Acta Prataculturae Sinica ›› 2024, Vol. 33 ›› Issue (3): 120-138.DOI: 10.11686/cyxb2023187
Hai-wang YUE(), Jian-wei WEI(), Guang-cai WANG, Peng-cheng LIU, Shu-ping CHEN, Jun-zhou BU()
Received:
2023-06-08
Revised:
2023-07-05
Online:
2024-03-20
Published:
2023-12-27
Contact:
Jun-zhou BU
Hai-wang YUE, Jian-wei WEI, Guang-cai WANG, Peng-cheng LIU, Shu-ping CHEN, Jun-zhou BU. Comprehensive evaluation of silage maize hybrids in the Huanghuaihai plain based on mega-environments delineated using envirotyping techniques[J]. Acta Prataculturae Sinica, 2024, 33(3): 120-138.
品种名称 Hybrid name | 品种缩写Hybrid abbreviation | 供种单位 Institution of seed supply |
---|---|---|
成单3601 Chengdan3601 | CD3601 | 四川省农业科学院作物研究所Crop Research Institute, Sichuan Academy of Agricultural Sciences |
皖农科青贮8号 Wannongkeqingzhu8 | WNKQZ8 | 安徽省农业科学院烟草研究所Institute of Tobacco Research, Anhui Academy of Agricultural Sciences |
渝单805 Yudan805 | YD805 | 重庆市农业科学院Chongqing Academy of Agricultural Sciences |
雅玉7758 Yayu7758 | YY7758 | 四川雅玉科技股份有限公司Sichuan Yayu Technology Co., Ltd. |
SN8872 | SN8872 | 山东农业大学Shandong Agricultural University |
青秀001 Qingxiu001 | QX001 | 绵阳市农业科学研究院Mianyang Institute of Agricultural Science |
正大511 Zhengda511 | ZD511 | 襄阳正大农业开发有限公司Xiangyang Zhengda Agricultural Development Co., Ltd. |
郑青贮7号 Zhengqingzhu7 | ZQZ7 | 河南省农业科学院粮食作物研究所Institute of Grain Crops, Henan Provincial Academy of Agricultural Sciences |
泓丰159 Hongfeng159 | HF159 | 北京新实泓丰种业有限公司Beijing Xinshi Hongfeng Seed Co., Ltd. |
连青贮303 Lianqingzhu303 | LQZ303 | 连云港市农业科学院Lianyungang Academy of Agricultural Sciences |
安科青2号 Ankeqing2 | AKQ2 | 安徽科技学院Anhui Science and Technology University |
金诚6 Jincheng6 | JC6 | 河南金苑种业股份有限公司Henan Jinyuan Seed Co., Ltd. |
衡玉1996 Hengyu1996 | HY1996 | 河北省农林科学院旱作农业研究所Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences |
KNX22002 | KNX22002 | 湖北省康农生物育种研究院Hubei Kangnong Biological Breeding Research Institute |
雅玉青贮8号Yayuqingzhu8 | YYQZ8 | 四川雅玉科技股份有限公司Sichuan Yayu Technology Co., Ltd. |
Table 1 Description of the hybrids used in this study
品种名称 Hybrid name | 品种缩写Hybrid abbreviation | 供种单位 Institution of seed supply |
---|---|---|
成单3601 Chengdan3601 | CD3601 | 四川省农业科学院作物研究所Crop Research Institute, Sichuan Academy of Agricultural Sciences |
皖农科青贮8号 Wannongkeqingzhu8 | WNKQZ8 | 安徽省农业科学院烟草研究所Institute of Tobacco Research, Anhui Academy of Agricultural Sciences |
渝单805 Yudan805 | YD805 | 重庆市农业科学院Chongqing Academy of Agricultural Sciences |
雅玉7758 Yayu7758 | YY7758 | 四川雅玉科技股份有限公司Sichuan Yayu Technology Co., Ltd. |
SN8872 | SN8872 | 山东农业大学Shandong Agricultural University |
青秀001 Qingxiu001 | QX001 | 绵阳市农业科学研究院Mianyang Institute of Agricultural Science |
正大511 Zhengda511 | ZD511 | 襄阳正大农业开发有限公司Xiangyang Zhengda Agricultural Development Co., Ltd. |
郑青贮7号 Zhengqingzhu7 | ZQZ7 | 河南省农业科学院粮食作物研究所Institute of Grain Crops, Henan Provincial Academy of Agricultural Sciences |
泓丰159 Hongfeng159 | HF159 | 北京新实泓丰种业有限公司Beijing Xinshi Hongfeng Seed Co., Ltd. |
连青贮303 Lianqingzhu303 | LQZ303 | 连云港市农业科学院Lianyungang Academy of Agricultural Sciences |
安科青2号 Ankeqing2 | AKQ2 | 安徽科技学院Anhui Science and Technology University |
金诚6 Jincheng6 | JC6 | 河南金苑种业股份有限公司Henan Jinyuan Seed Co., Ltd. |
衡玉1996 Hengyu1996 | HY1996 | 河北省农林科学院旱作农业研究所Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences |
KNX22002 | KNX22002 | 湖北省康农生物育种研究院Hubei Kangnong Biological Breeding Research Institute |
雅玉青贮8号Yayuqingzhu8 | YYQZ8 | 四川雅玉科技股份有限公司Sichuan Yayu Technology Co., Ltd. |
省份 Province | 试点 Location | 纬度 Latitude (N,°) | 经度 Longitude (E,°) | 海拔 Altitude (m) |
---|---|---|---|---|
安徽Anhui | 合肥Hefei | 32.87 | 117.56 | 25 |
安徽Anhui | 宿州Suzhou | 33.70 | 117.08 | 29 |
河北Hebei | 邯郸Handan | 36.49 | 114.54 | 55 |
河南Henan | 郑州Zhengzhou | 34.79 | 113.68 | 52 |
河南Henan | 濮阳Puyang | 35.76 | 115.04 | 56 |
江苏Jiangsu | 连云港Lianyungang | 34.54 | 119.21 | 7 |
陕西Shaanxi | 杨凌Yangling | 34.27 | 108.08 | 465 |
陕西Shaanxi | 富平Fuping | 34.75 | 109.17 | 388 |
陕西Shaanxi | 宝鸡Baoji | 34.37 | 107.20 | 837 |
山东Shandong | 德州Dezhou | 37.68 | 116.81 | 23 |
山东Shandong | 嘉祥Jiaxiang | 35.36 | 116.40 | 36 |
