Journal of Chemistry
Volume 2019 (2019), Article ID 2013109, 10 pages
https://doi.org/10.1155/2019/2013109

Research Article

Evaluation of Edible Quality of Sorghum Based on Principal Component Analysis

Chunlei Ni,¹ Shan Zhang,¹ Gaopeng Zhang,¹ Jianjun Cheng,¹ and Huanyu Zheng1,2,3

¹College of Food Science, Northeast Agricultural University, Harbin 150030, China
²Heilongjiang Green Food Science Research Institute, Harbin 150028, China
³National Research Center of Soybean Engineering and Technology, Harbin 150028, China

Correspondence should be addressed to Jianjun Cheng; jjcheng@neau.edu.cn and Huanyu Zheng; zhenghuanyu1@163.com

Received 14 June 2019; Accepted 5 September 2019; Published 24 September 2019

Academic Editor: João Paulo Leal

Copyright © 2019 Chunlei Ni et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

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 [5–7]. 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 [13–15]. 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 [22–24]. 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 (TA.XT.plus, 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.

Table 1: The sensory evaluation of sorghum rice.

Variety
Smell (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)

1
14.00
5.50
5.00
4.50
5.50
5.00
6.50
18.00
3.80
67.80

2
16.20
5.65
6.50
3.30
6.00
6.00
7.50
18.00
3.80
72.95

3
15.00
5.00
5.25
4.25
5.40
4.50
6.50
17.50
3.50
66.90

4
16.40
4.50
6.80
3.60
5.60
4.50
6.20
18.00
3.00
68.60

5
16.50
5.00
4.80
4.30
5.50
5.00
7.20
17.00
3.75
69.05

6
13.60
4.50
5.80
3.20
5.75
4.00
6.30
19.00
3.50
65.65

7
13.65
3.80
5.75
3.50
6.80
5.50
7.20
18.00
3.50
67.70

8
13.80
6.00
5.75
3.00
6.50
4.50
6.50
18.00
3.50
67.55

9
15.00
4.50
5.00
3.50
5.80
5.50
6.00
17.50
4.00
66.80

10
16.40
5.60
5.25
4.25
4.50
5.00
5.80
18.00
3.35
68.15

11
15.00
4.50
5.30
3.30
4.20
5.50
6.50
16.50
3.90
64.70

12
15.00
5.00
5.40
3.40
4.00
5.50
6.50
16.50
3.50
64.80

13
16.70
6.80
5.60
4.30
3.80
3.00
6.20
17.00
2.85
66.25

14
15.00
4.50
7.00
4.80
8.20
6.50
8.50
20.00
4.50
79.00

15
17.00
4.50
7.00
4.80
8.25
7.00
8.20
21.00
4.50
82.25

16
16.50
5.00
6.50
4.30
6.00
6.00
7.50
18.50
3.75
74.05

17
15.00
5.85
5.30
3.80
6.00
4.75
6.50
17.00
3.50
67.70

18
14.00
6.20
7.00
2.80
5.80
4.00
8.00
16.50
3.80
68.10

19
14.60
4.00
6.80
4.30
8.30
6.00
7.25
19.00
4.85
75.10

20
14.50
6.70
6.50
3.40
7.80
7.00
8.75
18.00
4.50
77.15

21
14.50
6.60
5.70
4.00
7.50
5.50
7.50
20.00
3.50
74.80

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].

Table 2: Physicochemical components, pasting properties, and textual properties of sorghum.

Variety
Moisture (%)
Protein (%)
Starch (%)
Oil (%)
Tannin (%)
Ash (%)
PT (°C)
PV (cP)
BD (cP)
SB (cP)
Hardness (g)
Stickiness (g·m⁻¹)
Adhesiveness
Chewiness
Responsiveness

1
10.05 ± 0.034jklm
8.28 ± 0.230gh
70.81 ± 1.136abc
1.83 ± 0.155efgh
0.049 ± 0.005cdef
0.53 ± 0.075efg
75.7 ± 0.26defg
3749 ± 33.56d
1451 ± 13.05cde
1875 ± 20.66b
429.770 ± 55.52ghij
−10.174 ± 0.157a
266.177 ± 37.68efgh
258.076 ± 41.87defgh
0.365 ± 0.030 cd

2
11.19 ± 0.076e
6.75 ± 0.114k
69.49 ± 0.929bc
2.25 ± 0.250cde
0.038 ± 0.006efgh
0.44 ± 0.047gh
75.2 ± 0.23fgh
3801 ± 86.32d
1462 ± 67.73 cd
1770 ± 50.51bcde
386.419 ± 57.27ghij
−1.497 ± 0.371a
229.890 ± 29.32efgh
211.348 ± 29.90efgh
0.353 ± 0.010 cd

