Journal of Chemistry

Journal of Chemistry / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 2013109 |

Chunlei Ni, Shan Zhang, Gaopeng Zhang, Jianjun Cheng, Huanyu Zheng, "Evaluation of Edible Quality of Sorghum Based on Principal Component Analysis", Journal of Chemistry, vol. 2019, Article ID 2013109, 10 pages, 2019.

Evaluation of Edible Quality of Sorghum Based on Principal Component Analysis

Academic Editor: João Paulo Leal
Received14 Jun 2019
Accepted05 Sep 2019
Published24 Sep 2019


Sorghum (Sorghum bicolor (L.) Moench) is one of the most important cereals in the Northeast China. The physicochemical, pasting, texture, and cooking properties of 21 sorghum varieties were determined, which were mainly cultivated in Northeast China. Then, the evaluation of edible quality of sorghum was based on principal component analysis and fitted with the score of sensory evaluation. Five principal components (PCs) with a cumulative contribution rate of 86.19% could be picked out to describe the taste, pasting, flavor, cooking, and variety of sorghum, respectively. And a comprehensive equation of sorghum edible quality in Northeast China was constructed which was Z = 0.45F1 + 0.25F2 + 0.12F3 + 0.10F4 + 0.08F5. The edible quality of No. 14 and No. 15 was the best. The sensory evaluation was used to verify the above equation with the fitting coefficient of 0.81, which indicated that the equation could be more accurate to evaluate the edible quality of sorghum in Northeast China.

1. Introduction

Sorghum (Sorghum bicolor (L.) Moench) is the fifth most produced cereal after wheat, rice, maize, and barley [1, 2] and is drought tolerant, resistant to water logging, and grows in various soil conditions [3]. In recent years, sorghum cultivation has been concentrated in Northeast China, and the yield accounted for 62% of the National Sorghum Yield in 2016 (data source: Department of Market and Economic Information, Ministry of Agriculture, China). Because sorghum is rich in starch and protein, it can be regarded as a substitute for the common cereals such as rice, wheat, millet, and soybean. The consumption of whole sorghum grains would contribute toward health benefits through bioactive compounds such as fiber and phenolics [4]. In Western countries such as the United States, Australia, and Brazil, sorghum is developed and cultivated primarily for animal feeding, while in semiarid regions of the world, it is mainly used in human feeding as coarse grains [57]. In China, the history of Kaoliang Spirit has been more than 2500 years [8]. With the short of pure water resources, sorghum which is an ecologically friendly and tolerant crop will become an important crop in the future. As sorghum is one of the three main grains in China, how to evaluate its edible quality scientifically and realize its value better is a question worthy of in-depth study.

Nowadays, the evaluation of the edible quality of cereals is mainly focused on the fine grains such as rice and wheat. Evaluation methods include sensory evaluation and instrumental analysis. Sensory evaluation was affected by the regional eating habits, environment of the participants, and difficulty in quantitatively describing the food taste [9]. Some scholars have made comprehensive analysis of cereal quality by means of instrument and physicochemical characteristics that include the texture tester and the rapid viscosity analyser (RVA). The hardness and stickiness in the texture characteristics can be used to evaluate the softness and looseness of rice, while the pasting temperature and setback viscosity of gelatinized flour starch pastes can be used to evaluate the cooking time and the texture of meal [10, 11]. Based on the analysis of the correlation among the gelatinization properties, texture properties, and sensory evaluation of cereals, a method for predicting the texture of rice can be established [12]. In addition, physicochemical components are often used to analyse the quality of rice taste. The composition content and structure of starch were the important factors of edible quality, while protein, moisture, and ash content were significantly correlated with taste, appearance, and comprehensive score of rice [1315]. Literature review shows the varieties of rice with better taste quality had a shorter cooking time, higher iodine blue value, and lower water absorption [16]. So far, principal component analysis, cluster analysis, and discriminant analysis are the main methods used in the comprehensive analysis of cereals. However, principal component analysis is the most commonly method for cereal quality evaluation.

Principal component analysis (PCA) is an analytical method for transforming multiple indexes into fewer new ones [17]. PCA combined with the determination of cereal quality characteristics can simplify the cereal quality index into several principal components with a cumulative contribution rate of more than 80% and then analysed the edible quality of cereals to study the effects of physicochemical components and quality characteristics of cereals on edible quality [18, 19].The principal component analysis (PCA) was used to study the edible quality of rice, the suitable processability of sweet waxy corn, and the physical properties and processing characteristics of oat grains [18, 20, 21]. Besides, it can be used to establish the evaluation model of edible quality which included Indica rice cake, Japonica rice, and Indica rice [2224]. There are relatively few studies on the evaluation of sorghum edible quality.

The aim of the paper was to evaluate the edible quality of sorghum. 21 sorghum varieties which were mainly cultivated in Northeast China were selected to analyse their physicochemical, pasting, texture, and cooking properties and edible quality. Then, the properties of sorghum were analysed by PCA, and the evaluation equation was obtained. Finally, the equation was fitted with the score of sensory evaluation. The results showed it was more intuitive and objective and provided a theoretical basis for the edible quality of sorghum.

2. Materials and Methods

2.1. Materials

Nos. 1–13 sorghum (Sorghum bicolor (L.) Moench) varieties were provided by Jilin Academy of Agricultural Sciences (Jilin province, China), which were Z1001—Z1013. Nos. 14–21 were provided by Heilongjiang Academy of Agricultural Sciences (Heilongjiang Province, China), which were 16-5071, 16-5072, Dragon Miscellaneous 17, Dragon Miscellaneous 18, Dragon Miscellaneous 16, Dragon Glutinous 13-2, Dragon Rice Grain 2, and Dragon Rice Grain 1. All chemicals were analytical grade reagents.

