欢迎访问作物学报，今天是
作物学报

作物学报 ›› 2021, Vol. 47 ›› Issue (4): 660-671.doi: 10.3724/SP.J.1006.2021.04135

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

基于GYT双标图对西北内陆棉区国审棉花品种的分类评价

许乃银1(), 赵素琴2, 张芳3, 付小琼4, 杨晓妮1, 乔银桃1,5, 孙世贤3   

  1. 1江苏省农业科学院经济作物研究所 / 农业农村部长江下游棉花与油菜重点实验室, 江苏南京 210014
    2新疆维吾尔自治区种业发展中心, 新疆乌鲁木齐 830006
    3全国农业技术推广服务中心, 北京 100125
    4中国农业科学院棉花研究所, 河南安阳 455000
    5江苏大学农业工程学院, 江苏镇江 212013
  • 收稿日期:2020-06-22 接受日期:2020-10-14 出版日期:2021-04-12 网络出版日期:2020-11-02
  • 作者简介:E-mail: naiyin@126.com
  • 基金资助:
    国家农业技术试验示范与服务支持(品种试验)项目(012022911108)

Retrospective evaluation of cotton varieties nationally registered for the Northwest Inland cotton growing regions based on GYT biplot analysis

XU Nai-Yin1(), ZHAO Su-Qin2, ZHANG Fang3, FU Xiao-Qiong4, YANG Xiao-Ni1, QIAO Yin-Tao1,5, SUN Shi-Xian3   

  1. 1Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences / Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing 210014, Jiangsu, China
    2Xinjiang Uygur Autonomous Region Seed Industry Development Center, Urumqi 830006, Xinjiang, China
    3National Extension and Service Center of Agricultural Technology, Beijing 100125, China
    4Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
    5School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China
  • Received:2020-06-22 Accepted:2020-10-14 Published:2021-04-12 Published online:2020-11-02
  • Supported by:
    National Agricultural Technology Field Experiment, Demonstration and Service Support (Variety Test) Project(012022911108)

RichHTML

11

PDF

503

摘要：

西北内陆棉区是我国最重要的主产棉区, 对该棉区历年国审棉花品种进行科学分类和综合评价有利于国审品种资源的合理利用和棉花生产效率的提升。本研究采用GYT双标图分析对2003—2019年期间西北内陆棉区37个国审棉花品种的产量与霜前花率、纤维长度、比强度、马克隆值、枯萎病指数和黄萎病指数等性状的组合水平进行了综合分析和品种分类评价。结果表明, 西北内陆棉区37个国审棉花品种可划分为3个特征明显的品种类型。其中, I型品种包括新陆早13号、中棉所49、新陆早21号、巴13222、新46、天云0769、Z1112、新石K18、J206-5、新石K21、禾棉A9-9、创棉508、H33-1-4、金科20、新K28、创棉512和J8031等17个品种, 是产量与其余性状组合协调最好的品种类型, 在生产上推广应用价值最高。II型品种产量和纤维品质表现一般, 抗病性差, 在当前生产上应用价值有限。III型品种的抗枯萎病性表现最好, 但在其余性状上表现略差, 综合生产应用价值有限, 也许可作为抗病亲本应用。同时, 根据各品种的理想指数筛选出创棉512、J8031、新K28、H33-1-4、金科20、新陆早13号和创棉508等综合表现优良的品种, 也鉴别出新陆棉1号、新陆早33号、创棉501号和新陆早51号等综合表现相对略差的品种。本研究采用的GYT双标图分析方法是基于“产量-性状”组合水平对品种进行综合评价和分类研究, 产量-性状组合之间的相关关系更加简单, 多数组合间表现显著正相关, 更适用于品种的多性状直观选择和综合评价, 通常比先前的GT双标图解释的变异比率高, 双标图模型拟合度更好, 结果更可靠。本研究采用GYT双标图分析方法对西北内陆棉区国审品种的分类研究揭示了该棉区国审棉花品种的分类特征和应用价值, 为本区的国家棉花品种试验审定提供了借鉴, 也为其他作物品种的类似研究提供了范例。

