Scientia Agricultura Sinica ›› 2019, Vol. 52 ›› Issue (13): 2193-2207.doi: 10.3864/j.issn.0578-1752.2019.13.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Comprehensive Analysis on Grain and Processing Quality of Several Wheat Varieties in the Middle and Lower Reaches of Yangtze River

WU Hao1,HUANG YuanYuan1,WANG Hui1,ZHOU Yu1,SHEN JiaCheng1,ZHANG Can1,DING JinFeng2,ZOU Juan3,MA ShangYu1,GUO WenShan2,ZHENG WenYin1(),YAO DaNian1()   

  1. 1 College of Agronomy, Anhui Agricultural University/Key Laboratory of Wheat Biology, Genetic and Breeding in Huang-Huai Southern Areas, The Ministry of Agriculture, Hefei 230036
    2 Yangzhou University/Co-Innovation Center for Modern Production Technology in Grain Crops of Jiangsu Province, Yangzhou 225009, Jiangsu
    3 Institute of Food Crops , Hubei Academy of Agricultural Sciences, Wuhan 430064
  • Received:2019-03-05 Accepted:2019-04-18 Online:2019-07-01 Published:2019-07-11
  • Contact: WenYin ZHENG,DaNian YAO E-mail:zhengwenyin_75@163.com;dnyao@163.com

Abstract:

【Objective】 The present study was conducted to analyze the quality differences of tested wheat varieties in the middle and lower reaches of Yangtze River, including Jiangsu, Anhui and Hubei Provinces. The important factors influencing the noodle quality was assessed in providing theoretical basis for the wheat quality evaluation, variety selection with high-quality, and regional distribution of wheat quality. 【Method】 Based on the variance analysis of quality properties, principal component analysis was carried out in 25 quality traits of 13 wheat varieties planted in 6 pilot sites from 3 provinces, so as to evaluate and screen the important quality properties in this area. Then, partial least square analysis was used to distinguish the quality variation among provinces. Finally, the factors affecting the quality of noodle were analyzed by path analysis. 【Result】 Principal component analysis classified all quality traits into starch gelatinization index, flour water absorption index, flour quality index, protein index, flour color index, glutenin index and starch breakdown index and their cumulative contribution value reached 81.250% covering the vast majority of quality indexes. In the middle and lower reaches wheat areas of the Yangtze River, starch gelatinization index was the leading factor in quality evaluation, followed by flour water absorption index and flour quality index. The results of orthogonal partial least squares discriminant analysis (OPLS-DA) showed that the specific quality differences among the three provinces in this region were manifested in the gelatinization characteristics of starch, such as final viscosity and setback. From the results of path analysis, sodium carbonate solvent retention capacity could be seen as the largest directly positive effect on the sensory evaluation of noodles, while the disintegrating value of starch gelatinization and gluten performance index had relatively great negative effect on noodle quality. 【Conclusion】 Wheat quality in the middle and lower reaches of the Yangtze River is a complex integrative character, and there are significant differences in quality traits among different cultivars and planting areas. Starch gelatinization index and other quality traits are all easily affected by the environment. The great quality variation among the three provinces is setback and final viscosity of starch. With the increase of Trough, final viscosity and setback in starch, the quality of noodle enhance. Damaged starch content is the main factor that affects the quality of noodles based on the sensory evaluation. The wheat flour with high damaged starch content could be used to produce the high-quality noodle.

Key words: wheat, quality, principal component analysis, orthogonal partial least squares discriminant analysis, path analysis

Table 1

Analysis of variance of quality traits and product quality"

