Crops ›› 2023, Vol. 39 ›› Issue (3): 205-214.doi: 10.16035/j.issn.1001-7283.2023.03.029

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Analysis of Influencing Factors of Maize Yield under Different Ecological Conditions

Guo Shulei1(), Wang Ying2(), Wei Liangming1, Zhang Xin1, Liu Yan3, Wu Weihua4, Lu Daowen5, Lei Xiaobing6, Wang Zhenhua1(), Lu Xiaomin1()   

  1. 1Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
    2Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
    3Nanyang Academy of Agricultural Sciences, Nanyang 473000, Henan, China
    4Luohe Academy of Agricultural Sciences, Luohe 462000, Henan, China
    5Anyang Academy of Agricultural Sciences, Anyang 455000, Henan, China
    6Luoyang Academy of Agriculture and Forestry Sciences, Luoyang 471023, Henan, China
  • Received:2021-11-08 Revised:2022-02-18 Online:2023-06-15 Published:2023-06-16

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Abstract:

The difference of environmental factors under different ecological conditions are important reasons for the difference of maize yield. In order to clarify the main yield components in different regions, 15 inbred lines and 18 hybrids were evaluated and screened by using the climate environment pressure and adversity stress in different ecological areas. Combined with drought and shading stress treatment, and the contribution effects of yield components to yield in different regions were analyzed, the evaluation method of selecting suitable high- yield varieties in different regions was clarified. The results showed that the contribution effects of ear diameter, grain number per row, ear length, 100-grain weight and ear position coefficient directly related to yield were greater than those of disease and lodging, and these yield factors had different contribution and effects on yield under the influence of different climatic environments. The optimal linear regression model of yield were established in different areas with more yield factors, the higher the yield was. There are five, four, four and two factors directly related to yield were introduced into the optimal linear equations in Nanyang, Luoyang, Anyang and Luohe under different ecological environments, respectively. The multi-site joint identification showed that the yields of Zhengdan 1868 and LX201 did not decrease after drought stress, the yields decreased relatively less after shading stress, the average yields were relatively higher, and the comprehensive resistance were better in this study.

Key words: Maize, Yield factor, Environment factor, Path analysis

Table 1

Environmental factor parameters of different test locations"

地点
Location		 海拔
Altitude
(m)		 有效积温
Effective accumulated
temperature (℃)		 降雨量
Rainfall
(mm)		 日照时数
Sunshine
hour (h)		 日均最高气温
Average daily maximum
temperature (℃)		 日均最低气温
Average daily minimum
temperature (℃)		 最高气温
Maximum
temperature (℃)
南阳Nanyang 130 3247 493 574 28.20 20.36 37
漯河Luohe 57 3131 453 531 29.25 20.61 39
洛阳Luoyang 136 3003 370 554 27.63 20.30 39
安阳Anyang 67 3073 447 669 28.66 20.17 40

Table 2

Multi-site analysis of variance for different traits"

项目
Item		 产量
Yield		 百粒重
100-seed weight		 穗位系数
Ear position coefficient		 穗长
Ear length		 穗粗
Ear thickness		 穗行数
Ear rows		 行粒数
Kernels per row		 突尖
Barren ear tip
材料Material 95.25** 40.42** 10.56** 73.92** 39.40** 22.64** 38.76** 29.15**
地点Location 86.67** 186.23** 45.97** 68.77** 181.39** 8.25** 156.89** 64.63**
重复Repeat 0.37 2.51 0.19 0.24 2.36 0.67 0.13 2.73
材料×地点Material×location 56.99** 70.46** 14.03** 114.56** 21.16** 10.39** 105.19** 36.35**

Table 3

Correlation coefficients of yield traits of different materials"

指标
Index		 产量
Yield		 百粒重
100-seed
weight		 穗位系数
Ear position
coefficient		 穗长
Ear
length		 穗粗
Ear
thickness		 穗行数
Ear
rows		 行粒数
Kernels
per row		 秃尖长
Barren ear
tip length
产量Yield 0.306** 0.137 0.400** 0.491** 0.106 0.255** -0.117
百粒重100-seed weight 0.180** -0.104 0.291** 0.141 -0.449** -0.014 0.022
穗位系数Ear position coefficient 0.211** 0.411** 0.213** 0.402** 0.135 0.427** 0.320**
穗长Ear length 0.481** -0.097 0.009 0.478** 0.216** 0.445** 0.169*
穗粗Ear thickness 0.556** 0.640** 0.399** 0.203** 0.419** 0.395** 0.085
穗行数Ear rows -0.063 -0.111 -0.304** -0.070 0.124 0.334** 0.031
行粒数Kernels per row 0.352** -0.232** -0.053 0.701** -0.042 -0.070 0.444**
秃尖长Barren ear tip length 0.159* 0.041 -0.166* 0.191** 0.232** 0.265** -0.135*