山东Shandong | 泰安Taian | 36.20 | 117.09 | 147 |
Table 2 Locations, geography and altitude of the silage maize regional trial in 2022
省份 Province | 试点 Location | 纬度 Latitude (N,°) | 经度 Longitude (E,°) | 海拔 Altitude (m) |
---|---|---|---|---|
安徽Anhui | 合肥Hefei | 32.87 | 117.56 | 25 |
安徽Anhui | 宿州Suzhou | 33.70 | 117.08 | 29 |
河北Hebei | 邯郸Handan | 36.49 | 114.54 | 55 |
河南Henan | 郑州Zhengzhou | 34.79 | 113.68 | 52 |
河南Henan | 濮阳Puyang | 35.76 | 115.04 | 56 |
江苏Jiangsu | 连云港Lianyungang | 34.54 | 119.21 | 7 |
陕西Shaanxi | 杨凌Yangling | 34.27 | 108.08 | 465 |
陕西Shaanxi | 富平Fuping | 34.75 | 109.17 | 388 |
陕西Shaanxi | 宝鸡Baoji | 34.37 | 107.20 | 837 |
山东Shandong | 德州Dezhou | 37.68 | 116.81 | 23 |
山东Shandong | 嘉祥Jiaxiang | 35.36 | 116.40 | 36 |
山东Shandong | 泰安Taian | 36.20 | 117.09 | 147 |
来源Source | 协变量名称Environmental covariables name | 单位Unit |
---|---|---|
NASA POWERa | 水平面太阳辐射量Insolation incident on a horizontal surface (ALLSKY_SFC_SW_DWN) | MJ·m-2·d-1 |
向下热红外(长波)辐射通量Downward thermal infrared (longwave) radiative flux (ALLSKY_SFC_LW_DWN) | MJ·m-2·d-1 | |
地外辐射量Extraterrestrial radiation (RTA) | MJ·m-2·d-1 | |
离地2 m处的风速Wind speed at 2 m above the surface of the earth (WS2M) | m·s-1 | |
离地2 m处的最低温度Minimum air temperature at 2?m above the surface of the earth (T2M_MIN) | ℃·d -1 | |
离地2 m处的平均温度Average air temperature at 2 m?above the surface of the earth (T2M) | ℃·d -1 | |
离地2 m处的最高温度Maximum air temperature at 2?m above the surface of the earth (T2M_MAX) | ℃·d -1 | |
离地2 m处的露点温度Dew-point temperature at 2 m above the surface of the earth (T2MDEW) | ℃·d -1 | |
离地2 m处的相对湿度Relative air humidity at 2 m above the surface of the earth (RH2M) | % | |
降水量Precipitation (PRECTOT) | mm·d-1 | |
Calculatedb | 离地2 m处的温度区间Temperature range at 2 m above the surface of the earth (T2M_RANGE) | ℃·d -1 |
潜在蒸散量Potential evapotranspiration (ETP) | mm·d-1 | |
降水亏缺Deficit by precipitation (PEPT) | mm·d-1 | |
饱和水汽压差Vapor pressure deficit (VPD) | kPa·℃·d-1 | |
饱和蒸汽压曲线斜率Slope of saturation vapor pressure curve (SPV) | kPa·℃·d-1 | |
温度对辐射利用效率的影响Effect of temperature on radiation-use efficiency (FRUE) | 0~1 | |
生长度日Growing degree day (GDD) | ℃·d -1 | |
实际日照时间Actual duration of sunshine (n) | h | |
白昼时间Daylight hours (N) | h |
Table 3 List of environmental covariables (EC) used in this study
来源Source | 协变量名称Environmental covariables name | 单位Unit |
---|---|---|
NASA POWERa | 水平面太阳辐射量Insolation incident on a horizontal surface (ALLSKY_SFC_SW_DWN) | MJ·m-2·d-1 |
向下热红外(长波)辐射通量Downward thermal infrared (longwave) radiative flux (ALLSKY_SFC_LW_DWN) | MJ·m-2·d-1 | |
地外辐射量Extraterrestrial radiation (RTA) | MJ·m-2·d-1 | |
离地2 m处的风速Wind speed at 2 m above the surface of the earth (WS2M) | m·s-1 | |
离地2 m处的最低温度Minimum air temperature at 2?m above the surface of the earth (T2M_MIN) | ℃·d -1 | |
离地2 m处的平均温度Average air temperature at 2 m?above the surface of the earth (T2M) | ℃·d -1 | |
离地2 m处的最高温度Maximum air temperature at 2?m above the surface of the earth (T2M_MAX) | ℃·d -1 | |
离地2 m处的露点温度Dew-point temperature at 2 m above the surface of the earth (T2MDEW) | ℃·d -1 | |
离地2 m处的相对湿度Relative air humidity at 2 m above the surface of the earth (RH2M) | % | |
降水量Precipitation (PRECTOT) | mm·d-1 | |
Calculatedb | 离地2 m处的温度区间Temperature range at 2 m above the surface of the earth (T2M_RANGE) | ℃·d -1 |
潜在蒸散量Potential evapotranspiration (ETP) | mm·d-1 | |
降水亏缺Deficit by precipitation (PEPT) | mm·d-1 | |
饱和水汽压差Vapor pressure deficit (VPD) | kPa·℃·d-1 | |
饱和蒸汽压曲线斜率Slope of saturation vapor pressure curve (SPV) | kPa·℃·d-1 | |
温度对辐射利用效率的影响Effect of temperature on radiation-use efficiency (FRUE) | 0~1 | |
生长度日Growing degree day (GDD) | ℃·d -1 | |
实际日照时间Actual duration of sunshine (n) | h | |
白昼时间Daylight hours (N) | h |
性状 Traits | 变异来源 Source of variations | 自由度 Degrees of freedom | 平方和 Sum of square | 占总变异百分比 Percentage of total variation (%) | 占互作百分比 Percentage of interaction (%) |
---|---|---|---|---|---|
生物干重 Dry yield | 基因型 Genotype (G) | 14 | 95.16** | 3.43 | |
环境 Environment (E) | 11 | 2276.58** | 82.12 | ||
互作G×E | 154 | 400.50** | 14.45 | ||
