Crops ›› 2024, Vol. 40 ›› Issue (6): 55-60.doi: 10.16035/j.issn.1001-7283.2024.06.007

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Genotype-by-Environment Interaction and Stability of Yield Components in Peanut

Yu Mu1(), Yang Haitang1(), Hu Yanling1, Liu Ruanzhi1, Shi Yanzhao1, Li Pan1, Han Yanhong1, Zhu Zhenzhen1, Li Shizhong2, Guo Zhenchao3   

  1. 1Zhengzhou Institute of Agricultural Science and Technology, Zhengzhou 450005, Henan, China
    2Zhengzhou Machinery Research Institute Co. Ltd., Zhengzhou 450000, Henan, China
    3Xinzheng Agricultural Technology Science Research Institute, Xinzheng 451100, Henan, China
  • Received:2023-07-24 Revised:2023-11-27 Online:2024-12-15 Published:2024-12-05

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Abstract:

The yield composition of wheat interplanting peanut varieties was analyzed to provide reference for variety evaluation and high-yield breeding. Based on the regional trial data of peanut complex in Henan province from 2016 to 2017, path analysis and GGE biplot analysis of yield and its related nine agronomic traits were performed. The results showed that the variation range of milled rice rate was the smallest, and the variation coefficients of main stem height, number of pods per plant and pod weight per plant were larger, which had the potential for improvement. Yield showed a significant positive correlation with 100-seed weight and 100-pod weight. The direct path coefficient of 100-seed weight was the largest. The order of direct path coefficients and correlation coefficients of agronomic traits and yield were not completely consistent, it was mainly dued to the interaction between agronomic traits and their indirect effects on yield. The results of GGE biplot showed that the top four varieties with high and stable yield were Kainong 79, Shanghua 21, Luohua 1 and Zhengnonghua 18. The selection of 100-seed weight and 100-pod weight, the key factors affecting yield, should be emphasized, and the main stem height, lateral branche length, total branching number and number of pod branches should be controlled in the selection of peanut varieties.

Key words: Peanut, Yield components, Correlation analysis, Path analysis, GGE biplot

Table 1

Codes and names of tested peanut varieties"

编号Code 品种Variety
G1 开农79
G2 洛花1号
G3 濮学花0815
G4 商花21
G5 豫花81号
G6 豫花82号
G7 豫花9326
G8 郑农花18
G9 周花5号

Table 2

Precipitation of the test sites mm"

编号
Code		 地点
Location		 降水量Precipitation
2016 2017
E1 开封 556.00 599.50
E2 漯河 685.60 813.00
E3 南阳 734.50 930.80
E4 濮阳 563.80 487.00
E5 商丘 667.30 731.70
E6 原阳 889.20 482.10
E7 周口 721.00 855.20
E8 驻马店 922.00 1052.40

Table 3

Pod yield of peanut varieties kg/hm2"

编号
Code		 2016 2017 平均产量
Average yield
G1 5545.20±723.60 6011.30±1150.90 5778.30±233.10
G2 5630.80±1097.50 5969.70±1106.10 5800.20±169.50
G3 5004.50±748.40 5414.40±1300.80 5209.40±204.90
G4 5677.20±913.20 6023.30±1000.10 5850.20±173.00
G5 5566.80±905.30 5695.40±1114.30 5631.10±64.30
G6 5193.20±1102.00 5644.20±942.00 5418.70±225.50
G7 5045.90±926.00 5185.40±1241.90 5115.60±69.80
G8 5402.90±1073.70 5635.30±1037.40 5519.10±116.20
G9 5036.70±1261.20 5290.50±1030.20 5163.60±126.90
平均值
Average		 5344.80
 5652.20
 5498.50
变异系数
CV (%)		 4.86
 5.19
 5.76

Table 4

Agronomic traits of tested peanut varieties"