关键词: 棉花(Gossypium hirsutum L.), 品种审定, 品种分类, 多性状, GT双标图, GYT双标图, 西北内陆棉区

Abstract:

The Northwest inland cotton growing regions (NICR) is currently the most important cotton producing area in China. The scientific classification and comprehensive evaluation of national cotton varieties over the years in this cotton area is beneficial to the rational utilization of national cotton varieties resources and the improvement of cotton production efficiency. According to the national registration bulletins of cotton cultivars, up to 37 cotton cultivars in this region were registered in the national level from 2003 to 2019. These cultivars were evaluated and classified using genotype by yield-trait (GYT) biplot analysis based on their levels in combine with lint cotton yield and other important characteristics including pre-frost yielding rate (PFR), fiber length, fiber strength, micronaire, fusarirum wilt index (FWI), and verticillium wilt index (VWI). Results showed that the 37 cotton cultivars can be clustered into three types with distinct trait profiles. Type I consisted of 17 cotton cultivars, namely Xinluzao 13, Zhongmiansuo 49, Xinluzao 21, Ba 13222, Xin 46, Tianyun 0769, Z1112, Xinshi K18, J206-5, Xinshi K21, Hemian A9-9, Chuangmian 508, H33-1-4, Jinke 20, Xin K28, Chuangmian 512, and J8031, showing high levels of combinations between yield and other target traits, and was the most suitable for cotton production in the region. Type II was characterized by poor performance in FWI, and moderate yielding ability and fiber quality traits, and was of limited application in this area. Type III was characterized by an excellent performance in FWI but poor performance on the other traits, and cultivars of this type may be useful for sources of disease resistance. Cultivars Chuangmian 512, J8031, Xin K28, H33-1-4, Jinke 20, Xinluzao 13, and Chuangmian 508 were selected for their high superiority index, such as high levels of combination between yield and other traits, while Xinlumian 1, Xinluzao 33, Chuangmian 501, and Xinluz 51 were inferior in this context. The GYT biplot analysis in this study differed from traditional index selection in that it was based on the combinatoin level of yield and other traits rather than on the levels of individual traits. In GYT biplot the various yield-trait combinaitons tended to be positievly correlated, allowing for easy visualizationand objective selection of cultivars based on multiple traits. Compared with the more traditional genotype by trait (GT) biplot, GYT biplot normally explained more of the total variation and achieve higher goodness of fit. In addition, the method used in this study could be applied to other regions and crops in this reasearch topic.

Key words: cotton (Gossypium hirsutum L.), cultivar registration, cultivar classification, multiple traits, genotype by trait (GT) biplot, genotype by yield-trait (GYT) biplot, northwest inland cotton growing region (NICR)

表1

2003-2019年我国西北内陆棉区37个国审棉花品种主要性状表"

