics.
The cyanidin-3-glucoside, which was major anthocyanin in black rice, analysis using HPLC is requiring high cost, more time and labor than NIRS method. Therefore, this study was conducted to establish a rapid analysis method for determining cyanidin-3-glucoside contents of black rice using VIS/NIRS technique and to provide the mass screening technique for high quality blackish rice breeding.
MATERIALS AND METHODS
A total number of 60 black rice samples were grown at the experimental field of National Institute of Crop Science at Milyang South Korea. The rice samples were harvested at the stage of 20～25% moisture contents and dried immediately to 11～13% constant moisture contents by air-drying at ambient temperatures. The uniform ranged rice samples were used for further analysis. The whole rice samples were measured VIS/NIRS method, and then rice samples (20 g) were ground in a Heiko Sample Mill with 1.0 mm screen for 2 min. The ground rice samples were well-mixed and used for the analysis of cyanidin-3-glucoside content by HPLC and VIS/NIRS methods.
Analysis of cyanidin-3-glucoside contents
Isolation and purification of cyanidin-3-glucoside in rice sample was performed following the Choi et al. (1994), and the chemical structure of isolated cyanidin-3-glucoside was confirmed by Choung et al. (2001). The relative purity of isolated cyanidin-3-glucoside was 99.5% by RP-HPLC with UV-VIS detector (Fig. 1).
Fig. 1. Chromatogram of cyanidin-3-glucoside standard (left) and black rice sample (right) using RP-HPLC.
To determine the cyanidin-3-glucoside contents, 0.4 g rice sample was weighted and extracted four times with 10 mL of 1% HCl in 80% methanol (v/v) at 4℃ for 24 hrs, and each extract was centrifuged at 10,000 rpm for 10 min. The combined extract was made up in a total volume 100 mL volumetric flask using distilled water. Finally, the extracted solution was filtered with a 0.45 ㎛ membrane filter to analyze by reverse-phase HPLC(RP-HPLC). The cyanidin-3-glucoside content of crude black rice extract was determination by RP-HPLC. The HPLC system was composed of an L-6200 intelligent pump, an L-4250 UVvisible variable wavelength detector, and a D-2500 integrator (Hitachi Co., Japan). Injections were carried out with a Rheodyne 7725i injector equipped with a 20 μL sample loop. The column was a Tosoh ODS-120T (150×4.6 mm i.d., Japan), and the flow rate was set at 0.7 mL/min by isocratic elution, using a Water: MeOH: Formic acid (70:25:5, v/v/v) with monitoring at 530 nm, and the column temperature was set at 30℃. For protection of the analytical column, a Novapak-pak C18 guard insert column (Waters, Milford, MA) was used. The cyanidin-3-glucoside contents were calculated by HPLC peak area compared with external standard calibration curve. The linear standard calibration curve (r≥ 0.999) was generated by injecting 0.05 μg to 1 μg of purified cyanidin-3-glucoside in 20 μL of 1% HCl in 80% methanol (v/v).
Visible/near-infrared spectroscopy measurement
The whole and grind samples were scanned on a monochromator NIRS systems model 6500 (Silver Spring, MD, USA). For each sample, approximately 5 g was poured into a small cell cup (standard cell cup) with flour or whole seed, presented to the instrument in reflectance mode, and scanned from 400 to 2,500 nm at 2 nm intervals. Each sample was scanned 2 times, and the average reflectance spectrum was stored for calibration (40 samples) and validation (20 samples). The validation sample set was not used for the calibration.
The instrument was operated by the software package NIRS 3 (version 3. 11), which includes module for acquisition and processing of spectra. Accuracy of calibration equation was determined as standard error of prediction (SEP) value and coefficient of determination (r2) value of the external validation sample sets.
RESULTS AND DISCUSSION
The log 1/R spectra of the rice flour with different cyanidin-3-glucoside contents are shown in Fig. 2. The changes on cyanidin-3-glucoside contents of rice flour samples showed vast transformation of absorbance between 400 and 1,200 nm. These spectra indicate that the functional groups of the rice flour colorant were closely connected with this wavelength range.
Fig. 2. Raw spectra of NIRS with different Cyanidin-3-glucoside (C3G) contents in rice flour samples.
The laboratory reference statistics values for cyanidin-3- glucoside content based on rice flour samples are showed in Table 1. The cyanidin-3-glucoside content of calibration sample set was ranged from 102 to 1,250 mg/100 g and external validation sample set were ranged from 218 to 809 mg/100 g. The range of cyanidin-3-glucoside content in external validation sample set fell within the calibration sample set.