第一主成分PC1 | 24 | 189.27** | 47.26 | ||
第二主成分PC2 | 22 | 84.44** | 21.08 | ||
残差Residuals | 128 | 126.79 | |||
总变异Total variation | 179 | 2772.24 | |||
生育期 Growth period | 基因型 Genotype (G) | 14 | 79.37** | 3.81 | |
环境 Environment (E) | 11 | 1748.95** | 84.05 | ||
互作G×E | 154 | 252.63** | 12.14 | ||
第一主成分PC1 | 24 | 112.15** | 44.39 | ||
第二主成分PC2 | 22 | 79.10** | 31.31 | ||
残差Residuals | 128 | 83.83 | |||
总变异Total variation | 179 | 14864.15 | |||
株高 Plant height | 基因型 Genotype (G) | 14 | 36968.14** | 50.31 | |
环境 Environment (E) | 11 | 100822.91** | 27.97 | ||
互作G×E | 154 | 34840.26** | 21.72 | ||
第一主成分PC1 | 24 | 11410.03** | 32.75 | ||
第二主成分PC2 | 22 | 8889.42** | 25.51 | ||
残差Residuals | 128 | 1540.81 | |||
总变异Total variation | 179 | 172631.31 | |||
干物质含量 Dry matter content | 基因型 Genotype (G) | 14 | 480.96** | 5.07 | |
环境 Environment (E) | 11 | 5046.51** | 53.27 | ||
互作G×E | 154 | 3946.87** | 41.66 | ||
第一主成分PC1 | 24 | 3250.96** | 82.37 | ||
第二主成分PC2 | 22 | 313.20** | 7.94 | ||
残差Residuals | 128 | 531.82 | |||
总变异Total variation | 179 | 9474.14 | |||
茎腐病 Stalk rot | 基因型 Genotype (G) | 14 | 67.72** | 8.46 | |
环境 Environment (E) | 11 | 209.99** | 26.25 | ||
互作G×E | 154 | 522.40** | 65.29 | ||
第一主成分PC1 | 24 | 399.31** | 76.44 | ||
第二主成分PC2 | 22 | 109.14** | 20.89 | ||
残差Residuals | 128 | 24.84 | |||
总变异Total variation | 179 | 800.11 | |||
倒伏率 Lodging rate | 基因型 Genotype (G) | 14 | 1002.30** | 5.32 | |
环境 Environment (E) | 11 | 5264.89** | 27.92 | ||
互作G×E | 154 | 12589.04** | 66.76 | ||
第一主成分PC1 | 24 | 7654.30** | 60.80 | ||
第二主成分PC2 | 22 | 3271.77** | 25.99 | ||
残差Residuals | 128 | 2315.76 | |||
总变异Total variation | 179 | 18856.24 | |||
倒折率 Discount rate | 基因型 Genotype (G) | 14 | 685.08** | 7.03 | |
环境 Environment (E) | 11 | 1359.77** | 13.96 | ||
互作G×E | 154 | 7697.88** | 79.01 | ||
第一主成分PC1 | 24 | 7105.94** | 92.31 | ||
第二主成分PC2 | 22 | 408.53** | 5.31 | ||
残差Residuals | 128 | 311.46 | |||
总变异Total variation | 179 | 9742.72 | |||
空秆率 Empty ears rate | 基因型 Genotype (G) | 14 | 779.86** | 6.94 | |
环境 Environment (E) | 11 | 2481.37** | 22.07 | ||
互作G×E | 154 | 7981.68** | 70.99 | ||
第一主成分PC1 | 24 | 7089.47** | 88.82 | ||
第二主成分PC2 | 22 | 354.93** | 4.45 | ||
残差Residuals | 128 | 809.12 | |||
总变异Total variation | 179 | 11242.91 | |||
穗位高 Ear height | 基因型 Genotype (G) | 14 | 24024.48** | 33.47 | |
环境 Environment (E) | 11 | 27545.98** | 38.38 | ||
互作G×E | 154 | 20203.52ns | 28.15 | ||
第一主成分PC1 | 24 | 5625.45** | 27.84 | ||
第二主成分PC2 | 22 | 4527.88** | 22.41 | ||
残差Residuals | 128 | 13196.68 | |||
总变异Total variation | 179 | 71773.98 | |||
小斑病 Southern leaf blight | 基因型 Genotype (G) | 14 | 10.13** | 2.85 | |
环境 Environment (E) | 11 | 265.13** | 74.52 | ||
互作G×E | 154 | 80.53** | 22.63 | ||
第一主成分PC1 | 24 | 36.88** | 45.80 | ||
第二主成分PC2 | 22 | 16.25** | 20.18 | ||
残差Residuals | 128 | 38.02 | |||
总变异Total variation | 179 | 355.80 | |||
弯孢叶斑病 Curvular leaf spot | 基因型 Genotype (G) | 14 | 13.91** | 7.51 | |
环境 Environment (E) | 11 | 105.24** | 56.82 | ||
互作G×E | 154 | 66.09** | 35.68 | ||
第一主成分PC1 | 24 | 26.12** | 39.52 | ||
第二主成分PC2 | 22 | 21.17** | 32.03 | ||
残差Residuals | 128 | 28.61 | |||
总变异Total variation | 179 | 185.24 | |||
南方锈病 Southern corn rust | 基因型 Genotype (G) | 14 | 4.31** | 6.37 | |
环境 Environment (E) | 11 | 22.31** | 32.99 | ||
互作G×E | 154 | 41.02** | 60.65 | ||
第一主成分PC1 | 24 | 27.65** | 67.40 | ||
第二主成分PC2 | 22 | 13.37** | 32.60 | ||
残差Residuals | 128 | 16.74 | |||
总变异Total variation | 179 | 67.64 | |||
黑粉病 Common smut | 基因型 Genotype (G) | 14 | 23.71** | 7.45 | |
环境 Environment (E) | 11 | 63.73** | 20.07 | ||
互作G×E | 154 | 230.09** | 72.46 | ||
第一主成分PC1 | 24 | 199.15** | 86.55 | ||
第二主成分PC2 | 22 | 24.65** | 10.71 | ||
残差Residuals | 128 | 9.28 | |||
总变异Total variation | 179 | 317.53 |
Table 4 The analysis of AMMI model for various agronomic traits of evaluated silage maize genotypes
性状 Traits | 变异来源 Source of variations | 自由度 Degrees of freedom | 平方和 Sum of square | 占总变异百分比 Percentage of total variation (%) | 占互作百分比 Percentage of interaction (%) |
---|---|---|---|---|---|
生物干重 Dry yield | 基因型 Genotype (G) | 14 | 95.16** | 3.43 | |