3
10.61 ± 0.064gh
9.80 ± 0.161c
72.86 ± 1.872abc
1.84 ± 0.207dfgh
0.053 ± 0.007cde
0.81 ± 0.040ab
76.0 ± 0.15def
3059 ± 22.65gh
1151 ± 23.50fghi
1651 ± 63.13efgh
529.797 ± 31.45defghi
−0.796 ± 0.559a
368.286 ± 19.25bcde
313.355 ± 20.22cde
0.450 ± 0.025abc

4
10.75 ± 0.033 fg
9.39 ± 0.108cd
77.21 ± 0.925abc
2.58 ± 0.183bc
0.058 ± 0.004c
0.7 ± 0.032bcd
76.7 ± 0.32cde
3135 ± 35.92g
1093 ± 15.01ghij
1744 ± 12.53cdef
689.326 ± 38.83bcd
−0.644 ± 0.373a
482.189 ± 27.29bc
440.334 ± 15.82abc
0.469 ± 0.017ab

5
10.38 ± 0.122hij
8.97 ± 0.014def
71.36 ± 5.129abc
2.23 ± 0.212cde
0.088 ± 0.006b
0.85 ± 0.069a
74.8 ± 0.10ghi
3462 ± 30.51ef
1269 ± 50.50efg
1843 ± 4.04bc
455.143 ± 147.17fghij
−0.334 ± 0.102a
322.299 ± 99.77defg
267.377 ± 92.46defg
0.479 ± 0.046a

6
10.16 ± 0.074ijk
9.08 ± 0.049de
76.8 ± 3.286abc
1.63 ± 0.043ghi
0.046 ± 0.004cdefg
0.52 ± 0.051fg
76.2 ± 0.60def
3490 ± 50.48e
1331 ± 101.53def
1699 ± 63.63defg
710.490 ± 55.29bcd
−3.907 ± 0.717a
444.294 ± 77.37bcd
348.042 ± 69.33bcd
0.377 ± 0.059bcd

7
9.88 ± 0.103klm
8.79 ± 0.2ef
75.27 ± 1.964abc
1.87 ± 0.006efgh
0.056 ± 0.002cd
0.52 ± 0.026efg
75.6 ± 0.36efg
3440 ± 32.25ef
1208 ± 34.65fghi
1734 ± 13.45cdef
330.941 ± 32.34ij
−0.662 ± 0.403a
201.869 ± 3.61gh
163.963 ± 6.08fgh
0.379 ± 0.030bcd

8
12.19 ± 0.041c
9.07 ± 0.019de
76.7 ± 2.347abc
2.12 ± 0.114def
0.042 ± 0.005defg
0.44 ± 0.048gh
76.5 ± 0.1de
3424 ± 59.48ef
1023 ± 29.57ijkl
1747 ± 32.56cdef
517.364 ± 43.95defghi
−12.019 ± 0.190a
331.832 ± 21.25defg
316.207 ± 24.07cde
0.392 ± 0.037abcd

9
9.77 ± 0.050lmn
10.35 ± 0.135b
74.79 ± 0.857abc
1.30 ± 0.089i
0.057 ± 0.008cd
0.68 ± 0.034cd
78.2 ± 0.87b
2997 ± 35.44gh
941 ± 117.75jkl
1751 ± 34.59bcdef
780.384 ± 41.04b
−1.004 ± 0.402a
502.311 ± 26.55ab
459.876 ± 12.35ab
0.408 ± 0.011abcd

10
10.10 ± 0.097jkl
10.4 ± 0.147b
74.15 ± 1.584abc
2.35 ± 0.110bcd
0.006 ± 0.001j
0.32 ± 0.020hi
78.1 ± 0.15b
3374 ± 28.57ef
791 ± 4.04l
1783 ± 36.91bcd
825.757 ± 74.18b
−1.033 ± 0.525a
501.149 ± 45.78ab
465.248 ± 38.09ab
0.379 ± 0.014bcd

11
10.46 ± 0.285ghi
9.03 ± 0.2de
71.76 ± 1.113abc
1.78 ± 0.175fgh
0.076 ± 0.008b
0.64 ± 0.020cde
76.7 ± 0.40cd
3052 ± 20.22gh
1078 ± 23.44hijk
1601 ± 18.01ghi
630.415 ± 36.47bcdef
−45.874 ± 1.587b
285.404 ± 39.10efgh
232.949 ± 17.29defgh
0.228 ± 0.031efg