编号Code X1 (cm) X2 (cm) X3 X4 X5 X6 (g) X7 (g) X8 (g) X9 (%)
G1 59.60±12.80 59.10±8.90 7.00±0.90 13.70±2.70 6.00±0.60 20.60±1.80 264.30±14.20 103.40±4.80 67.00±1.60
G2 65.20±12.60 52.70±8.90 7.90±0.60 14.20±2.50 6.50±0.80 21.30±4.10 259.60±17.20 100.50±4.60 66.70±1.60
G3 62.40±12.30 67.40±13.00 6.50±0.90 12.30±2.50 5.30±0.70 18.30±1.40 298.60±18.00 115.40±4.70 68.50±2.00
G4 52.20±6.20 56.30±6.90 8.10±1.40 14.10±2.90 6.20±0.80 22.30±3.90 285.30±10.50 108.70±5.30 68.90±1.70
G5 57.40±10.30 61.40±11.50 7.20±0.80 14.40±2.70 5.90±0.60 20.80±4.30 239.60±13.50 97.70±5.30 68.90±1.70
G6 46.40±7.10 52.30±9.80 8.20±0.90 16.00±2.20 6.60±0.80 22.30±4.60 223.10±9.20 91.40±3.80 71.60±1.10
G7 53.10±8.80 57.80±8.40 8.50±0.70 15.70±2.70 6.50±0.50 20.20±3.00 217.40±10.00 88.20±5.40 67.70±1.80
G8 54.50±9.00 58.30±9.00 7.20±1.40 15.10±3.40 6.00±0.90 23.50±4.60 242.30±16.50 95.60±8.20 68.80±1.20
G9 50.40±9.20 54.20±9.70 8.10±1.00 16.90±4.90 6.40±0.80 22.30±6.30 231.50±11.30 92.90±8.00 70.30±1.40
平均值Average 55.70 57.70 7.60 14.70 6.10 21.30 251.30 99.30 68.70
变异系数CV (%) 20.73 18.52 15.24 22.56 13.66 20.22 11.78 10.10 3.11

Fig.1

Heat map of correlation coefficients between yield and agronomic traits of peanut varieties “*”and“**”indicate significant correlation at the 0.05 and 0.01 levels, respectively."

Table 5

Path coefficients of peanut pod yield and agronomic characteristics"

性状
Trait		 直接通径系数
Direct path coefficient		 间接通径系数Indirect path coefficient
X1 X2 X3 X4 X5 X6 X7 X8 X9
X1 0.0570 － 0.0557 0.0010 -0.0145 0.0037 -0.0050 -0.0021 -0.0044 0.0070
X2 -0.5210 -0.5090 － -0.0089 0.1323 -0.0339 0.0453 0.0193 0.0401 -0.0641
X3 0.1770 0.0030 0.0096 － -0.0450 0.0115 -0.0154 -0.0065 -0.0136 0.0218
X4 0.0260 -0.0066 -0.0065 0.0071 － 0.0017 -0.0023 -0.0010 -0.0020 0.0032
X5 -0.1910 -0.0124 -0.0107 -0.1199 -0.0252 － 0.0166 0.0071 0.0147 -0.0235
X6 -0.3010 0.0262 0.0334 -0.0352 -0.1565 -0.0888 － 0.0111 0.0232 -0.0370
X7 0.1210 -0.0045 -0.0047 -0.0178 -0.0173 -0.0132 0.0127 － -0.0093 0.0149
X8 0.1970 -0.0152 -0.0195 -0.0288 0.0211 -0.0396 0.0349 0.1521 － 0.0242
X9 0.1090 0.0134 0.0138 0.0100 -0.0144 0.0174 -0.0060 -0.0208 -0.0275 －

Fig.2

Trait stability of different peanut varieties (a) yield, (b) 100-seed weight, the same below."

Fig.3

Adaptability analysis of different peanut varieties"

Fig.4

Sorting diagram of ideal varieties"

