欢迎访问《中国农学通报》,

中国农学通报 ›› 2023, Vol. 39 ›› Issue (8): 7-14.doi: 10.11924/j.issn.1000-6850.casb2022-0173

• 农学·农业基础科学 • 上一篇    下一篇

基于R语言的GGE双标图法在甜菜品种区域试验中的应用

江婉玥1(), 胡晓航1,2(), 马亚怀1,2, 李彦丽1,2   

  1. 1 黑龙江大学现代农业与生态环境学院,哈尔滨 150080
    2 国家糖料改良中心,哈尔滨 150080
  • 收稿日期:2022-03-15 修回日期:2022-07-15 出版日期:2023-03-15 发布日期:2023-03-14
  • 通讯作者: 胡晓航,女,1980年出生,黑龙江哈尔滨人,副研究员,博士,主要从事土壤生态与作物栽培方向的研究。通信地址:150080 黑龙江省哈尔滨市南岗区学府路74号,Tel:0451-86609312,E-mail:hxhlmz@163.com
  • 作者简介:

    江婉玥,女,1998年出生,浙江安吉人,研究生,研究方向:农艺与种业。通信地址:150080 黑龙江省哈尔滨市南岗区学府路74号, E-mail:

  • 基金资助:
    黑龙江省省属高等学校基本科研业务费项目“DSSAT-CERES-BEET模型在东北寒地甜菜生产中的适用性评价”(2020-KYYWF-1025); 财政部和农业农村部林木遗传育种国家重点实验室开放基金项目“蓖麻CRISPR/Cas9基因编辑体系的建立”(K2021202); 国家糖料产业技术体系分解项目“基于无人机遥感技术的糖用甜菜施肥决策模型研究”(CARS-170202); 2022年黑龙江大学创新科研项目“基于GGE双标图的糖用甜菜区试品种综合评价研究”(YJSCX2022-261HLJU)

GGE-biplot Based on R Language: Application in Regional Trial of Sugar Beet Varieties

JIANG Wanyue1(), HU Xiaohang1,2(), MA Yahuai1,2, LI Yanli1,2   

  1. 1 Academy of Modern Agriculture and Ecology Environment, Heilongjiang University, Harbin 150080
    2 National Sugar Improvement Center, Harbin 150080
  • Received:2022-03-15 Revised:2022-07-15 Online:2023-03-15 Published:2023-03-14

摘要:

为了明确糖用甜菜品种在全国不同区域试验中参试品种的丰产性、稳产性、适应性及各试验点的区分力和代表力。2020年在全国不同生态区域的9个试验基地,以16个引种的KWS系列糖用甜菜品种为试材,采用基于R语言的GGE双标图法对糖用甜菜品种的产糖量指标进行分析。结果表明,在2020年品种区域试验中,KWS 0015(G16)丰产性最佳;KWS 7748(G6)、KWS 9921(G15)具有较好的稳产性;KWS 0015(G16)适宜种植的区试点最多,具有较强区域适应性,较其他品种高产稳产,为本试验理想品种。此外,呼和浩特(E9)具有较高区分力和较好代表性,是本研究的理想区试点。GGE双标图法对综合分析糖用甜菜品种基因型、环境与基因型交互效应具有科学合理性。

关键词: GGE双标图, R语言, 糖用甜菜, 区域试验, 产糖量

Abstract:

The aims are to clarify the yielding ability, yield stability, and adaptability of sugar beet varieties tested in different regional trials across China, and to identify the discriminability and representativeness of each test point. In 2020, 16 introduced KWS series sugar beet varieties were used as the test materials in 9 test bases in different ecological regions across the country. The sugar yield indicators of the varieties were analyzed by GGE biplot method based on R language. The results showed that KWS 0015(G16) had the highest yield in the regional trial of sugar beet varieties in 2020. KWS 7748(G6) and KWS 9921(G15) had relatively stable yield; and KWS 0015(G16) was the ideal variety for most test bases because of its strong regional adaptability, high and stable yield compared with other varieties. In addition, Hohhot (E9) had higher discriminability and better representativeness, and was an ideal pilot area for this study. In conclusion, the GGE biplot method is scientific for the comprehensive analysis of genotype, and environment and genotype interaction effects of sugar beet varieties.

Key words: GGE biplot, R language, sugar beet, regional trial, sugar yield