首页|基于R语言的AMMI模型和GGE双标图在大豆区试中的应用评价

基于R语言的AMMI模型和GGE双标图在大豆区试中的应用评价

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为提高甘肃省大豆品种的选育和应用效率,利用大豆区域试验数据,从基因型与环境的互作分析出发,对甘肃省大豆新品种的稳定性、适应性以及各试点的鉴别力进行全面评估.本研究采用AMMI模型与GGE双标图相结合的方法对甘肃省9个大豆品种在5个试验点的产量进行分析,结果表明,AMMI模型中主成分值(IPCA1、IPCA2)占总变异平方和的95%;其中'中黄318'属于高产稳产性品种,而'陇黄3号'和'铁丰31'虽然产量较高,但其稳定性中等,适合在特定区域栽培.在5个试验点中,凉州分辨力最强,镇原分辨力较弱.综合运用AMMI模型和GGE双标图法,能够更准确直观地反映各品种生产力、稳定性和适应能力,以及在不同试验区域的分辨能力和代表性.
Application Evaluation of AMMI Model and GGE Biplot Based on R Language in Soybean Regional Test
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.

AMMI modelGGE biplotssoybeanstabilityadaptability

张恺东、张凡巧、董博、段佳霖、陈光荣、王立明、杨如萍

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甘肃省农业科学院榆中高寒农业试验站/甘肃绿星农业科技有限责任公司,兰州 730070

甘肃省农业科学院旱地农业研究所,兰州 730700

通渭县林业和草原服务中心,甘肃通渭 743300

甘肃农业大学资源与环境学院,兰州 730070

甘肃省寒旱生态农业研究所,兰州 730070

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AMMI模型 GGE双标图 大豆 稳定性 适应性

现代农业产业技术体系建设项目甘肃省农科院重点研发计划甘肃省农科院重点研发计划甘肃省农科院重点研发计划甘肃省重点研发计划

CARS-04-CES252020GAAS112021GAAS162022GAAS1020YF8NA107

2024

中国农学通报
中国农学会

中国农学通报

CSTPCD
影响因子:0.891
ISSN:1000-6850
年,卷(期):2024.40(13)