环境 Environment (E) | 11 | 2276.58** | 82.12 | ||
互作G×E | 154 | 400.50** | 14.45 | ||
第一主成分PC1 | 24 | 189.27** | 47.26 | ||
第二主成分PC2 | 22 | 84.44** | 21.08 | ||
残差Residuals | 128 | 126.79 | |||
总变异Total variation | 179 | 2772.24 | |||
生育期 Growth period | 基因型 Genotype (G) | 14 | 79.37** | 3.81 | |
环境 Environment (E) | 11 | 1748.95** | 84.05 | ||
互作G×E | 154 | 252.63** | 12.14 | ||
第一主成分PC1 | 24 | 112.15** | 44.39 | ||
第二主成分PC2 | 22 | 79.10** | 31.31 | ||
残差Residuals | 128 | 83.83 | |||
总变异Total variation | 179 | 14864.15 | |||
株高 Plant height | 基因型 Genotype (G) | 14 | 36968.14** | 50.31 | |
环境 Environment (E) | 11 | 100822.91** | 27.97 | ||
互作G×E | 154 | 34840.26** | 21.72 | ||
第一主成分PC1 | 24 | 11410.03** | 32.75 | ||
第二主成分PC2 | 22 | 8889.42** | 25.51 | ||
残差Residuals | 128 | 1540.81 | |||
总变异Total variation | 179 | 172631.31 | |||
干物质含量 Dry matter content | 基因型 Genotype (G) | 14 | 480.96** | 5.07 | |
环境 Environment (E) | 11 | 5046.51** | 53.27 | ||
互作G×E | 154 | 3946.87** | 41.66 | ||
第一主成分PC1 | 24 | 3250.96** | 82.37 | ||
第二主成分PC2 | 22 | 313.20** | 7.94 | ||
残差Residuals | 128 | 531.82 | |||
总变异Total variation | 179 | 9474.14 | |||
茎腐病 Stalk rot | 基因型 Genotype (G) | 14 | 67.72** | 8.46 | |
环境 Environment (E) | 11 | 209.99** | 26.25 | ||
互作G×E | 154 | 522.40** | 65.29 | ||
第一主成分PC1 | 24 | 399.31** | 76.44 | ||
第二主成分PC2 | 22 | 109.14** | 20.89 | ||
残差Residuals | 128 | 24.84 | |||
总变异Total variation | 179 | 800.11 | |||
倒伏率 Lodging rate | 基因型 Genotype (G) | 14 | 1002.30** | 5.32 | |
环境 Environment (E) | 11 | 5264.89** | 27.92 | ||
互作G×E | 154 | 12589.04** | 66.76 | ||
第一主成分PC1 | 24 | 7654.30** | 60.80 | ||
第二主成分PC2 | 22 | 3271.77** | 25.99 | ||
残差Residuals | 128 | 2315.76 | |||
总变异Total variation | 179 | 18856.24 | |||
倒折率 Discount rate | 基因型 Genotype (G) | 14 | 685.08** | 7.03 | |
环境 Environment (E) | 11 | 1359.77** | 13.96 | ||
互作G×E | 154 | 7697.88** | 79.01 | ||
第一主成分PC1 | 24 | 7105.94** | 92.31 | ||
第二主成分PC2 | 22 | 408.53** | 5.31 | ||
残差Residuals | 128 | 311.46 | |||
总变异Total variation | 179 | 9742.72 | |||
空秆率 Empty ears rate | 基因型 Genotype (G) | 14 | 779.86** | 6.94 | |
环境 Environment (E) | 11 | 2481.37** | 22.07 | ||
互作G×E | 154 | 7981.68** | 70.99 | ||
第一主成分PC1 | 24 | 7089.47** | 88.82 | ||
第二主成分PC2 | 22 | 354.93** | 4.45 | ||
残差Residuals | 128 | 809.12 | |||
总变异Total variation | 179 | 11242.91 | |||
穗位高 Ear height | 基因型 Genotype (G) | 14 | 24024.48** | 33.47 | |
环境 Environment (E) | 11 | 27545.98** | 38.38 | ||
互作G×E | 154 | 20203.52ns | 28.15 | ||
第一主成分PC1 | 24 | 5625.45** | 27.84 | ||
第二主成分PC2 | 22 | 4527.88** | 22.41 | ||
残差Residuals | 128 | 13196.68 | |||
总变异Total variation | 179 | 71773.98 | |||
小斑病 Southern leaf blight | 基因型 Genotype (G) | 14 | 10.13** | 2.85 | |
环境 Environment (E) | 11 | 265.13** | 74.52 | ||
互作G×E | 154 | 80.53** | 22.63 | ||
第一主成分PC1 | 24 | 36.88** | 45.80 | ||
第二主成分PC2 | 22 | 16.25** | 20.18 | ||
残差Residuals | 128 | 38.02 | |||
总变异Total variation | 179 | 355.80 | |||
弯孢叶斑病 Curvular leaf spot | 基因型 Genotype (G) | 14 | 13.91** | 7.51 | |
环境 Environment (E) | 11 | 105.24** | 56.82 | ||
互作G×E | 154 | 66.09** | 35.68 | ||
第一主成分PC1 | 24 | 26.12** | 39.52 | ||
第二主成分PC2 | 22 | 21.17** | 32.03 | ||
残差Residuals | 128 | 28.61 | |||
总变异Total variation | 179 | 185.24 | |||
南方锈病 Southern corn rust | 基因型 Genotype (G) | 14 | 4.31** | 6.37 | |
环境 Environment (E) | 11 | 22.31** | 32.99 | ||
互作G×E | 154 | 41.02** | 60.65 | ||
第一主成分PC1 | 24 | 27.65** | 67.40 | ||
第二主成分PC2 | 22 | 13.37** | 32.60 | ||
残差Residuals | 128 | 16.74 | |||
总变异Total variation | 179 | 67.64 | |||
黑粉病 Common smut | 基因型 Genotype (G) | 14 | 23.71** | 7.45 | |
环境 Environment (E) | 11 | 63.73** | 20.07 | ||
互作G×E | 154 | 230.09** | 72.46 | ||
第一主成分PC1 | 24 | 199.15** | 86.55 | ||
第二主成分PC2 | 22 | 24.65** | 10.71 | ||
残差Residuals | 128 | 9.28 | |||
总变异Total variation | 179 | 317.53 |
产量×性状 Yield×trait | 产量×酸性洗涤纤维含量Y×ADF(-1) | 产量×弯孢叶斑病 Y×CLS(-1) | 产量×粗蛋白含量 Y×CPC | 产量×黑粉病Y×CS(-1) | 产量×干物质含量Y×DM | 产量×倒折率Y×DR(-1) | 产量×空秆率Y×EER(-1) | 产量×穗位高Y×EH | 产量×生育期Y×GP | 产量×倒伏率Y×LR(-1) | 产量×中性洗涤纤维含量Y×NDF(-1) | 产量×株高Y×PH | 产量×南方锈病Y×SCR(-1) | 产量×小斑病Y×SLB(-1) | 产量×茎腐病Y×SR(-1) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