品质性状
Quality property
FF value
区组间
Block
地点间
Location
品种间
Variety
品种×地点间
Variety×Location
蛋白质Protein (%) 0.0539 9.0487** 6.7494** 1.0793**
降落值Falling number (sec) 328.1474 22247.6218** 19926.625** 2567.5301**
面粉亮度Flour luminance 0.0065 9.0074** 6.8634** 0.4539**
面粉白度Flour whiteness 0.0205 10.6391** 21.7507** 1.0101**
湿面筋 Wet gluten (%) 0.4220 89.4197** 83.8889** 13.1562**
面筋指数Gluten index 3.9610 1812.2815** 1469.8901** 161.3336**
水溶剂保持力Water solvent retention capacity 5.1580 95.2930** 153.6895** 23.5004**
乳酸溶剂保持力Lactic acid solvent retention capacity 3.6162 331.2689** 967.0910** 90.7725**
碳酸钠溶剂保持力Sodium carbonate solvent retention capacity 1.0222 135.0994** 187.8755** 46.2986**
蔗糖溶剂保持力Sucrose solvent retention capacity 13.5631 62.6446** 226.8113** 58.2454**
面筋表现指数Gluten performance index 0.0004 0.0149** 0.0340** 0.0029**
峰值黏度Peak 1 (cp) 4426 1209124** 1924377** 111601**
低谷黏度Trough 1 (cp) 4939 2487849** 668651** 68371**
崩解值 Breakdown (cp) 1978 308051** 725426** 28413**
最终黏度Final visc (cp) 5871 2298276** 1323089** 134582**
反弹值 Setback (cp) 943 809361** 135667** 19857**
峰值时间Peak time (min) 0.0039 1.9072** 0.1921** 0.0254**
糊化温度Pasting temp (℃) 24.4025 201.4817** 675.2045** 84.4338**
形成时间Development time (min) 1.5124 71.7727** 379.1786** 44.1352**
稳定时间Stabilization time (min) 1.5124 71.7727** 379.1786** 44.1352**
吸水率Water absorption (%) 2.1264 190.9412** 215.9343** 19.0714**
粉质参数Farinograph quality number 2.3491 323.6375** 375.1552** 93.5419**
弱化度 Degree of softening 3.5808 487.2625** 73.0302** 31.9312**
破损淀粉率 Damage starch(UCDc) 1.6864 122.9761** 135.9707** 19.9380**
籽粒硬度 Grain hardness 1.3699 821.9943** 9 693.4730** 448.1408**
面条感官评价Sensory evaluation of noodles 17.9359 216.8043** 291.8426** 47.2469**

Table 2

Eigenvalue and contribution rate of correlation matrix"

性状
Characters
成分1
Component1
成分2
Component2
成分3
Component3
成分4
Component4
成分5
Component5
成分6
Component6
成分7
Component7
水溶剂保持力Water solvent retention capacity -0.109 0.856 0.007 0.106 0.030 0.169 -0.033
乳酸溶剂保持力Lactic acid solvent retention capacity -0.007 0.312 0.284 -0.001 0.143 0.816 0.082
碳酸钠溶剂保持力Sodium carbonate solvent retention capacity -0.111 0.904 0.085 -0.054 0.109 -0.102 -0.006
蔗糖溶剂保持力Sucrose solvent retention capacity -0.050 0.310 0.324 -0.079 0.129 -0.593 0.230
面筋表现指数Gluten performance index 0.048 -0.051 0.142 0.045 0.070 0.968 0.007
湿面筋Wet gluten -0.229 0.206 0.188 0.764 -0.255 0.165 0.177
面筋指数Gluten index 0.088 -0.032 0.293 -0.816 0.127 0.179 0.128
峰值黏度Peak 1 (cp) 0.838 -0.089 0.106 -0.111 0.058 0.004 0.490
低谷黏度Trough 1 (cp) 0.955 0.051 0.214 -0.090 0.062 0.028 -0.022
崩解值Breakdown (cp) 0.077 -0.231 -0.128 -0.065 0.011 -0.033 0.897
最终粘度Final Visc (cp) 0.858 0.121 0.182 -0.353 -0.065 0.014 0.207
反弹值Setback (cp) 0.111 0.178 0 -0.631 -0.268 -0.022 0.514
峰值时间Peak time (min) 0.837 0.040 0.191 0.210 0.179 0.040 -0.347
糊化温度Pasting temp (℃) -0.020 0.045 0.014 0.445 0.318 0.207 -0.168
降落值Falling number (sec) 0.229 0.668 -0.151 -0.118 0.079 -0.001 -0.132
面粉白度Flour whiteness 0.090 0.033 -0.145 -0.081 0.920 0.097 -0.021
面粉亮度Flour luminance 0.113 0.137 -0.100 0.035 0.906 -0.013 -0.053
蛋白质Protein (%) -0.156 -0.441 0.365 0.499 -0.120 0.246 0.250
破损淀粉率 Damage starch (UCDc) 0.070 0.500 0.164 0.112 -0.516 0.010 -0.285
籽粒硬度Grain hardness 0.148 0.553 0.203 0.372 -0.455 -0.026 -0.010
吸水率 Water absorption 0.116 0.684 0.151 0.587 -0.142 -0.029 0.032
形成时间Development time (min) 0.043 0.127 0.814 0.148 -0.231 0.069 0.115
稳定时间Stabilization time (min) 0.270 -0.042 0.891 -0.093 -0.033 0.131 -0.117
弱化度Degree of softening -0.486 0.042 -0.620 0.167 0.087 -0.026 0.367
粉质参数Farinograph quality number 0.210 0.028 0.911 0.020 -0.102 0.032 -0.070
特征值Eigen value 5.130 4.246 3.148 2.690 1.974 1.726 1.399
贡献率Contribution rate (%) 20.519 16.985 12.592 10.760 7.896 6.903 5.595
累计百分比Cumulative percentage (%) 20.519 37.504 50.097 60.856 68.753 75.656 81.250

