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Chinese Agricultural Science Bulletin ›› 2024, Vol. 40 ›› Issue (13): 140-145.doi: 10.11924/j.issn.1000-6850.casb2023-0388

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Application Evaluation of AMMI Model and GGE Biplot Based on R Language in Soybean Regional Test

ZHANG Kaidong1,2(), ZHANG Fanqiao3, DONG Bo2(), DUAN Jialin4,5(), CHEN Guangrong2, WANG Liming2, YANG Ruping2   

  1. 1 Yuzhong Alpine Agricultural Experiment Station, Gansu Academy of Agricultural Sciences/Gansu Greenstar Agro-tech Co. LTD., Lanzhou 730100
    2 Dryland Agriculture Institute, Gansu Academy of Agricultural Sciences, Lanzhou 730070
    3 Forestry and Grassland Service Center of Tongwei County, Tongwei, Gansu 743300
    4 College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070
    5 Gansu Province Institute of Cold-Arid and Ecological Agriculture, Lanzhou 730070
  • Received:2023-05-24 Revised:2023-12-27 Online:2024-04-28 Published:2024-04-28

Abstract:

To improve the selection and application efficiency of soybean varieties in Gansu Province, data from soybean regional trials were used to comprehensively assess the stability and adaptability of new soybean varieties in Gansu Province and the discrimination power of each pilot site in terms of the interaction analysis between genotype and environment. This paper used the AMMI model combined with GGE double-labeled plots to analyze the yields of nine soybean varieties in Gansu Province at five trial sites. The results showed that the principal component values (IPCA1 and IPCA2) in the AMMI model accounted for 95% of the sum of squares of the total variation; among them, ‘Zhonghuang 318’ was a high-yield and stable variety, while ‘Longhuang 3’ and ‘Tiefeng 31’ had higher yields but moderate stability, making them only suitable for cultivation in specific areas. Among the five trial sites, Liangzhou had the strongest discrimination power and Zhenyuan was weaker. The combined use of the AMMI model and the GGE double-labeled map method can more accurately and intuitively reflect the productivity, stability and adaptability of each variety as well as the discrimination power and representativeness of each trial site.

Key words: AMMI model, GGE biplots, soybean, stability, adaptability