Table 1. Cyanidin-3-glucoside (C3G) contents of black rice for the NIRS calibration and external validation set.
Calibration was obtained by partial least square regression (PLS) or automatic regression method as described by Williams et al. (1991). Table 2 and 3 showed the values of multiple correlation (MR) and standard error of calibration (SEC) of the cyanidin-3-glucoside content using PLS method and automatic regression method for calibration sample set, respectively. The MR and SEC values of cyanidin-3-glucoside content in calibration sample set by PLS regression method were higher than those by the automatic regression method in both rice flour and whole rice seed sample. Compare to rice flour sample and whole rice seed sample, the MR and SEC values of rice flour sample were higher than those in whole rice seed sample.
Table 2. Comparisons on the effects of different sample type for calibration equation by partial least square regression (PLS).
Table 3. Comparisons on the effects of different sample type for calibration equation by automatic regression.
Low coefficient of determination (r2 ) of whole rice seed sample set was considered due to the gaps between rice seed in small sample cup, and the degree of uniformity for external shape of rice seed. Norris and Williams (1984) and Windham et al. (1997) reported that the difference of particle size in sample was one of the most important factors in NIRS analysis. Because the difference of particle size causes a change in the amount of radiation scattered by samples.
In the case of automatic regression method (Table 3), the best accurate results of calibration equation and prediction were obtained by combining the VIS/NIRS wavelength range (400～700 nm and 2,230 nm). Chen et al. (1997) reported that the best calibration and prediction results of quantifying surface lipid content of milled rice were VIS/ NIRS wavelength range (400～700 nm, and 1,500～2,500 nm). However, extending the combined wavelength range to the entire VIS/NIRS spectrum (400～2,500 nm) did not improve the SEC and SEP value.
External validation sample set allows NIRS equation to be validated for prediction accuracy based on random samples not used in calibration sample sets. The value of coefficient of determination (r2), SEP and bias of cyanidin- 3-glucoside content by the PLS method were higher than those by the automatic regression method in both rice flour and whole seed rice sample. In comparison with different sample types, flour samples were higher than whole rice seed samples (Table 2 and 3).
The value of coefficient of determination (r2), SEP and bias were represented as accuracy of NIRS equation (Windham et al. 1997). Based on the coefficient of determination (r2), SEP and bias, the optimal equation using partial least square regression method was accurately predicting the cyanidin-3-glucoside contents of external validation sample set.
The quality of a NIRS equation has been judged by the ability to predict accurately from independent spectra. In this study, the well predicting NIRS equation of cyanidin 3-glucoside content in rice flour sample was obtained from the PLS method. The coefficient of determination (r2), SEP and bias of NIRS equation for cyanidin-3-glucoside in rice flour sample were 0.922, 22.5 and -1.45 in the calibration transformed to the N-point smooth of log 1/R signal, respectively (Fig. 3). However, in the case of whole rice seed samples, coefficient of determination (r2) and SEP values were 0.653 and 97.2 by PLS method (Table 2). The coefficient of determination (r2) and SEP values of whole rice seed samples were lower than those of rice flour samples (Table 2 and 3). Chen et al. (1997) reported that in developing calibration equation by means of PLS techniques, the number of principal components is an important factor affecting SEP. Therefore, SEP tended to increase again as the number of principal components was increased due to data overfitting. The optimum number of PLS factors has been determined for each spectral range by identifying the minimum SEP. In the reported PLS calibration, five principal components were included in the calibration equation (Table 2).
Fig. 3. Scatter plots of Cyanidin-3-glucoside (C3G) content in brown rice flour samples by HPLC vs. NIRS for the calibration (upper) and external validation (lower) samples set by PLS.
Based on our results, it seemed to be difficult to analyze cyanidin-3-glucoside content in whole rice seed samples using VIS/NIRS method, due to gap between grain samples (different particle size of intact seed), uniformity of colored area in external rice shape and amount of small cell. Accordingly, the VIS/NIRS analysis for cyanidin-3-glucoside content in whole rice seed samples require further examination to be acceptation rapid and accurate scan method.
In rice flour sample, the best accurate equation model was obtained from the PLS method. The value of coefficient of determination (r2) and SEP were 0.922 and 22.5, in the calibration transformed to the N-point smooth of log 1/R signal, 5 factors, respectively. Therefore, the results of our study clearly demonstrate that the VIS/NIRS method would be applicable only for rapid determination of cyanidin -3-glucose content of blackish rice flour samples.
This work was carried out with the support of Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ9070482012) Rural Development Administration and fund by National Institute Crop Science, Republic of Korea.
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