Fig. 1

PCA score chart of Hubei province, Anhui province and Jiangsu province WH: Wuhan, ZY: Zaoyang, SN: Suining, YZ: Yangzhou, FT: Fengtai, LJ: Lujiang; 1: Annong 0711, 2: Annong 1124, 3: Emai 580, 4: Emai 596, 5: Haomai 1, 6: Huaimai 35, 7: Jimai 22, 8: Ningmai 13, 9: Sumai 188, 10: Yangmai 16, 11: Yangmai 20, 12: Yangmai 23, 13: Zhengmai 9023. The same as below. t[1] and t[2] represent first two principal component"

Fig. 2

Orthogonal corrected partial least squares method for wheat quality characters in Hubei and Anhui provinces (up) and alignment verification diagram (down) Parameters R2 and Q2 respectively represent the interpretability and predictive ability of the model. The same as below"

Fig. 3

Distribution map of VIP predictive value of quality characters in Hubei and Anhui"

Fig. 4

Orthogonal correction partial least squares method for wheat quality characters in Jiangsu and Hubei provinces (up) and alignment verification diagram (down)"

Fig. 5

Distribution map of VIP predictive value of quality characters in Jiangsu and Hubei provinces"

Fig. 6

orthogonal corrected partial least squares method for wheat quality characters in Anhui and Jiangsu provinces (up) and alignment verification diagram (down) "

Fig. 7

Distribution map of VIP predictive value of quality characters in Anhui and Jiangsu provinces"

Table 3

Path analysis of noodles quality"

通径系数
Path coefficient
X1-Y X2-Y X3-Y X4-Y X5-Y X6-Y X7-Y
X1 0.0777 -0.0005 0.0195 -0.0106 0.0044 -0.0425 0.0868
X2 -0.0002 0.1784 0.0028 -0.0067 0.0756 -0.0018 0.0140
X3 0.0284 0.0092 0.0533 0.0162 0.0422 -0.0352 -0.0228
X4 0.0088 0.0128 -0.0092 -0.0936 -0.0074 -0.0291 0.1135
X5 -0.0010 -0.0409 -0.0068 -0.0021 -0.3292 -0.0220 -0.0087
X6 0.0186 0.0018 0.0105 -0.0153 -0.0406 -0.1779 0.0694
X7 -0.0291 -0.0108 0.0053 0.0459 -0.0123 0.0533 -0.2315
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