产量×弯孢叶斑病Y×CLS(-1) | 0.153 | ||||||||||||||
产量×粗蛋白含量Y×CPC | 0.230 | 0.223 | |||||||||||||
产量×黑粉病Y×CS(-1) | 0.084 | 0.266 | 0.049 | ||||||||||||
产量×干物质含量Y×DM | 0.265 | 0.402 | 0.141 | 0.573* | |||||||||||
产量×倒折率Y×DR(-1) | 0.151 | -0.019 | 0.282 | 0.038 | 0.157 | ||||||||||
产量×空秆率Y×EER(-1) | 0.473 | -0.034 | 0.349 | -0.017 | 0.432 | 0.429 | |||||||||
产量×穗位高Y×EH | 0.530* | 0.673** | 0.252 | 0.043 | 0.078 | -0.195 | -0.095 | ||||||||
产量×生育期Y×GP | 0.661** | 0.516* | 0.396 | 0.230 | 0.571* | 0.125 | 0.192 | 0.710 | |||||||
产量×倒伏率Y×LR(-1) | 0.218 | -0.081 | 0.592* | -0.039 | -0.037 | 0.623** | 0.256 | -0.034 | 0.268 | ||||||
产量×中性洗涤纤维含量Y×NDF(-1) | 0.931** | 0.233 | 0.200 | 0.197 | 0.323 | 0.181 | 0.324 | 0.542* | 0.735** | 0.257 | |||||
产量×株高Y×PH | 0.495* | 0.727** | 0.265 | 0.193 | 0.421 | 0.011 | -0.083 | 0.837** | 0.864** | 0.000 | 0.599* | ||||
产量×南方锈病Y×SCR(-1) | 0.185 | 0.177 | 0.018 | -0.020 | 0.293 | -0.264 | -0.360 | 0.263 | 0.513* | -0.065 | 0.199 | 0.532* | |||
产量×小斑病Y×SLB(-1) | 0.331 | 0.508* | 0.179 | 0.048 | 0.204 | 0.234 | 0.010 | 0.615** | 0.711** | 0.371 | 0.430 | 0.651** | 0.208 | ||
产量×茎腐病Y×SR(-1) | 0.239 | -0.267 | 0.101 | 0.130 | 0.008 | 0.328 | -0.031 | -0.046 | 0.216 | 0.447 | 0.356 | 0.051 | -0.013 | 0.354 | |
产量×全株淀粉含量Y×WPSC | 0.860** | 0.240 | 0.137 | 0.270 | 0.299 | 0.194 | 0.339 | 0.510 | 0.652** | 0.211 | 0.960** | 0.539* | 0.027 | 0.382 | 0.232 |
Table 5 Pearson correlations between yield-trait in 2022
产量×性状 Yield×trait | 产量×酸性洗涤纤维含量Y×ADF(-1) | 产量×弯孢叶斑病 Y×CLS(-1) | 产量×粗蛋白含量 Y×CPC | 产量×黑粉病Y×CS(-1) | 产量×干物质含量Y×DM | 产量×倒折率Y×DR(-1) | 产量×空秆率Y×EER(-1) | 产量×穗位高Y×EH | 产量×生育期Y×GP | 产量×倒伏率Y×LR(-1) | 产量×中性洗涤纤维含量Y×NDF(-1) | 产量×株高Y×PH | 产量×南方锈病Y×SCR(-1) | 产量×小斑病Y×SLB(-1) | 产量×茎腐病Y×SR(-1) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
产量×弯孢叶斑病Y×CLS(-1) | 0.153 | ||||||||||||||
产量×粗蛋白含量Y×CPC | 0.230 | 0.223 | |||||||||||||
产量×黑粉病Y×CS(-1) | 0.084 | 0.266 | 0.049 | ||||||||||||
产量×干物质含量Y×DM | 0.265 | 0.402 | 0.141 | 0.573* | |||||||||||
产量×倒折率Y×DR(-1) | 0.151 | -0.019 | 0.282 | 0.038 | 0.157 | ||||||||||
产量×空秆率Y×EER(-1) | 0.473 | -0.034 | 0.349 | -0.017 | 0.432 | 0.429 | |||||||||
产量×穗位高Y×EH | 0.530* | 0.673** | 0.252 | 0.043 | 0.078 | -0.195 | -0.095 | ||||||||
产量×生育期Y×GP | 0.661** | 0.516* | 0.396 | 0.230 | 0.571* | 0.125 | 0.192 | 0.710 | |||||||
产量×倒伏率Y×LR(-1) | 0.218 | -0.081 | 0.592* | -0.039 | -0.037 | 0.623** | 0.256 | -0.034 | 0.268 | ||||||
产量×中性洗涤纤维含量Y×NDF(-1) | 0.931** | 0.233 | 0.200 | 0.197 | 0.323 | 0.181 | 0.324 | 0.542* | 0.735** | 0.257 | |||||
产量×株高Y×PH | 0.495* | 0.727** | 0.265 | 0.193 | 0.421 | 0.011 | -0.083 | 0.837** | 0.864** | 0.000 | 0.599* | ||||
产量×南方锈病Y×SCR(-1) | 0.185 | 0.177 | 0.018 | -0.020 | 0.293 | -0.264 | -0.360 | 0.263 | 0.513* | -0.065 | 0.199 | 0.532* | |||
产量×小斑病Y×SLB(-1) | 0.331 | 0.508* | 0.179 | 0.048 | 0.204 | 0.234 | 0.010 | 0.615** | 0.711** | 0.371 | 0.430 | 0.651** | 0.208 | ||
产量×茎腐病Y×SR(-1) | 0.239 | -0.267 | 0.101 | 0.130 | 0.008 | 0.328 | -0.031 | -0.046 | 0.216 | 0.447 | 0.356 | 0.051 | -0.013 | 0.354 | |
产量×全株淀粉含量Y×WPSC | 0.860** | 0.240 | 0.137 | 0.270 | 0.299 | 0.194 | 0.339 | 0.510 | 0.652** | 0.211 | 0.960** | 0.539* | 0.027 | 0.382 | 0.232 |
品种名称 Genotype name | 产量×酸性洗涤纤维含量Y×ADF(-1) | 产量×弯孢叶斑病Y×CLS(-1) | 产量×粗蛋白含量Y×CPC | 产量×黑粉病Y×CS(-1) | 产量×干物质含量Y×DM | 产量×倒折率Y×DR(-1) | 产量×空秆率Y×EER(-1) | 产量×穗位高Y×EH | 产量×生育期Y×GP | 产量×倒伏率Y×LR(-1) | 产量×中性洗涤纤维含量Y×NDF(-1) | 产量×株高Y×PH | 产量×南方锈病Y×SCR(-1) | 产量×小斑病Y×SLB(-1) | 产量×茎腐病Y×SR(-1) | 产量×全株淀粉含量Y×WPSC | 理想指数SI |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
安科青2号 AKQ2 | -2.33 | -0.40 | 0.77 | 0.03 | -1.10 | 0.69 | -0.34 | -1.02 | -1.50 | 1.04 | -2.54 | -1.39 | -1.38 | 0.03 | -0.37 | -2.28 | -0.76 |
成单3601 CD3601 | -0.12 | -1.16 | -0.75 | 0.64 | 0.41 | 0.57 | -0.75 | -0.56 | 0.47 | -0.12 | 0.24 | 0.29 | 0.99 | -0.61 | -0.13 | 0.49 | -0.01 |
泓丰159 HF159 | -0.22 | 0.21 | 0.12 | 0.98 | 0.08 | -1.84 | -1.62 | 0.53 | 0.71 | 0.67 | 0.29 | 0.17 | 1.05 | 0.62 | 0.74 | 0.16 | 0.16 |