12
11.83 ± 0.051d
10.56 ± 0.207b
74.95 ± 2.013abc
1.55 ± 0.039hi
0.12 ± 0.008a
0.53 ± 0.058efg
77.6 ± 0.31bc
3331 ± 37.10f
905 ± 62.92kl
1520 ± 65.90i
575.252 ± 16.23cdefg
−0.380 ± 0.183a
353.720 ± 21.29cdef
291.039 ± 26.58def
0.371 ± 0.044bcd

13
9.46 ± 0.094n
11.23 ± 0.014a
79.39 ± 0.801a
2.33 ± 0.190cd
0 ± 0.001fj
0.82 ± 0.060ab
80.7 ± 0.21a
2962 ± 17.62h
539 ± 37.32m
2061 ± 50.74a
1039.629 ± 165.83a
−1.441 ± 0.497a
639.617 ± 110.54a
525.244 ± 110.37a
0.390 ± 0.009abcd

14
10.37 ± 0.253hij
9.73 ± 0.153c
69.8 ± 1.065bc
2.59 ± 0.079bc
0.031 ± 0.005gh
0.55 ± 0.014efg
72.4 ± 0.21k
2491 ± 52.16j
1079 ± 57.01hijk
387 ± 21.17k
630.070 ± 22.03bcdef
−103.183 ± 9.619d
249.144 ± 15.51efgh
215.052 ± 16.53defgh
0.176 ± 0.020fg

15
9.70 ± 0.118mn
9.74 ± 0.143c
68.15 ± 2.619c
3.93 ± 0.278a
0.033 ± 0.003fgh
0.48 ± 0.026fg
74.4 ± 0.35hij
2691 ± 69.48i
1065 ± 46.32ijkl
422 ± 14.98k
655.698 ± 17.47bcde
−73.924 ± 6.344c
261.301 ± 34.55efgh
222.242 ± 22.03defgh
0.189 ± 0.022fg

16
11.04 ± 0.013ef
8.92 ± 0.21def
78.07 ± 2.79ab
1.98 ± 0.055defgh
0.048 ± 0.004cdefg
0.51 ± 0.017fg
73.5 ± 0.15j
3666 ± 41.58d
1282 ± 42.23def
1561 ± 43.92hi
471.276 ± 21.33efghij
−13.040 ± 1.474a
263.025 ± 51.39efgh
232.006 ± 42.10defgh
0.313 ± 0.078de

17
12.35 ± 0.067bc
8.53 ± 0.258fg
71.34 ± 9.82abc
2.79 ± 0.119b
0.046 ± 0.007cdef
0.64 ± 0.043cde
73.8 ± 0.21ij
3478 ± 25.51ef
1255 ± 11.59fgh
1573 ± 6.81hi
732.777 ± 17.97bc
−0.958 ± 0.084a
285.888 ± 9.15efgh
228.509 ± 2.52defgh
0.237 ± 0.014ef

18
14.42 ± 0.032a
7.19 ± 0.074jk
74.44 ± 0.846abc
2.28 ± 0.067cde
0.040 ± 0.002defgh
0.75 ± 0.023abc
73.6 ± 0.15j
4071 ± 41.88c
1607 ± 54.05c
1584 ± 42.93ghi
465.250 ± 22.11efghij
−7.602 ± 0.481a
245.135 ± 20.32efgh
188.748 ± 18.56efgh
0.357 ± 0.011cd

19
10.01 ± 0.138klm
7.42 ± 0.27ij
68.93 ± 1.469bc
2.02 ± 0.056defg
0.091 ± 0.009b
0.6 ± 0.027def
71.1 ± 0.36l
2498 ± 58.82j
1061 ± 52.56ijkl
627 ± 23.69j
536.816 ± 21.92cdefgh
−59.164 ± 9.732bc
168.578 ± 9.37h
138.518 ± 7.07gh
0.138 ± 0.015g

20
12.63 ± 0.103b
7.15 ± 0.134jk
69.85 ± 4.243bc
2.62 ± 0.056bc
0.023 ± 0.003hi
0.27 ± 0.031i
71.7 ± 0.15kl
4622 ± 120.09b
2918 ± 81.07b
1664 ± 43.51defgh
375.310 ± 58.96hij
−65.696 ± 17.021c
155.624 ± 17.28h
126.917 ± 16.68h
0.189 ± 0.028fg

21
10.47 ± 0.084ghi
7.91 ± 0.154hi
71.92 ± 0.851abc
1.73 ± 0.091fghi
0.014 ± 0.013ij
0.46 ± 0.021g
72.0 ± 0.60kl
4999 ± 47.08a
2655 ± 122.41a
1642 ± 63.98fghi
315.927 ± 88.82j
−0.281 ± 0.173a
217.263 ± 61.70fgh
204.781 ± 56.77efgh
0.448 ± 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].