2.2. Proximate Analysis

Moisture content was determined according to the procedure in AACC (44-19,2000). Ash content was determined by dry ashing in a furnace oven at 550°C (AACC 8-01,2000). The crude protein was calculated by converting the nitrogen content determined by the Kjeldahl method (N6.25) (AACC 46-12,2000). Crude lipid, using a Soxhlet apparatus (AACC 30-25,2000), was also determined. Starch content was determined according to the procedure in AACC (76.13.2000). Tannin content was determined referring to the method of Maxson by spectrophotometry [25].

2.3. RVA Pasting Properties

Sorghum pasting properties were determined using a Rapid Visco Analyser (RVA, Super3, Newport Scientific, Warriewood, Australia). Flour (3.00 g, based on 12% moisture) was mixed with 25 g of distilled water in an RVA sample canister. The RVA was run using Thermocline for Windows software (Version 1.2). The Rice Method 1 program was used with heating and cooling cycle set as follows: (1) holding at 50°C for 1 min, (2) heated to 95°C in 3.8 min, (3) holding at 95°C for 2.5 min, (4) cooling to 50°C in 3.8 min, and (5) holding at 50°C in 1.4 min. The pasting temperature (PT), peak viscosity (PV), breakdown (BD), and setback (SB) were recorded form the Thermocline for Windows software (Version 1.2) [26].

2.4. Cooking Characteristics
2.4.1. Preparation of Sorghum Rice

Experiments were conducted with an automatic rice cooker (CFXB4003-A1, 4.0 L, 700 W, 220 V, 50 Hz, Guangzhou domestic appliance Ltd., China). 1000 g sorghum rice was soaked in a pot for 30 min with 1500 mL of tap water. After the sorghum rice cooked for 40 min, the thermostat coupled with microswitch automatically switched off the automatic rice cooker. The cooked sorghum rice samples were held in the rice cooker for an additional 20 min. Finally, the cooked sorghum rice was obtained.

2.4.2. Water Absorption Rate

The sorghum sample of a certain mass was weighed and recorded as M1, which was placed in a beaker. Then, a certain volume of distilled water was added, cooked in a boiling water bath for 20 minutes, and finally cooled to room temperature, and the weight of M2 was recorded. The calculation formula is as follows [27]:

2.4.3. Volume Expansion Ratio

The volume of sorghum rice sample before and after cooking was measured by the drainage method, as described in [16]. The sample of sorghum rice of certain mass was poured into the measuring cylinder that contains 50 mL distilled water, and the volume V1 was recorded. Then, the sorghum rice sample was cooked in a boiling water bath for 20 minutes. After cooking, the sample was poured into the same measuring cylinder as above, and the volume V2 was recorded. The formula is as follows:

2.4.4. Iodine Blue Value

The rice soup was cooled to room temperature and diluted to 100 mL. After [27] centrifugation (Allegra X-30R Multifunctional Centrifuge, American Beckman Coulter, USA),1.0 mL rice soup was added to 50 mL distilled water and then 5 mL of 0.5 mol/L HCl solution and 1 mL of 0.2 g/100 mL of iodine reagent were added; finally, the volume was adjusted to 100 mL. The absorbance was measured at a wavelength of 660 nm by Ultraviolet visible spectrophotometer (UVmini-1240, Shimadzu Co., Ltd, Japan). The iodine blue value of rice soup is expressed by absorbance [28].

2.5. Textural Profile Analysis

Textural profile analysis (TPA) of the cooked sorghum rice was performed using a texture analyser (, Texture Technologies Corp., UK). The hardness, stickiness, adhesiveness, chewiness, and responsiveness were determined. The texture was determined according to the method of Yu et al. [29] with minor modifications. The texture analyser was linked to a computer that recorded the data via a software program called Texture Expert Excede Version 1.0 (Stable Micro Systems Software). The P50 probe was used to compress 3 sorghum rice grains, under the compression distance of 1.4 mm and the trigger point force of 10.0 g, with pretest speed, test speed, and posttest speed of 10.0 mm/s, 0.5 mm/s, and 5.0 mm/s, respectively. All textural analyses were replicated six times per sample, and the results are presented as mean values.

2.6. Sensory Evaluation

The sensory analysis of the cooked sorghum rice was carried out in laboratory conditions. Sensory assessments were determined by 20 trained panelists (staff aged from 30 to 40 years old and graduate students aged from 20 to 30 years old): ten females and ten males. The evaluation was carried out using the 100-point scale test with the distinctions of quality (smell, appearance, taste, texture, and acceptability) [30, 31], and the results are shown in Table 1. In the process of sensory quality evaluation, 4 servings of sorghum rice were tasted each time, and the evaluation time was arranged 1 hour before and 2 hours after meal. The average value of each evaluator was calculated as the comprehensive evaluation value of sorghum rice, and the edible quality of sorghum was measured.

VarietySmell (20)Color (7)Appearance (20)Rice grain integrity (5)Stickiness (10)Acceptability (30)Soft and hard degree (10)Taste (25)Texture (5)Score (100)
Glossiness (8)Elasticity (10)


2.7. Principal Component Analysis

Principal component analysis (PCA) converts observations of correlated variables into a set of linearly uncorrelated orthogonal variables (principal components, PCs), ordered in such a way that each PC has the largest possible variance under the constraint of being orthogonal to all preceding components [32].