代码
Code		 品种
Cultivar		 RY YLD/CK
(%)		 PFR
(%)		 LEN
(mm)		 STR
(cN tex-1)		 MIC FWI VWI SI TYPE
G1 新陆早13号 Xinluzao 13 2003 112.9 92.8 31.2 29.7 4.3 47.5 4.6 0.67 I
G2 新陆中20号 Xinluzhong 20 2004 107.4 91.6 30.6 29.5 4.4 3.5 72.0 -0.49 III
G3 中棉所49 Zhongmiansuo 49 2004 110.9 93.7 30.5 29.0 4.3 7.1 31.8 0.36 I
G4 新陆早21号 Xinluzao 21 2005 112.3 90.9 29.6 29.3 4.2 19.0 47.9 0.16 I
G5 新陆棉1号 Xinlumian 1 2006 106.4 88.9 30.3 28.9 4.4 45.2 77.2 -1.17 II
G6 新陆早33号 Xinluzao 33 2007 103.8 88.6 30.2 30.3 4.3 25.9 62.0 -1.03 III
G7 新陆中34号 Xinluzhong 34 2008 104.7 93.9 29.5 31.2 4.2 65.1 38.5 -0.76 II
G8 新陆早49号 Xinluzao 49 2010 107.4 90.2 32.2 32.7 4.6 62.0 76.0 -0.63 II
G9 新陆早51号 Xinluzao 51 2011 104.7 95.7 30.3 30.9 4.5 50.5 70.4 -0.97 II
G10 新陆早48号 Xinluzao 48 2011 114.4 97.7 28.8 28.1 4.3 52.7 51.6 0.08 II
G11 新陆中51号 Xinluzhong 51 2011 110.4 93.8 31.9 32.7 4.3 69.0 66.5 0.05 II
G12 新桑塔6号 Xinsangta 6 2011 110.0 94.3 30.5 30.8 4.3 60.9 78.8 -0.40 II
代码
Code		 品种
Cultivar		 RY YLD/CK
(%)		 PFR
(%)		 LEN
(mm)		 STR
(cN tex-1)		 MIC FWI VWI SI TYPE
G13 新陆中60号 Xinluzhong 60 2012 101.2 91.9 30.3 33.2 4.3 3.6 51.2 -0.71 III
G14 K07-12 2013 106.4 94.0 29.7 30.4 4.3 1.1 65.3 -0.42 III
G15 巴13222 Ba 13222 2013 111.8 93.7 30.3 30.8 4.8 10.4 58.5 0.05 I
G16 万氏472 Wanshi 472 2014 97.0 93.0 33.8 32.1 3.9 0.7 61.9 -0.83 III
G17 新46 Xin 46 2014 116.4 87.5 30.2 28.5 4.8 0.2 50.6 0.27 I
G18 天云0769 Tianyun 0769 2015 111.9 91.5 30.4 30.2 4.2 7.6 55.3 0.35 I
G19 DJ09520 2015 107.7 93.5 31.0 30.9 4.5 3.4 53.2 -0.09 III
G20 创棉50号 Chuangmian 50 2015 109.0 92.6 29.0 30.0 4.9 5.2 54.4 -0.57 III
G21 Z1112 2016 109.6 93.9 29.9 31.6 3.9 5.1 55.1 0.37 I
G22 新石K18 Xinshi K18 2016 107.1 97.7 30.5 29.9 4.0 5.2 64.6 0.01 I
G23 J206-5 2016 112.4 94.8 30.5 30.2 4.1 12.0 61.9 0.52 I
G24 创棉501号 Chuangmian 501 2016 105.8 93.0 29.2 29.5 4.7 10.3 64.7 -0.98 III
G25 惠远720 Huiyuan 720 2017 105.6 97.4 31.4 29.4 4.4 1.5 39.7 -0.13 III
G26 新石K21 Xinshi K21 2017 109.7 98.5 29.8 30.1 4.2 3.8 47.6 0.35 I
G27 禾棉A9-9 Hemian A9-9 2017 108.2 93.6 30.7 30.2 4.2 9.9 19.0 0.31 I
G28 创棉508 Chuangmian 508 2018 110.4 97.2 30.4 31.9 4.4 3.0 43.2 0.57 I
G29 庄稼汉902 Zhuangjiahan 902 2019 105.1 95.8 29.8 31.6 4.4 6.3 33.7 -0.21 III
G30 F015-5 2019 106.6 97.0 30.8 35.4 4.9 3.6 24.0 0.33 III
G31 H33-1-4 2019 110.9 94.9 31.3 32.4 4.3 4.2 33.4 0.86 I
G32 金科20 Jinke 20 2019 110.0 94.1 32.4 33.1 4.3 12.5 34.3 0.85 I
G33 惠远1401 Huiyuan 1401 2019 103.5 96.4 31.0 31.0 4.7 3.6 37.3 -0.49 III
G34 新K28 Xin K28 2019 111.3 95.8 31.1 31.8 4.2 6.7 28.2 0.95 I
G35 中棉201 Zhongmian 201 2019 105.3 94.9 30.8 32.6 4.3 4.5 33.8 0.07 III
G36 创棉512 Chuangmian 512 2019 114.6 97.7 31.1 32.0 4.4 4.2 20.0 1.45 I
G37 J8031 2019 113.4 97.3 31.6 32.6 4.4 7.4 31.5 1.27 I