(a)

(b)

(c)

Figure 1: Cooking characteristics of sorghum: (a) water absorption rate; (b) volume expansion ratio; (c) iodine blue value.

Table 3: The loadings of the individual variables as calculated during PCA.

Individual variable
F₁
F₂
F₃
F₄
F₅

X₁
−0.250
0.563
−0.176
0.289
0.631

X₂
0.733
−0.503
0.075
0.094
−0.129

X₃
0.796
0.264
0.043
0.114
0.134

X₄
−0.367
−0.480
0.323
0.138
0.490

X₅
0.058
0.050
−0.902
0.027
−0.276

X₆
0.430
−0.139
−0.429
−0.457
0.219

X₇
0.489
0.450
−0.388
−0.045
0.525

X₈
0.675
0.253
−0.129
0.614
−0.080

X₉
0.400
0.394
−0.134
0.741
−0.208

X₁₀
0.900
−0.120
0.105
−0.062
−0.039

X₁₁
−0.270
0.842
0.411
−0.025
−0.012

X₁₂
−0.625
0.590
0.351
0.121
−0.138

X₁₃
0.570
0.673
0.205
−0.229
−0.010

X₁₄
0.666
−0.578
0.175
0.164
0.236

X₁₅
0.641
0.604
−0.003
−0.327
0.017

X₁₆
0.926
−0.215
0.241
0.020
0.040

X₁₇
0.913
−0.191
0.284
0.035
−0.016

X₁₈
0.648
0.496
0.114
−0.348
−0.171

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 X₁–X₁₈, 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 F₁–F₅ 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.

Figure 2: Scree plot of the eigenvalues of PCA.

Table 4: Contribution rate (CR) and cumulative contribution rate (CCR) of individual variables (IV) to PC.

IV
F₁
IV
F₂
IV
F₃
IV
F₄
IV
F₅

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

X₁₆
12.30
12.30
X₁₁
18.35
18.35
X₅
43.89
43.89
X₉
34.53
34.53
1
32.38
32.38

X₁₇
11.94
24.24
X₁₃
11.72
30.07
X₆
9.92
53.81
X₈
23.74
58.27
7
22.41
54.79

X₁₀
11.62
35.86
X₁₅
9.44
39.50
X₁₁
9.12
62.93
X₆
13.14
71.41
4
19.51
74.30

X₃
9.08
44.94
X₁₂
9.01
48.51
X₇
8.14
71.07
X₁₈
7.61
79.02
5
6.20
80.50

X₂
7.71
52.65
X₁₄
8.63
57.15
X₁₂
6.65
77.72
X₁₅
6.73
85.74
14
4.54
85.04

X₈
6.54
59.18
X₁
8.20
65.34
X₄
5.62
83.33

X₁₄
6.35
65.53
X₂
6.54
71.89
X₁₇
4.37
87.70

X₁₈
6.02
71.56
X₁₈
6.37
78.26

X₁₅
5.90
77.45
X₄
5.96
84.22

X₁₂
5.59
83.05
X₇
5.24
89.46

X₁₃
4.66
87.71

The loadings of the individual variables in each PC were done (Table 3), in order to investigate the correlations among the five main variables F₁–F₅ 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.

Table 5: Eigenvector of primary components.

Individual variable
Principal component function

F₁
F₂
F₃
F₄
F₅

X₁
−0.095
0.286
−0.129
0.229
0.569

X₂
0.278
−0.256
0.055
0.074
−0.116

X₃
0.301
0.134
0.031
0.090
0.121

X₄
−0.139
−0.244
0.237
0.109
0.442

X₅
0.022
0.025
−0.663
0.021
−0.249

X₆
0.163
−0.071
−0.315
−0.362
0.197

X₇
0.185
0.229
−0.285
−0.036
0.473

X₈
0.256
0.129
−0.095
0.487
−0.072

X₉
0.152
0.201
−0.098
0.588
−0.188

X₁₀
0.341
−0.061
0.077
−0.049
−0.036

X₁₁
−0.102
0.428
0.302
−0.020
−0.011

X₁₂
−0.237
0.300
0.258
0.096
−0.124

X₁₃
0.216
0.342
0.150
−0.181
−0.009

X₁₄
0.252
−0.294
0.129
0.130
0.213

X₁₅
0.243
0.307
−0.002
−0.259
0.015

X₁₆
0.351
−0.109
0.177
0.016
0.036

X₁₇
0.346
−0.097
0.209
0.028
−0.014

X₁₈
0.245
0.252
0.084
−0.276
−0.154

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 (F₁–F₅) 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.

Consent

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.

Acknowledgments

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).

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