The variables of n samples (X1, X2, …, Xp) was transformed into k (k < ) complex variables (F1, F2, …, Fk), which was the linear combination of original variables. Comprehensive variables F1, F2, …, Fk were called the first, second, …, the kth PC of the original variable, respectively:

The quantized values of each sample are weighted by the ratio βi (i = 1, 2, …, k) of the k PCs of different eigenvalues, and the comprehensive evaluation function: Z = β1F1 + β2F2 + ⋯ + βkFk was used to calculate the scores of sorghum rice samples [33].

2.8. Statistical Analysis

SPSS software (Version 17.0, SPSS Inc., Chicago, USA) was used to analyse the data. The means were compared using Pearson’s test at a 5% level of significance using the analysis of variance (ANOVA). Analyses of the samples were completed in triplicate, and the data were expressed as the mean ± standard deviation.

3. Results and Discussion

3.1. Proximate Analysis of Sorghum

There were significant differences in physicochemical components among different sorghum grain varieties (), as shown in Table 2. Starch and protein were the main components of sorghum grains and played an extremely important role in the cooking process. The starch content of 21 sorghum varieties ranged from 68.15% to 79.39%, with an average content of 73.24%, which was lower than the average starch content in other cereals (78% of rice and 75% of corn) [34].The protein content varied from 6.75% to 11.23%. Most of them were higher than 8.25% except for No. 2 and Nos. 18–21. The result showed there were regional differences of the starch content and protein content, and sorghum planted in Heilongjiang are generally lower than those in Jilin. Therefore, the difference in starch and protein content among different varieties may be one of the main factors causing the difference in taste quality [35].

VarietyMoisture (%)Protein (%)Starch (%)Oil (%)Tannin (%)Ash (%)PT (°C)PV (cP)BD (cP)SB (cP)Hardness (g)Stickiness (g·m−1)AdhesivenessChewinessResponsiveness