图1

我国西北内陆棉区国审棉花品种的GT双标图(a)和GYT双标图(b)的性状相关性功能图缩写同表1和表2。Abbreviations are the same as those given in Table 1 and Table 2."

图2

我国西北内陆棉区国审棉花品种的GYT双标图的平均性状功能图(a)品种聚类功能图(b) 图2-b中椭圆形虚线包围的品种与基于GYT双标图前两主成分聚类分析的前3个分类相同(聚类图略)。I、II和III分别表示I型品种、II型品种和III型品种。缩写同表1和表2。"

表2

我国西北内陆棉区37个国审棉花品种产量与性状组合相关性分析"

产量×性状组合
Yield×trait combination		 Y×PFR Y×LEN Y×STR Y×MIC (~1) Y×FWI (-1) Y×VWI (-1) SI
产量×霜前花率Yield× pre-frost yielding rate (Y×PFR) 1
产量×纤维长度Yield× fiber length (Y×LEN) 0.586** 1
产量×比强度Yield× fiber strength(Y×STR) 0.518** 0.624** 1
产量×马克隆值Yield× micronaire [Y×MIC(~1)] 0.516** 0.471** 0.170 ns 1
产量×枯萎病指数
Yield× fusarirum wilt index [Y×FWI(-1)]		 0.136 ns 0.031 ns 0.070 ns -0.043 ns 1
产量×黄萎病指数
Yield× verticillium wilt index[Y×VWI(-1)]		 0.458** 0.359* 0.410** 0.191 ns 0.316* 1
品种理想指数Cultivar superiority index (SI) 0.813** 0.776** 0.707** 0.583** 0.382* 0.692** 1

表3

基于GYT双标图分析的西北内陆棉区国审棉花品种分类特征比较"

产量×性状组合
Yield × trait combination		 I型品种
Variety type I
(mean ± SE)		 II型品种
Variety type II
(mean ± SE)		 III型品种
Variety type III
(mean ± SE)
产量×霜前花率Yield × pre-frost yielding rate (Y×PFR) 0.63±0.15 a -0.16±0.44 b -0.73±0.23 b
产量×纤维长度Yield × fiber length (Y×LEN) 0.66±0.18 a -0.14±0.40 b -0.79±0.17 b
产量×比强度Yield × fiber strength (Y×STR) 0.40±0.21 a -0.15±0.39 ab -0.44±0.28 b
产量×马克隆值Yield × micronaire [Y×MIC(~1)] 0.69±0.16 a -0.03±0.31 b -0.89±0.20 c
产量×枯萎病指数 Yield × fusarirum wilt index [Y×FWI(-1)] 0.43±0.12 a -1.86±0.15 b 0.45±0.08 a
产量×黄萎病指数Yield × verticillium wilt index [Y×VWI(-1)] 0.50±0.23 a -0.92±0.30 b -0.15±0.22 ab
品种理想指数 Cultivar superiority index (SI) 0.55±0.10 a -0.54±0.18 b -0.43±0.11 b

附表1

2003-2019年西北内陆棉区37个国审棉花品种的GYT和标准化GYT数据及理想指数(SI)表"