衡玉1996 HY1996 | 0.63 | -0.02 | 0.16 | 0.85 | -0.12 | 0.99 | 0.56 | -0.44 | -0.24 | 0.30 | 0.43 | -0.78 | -1.03 | -0.18 | 0.67 | 0.37 | 0.13 |
金诚6 JC6 | 0.03 | -2.27 | -0.71 | 0.05 | -0.86 | 0.09 | 0.69 | -2.06 | -1.87 | 0.10 | 0.06 | -2.18 | -1.43 | -1.64 | 0.39 | 0.38 | -0.70 |
KNX22002 | -1.16 | -0.61 | -0.83 | -0.44 | 1.01 | -0.78 | 0.36 | -0.78 | -0.23 | -1.67 | -1.17 | -0.56 | -0.07 | -0.13 | 0.20 | -1.29 | -0.51 |
连青贮303 LQZ303 | 0.09 | 1.39 | -0.24 | 0.19 | 0.80 | -1.25 | 0.88 | 0.53 | 0.01 | -1.39 | -0.28 | 0.19 | -0.02 | -0.66 | -3.28 | 0.18 | -0.18 |
青秀001 QX001 | -0.29 | 1.63 | 0.81 | 0.54 | 0.45 | 0.67 | -1.09 | 0.67 | 0.93 | 0.07 | 0.38 | 1.72 | 1.14 | 1.29 | 0.11 | 0.34 | 0.59 |
SN8872 | -0.51 | 0.63 | 0.63 | 0.48 | 1.37 | 1.05 | 0.66 | -1.00 | -0.38 | 0.57 | -0.33 | -0.21 | -0.12 | -1.31 | 0.08 | -0.47 | 0.07 |
晥农科青贮8号 WNKQZ8 | 1.10 | 0.28 | 1.02 | 0.58 | 0.54 | -0.92 | 0.71 | 0.80 | 0.82 | -0.48 | 0.98 | 0.99 | 0.18 | 0.09 | 0.75 | 0.77 | 0.51 |
渝单805 YD805 | 1.41 | 1.11 | 0.24 | 0.41 | 0.51 | 1.33 | 1.20 | 1.75 | 1.49 | 1.01 | 1.80 | 1.29 | -1.60 | 2.04 | 0.83 | 2.20 | 1.06 |
雅玉7758 YY7758 | -0.29 | 0.38 | -2.70 | 0.30 | -0.44 | -0.74 | -1.51 | 0.27 | -0.79 | -1.62 | -0.45 | 0.16 | 0.53 | 0.18 | 0.08 | -0.56 | -0.45 |
雅玉青贮8号 YYQZ8 | -0.56 | -0.37 | -0.01 | -2.34 | -2.69 | -1.02 | -1.36 | 0.71 | -1.13 | -0.72 | -0.61 | -0.31 | -0.49 | -1.04 | -0.63 | -0.61 | -0.82 |
正大511 ZD511 | 1.53 | -0.33 | 1.46 | 0.01 | 0.31 | 0.27 | 0.71 | 1.04 | 1.12 | 0.70 | 0.74 | 0.69 | 1.21 | 0.15 | 0.10 | 0.27 | 0.62 |
郑青贮7号 ZQZ7 | 0.69 | -0.48 | 0.02 | -2.26 | -0.26 | 0.91 | 0.91 | -0.45 | 0.59 | 1.56 | 0.47 | -0.08 | 1.01 | 1.17 | 0.47 | 0.05 | 0.27 |
Table 6 Standardized genotype by yield×trait (GYT) data and superiority index (SI) for the evaluated maize genotypes in 2022
品种名称 Genotype name | 产量×酸性洗涤纤维含量Y×ADF(-1) | 产量×弯孢叶斑病Y×CLS(-1) | 产量×粗蛋白含量Y×CPC | 产量×黑粉病Y×CS(-1) | 产量×干物质含量Y×DM | 产量×倒折率Y×DR(-1) | 产量×空秆率Y×EER(-1) | 产量×穗位高Y×EH | 产量×生育期Y×GP | 产量×倒伏率Y×LR(-1) | 产量×中性洗涤纤维含量Y×NDF(-1) | 产量×株高Y×PH | 产量×南方锈病Y×SCR(-1) | 产量×小斑病Y×SLB(-1) | 产量×茎腐病Y×SR(-1) | 产量×全株淀粉含量Y×WPSC | 理想指数SI |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
安科青2号 AKQ2 | -2.33 | -0.40 | 0.77 | 0.03 | -1.10 | 0.69 | -0.34 | -1.02 | -1.50 | 1.04 | -2.54 | -1.39 | -1.38 | 0.03 | -0.37 | -2.28 | -0.76 |
成单3601 CD3601 | -0.12 | -1.16 | -0.75 | 0.64 | 0.41 | 0.57 | -0.75 | -0.56 | 0.47 | -0.12 | 0.24 | 0.29 | 0.99 | -0.61 | -0.13 | 0.49 | -0.01 |
泓丰159 HF159 | -0.22 | 0.21 | 0.12 | 0.98 | 0.08 | -1.84 | -1.62 | 0.53 | 0.71 | 0.67 | 0.29 | 0.17 | 1.05 | 0.62 | 0.74 | 0.16 | 0.16 |
衡玉1996 HY1996 | 0.63 | -0.02 | 0.16 | 0.85 | -0.12 | 0.99 | 0.56 | -0.44 | -0.24 | 0.30 | 0.43 | -0.78 | -1.03 | -0.18 | 0.67 | 0.37 | 0.13 |
金诚6 JC6 | 0.03 | -2.27 | -0.71 | 0.05 | -0.86 | 0.09 | 0.69 | -2.06 | -1.87 | 0.10 | 0.06 | -2.18 | -1.43 | -1.64 | 0.39 | 0.38 | -0.70 |
KNX22002 | -1.16 | -0.61 | -0.83 | -0.44 | 1.01 | -0.78 | 0.36 | -0.78 | -0.23 | -1.67 | -1.17 | -0.56 | -0.07 | -0.13 | 0.20 | -1.29 | -0.51 |
连青贮303 LQZ303 | 0.09 | 1.39 | -0.24 | 0.19 | 0.80 | -1.25 | 0.88 | 0.53 | 0.01 | -1.39 | -0.28 | 0.19 | -0.02 | -0.66 | -3.28 | 0.18 | -0.18 |
青秀001 QX001 | -0.29 | 1.63 | 0.81 | 0.54 | 0.45 | 0.67 | -1.09 | 0.67 | 0.93 | 0.07 | 0.38 | 1.72 | 1.14 | 1.29 | 0.11 | 0.34 | 0.59 |
SN8872 | -0.51 | 0.63 | 0.63 | 0.48 | 1.37 | 1.05 | 0.66 | -1.00 | -0.38 | 0.57 | -0.33 | -0.21 | -0.12 | -1.31 | 0.08 | -0.47 | 0.07 |
晥农科青贮8号 WNKQZ8 | 1.10 | 0.28 | 1.02 | 0.58 | 0.54 | -0.92 | 0.71 | 0.80 | 0.82 | -0.48 | 0.98 | 0.99 | 0.18 | 0.09 | 0.75 | 0.77 | 0.51 |
渝单805 YD805 | 1.41 | 1.11 | 0.24 | 0.41 | 0.51 | 1.33 | 1.20 | 1.75 | 1.49 | 1.01 | 1.80 | 1.29 | -1.60 | 2.04 | 0.83 | 2.20 | 1.06 |
雅玉7758 YY7758 | -0.29 | 0.38 | -2.70 | 0.30 | -0.44 | -0.74 | -1.51 | 0.27 | -0.79 | -1.62 | -0.45 | 0.16 | 0.53 | 0.18 | 0.08 | -0.56 | -0.45 |
雅玉青贮8号 YYQZ8 | -0.56 | -0.37 | -0.01 | -2.34 | -2.69 | -1.02 | -1.36 | 0.71 | -1.13 | -0.72 | -0.61 | -0.31 | -0.49 | -1.04 | -0.63 | -0.61 | -0.82 |
正大511 ZD511 | 1.53 | -0.33 | 1.46 | 0.01 | 0.31 | 0.27 | 0.71 | 1.04 | 1.12 | 0.70 | 0.74 | 0.69 | 1.21 | 0.15 | 0.10 | 0.27 | 0.62 |