110.05 ± 0.034jklm8.28 ± 0.230gh70.81 ± 1.136abc1.83 ± 0.155efgh0.049 ± 0.005cdef0.53 ± 0.075efg75.7 ± 0.26defg3749 ± 33.56d1451 ± 13.05cde1875 ± 20.66b429.770 ± 55.52ghij−10.174 ± 0.157a266.177 ± 37.68efgh258.076 ± 41.87defgh0.365 ± 0.030 cd
211.19 ± 0.076e6.75 ± 0.114k69.49 ± 0.929bc2.25 ± 0.250cde0.038 ± 0.006efgh0.44 ± 0.047gh75.2 ± 0.23fgh3801 ± 86.32d1462 ± 67.73 cd1770 ± 50.51bcde386.419 ± 57.27ghij−1.497 ± 0.371a229.890 ± 29.32efgh211.348 ± 29.90efgh0.353 ± 0.010 cd
310.61 ± 0.064gh9.80 ± 0.161c72.86 ± 1.872abc1.84 ± 0.207dfgh0.053 ± 0.007cde0.81 ± 0.040ab76.0 ± 0.15def3059 ± 22.65gh1151 ± 23.50fghi1651 ± 63.13efgh529.797 ± 31.45defghi−0.796 ± 0.559a368.286 ± 19.25bcde313.355 ± 20.22cde0.450 ± 0.025abc
410.75 ± 0.033 fg9.39 ± 0.108cd77.21 ± 0.925abc2.58 ± 0.183bc0.058 ± 0.004c0.7 ± 0.032bcd76.7 ± 0.32cde3135 ± 35.92g1093 ± 15.01ghij1744 ± 12.53cdef689.326 ± 38.83bcd−0.644 ± 0.373a482.189 ± 27.29bc440.334 ± 15.82abc0.469 ± 0.017ab
510.38 ± 0.122hij8.97 ± 0.014def71.36 ± 5.129abc2.23 ± 0.212cde0.088 ± 0.006b0.85 ± 0.069a74.8 ± 0.10ghi3462 ± 30.51ef1269 ± 50.50efg1843 ± 4.04bc455.143 ± 147.17fghij−0.334 ± 0.102a322.299 ± 99.77defg267.377 ± 92.46defg0.479 ± 0.046a
610.16 ± 0.074ijk9.08 ± 0.049de76.8 ± 3.286abc1.63 ± 0.043ghi0.046 ± 0.004cdefg0.52 ± 0.051fg76.2 ± 0.60def3490 ± 50.48e1331 ± 101.53def1699 ± 63.63defg710.490 ± 55.29bcd−3.907 ± 0.717a444.294 ± 77.37bcd348.042 ± 69.33bcd0.377 ± 0.059bcd
79.88 ± 0.103klm8.79 ± 0.2ef75.27 ± 1.964abc1.87 ± 0.006efgh0.056 ± 0.002cd0.52 ± 0.026efg75.6 ± 0.36efg3440 ± 32.25ef1208 ± 34.65fghi1734 ± 13.45cdef330.941 ± 32.34ij−0.662 ± 0.403a201.869 ± 3.61gh163.963 ± 6.08fgh0.379 ± 0.030bcd
812.19 ± 0.041c9.07 ± 0.019de76.7 ± 2.347abc2.12 ± 0.114def0.042 ± 0.005defg0.44 ± 0.048gh76.5 ± 0.1de3424 ± 59.48ef1023 ± 29.57ijkl1747 ± 32.56cdef517.364 ± 43.95defghi−12.019 ± 0.190a331.832 ± 21.25defg316.207 ± 24.07cde0.392 ± 0.037abcd
99.77 ± 0.050lmn10.35 ± 0.135b74.79 ± 0.857abc1.30 ± 0.089i0.057 ± 0.008cd0.68 ± 0.034cd78.2 ± 0.87b2997 ± 35.44gh941 ± 117.75jkl1751 ± 34.59bcdef780.384 ± 41.04b−1.004 ± 0.402a502.311 ± 26.55ab459.876 ± 12.35ab0.408 ± 0.011abcd
1010.10 ± 0.097jkl10.4 ± 0.147b74.15 ± 1.584abc2.35 ± 0.110bcd0.006 ± 0.001j0.32 ± 0.020hi78.1 ± 0.15b3374 ± 28.57ef791 ± 4.04l1783 ± 36.91bcd825.757 ± 74.18b−1.033 ± 0.525a501.149 ± 45.78ab465.248 ± 38.09ab0.379 ± 0.014bcd
1110.46 ± 0.285ghi9.03 ± 0.2de71.76 ± 1.113abc1.78 ± 0.175fgh0.076 ± 0.008b0.64 ± 0.020cde76.7 ± 0.40cd3052 ± 20.22gh1078 ± 23.44hijk1601 ± 18.01ghi630.415 ± 36.47bcdef−45.874 ± 1.587b285.404 ± 39.10efgh232.949 ± 17.29defgh0.228 ± 0.031efg
1211.83 ± 0.051d10.56 ± 0.207b74.95 ± 2.013abc1.55 ± 0.039hi0.12 ± 0.008a0.53 ± 0.058efg77.6 ± 0.31bc3331 ± 37.10f905 ± 62.92kl1520 ± 65.90i575.252 ± 16.23cdefg−0.380 ± 0.183a353.720 ± 21.29cdef291.039 ± 26.58def0.371 ± 0.044bcd
139.46 ± 0.094n11.23 ± 0.014a79.39 ± 0.801a2.33 ± 0.190cd0 ± 0.001fj0.82 ± 0.060ab80.7 ± 0.21a2962 ± 17.62h539 ± 37.32m2061 ± 50.74a1039.629 ± 165.83a−1.441 ± 0.497a639.617 ± 110.54a525.244 ± 110.37a0.390 ± 0.009abcd
1410.37 ± 0.253hij9.73 ± 0.153c69.8 ± 1.065bc2.59 ± 0.079bc0.031 ± 0.005gh0.55 ± 0.014efg72.4 ± 0.21k2491 ± 52.16j1079 ± 57.01hijk387 ± 21.17k630.070 ± 22.03bcdef−103.183 ± 9.619d249.144 ± 15.51efgh215.052 ± 16.53defgh0.176 ± 0.020fg
159.70 ± 0.118mn9.74 ± 0.143c68.15 ± 2.619c3.93 ± 0.278a0.033 ± 0.003fgh0.48 ± 0.026fg74.4 ± 0.35hij2691 ± 69.48i1065 ± 46.32ijkl422 ± 14.98k655.698 ± 17.47bcde−73.924 ± 6.344c261.301 ± 34.55efgh222.242 ± 22.03defgh0.189 ± 0.022fg
1611.04 ± 0.013ef8.92 ± 0.21def78.07 ± 2.79ab1.98 ± 0.055defgh0.048 ± 0.004cdefg0.51 ± 0.017fg73.5 ± 0.15j3666 ± 41.58d1282 ± 42.23def1561 ± 43.92hi471.276 ± 21.33efghij−13.040 ± 1.474a263.025 ± 51.39efgh232.006 ± 42.10defgh0.313 ± 0.078de
1712.35 ± 0.067bc8.53 ± 0.258fg71.34 ± 9.82abc2.79 ± 0.119b0.046 ± 0.007cdef0.64 ± 0.043cde73.8 ± 0.21ij3478 ± 25.51ef1255 ± 11.59fgh1573 ± 6.81hi732.777 ± 17.97bc−0.958 ± 0.084a285.888 ± 9.15efgh228.509 ± 2.52defgh0.237 ± 0.014ef
1814.42 ± 0.032a7.19 ± 0.074jk74.44 ± 0.846abc2.28 ± 0.067cde0.040 ± 0.002defgh0.75 ± 0.023abc73.6 ± 0.15j4071 ± 41.88c1607 ± 54.05c1584 ± 42.93ghi465.250 ± 22.11efghij−7.602 ± 0.481a245.135 ± 20.32efgh188.748 ± 18.56efgh0.357 ± 0.011cd
1910.01 ± 0.138klm7.42 ± 0.27ij68.93 ± 1.469bc2.02 ± 0.056defg0.091 ± 0.009b0.6 ± 0.027def71.1 ± 0.36l2498 ± 58.82j1061 ± 52.56ijkl627 ± 23.69j536.816 ± 21.92cdefgh−59.164 ± 9.732bc168.578 ± 9.37h138.518 ± 7.07gh0.138 ± 0.015g
2012.63 ± 0.103b7.15 ± 0.134jk69.85 ± 4.243bc2.62 ± 0.056bc0.023 ± 0.003hi0.27 ± 0.031i71.7 ± 0.15kl4622 ± 120.09b2918 ± 81.07b1664 ± 43.51defgh375.310 ± 58.96hij−65.696 ± 17.021c155.624 ± 17.28h126.917 ± 16.68h0.189 ± 0.028fg
2110.47 ± 0.084ghi7.91 ± 0.154hi71.92 ± 0.851abc1.73 ± 0.091fghi0.014 ± 0.013ij0.46 ± 0.021g72.0 ± 0.60kl4999 ± 47.08a2655 ± 122.41a1642 ± 63.98fghi315.927 ± 88.82j−0.281 ± 0.173a217.263 ± 61.70fgh204.781 ± 56.77efgh0.448 ± 0.009abc

Different letters in the same column indicate significant difference ().