[1] Yan W K, Frégeau-Reid J. Breeding line selection based on multiple traits. Crop Sci, 2008,48:417-423.
doi: 10.2135/cropsci2007.05.0254
[2] Yan W K, Frégeau-Reid J. Genotype by yield*trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Sci Rep, 2018,8:8242.
doi: 10.1038/s41598-018-26688-8 pmid: 29844453
[3] Cooper M, Woodruff D R, Eisemann R L, Brennan P S, Delacy I H. A selection strategy to accommodate genotype-by-environment interaction for grain yield of wheat: managed-environments for selection among genotypes. Theor Appl Genet, 1995,90:492-502.
doi: 10.1007/BF00221995 pmid: 24173943
[4] 许乃银, 李健. 棉花区试中品种多性状选择的理想试验环境鉴别. 作物学报, 2014,40:1936-1945.
doi: 10.3724/SP.J.1006.2014.01936
Xu N Y, Li J. Identification of ideal test environments for multiple traits selection in cotton regional trials. Acta Agron Sin, 2014,40:1936-1945 (in Chinese with English abstract).
[5] 许乃银, 李健. 基于GGE双标图的长江流域国审棉花品种分类特征评价. 中国农业科学, 2014,47:4780-4789.
doi: 10.3864/j.issn.0578-1752.2014.24.002
Xu N Y, Li J. Evaluation on the classification characteristics of national registered cotton varieties in the Yangtze River Valley based on GGE biplot. Sci Agric Sin, 2014,47:4780-4789 (in Chinese with English abstract).
[6] Yan W K. Crop Variety Trials: Data Management and Analysis. Oxford: Wiley-Blackwell, 2014. pp 163-186.
[7] 许乃银, 李健. 我国主产棉区棉花纤维品质性状的区域分布特征. 中国生态农业学报, 2016,24:1547-1554.
Xu N Y, Li J. Regional distribution characteristics of cotton fiber quality in main cotton production areas in China. Chin J Eco- Agric, 2016,24:1547-1554 (in Chinese with English abstract).
[8] Xu N Y, Fok M, Zhang G W, Li J, Zhou Z G. The application of GGE biplot analysis for evaluating test locations and mega- environment investigation of cotton regional trials. J Integr Agric, 2014,13:1921-1933.
doi: 10.1016/S2095-3119(13)60656-5
[9] Merrick L F, Glover K D, Yabwalo D, Byamukama E. Use of genotype by yield*trait (GYT) analysis to select hard red spring wheat with elevated performance for agronomic and disease resistance traits. Crop Breed Genet Genom, 2020,2:e200009.
[10] Yan W K, Frégeau-Reid J, Mountain N, Kobler J. Genotype and management evaluation based on genotype by yield*trait (GYT) analysis. Crop Breed Genet Genom, 2019,1:e190002.
[11] Yan W K, Holland J B. A heritability-adjusted GGE biplot for test environment evaluation. Euphytica, 2010,171:355-369.
doi: 10.1007/s10681-009-0030-5
[12] 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, 2010,36:1805-1819.
doi: 10.3724/SP.J.1006.2010.01805
Yan W K. Optimal use of biplots in analysis of multi-location variety test data. Acta Agron Sin, 2010,36:1805-1819 (in Chinese with English abstract).
[13] Yan W K, Kang M S, Ma B L, Woods S, Cornelius P L. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci, 2007,47:643-655.
doi: 10.2135/cropsci2006.06.0374
[14] Yan W K. Singular-value partioning in biplot analysis of multienvironment trial data. Agron J, 2002,94:990-996.
doi: 10.2134/agronj2002.0990
[15] Xu N Y, Fok M, Li J, Yang X N, Yan W K. Optimization of cotton variety registration criteria aided with a genotype-by-trait biplot analysis. Sci Rep, 2017,7:17237.
doi: 10.1038/s41598-017-17631-4 pmid: 29222523
[16] Adugna W, Labuschagne M T. Cluster and canonical variate analyses in multilocation trials of linseed. J Agric Sci, 2003,140:297-304.
doi: 10.1017/S0021859603003174
[1] 许乃银,李健. 棉花区试中品种多性状选择的理想试验环境鉴别[J]. 作物学报, 2014, 40(11): 1936-1945.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2