Crops ›› 2023, Vol. 39 ›› Issue (2): 115-120.doi: 10.16035/j.issn.1001-7283.2023.02.016

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Comprehensive Analysis of Milling Quality and Eating Quality of Japonica Rice in Cold Region

Wang Rongsheng1,2,3(), Mu Fengchen2,3(), Li Kun2,3, Zhang Wei2,3, Liu Hui2,3, Ding Guohua4, Yang Guang4, Wang Nanbo2,3, Zhang Guomin2,3, Liu Yuming2,3, Tao Yongqing2,3   

  1. 1Post-Doctoral Research Center, Heilongjiang Academy of Agricultural Sciences, Harbin 150086,Heilongjiang, China
    2Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences,Harbin 150028, Heilongjiang, China
    3Heilongjiang Key Laboratory of Crop and Livestock Molecular Breeding,Harbin 150028, Heilongjiang, China
    4Cultivation and Farming Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, Heilongjiang, China
  • Received:2021-11-01 Revised:2021-12-08 Online:2023-04-15 Published:2023-04-11

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Abstract:

In order to clarify the interrelationship between milling quality and eating quality of japonica rice, this research focused on 337 high generation inbred accessions and their eleven quality-related characteristics were surveyed to calculate their correlation matrix, conduct principal component analysis (PCA), clustering analysis and multiple linear regression were performed. The results showed that significant positive correlation was existed among brown rice rate, milled rice rate and head rice rate. Eating scores showed correlation with both amylose content and protein content. In PCA, the cumulative variance contribution rate of four principal components were up to 80%. The first five rice varieties ranked by integrating score were J139, J201, J141, J204 and J138. Eating score was treated as dependent variable, brown rice rate, milled rice rate, protein content, water content and amylose content were treated as independent variable in regression analysis, and regression equation was obtained. All these analysis methods and the equation of eating scores can be used in preliminary evaluation for new rice strains. The comparation of new varieties would be more efficiency and precise.

Key words: Rice, Milling quality, Eating quality, Correlation, Multiple linear regression analysis, Principal component analysis

Table 1

Statistical overview of different traits of 337 rice lines"

项目
Item		 糙米率
Brown
rice
rate (%)		 精米率
Milled
rice
rate (%)		 整精米率
Head rice
rate (%)		 食味评分
Eating
score		 蛋白质含量
Protein
content
(%)		 含水量
Water
content
(%)		 直链淀
粉含量
Amylose
content (%)		 粒长
Grain
length
(mm)		 粒宽
Grain
width
(mm)		 粒厚
Grain
thickness
(mm)		 长宽比
Length-
width
ratio
最小值Minimum 61.50 47.50 38.00 69.00 6.00 12.50 5.00 4.53 2.12 1.23 1.28
最大值Maximum 85.20 77.30 76.30 85.00 12.10 18.10 22.20 7.97 3.67 2.97 3.25
平均值Average 80.71 70.06 67.48 79.58 7.93 15.47 18.79 6.18 2.56 1.95 2.44
标准差Standard deviation 2.73 3.92 5.52 2.56 0.94 0.82 2.32 0.61 0.23 0.21 0.36
变异系数Coefficient of variation (%) 3.38 5.60 8.18 3.21 11.85 5.29 12.36 9.87 9.02 10.84 14.93

Table 2

Correlation coefficients of different rice lines in each rice quality characteristics"

表型性状
Phenotype trait		 糙米率
Brown
rice rate		 精米率
Milled
rice rate		 整精米率
Head rice
rate		 食味评分
Eating
score		 蛋白质含量
Protein
content		 含水量
Water
content		 直链淀
粉含量
Amylose content		 粒长
Grain
length		 粒宽
Grain
width		 粒厚
Grain
thickness
精米率Milled rice rate 0.74***
整精米率Head rice rate 0.63*** 0.84***
食味评分Eating score 0.17** -0.04 -0.07
蛋白质含量Protein content -0.18*** 0.00 0.07 -0.80***
含水量Water content 0.24*** 0.14** 0.23*** -0.05 0.34***
直链淀粉含量Amylose content 0.14** -0.09 -0.15** 0.61*** -0.91*** -0.34***
粒长Grain length 0.07 -0.14* -0.22*** 0.17** -0.20*** -0.14** 0.20***
粒宽Grain width 0.02 0.19*** 0.27*** -0.21*** 0.33*** 0.32*** -0.34*** -0.48***
粒厚Grain thickness 0.04 0.15** 0.16** -0.14* 0.19*** 0.17** -0.24*** -0.21*** 0.57***
长宽比Length-width ratio 0.00 -0.21*** -0.30*** 0.22*** -0.29*** -0.28*** 0.29*** 0.88*** -0.82*** -0.43***

Table 3

The eigenvalue, variance contribution rate and cumulative variance contribution rate of each principal component"

主成分
Principal
component		 特征值
Eigenvalue		 方差贡献率
Variance
contribution rate (%)		 累计方差贡献率
Cumulative variance
contribution rate (%)
PC1 3.8437 34.94 34.94
PC2 2.5338 23.03 57.98
PC3 1.6953 15.41 73.39
PC4 0.9629 8.75 82.14
PC5 0.8434 7.67 89.81
PC6 0.3601 3.27 93.08
PC7 0.3384 3.08 96.16
PC8 0.2507 2.28 98.44
PC9 0.1283 1.17 99.60
PC10 0.0346 0.31 99.92
PC11 0.0089 0.08 100.00

Table 4

Eigenvector of the first four principal components"

品质指标
Quality indicator		 特征向量Eigenvector
PC1 PC2 PC3 PC4
x1 -0.074 -0.533 -0.226 -0.085
x2 -0.208 -0.494 -0.226 0.194
x3 -0.254 -0.451 -0.190 0.186
x4 0.277 -0.292 0.340 -0.322
x5 -0.349 0.330 -0.365 0.016
x6 -0.243 -0.060 -0.118 -0.675
x7 0.350 -0.263 0.347 0.047
x8 0.321 -0.002 -0.407 -0.391
x9 -0.397 -0.009 0.309 -0.184
x10 -0.274 -0.019 0.213 -0.389
x11 0.413 0.020 -0.416 -0.143

Table 5

Comprehensive PCA scores of first five accessions in rice quality characteristics"

品系
Line		 食味评分
Eating score		 糙米率
Brown rice rate (%)		 精米率
Milled rice rate (%)		 蛋白质含量
Protein content (%)		 含水量
Water content (%)		 直链淀粉含量
Amylose content (%)
J139 72.00 80.70 72.90 11.20 17.90 11.20
J201 79.00 82.08 73.08 11.50 18.00 5.60
J141 76.00 81.48 72.54 11.30 17.70 10.20
J204 77.00 79.44 72.42 10.40 17.20 13.30
J138 81.00 82.60 73.54 10.80 18.10 6.70

Table 6

The results of multiple linear regression analysis and significance test"

项目
Item		 系数估计值
Estimated
value		 标准误
Standard
error		 t值
t value		 P值
P value
(>|t|)
截距Intercept 119.366 3.376 35.354 2.00E-16
糙米率
Brown rice rate		 0.102 0.040 2.575 0.011
精米率
Milled rice rate		 -0.147 0.027 -5.506 7.38E-08
蛋白质含量
Protein content		 -4.170 0.169 -24.732 2.00E-16
含水量
Water content		 0.694 0.091 7.670 1.94E-13
直链淀粉含量
Amylose content		 -0.821 0.070 -11.786 2.00E-16
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