The moisture and tannin in sorghum were 9.46%∼14.42% and 0.00%∼0.12%, respectively. Water can bind to macromolecules such as protein and starch, which has an important effect on starch gelatinization and edible quality of cereals. Especially, the content of tannin in No. 13 was 0, which may have a positive effect on the good taste quality of sorghum rice. The range of the oil content was 1.30%∼3.93%, with the highest content in No. 15 Sorghum of 3.93%, which was much higher than that in rice (0.24%∼0.67%). The oil in sorghum can improve the edible quality of rice and give the special flavor of rice. However, the oil forms the complex with starch, which inhibits the gelatinization of starch and affects the taste quality of rice [36].

3.2. Pasting Properties

The significant differences in pasting properties among different varieties are shown in Table 2 (). Gelatinization is one of the physicochemical properties of starch, and it is an important indicator to determine the cooking quality and edible quality of rice. The PT of 21 sorghum varieties ranged from 71.1°C to 80.7°C, and the PT of sorghum from Jilin (74.8°C∼80.7°C) was significantly higher than that of Heilongjiang (71.1°C∼74.4°C) (), which indicated that sorghum from Jilin was not easy to gelatinize. Compared to the analysis of protein content in different sorghum varieties, the protein content of sorghum planted in Jilin was generally high, which was consistent with the results of Chandrashekar and Kirleis [37] that higher protein content would inhibit gelatinization of sorghum starch [37, 38].

The PV of 21 sorghum varieties was concentrated in the range of 3000∼4000 cP, while the PV of sorghum varieties Nos. 14, 15, and 19 from Heilongjiang was 2491 cP, 2691 cP, and 2498 cP, respectively, which were much lower than that of other varieties. The results indicated that the starch granules of the three varieties were easy to expand during cooking and gelatinization and easy to be softened and break during the thickening process [39].

The BD is a measure of the difficulty of particle structure disintegration in the heating process of starch [40]. The BD varied from 539 cP to 2918 cP, which indicated that the effect of starch on the taste quality of sorghum was different. The SB of different varieties varied widely, ranging from 387 to 2061 cP. The SB of sorghum varieties Nos. 14, 15, and 19 was 387 cP, 422 cP, and 627 cP, respectively, while the SB of other sorghum varieties was above 1500 cP. This may be related to the starch content; that is, the varieties with a lower amylose content have lower SB. After cooking and gelatinization, the aging rate of starch is slower, and the taste quality of rice is better [29].

3.3. Cooking Characteristics

The significant differences in volume expansion ratio, water absorption rate, and iodide blue value among different varieties () are shown in Figure 1. It can be seen from Figures 1(a) and 1(b) that the volume expansion ratio and the water absorption rate of Nos. 4, 8, 9, and 12 were 270.85%, 276.23%, 288.23%, and 279.28% and 242.95%, 242.19%, 241.86%, and 236.52%, respectively, which were significantly higher than other varieties (). The water absorption rate and the volume expansion ratio of rice grains were the important indicators of cooking characteristics. And the bigger the grains are, the higher the fluffy quality of rice is; more likely, it was that rice grains appear to explode [15]. So that the acceptability of Nos. 4, 8, 9, and 12 with high water absorption rate and volume expansion ratio may be poor (Table 1). It could be seen from Figure 1(c) that the iodine blue value of sorghum ranged from 0.071 to 1.561, and most of the varieties were concentrated in the range of 0.650 to 0.850. However, the iodine blue value of Nos. 14, 15, 19, 20, and 21 in Heilongjiang was 0.122, 0.123, 0.297, 0.161, and 0.071, respectively, which were significantly lower than those of other varieties (). At the same time, compared with Table 3, it was found that the PV and SB of Nos. 14, 15, and 19 with a lower iodine blue value were also significantly lower than other sorghum varieties (). It indicated that the starch granules of these varieties were easily to be broken, easy to gelatinize, and not easy to regenerate during the cooking process and with better edible quality. Some studies have shown that the cooking quality of sorghum was mainly affected by the composition and gelation of starch. The gelation humidity of amylose is high, so that the water absorption and the expansion rate was large, which led to the dryness of cooked rice. Meanwhile, the more the amylose content, the more the starch content dissolved in the cooking process, resulting in the larger iodine blue value of soup and the worse grain integrity and acceptability (stickiness and elasticity) of sorghum rice [41]. On the contrary, the sorghum rice with more amylopectin content was wet, and the taste was better [42].

Individual variableF1F2F3F4F5


3.4. Textural Characteristics

The significant differences in textural properties among different varieties () are shown in Table 2. The hardness of sorghum rice ranged from 315.93 to 1039.63 g, and most of the varieties were concentrated in the range of 300 g to 600 g. It was not difficult to find that the stickiness of 21 varities of sorghum is generally very low, only the Jilin No. 11 and Heilongjiang Nos. 14, 15, 19, and 20 with higher stickiness, which are −45.874 g·m−1, −103.183 g·m−1, −73.924 g·m−1, −59.164 g·m−1, and −65.696 g·m−1, respectively. The stickiness of No. 14 was the highest, which was significantly higher than that of other sorghum varieties (). Stickiness of rice was related to the composition of starch; that is, the varieties with a lower amylose content have higher stickiness [43]. The results also verified the experimental iodine blue value; that is, in sorghum varieties with a low iodine blue value, the rice soup will be more viscous, steamed rice stickiness was higher, and acceptability was better [44]. The hardness and stickiness were the main indicators to evaluate the quality of sorghum rice. The rice with a lower hardness and higher stickiness had shorter cooking time and better taste quality [15]. The chewiness is a comprehensive embodiment of adhesiveness and elasticity, which is related to the content of protein and starch [45]. No. 13, for example, which has the highest chewiness and adhesiveness, also has the highest protein content. In addition, there were significant differences in responsiveness among different varieties ().