Table 4

Changes in yield of different materials in different locations"

材料类型
Material type		 地点
Location		 均值
Mean (kg/hm2)		 极小值
Min. (kg/hm2)		 极大值
Max. (kg/hm2)		 标准偏差
Standard deviation		 变异系数
Variation coefficient		 偏度
Skewness		 峰度
Kurtosis
杂交种Hybrid 南阳 11 690.25 8524.95 14 635.95 94.69 0.12 0.05 0.11
漯河 10 447.95 8673.75 13 675.65 76.65 0.11 0.73 0.35
洛阳 10 818.75 8762.55 12 802.80 72.60 0.10 -0.11 -0.91
安阳 12 248.55 9972.00 14 500.50 74.00 0.09 -0.04 -0.59
自交系Inbred line 南阳 3542.70 1081.95 6920.25 99.51 0.42 0.34 -0.65
漯河 3184.65 1685.25 5278.35 60.16 0.28 0.78 -0.04
洛阳 5351.40 3216.15 7629.75 94.19 0.26 0.32 -1.35
安阳 4371.90 2331.60 7427.85 76.74 0.26 0.58 0.47

Table 5

Regression models and regression coefficients established under four ecological environments"

模型
Model		 非标准系数Unstandardized coefficient 标准系数
Standardized coefficient		 t P R R2
B 标准误差Standard error
1 常量 -628.775 46.718 -13.459 0.000 0.782 0.611
x3 73.525 2.955 0.782 24.885 0.000
2 常量 -1098.498 55.364 -19.842 0.000 0.847 0.718
x3 43.709 3.508 0.465 12.461 0.000
x4 212.769 17.421 0.456 12.214 0.000
3 常量 -1072.308 53.662 -19.983 0.000 0.859 0.738
x3 29.194 4.308 0.310 6.777 0.000
x4 199.827 16.984 0.428 11.766 0.000
x6 8.661 1.589 0.224 5.450 0.000
4 常量 -1125.673 52.515 -21.435 0.000 0.871 0.758
x3 24.641 4.225 0.262 5.833 0.000
x4 156.826 18.033 0.336 8.697 0.000
x6 10.108 1.551 0.262 6.517 0.000
x1 8.964 1.585 0.177 5.654 0.000
5 常量 -1009.523 59.975 -16.832 0.000 0.875 0.766
x3 22.072 4.208 0.235 5.245 0.000
x4 179.249 18.683 0.384 9.594 0.000
x6 10.895 1.539 0.282 7.079 0.000
x1 8.751 1.560 0.173 5.610 0.000
x2 -462.171 121.42 -0.102 -3.806 0.000

Table 6

Partial correlation coefficients between yield-related traits"

性状
Trait		 偏相关系数
Partial correlation coefficient		 显著水平
Significant
r(y, x3) 0.782** 0.000
r(y, x4) 0.779** 0.000
r(y, x6) 0.722** 0.000
r(y, x1) 0.578** 0.000
r(y, x2) 0.192** 0.000

Table 7

Regression model and regression coefficient established at Nanyang test site"

模型
Model		 非标准系数Unstandardized coefficient 标准系数
Standardized coefficient		 t P R R2
B 标准误差Standard error
6 常量 -1234.016 183.585 -6.722 0.000 0.929 0.864
x3 25.937 7.626 0.269 3.401 0.001
x6 25.485 3.628 0.458 7.025 0.000
x1 15.398 4.356 0.220 3.535 0.001
x2 -597.283 195.612 -0.133 -3.053 0.003
x8 -23.957 7.991 -0.123 -2.998 0.003
x4 16.852 6.800 0.108 2.478 0.015

Table 8

Regression model and regression coefficients established at Luohe test site"

模型
Model		 非标准系数Unstandardized coefficient 标准系数
Standardized coefficient		 t P R R2
B 标准误差Standard error
4 常量 76.600 152.706 -1.278 0.212 0.962 0.925
x6 2.568 4.182 0.991 6.023 0.000
x13 2.356 0.304 0.197 2.193 0.037
x12 -83.437 25.156 -0.296 -3.451 0.002
x11 -16.202 6.126 -0.154 -2.412 0.023

Table 9

Regression model and regression coefficients established at Luoyang test site"