郑青贮7号 ZQZ7 | 0.69 | -0.48 | 0.02 | -2.26 | -0.26 | 0.91 | 0.91 | -0.45 | 0.59 | 1.56 | 0.47 | -0.08 | 1.01 | 1.17 | 0.47 | 0.05 | 0.27 |
1 | He W R, Sun Q, Xi L Q, et al. Variety comparison test of silage corn in Aral area. Xinjiang Agricultural Sciences, 2022, 59(12): 2948-2956. |
何万荣, 孙强, 席琳乔, 等. 9个青贮玉米品种灰色关联综合评价. 新疆农业科学, 2022, 59(12): 2948-2956. | |
2 | Zhu L L, Zhang Y M, Li W C, et al. Adaption to the Plateau climate in Qinghai of 39 silage maize varieties cultivated in different ecological regions of China. Acta Prataculturae Sinica, 2023, 32(4): 68-78. |
朱丽丽, 张业猛, 李万才, 等. 39个我国不同生态区培育的青贮玉米品种在青海高原适应性研究. 草业学报, 2023, 32(4): 68-78. | |
3 | Bernardi A, Härter C J, Silva A W, et al. A meta-analysis examining lactic acid bacteria inoculants for maize silage: Effects on fermentation, aerobic stability, nutritive value and livestock production. Grass and Forage Science, 2019, 74(4): 596-612. |
4 | Qi H, Lu G, Li Z, et al. Cladosporium species causing leaf spot on silage maize based on multi-locus phylogeny in China. Journal of Phytopathology, 2023, 171(2): 82-91. |
5 | Liu X, Wang B, Zhu X Y, et al. A comparison of 21 varieties of silage maize in Henan Province. Acta Prataculturae Sinica, 2019, 28(8): 49-60. |
刘晓, 王博, 朱晓艳, 等. 21个粮饲兼用型青贮玉米在河南的品种比较试验. 草业学报, 2019, 28(8): 49-60. | |
6 | Ligarreto M G, Pimentel L C. Grain yield and genotype×environment interaction in bean cultivars with different growth habits. Plant Production Science, 2022, 25(2): 232-241. |
7 | Diouf I, Derivot L, Koussevitzky S, et al. Genetic basis of phenotypic plasticity and genotype×environment interactions in a multi-parental tomato population. Journal of Experimental Botany, 2020, 71(18): 5365-5376. |
8 | Wang X Y, Cheng J, Gao S, et al. Evaluation of adaptability of naked oat varieties in the alpine region of North China based on the AMMI model and GGE Biplot. Acta Prataculturae Sinica, 2022, 31(12): 76-84. |
王星宇, 程静, 高生, 等. 应用 AMMI模型和 GGE 双标图评价裸燕麦品种在华北高寒区的适应性. 草业学报, 2022, 31(12): 76-84. | |
9 | Zhang J H, Wu B, Bai S S, et al. Comprehensive evaluation of whole-plant yield and silage quality of 16 maize varieties in the Huang-Huai-Hai area of China. Journal of China Agricultural University, 2023, 28(3): 11-24. |
张进红, 吴波, 柏杉杉, 等. 16个玉米品种在黄淮海地区的全株产量与青贮效果综合评价. 中国农业大学学报, 2023, 28(3): 11-24. | |
10 | Jiang H X, Liu D, Zhang D M, et al. Investigation and analysis of whole corn silage production in Shandong Province. China Herbivore Science, 2020, 40(6): 63-66, 74. |
姜慧新, 刘栋, 张德敏, 等. 山东省全株玉米青贮生产情况调查与分析. 中国草食动物科学, 2020, 40(6): 63-66, 74. | |
11 | Ling M H, Han H B, Hu X Y, et al. Drought characteristics and causes during summer maize growth period on Huang-Huai-Hai Plain based on daily scale SPEI. Agricultural Water Management, 2023, 280: 108198. |
12 | Wicaksana N, Maulana H, Yuwariah Y, et al. Selection of high yield and stable maize hybrids in mega-environments of Java island, Indonesia. Agronomy, 2022, 12(12): 2923. |
13 | Crevelari J A, Souza Y P D, Santos J S, et al. Adaptability and stability of corn hybrids for silage via genotype and genotype×environment interaction biplot. Agronomy Journal, 2023, 115(2): 687-697. |
14 | Yan W K, Frégeau-reid J. Genotype by yield*trait (GYT) biplot: A novel approach for genotype selection based on multiple traits. Scientific Reports, 2018, 8(1): 8242. |
15 | Elfanah A M, Darwish M A, Selim A I, et al. Spectral reflectance indices’ performance to identify seawater salinity tolerance in bread wheat genotypes using genotype by yield*trait biplot approach. Agronomy, 2023, 13(2): 353. |
16 | Xu N Y, Zhao S Q, Zhang F, et al. Retrospective evaluation of cotton varieties nationally registered for the Northwest Inland cotton growing regions based on GYT biplot analysis. Acta Agronomica Sinica, 2021, 47(4): 660-671. |
许乃银, 赵素琴, 张芳, 等. 基于GYT双标图对西北内陆棉区国审棉花品种的分类评价. 作物学报, 2021, 47(4): 660-671. | |
17 | Yue H W, Han X, Wei J W, et al. Comprehensive evaluation of maize hybrids tested in Huang-Huai-Hai summer maize regional trial based on GYT biplot analysis. Acta Agronomica Sinica, 2023, 49(5): 1231-1248. |