[1] 国家统计局. 中国统计年鉴. 北京: 中国统计出版社, 2022.
[2] 董文召. 河南花生产业技术体系以创新引领产业高质量发展. 河南农业, 2023(4):10-11.
[3] 严威凯. 双标图分析在农作物品种多点试验中的应用. 作物学报, 2010, 36(11):1805-1819.
doi: 10.3724/SP.J.1006.2010.01805
[4] 严威凯. 农作物品种试验数据管理与分析. 北京: 中国农业科学技术出版社, 2015.
[5] 严威凯. 品种选育与评价的原理和方法评述. 作物学报, 2022, 48(9):2137-2154.
doi: 10.3724/SP.J.1006.2022.11105
[6] Yan W K, Tinker N A. Biplot analysis of multi-environment trial data: principles and applications. Canadian Journal of Plant Science, 2006, 86:623-645.
[7] Yan W K, Kang M S, Ma B L, et al. GGE Biplot vs. AMMI analysis of genotype-by-environment data. Crop Science, 2007, 47:641-653.
[8] Des Marais D L, Hernandez K M, Juenger T E. Genotype-by- environment interaction and plasticity: exploring genomic responses of plants to the abiotic environment. Annual Review of Ecology Evolution and Systematics, 2013, 44:5-29.
[9] 叶夕苗, 程鑫, 安聪聪, 等. 马铃薯产量组分的基因型与环境互作及稳定性. 作物学报, 2020, 46(3):354-364.
doi: 10.3724/SP.J.1006.2020.94089
[10] 周丙月, 袁剑龙, 张玉梅, 等. 马铃薯品种(系)农艺性状的适应性和稳定性分析. 核农学报, 2023, 37(2):274-289.
doi: 10.11869/j.issn.1000-8551.2023.02.0274
[11] 李建武, 李高峰, 文国宏, 等. 甘肃省多点联合试验马铃薯产量要素稳定性及试点鉴别力分析. 西北农业学报, 2022, 31 (11):1422-1434.
[12] 谢文锦, 李方明, 李宁, 等. 基于GGE双标图的北方地区鲜食糯玉米产量和品质性状及试点鉴别力分析. 作物杂志, 2023 (4):85-90.
[13] 肖继兵, 刘志, 孔凡信, 等. 基于GGE双标图的高粱品种农艺性状和稳产性分析. 作物杂志, 2023(2):36-45.
[14] 公丹, 罗高玲, 张晓艳, 等. 34个豇豆新品系在不同生态区的适应性评价. 作物杂志, 2022(2):89-95.
[15] 邵扬, 郭延平, 周丙月, 等. 蚕豆产量组分的基因型与环境互作及稳定性分析. 作物学报, 2024, 50(1):149-160.
doi: 10.3724/SP.J.1006.2024.24265
[16] 李艳花, 陈红, 王萍, 等. 蚕豆高代材料单株产量与农艺性状的相关和通径分析. 江苏农业科学, 2018, 46(20):79-81.
[17] 罗俊, 张华, 邓祖湖, 等. 应用GGE双标图分析甘蔗品种(系)的产量和品质性状. 作物学报, 2013, 39(1):142-152.
[18] 张志芬, 付晓峰, 刘俊青, 等. 用GGE双标图分析燕麦区域试验品系产量稳定性及试点代表性. 作物学报, 2010, 36(8):1377-1385.
[19] 邓丽, 郭敏杰, 苗建利, 等. 基于通径系数和GGE双标图的大粒花生综合分析. 江苏农业科学, 2021, 49(19):129-133.
[20] 邓丽, 郭敏杰, 殷君华, 等. 高油酸花生品种开农1760产量及其构成的可视化分析. 中国油料作物学报, 2021, 43(3):502-509.
[21] 于沐, 李盼, 胡延岭, 等. 基于双标图及通径系数对高油酸花生新品种郑农花23号的综合评价. 种子, 2022, 41(9):98-105,114,149.
[22] 徐益, 张列梅, 祁建民, 等. 黄麻纤维产量与主要农艺性状的相关分析. 作物学报, 2018, 44(6):859-866.
doi: 10.3724/SP.J.1006.2018.00859
[23] 张莹莹, 卢道文, 孙海潮, 等. 黄淮海区域玉米收获期籽粒含水量与主要农艺性状的相关分析和通径分析. 江苏农业科学, 2022, 50(13):119-123.
[24] 殷冬梅, 李拴柱, 崔党群. 花生主要农艺性状的相关性及聚类分析. 中国油料作物学报, 2010, 32(2):212-216.
[25] 郭敏杰, 邓丽, 苗建利, 等. 基于BLUP值的大粒花生农艺性状与产量的相关和通径分析. 河北农业大学学报, 2021, 44 (5):36-41.
doi: 10.13320/j.cnki.jauh.2021.0081
[26] 姜慧芳, 段乃雄. 花生种质资源描述规范和数据标准. 北京: 中国农业出版社, 2006.
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