模型
Model		 非标准系数Unstandardized coefficient 标准系数
Standardized coefficient		 t P R R2
B 标准误差Standard error
6 常量 -1211.546 143.002 -8.472 0.000 0.986 0.973
x6 22.264 2.151 0.541 10.350 0.000
x1 15.997 2.150 0.458 7.441 0.000
x5 43.133 7.579 0.332 5.691 0.000
x11 21.713 5.507 0.157 3.943 0.001
x4 -104.706 41.767 -0.230 -2.507 0.019
x12 45.885 18.831 0.101 2.437 0.022

Table 10

Regression model and regression coefficients established at Anyang test site"

模型
Model		 非标准系数Unstandardized coefficient 标准系数
Standardized coefficient		 t P R R2
B 标准误差Standard error
3 常量 -1633.504 162.686 -10.041 0.000 0.929 0.921
x4 279.961 52.047 0.454 5.379 0.000
x6 18.645 3.324 0.445 5.610 0.000
x1 14.410 4.253 0.197 3.388 0.000

Fig.1

Yield heat map of hybrids and inbred lines at different locations"

Table 11

HSC, WSI and CDRI of different materials"

材料类型
Material type		 名称
Name		 HSC 排名
Ranking		 遮阴水分胁迫指数
WSI of shading		 排名
Ranking		 干旱水分胁迫指数
WSI of drought		 排名
Ranking		 CDRI 排名
Ranking
杂交种Hybrid 宛玉231 0.986 1 0.703 18 0.025 8 1.0730 2
宛玉471 0.946 8 0.386 3 -0.081 3 1.0913 5
安玉109 0.935 14 0.455 10 0.079 12 2.2475 18
安玉909 0.950 6 0.528 15 0.062 11 1.7839 15
洛玉197 0.945 9 0.395 6 0.086 13 1.6656 13
洛玉199 0.944 10 0.493 14 0.147 15 1.6127 12
漯玉16 0.921 18 0.489 12 0.208 18 1.8845 16
漯玉18 0.933 15 0.443 9 0.181 17 1.4138 9
漯玉197 0.927 17 0.390 5 0.087 14 1.2212 7
郑单1868 0.977 2 0.232 2 -0.007 5 1.1762 6
郑单6095 0.952 5 0.493 13 -0.054 4 2.2416 17
郑单6122 0.938 12 0.429 8 -0.104 2 1.5238 11
郑单7137 0.947 7 0.487 11 0.044 10 1.2877 8
郑单7153 0.932 16 0.552 16 0.158 16 1.6720 14
郑单7167 0.939 11 0.414 7 -0.115 1 1.4286 10
郑单7168 0.955 4 0.389 4 0.017 7 0.9989 1
郑单7603 0.959 3 0.581 17 0.000 6 1.0730 3
郑单819 0.936 13 0.121 1 0.030 9 1.0730 4
平均值Mean 0.946 0.443 0.042 1.4700
自交系Inbred line A5855 0.933 9 0.116 3 -0.015 4 1.4434 3
A7648 0.943 6 0.792 15 0.113 11 2.2356 9
A7682 0.943 4 0.235 4 0.090 10 2.7067 13
L2258 0.858 15 0.491 8 0.165 14 2.4804 11
L2564 0.928 11 0.016 1 0.131 12 2.9141 14
L4653 0.955 1 0.698 13 0.062 8 2.2328 8
L5878 0.917 13 0.535 9 -0.119 1 1.2952 2
L753 0.916 14 0.749 14 -0.057 2 3.6169 15
自交系Inbred line LX201 0.947 3 0.111 2 0.006 5 1.8730 5
LX202 0.948 2 0.299 5 -0.041 3 1.4434 4
LX203 0.943 5 0.387 6 0.050 7 2.2434 10
郑71 0.917 12 0.673 11 0.194 15 2.5233 12
郑72 0.934 8 0.697 12 0.024 6 2.1876 7
郑493 0.930 10 0.405 7 0.164 13 1.9383 6
郑79 0.941 7 0.543 10 0.084 9 1.1915 1
平均值Mean 0.930 0.450 0.057 2.1550

Fig.2

Yield changes of different hybrids (a) and inbred lines (b) after drought and shading treatment"

Table 12

Traits related to shade tolerance and drought tolerance"

指标
Index		 耐阴性
Shade
tolerance		 耐旱性
Drought
tolerance		 脱水速率
Dehydration
rate		 穿刺强度
Penetration
strength		 综合抗病性
Comprehensive
disease resistance
耐阴性Shade tolerance 1.000
耐旱性Drought tolerance 0.169 1.000
脱水速率Dehydration rate 0.209 0.448** 1.000
穿刺强度Penetration strength 0.063 -0.061 0.422* 1.000
综合抗病性Comprehensive disease resistance 0.479** 0.032 -0.094 0.306 1.000
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