岳海旺, 韩轩, 魏建伟, 等. 基于GYT双标图分析对黄淮海夏玉米区域试验品种综合评价. 作物学报, 2023, 49(5): 1231-1248. | |
18 | Gholizadeh A, Oghan H A, Alizadeh B, et al. Phenotyping new rapeseed lines based on multiple traits: Application of GT and GYT biplot analyses. Food Science & Nutrition, 2023, 11(2): 853-862. |
19 | Costa-neto G, Galli G, Carvalho H F, et al. EnvRtype: A software to interplay enviromics and quantitative genomics in agriculture. G3 Genes Genomes Genetics, 2021, 11(4): DOI: 10.1093/g3journal/jkab040. |
20 | Kassambara A, Mundt F. Factoextra: Extract and visualize the results of multivariate data analyses. R package version 1.0.7. 2020. https://www.rdocumentation.org/packages/factoextra/versions/1.0.7. |
21 | Sparks A H. Nasapower: A NASA POWER global meteorology, surface solar energy and climatology data client for R. The Journal of Open Source Software, 2018, 3(30): 1035. |
22 | Ghanem M E, Marrou H, Sinclair T R. Physiological phenotyping of plants for crop improvement. Trends in Plant Science, 2015, 20(3): 139-144. |
23 | Yue H, Li H, Xu L, et al. Analysis of genotype-environment interactions of silage maize cultivars under environmental trials. Bangladesh Journal of Botany, 2020, 49(1): 55-63. |
24 | Kaplan M, Kokten K, Akcura M. Assessment of genotype×trait×environment interactions of silage maize genotypes through GGE Biplot. Chilean Journal of Agricultural Research, 2017, 77(3): 212-217. |
25 | Tang Q Y, Zhang C X. Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research. Insect Science, 2013, 20(2): 254-260. |
26 | Tao F L, Xiao D P, Zhang S, et al. Wheat yield benefited from increases in minimum temperature in the Huang-Huai-Hai plain of China in the past three decades. Agricultural and Forest Meteorology, 2017, 239: 1-14. |
27 | Wang P, Wu D, Yang J, et al. Summer maize growth under different precipitation years in the Huang-Huai-Hai Plain of China. Agricultural and Forest Meteorology, 2020, 285: 107927. |
28 | Shekoofa A, Sinclair T R, Messina C D, et al. Variation among maize hybrids in response to high vapor pressure deficit at high temperatures. Crop Science, 2016, 56(1): 392-396. |
29 | Sadok W, Lopez J R, Smith K P. Transpiration increases under high-temperature stress: Potential mechanisms, trade-offs and prospects for crop resilience in a warming world. Plant, Cell & Environment, 2021, 44(7): 2102-2116. |
30 | Berry J O, Mure C M, Yerramsetty P. Regulation of Rubisco gene expression in C4 plants. Current Opinion in Plant Biology, 2016, 31: 23-28. |
31 | Liu W M, Liu Y E, Liu G Z, et al. Estimation of maize straw production and appropriate straw return rate in China. Agriculture, Ecosystems and Environment, 2022, 328: 107865. |
32 | Xu Y B. Envirotyping and its applications in crop science. Scientia Agricultura Sinica, 2015, 48(17): 3354-3371. |
徐云碧. 作物科学中的环境型鉴定(Envirotyping)及其应用. 中国农业科学, 2015, 48(17): 3354-3371. | |
33 | Das J, Poonia V, Jha S, et al. Understanding the climate change impact on crop yield over Eastern Himalayan Region: Ascertaining GCM and scenario uncertainty. Theoretical and Applied Climatology, 2020, 142: 467-482. |
34 | Yue H W, Wei J W, Xie J L, et al. Effect of interaction between genotype and environment on the grain yield of summer maize hybrids in Huanghuaihai region. Journal of China Agricultural University, 2022, 27(4): 31-43. |
岳海旺, 魏建伟, 谢俊良, 等. 基因型和环境互作对黄淮海夏玉米品种籽粒产量的影响. 中国农业大学学报, 2022, 27(4): 31-43. | |
35 | Badu-Apraku B, Akinwale R O, Ajala S O, et al. Relationships among traits of tropical early maize cultivars in contrasting environments. Agronomy Journal, 2011, 103(3): 717-729. |
36 | Boureima S, Yaou A. Genotype by yield*trait combination biplot approach to evaluate sesame genotypes on multiple traits basis. Turkish Journal of Field Crops, 2019, 24(2): 237-244. |
37 | da Cruz D P, de Oliveira T R A, Gomes A B S, et al. Selection of cowpea lines for multiple traits by GYT biplot analysis. Journal of Agricultural Studies, 2020, 8(2): 124-137. |
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