3.5. Principal Component Analysis

The PCA was carried out with 18 quality indexes of 21 sorghum varieties, including moisture, protein, starch, fat, tannin, ash, iodine blue value, expansion volume, water absorption rate, PT, PV, BD, SB, hardness, stickiness, adhesiveness, chewiness, and responsiveness which were expressed by X1X18, respectively.

A scree plot that identifies the major groups of variables was done. The scree plot is shown in Figure 2. The first five principal components F1F5 had a high total variability equal to 86.19% and were considered representative of the data and further investigated. The component F1 is clearly the most significant principal component.

CR (%)CCR (%)CR (%)CCR (%)CR (%)CCR (%)CR (%)CCR (%)CR (%)CCR (%)


The loadings of the individual variables in each PC were done (Table 3), in order to investigate the correlations among the five main variables F1F5 and their components. The contribution rate of each index variable Xi to Fj was calculated and sorted. The first n index variables with a cumulative contribution rate of more than 85% to Fj were selected for the interpretation and analysis of Fj [46]. The results are shown in Table 4. Combining Tables 3 and 4, it could be seen that X16, X17, X10, X3, X2, X8, X14, X18, X15, X12, and X13 were grouped within F1 and can be treated as one variable. And so on, the relationship between other variables and principal components could be obtained. Among them, F1 mainly synthesized the variation information of protein content X2, starch content X3, PT X10, adhesiveness X16, and chewiness X17 with the variance of 0.54, 0.63, 0.81, 0.86, and 0.83, respectively, which were more than 50% and related to the texture of sorghum rice. F2 was mainly characterized in PV X11, SD X12, SB X13, hardness X14, and stickiness X15, which were related to the change of the gelatinization property in the sorghum cooking process. The tannin content X5 and ash content X6 have the largest contribution rate to F3, while the high tannin content will produce bitter taste, mainly affecting the flavor of sorghum. Volume expansion ratio X8 and water absorption ratio X9 are the main contribution variables to F4, which were related to cooking characteristics. The moisture X1 and iodine blue value X7 have the largest contribution rate to F5, and these two indexes were related to the waxy and nonwaxy varieties of sorghum. Therefore, F5 mainly reflected the quality of sorghum varieties.

Individual variablePrincipal component function


According to the results of PCA, the eigenvectors of the five PC were further calculated, as shown in Table 5. Then, the linear relationship was obtained as follows:

21 kinds of sorghum were evaluated by the equation, and the two varieties with the highest score were No. 14 and No. 15 cultivated in Heilongjiang.

Finally, in order to verify the accuracy and practicability of the equation, the sensory evaluation was taken as the ordinate and the comprehensive evaluation equation as the horizontal coordinate, and the linear regression analysis was used to verify the edible quality of sorghum rice. The formula was obtained, as follows:and the fitting coefficient was greater than 0.80, which indicated that the equation can accurately evaluate the edible quality of sorghum rice.

4. Conclusions

One-way ANOVA analysis of 18 indicators of 21 kinds of sorghum from the Northeast China revealed that there were significant differences among the quality characteristics of different varieties. Meanwhile, it could be seen that there were regional differences of the starch content, protein content, and PT. And the above indicators of sorghum varieties from Heilongjiang are generally lower than those from Jilin. Then, five principal components with a cumulative contribution rate of 86.19% could be picked out by PCA to describe the taste, pasting, flavor, cooking, and variety of sorghum, respectively. According to the results of PCA, a comprehensive equation was constructed, which is Z = 0.45F1 + 0.25F2 + 0.12F3 + 0.10F4 + 0.08F5, and two sorghum varieties with the highest score were obtained: No. 14 and No. 15. Meanwhile, the sensory quality analysis was used to verify the equation with the fitting coefficient of 0.81 (>0.80), which indicated that the five principal components (F1F5) could be more accurate to evaluate the edible quality of sorghum.

Data Availability

The data used to support the findings of this study are included within the article.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent was obtained from all individual participants included in the study.

Conflicts of Interest

The authors declare that there are no conflicts of interest.


The authors are thankful to Jilin Academy of Agricultural Sciences (Jilin Province, China) and Heilongjiang Academy of Agricultural Sciences (Heilongjiang Province, China) for providing sorghum varieties. This study was funded by the Project of National Key Technology Research and Development Program from the 13th Five-Year Plan (grant no. 2017YFD0401204).


  1. Food and Agricultural Organization, Food and Agriculture Organization Corporate Statistical Database (Faostat), Food and Agricultural Organization, Rome, Italy, 2010.
  2. L. D. Moraiscardoso, S. S. Pinheiro, H. S. D. Martino, and H. M. A. Pinheiro-Sant, “Sorghum (Sorghum bicolor L.): nutrients, bioactive compounds, and potential impact on human health,” Critical Reviews in Food Science and Nutrition, vol. 57, no. 2, pp. 372–390, 2015. View at: Publisher Site | Google Scholar
  3. J. Taylor and P. Shewry, “Preface to sorghum and millets reviews,” Journal of Cereal Science, vol. 44, no. 3, p. 223, 2006. View at: Publisher Site | Google Scholar
  4. J. W. Vargas-Solórzano, C. W. P. Carvalho, C. Y. Takeiti, J. L. R. Ascheri, and V. A. V. Queiroz, “Physicochemical properties of expanded extrudates from colored sorghum genotypes,” Food Research International, vol. 55, pp. 37–44, 2014. View at: Publisher Site | Google Scholar
  5. A. E.-M. M. R. Afify, H. S. El-Beltagi, S. M. A. El-Salam, and A. A. Omran, “Bioavailability of iron, zinc, phytate and phytase activity during soaking and germination of white sorghum varieties,” PLoS One, vol. 6, no. 10, Article ID e25512, 2011. View at: Publisher Site | Google Scholar
  6. A. Akinfemi, O. A. Adu, and F. Doherty, “Conversion of sorghum stover into animal feed with white-rot fungi: Pleurotus ostreatus and Pleurotus pulmonarius,” African Journal of Biotechnology, vol. 9, no. 11, pp. 1706–1712, 2010. View at: Google Scholar
  7. V. Taleon, L. Dykes, W. L. Rooney, and L. W. Rooney, “Effect of genotype and environment on flavonoid concentration and profile of black sorghum grains,” Journal of Cereal Science, vol. 56, no. 2, pp. 470–475, 2012. View at: Publisher Site | Google Scholar
  8. Q. Peng, R. Tian, F. Chen, B. Li, and H. Gao, “Discrimination of producing area of Chinese Tongshan kaoliang spirit using electronic nose sensing characteristics combined with the chemometrics methods,” Food Chemistry, vol. 178, pp. 301–305, 2015. View at: Publisher Site | Google Scholar
  9. K. Wilkie, M. Wootton, and J. E. Paton, “Sensory testing of Australian fragrant, imported fragrant, and non-fragrant rice aroma,” International Journal of Food Properties, vol. 7, no. 1, pp. 27–36, 2004. View at: Publisher Site | Google Scholar
  10. A. M. Odenigbo, M. Ngadi, C. Ejebe, N. Woin, and S. A. Ndindeng, “Physicochemical, cooking characteristics and textural properties of TOX 3145 milled rice,” Journal of Food Research, vol. 3, no. 2, p. 82, 2014. View at: Publisher Site | Google Scholar
  11. M. Okabe, “Texture measurement of cooked rice and its relationship to the eating quality,” Journal of Texture Studies, vol. 10, no. 2, pp. 131–152, 2010. View at: Publisher Site | Google Scholar
  12. E. T. Champagne, K. L. Bett, B. T. Vinyard et al., “Correlation between cooked rice texture and rapid visco analyser measurements,” Cereal Chemistry Journal, vol. 76, no. 5, pp. 764–771, 1999. View at: Publisher Site | Google Scholar
  13. Y. Guo, F. LI, Y. Hong, and Y. Liu, “Study on the correlation between properties of rice and the quality of cooked rice,” Journal of Wuhan Polytechnic University, vol. 34, no. 3, pp. 1–6, 2015. View at: Google Scholar
  14. X.-Z. Han and B. R. Hamaker, “Amylopectin fine structure and rice starch paste breakdown,” Journal of Cereal Science, vol. 34, no. 3, pp. 279–284, 2001. View at: Publisher Site | Google Scholar
  15. D. Mohapatra and S. Bal, “Cooking quality and instrumental textural attributes of cooked rice for different milling fractions,” Journal of Food Engineering, vol. 73, no. 3, pp. 253–259, 2006. View at: Publisher Site | Google Scholar
  16. S. J. Bhonsle and K. Sellappan, “Grain quality evaluation of traditionally cultivated rice varieties of Goa, India,” Recent Research in Science and Technology, vol. 2, no. 3, pp. 88–97, 2010. View at: Publisher Site | Google Scholar
  17. S. K. Jain and P. R. Patel, “Principal component and cluster analysis in sorghum (Sorghum bicolor (L.) Moench),” Forage Research, vol. 42, pp. 90–95, 2016. View at: Google Scholar
  18. C. Mestres, F. Ribeyre, B. Pons, V. Fallet, and F. Matencio, “Sensory texture of cooked rice is rather linked to chemical than to physical characteristics of raw grain,” Journal of Cereal Science, vol. 53, no. 1, pp. 81–89, 2011. View at: Publisher Site | Google Scholar
  19. M. Osawa and N. Inoue, “Principal component analysis of starch digestibility and physicochemical properties related to texture of rice (quality and processing),” Japanese Journal of Crop Science, vol. 77, no. 1, pp. 61–68, 2008. View at: Publisher Site | Google Scholar
  20. H. Li, X. Li, Z. Ma, J. Li, X. Hu, and C. Ren, “Relationships between oat kernel,physicochemical and processing parameters,” Journal of Triticeae Crops, vol. 35, pp. 499–507, 2015. View at: Google Scholar
  21. Y. Liu, J. Song, D. LI, C. Liu, and B. Jin, “Principal component analysis during variety screening for instant corn,” Food Science, vol. 31, pp. 71–73, 2010. View at: Google Scholar
  22. L. Lu and Z. Zhu, “Prediction model for eating property of Indica rice,” Journal of Food Quality, vol. 37, no. 4, pp. 274–280, 2014. View at: Publisher Site | Google Scholar
  23. L. Wang, Y. Liu, and S. Zhao, “Quality improvement and evaluation model of rice cake,” Journal of the Chinese Cereals and Oils Association, vol. 31, no. 5, 2016. View at: Google Scholar
  24. M. Zhu, N. Xiong, H. Liu et al., “Establishment of models to evaluate the eating quality and comprehensive quality of Indica rice,” Food Science, vol. 37, pp. 97–103, 2016. View at: Google Scholar
  25. E. D. Maxson and L. W. Rooney, “Evaluation of methods for tannin analysis in sorghum grain,” Cereal Chemistry, vol. 49, no. 6, pp. 719–729, 1972. View at: Google Scholar
  26. J. Bao, “Accurate measurement of pasting temperature by the rapid visco-analyser: a case study using rice flour,” Rice Science, vol. 15, no. 1, pp. 69–72, 2018. View at: Publisher Site | Google Scholar
  27. Z. Wang, Quality Analysis of Grain, Oil and Food, China Light Industry Press, Beijing China, 2000.
  28. C. Liu, Y. Sun, D. Wang et al., “Performance and mechanism of low-frequency ultrasound to regenerate the biological activated carbon,” Ultrasonics Sonochemistry, vol. 34, pp. 142–153, 2017. View at: Publisher Site | Google Scholar
  29. S. Yu, Y. Ma, and D.-W. Sun, “Impact of amylose content on starch retrogradation and texture of cooked milled rice during storage,” Journal of Cereal Science, vol. 50, no. 2, pp. 139–144, 2009. View at: Publisher Site | Google Scholar
  30. M. Góral, K. Kozłowicz, U. Pankiewicz, D. Góral, F. Kluza, and A. Wójtowicz, “Impact of stabilizers on the freezing process, and physicochemical and organoleptic properties of coconut milk-based ice cream,” LWT, vol. 92, pp. 516–522, 2018. View at: Publisher Site | Google Scholar
  31. A. Kurt and I. Atalar, “Effects of quince seed on the rheological, structural and sensory characteristics of ice cream,” Food Hydrocolloids, vol. 82, pp. 186–195, 2018. View at: Publisher Site | Google Scholar
  32. F. Artoni, A. Delorme, and S. Makeig, “Applying dimension reduction to EEG data by principal component analysis reduces the quality of its subsequent independent component decomposition,” NeuroImage, vol. 175, pp. 176–187, 2018. View at: Publisher Site | Google Scholar
  33. M. Zhang and H. Liu, “Assessment model of taste quality of millet based on principal component analysis method,” Journal of Northeast Agricultural University, vol. 42, pp. 7–12, 2011. View at: Google Scholar
  34. H. Wang, Research on Cooking Characteristics Andimproved Technology of Coix Seed, Southwest University, Chongqing, China, 2014.
  35. W. Srisawas and V. K. Jindal, “Sensory evaluation of cooked rice in relation to water-to-rice ratio and physicochemical properties,” Journal of Texture Studies, vol. 38, no. 1, pp. 21–41, 2010. View at: Publisher Site | Google Scholar
  36. K. Larsson, “Inhibition of starch gelatinization by amylose-lipid complex formation. Behinderung der Stärkeverkleisterung durch Bildung eines Amylose-Lipidkomplexes,” Starch-Stärke, vol. 32, no. 4, pp. 125-126, 1980. View at: Publisher Site | Google Scholar
  37. A. Chandashekar and A. W. Kirleis, “Influence of protein on starch gelatinization in sorghum,” Cereal Chemistry, vol. 65, pp. 457–462, 1988. View at: Google Scholar
  38. X. Mo, D. Qu, and J. Han, “Study on japonica rice starch and its gelatinization properties and edible quality of cooked rice,” Science & Technology of Food Industry, 2014. View at: Google Scholar
  39. X. Zhou, J. Sun, Y. Zhang, Y. Liu, and J. Gao, “Relationships between three-point bending mechanical properties with cooking and edible quality of rice,” Modern Food Science & Technology, vol. 32, pp. 35–41, 2016. View at: Google Scholar
  40. P. Leelayuthsoontorn and A. Thipayarat, “Textural and morphological changes of Jasmine rice under various elevated cooking conditions,” Food Chemistry, vol. 96, no. 4, pp. 606–613, 2006. View at: Publisher Site | Google Scholar
  41. K. Cheng, Physicochemical Characteristics and Molecular Structure and Their Correlation in Rice Starch, Huazhong Agricultural University, Wuhan, China, 2006.
  42. X. Tian, B. Tan, H. Tian, and M. Liu, “Properties of sorghum starches from twenty varieties in China,” Food Science, vol. 31, pp. 13–20, 2010. View at: Google Scholar
  43. C. E. Chávez-Murillo, Y.-J. Wang, A. G. Quintero-Gutierrez, and L. A. Bello-Pérez, “Physicochemical, textural, and nutritional characterization of Mexican rice cultivars,” Cereal Chemistry Journal, vol. 88, no. 3, pp. 245–252, 2011. View at: Publisher Site | Google Scholar
  44. X. Zhou, Study on Eating Qualities Analysis and Comprehensive Evaluation of Rice with Different Milling Degree, College of Life Sciences and Food Engineering, Nanchang University Nanchang, Nanchang, China, 2013.
  45. T. Huang, W. Wu, G. LI, and X. Feng, “Research on relativity between rice’s physical-chemical properties and mouth-feel quality,” Food and Nutrition in China, vol. 18, pp. 24–28, 2012. View at: Google Scholar
  46. F. Zhao, Quality Analyses of Oat Varieties and Processing Suitability for Oats Fermented Milk Graduate School of Agricultural Products Processing Institute, Chinese Academy of Agricultural Sciences Dissertation, Beijing, China, 2016.

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