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作物学报 ›› 2024, Vol. 50 ›› Issue (1): 149-160.doi: 10.3724/SP.J.1006.2024.24265

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

蚕豆产量组分的基因型与环境互作及稳定性分析

邵扬1(), 郭延平1, 周丙月2, 张峰3,4, 张兴民2, 王玉萍2,4,*()   

  1. 1甘肃省临夏回族自治州农业科学院, 甘肃临夏 731100
    2甘肃农业大学园艺学院, 甘肃兰州 730070
    3甘肃农业大学农学院,甘肃兰州 730070
    4甘肃农业大学/甘肃省作物遗传改良与种质创新重点实验室, 甘肃兰州 730070
  • 收稿日期:2022-11-30 接受日期:2023-04-17 出版日期:2024-01-12 网络出版日期:2023-12-16
  • 通讯作者: *王玉萍, E-mail: wangyp@gsau.edu.cn
  • 作者简介:E-mail: shaoyang1201@qq.com
  • 基金资助:
    国家自然科学基金项目(31760351);财政部和农业农村部国家现代农业产业技术体系建设专项(CARS-08)

Analysis of genotype × environment interaction and stability of yield components in faba bean lines

SHAO Yang1(), GUO Yan-Ping1, ZHOU Bing-Yue2, ZHANG Feng3,4, ZHANG Xin-Ming2, WANG Yu-Ping2,4,*()   

  1. 1Gansu Linxia Hui Autonomous Prefecture Academy of Agricultural Sciences, Linxia 731100, Gansu, China
    2College of Horticulture, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    3College of Agronomy, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    4Gansu Agricultural University / Gansu Key Laboratory of Crop Improvement & Germplasm Enhancement, Lanzhou 730070, Gansu, China
  • Received:2022-11-30 Accepted:2023-04-17 Published:2024-01-12 Published online:2023-12-16
  • Contact: *E-mail: wangyp@gsau.edu.cn
  • Supported by:
    National Natural Science Foundation of China(31760351);China Agriculture Research System of MOF and MARA(CARS-08)

摘要:

本研究通过综合评价蚕豆品系产量性状在不同试点的丰产性、适应性和稳定性, 筛选适应不同生态环境的产量性状稳定的优良品种(系)。同时评价各试点的区分力和代表性, 为试点选择提供依据。2017年和2018年在甘肃和政县、康乐县、积石山县、渭源县、临夏县和漳县6个试点分别种植5个蚕豆品系0215-1-4 (L1)、0208-3-1 (L2)、0208-3-2 (L3)、0323-2-1 (L4)、0161-1 (L5)与1个对照品种和政尕蚕豆(L6), 收获时记录株高、株粒数、小区产量、株荚数、分枝数、百粒重。采用联合方差和GGE (genotype + genotypes and environment interactions, GGE)双标图对产量性状进行基因型和基因型与环境互作分析。联合方差分析表明, 6个农艺性状的基因型除小区产量和株高基因型与环境互作效应无显著差异外, 其余性状的基因型与×环境互作效应均达到极显著水平(P<0.01); 除株高和株粒数基因型×年份互作效应达到极显著水平外(P<0.01), 其余农艺性状×年份互作效应无显著差异。相关性分析表明, 小区产量与株荚数和株粒数正相关, 与株荚数显著正相关(P<0.05), 与百粒重负相关。GGE分析结果表明, 品种(系)的适应性、丰产性和稳定性以及试点的区分力和代表性均具有较高的GGE变异值, 变幅在78.54%~97.38%之间。蚕豆品系L3在康乐县、积石山县、渭源县和临夏县试点的产量适应性均较高, 在和政县试点2018年产量适应性最高; 丰产性高的品种(系)依次为L3>L2>L6>L4, 稳定性最高的品种(系)依次为L4>L1>L5>L3。试点的区分力依次为康乐县2017年、积石山县2017年和2018年, 试点的代表性依次为渭源县2017年、康乐县2018年、积石山县2018年。高产且稳定的品系是L3和L4, 结合试点的区分力和代表性, 最理想的生态区试点是积石山县。本研究利用GGE双标图对甘肃蚕豆参试品种进行产量组分性状分析, 为蚕豆品种综合评价提供参考。

关键词: 蚕豆, GGE双标图, 多年多点, 产量组分, 试点评价

Abstract:

The objective of this study is to evaluate the productivity components, stability, and adaptability of faba bean yield traits of advance lines in different pilots and select excellent lines adapted to different mage-environments. The representativeness and discriminating ability of each test-environment pilots were also evaluated, providing a basis for the selection of test-pilots. To measure plant height, grains of per plant, pods of per plant, the number of branches, 100-grain weight, and yield of per plot, a total of five advance lines [0215-1-4 (L1), 0208-3-1 (L2), 0208-3-2 (L3), 0323-2-1 (L4), and 0161-1 (L5)] and one control variety Henzheng ga candou (L6) were planted in 2017 and 2018 in Gansu province insix pilots including Countries of Hezheng, Kangle, Jishishan, Weiyuan, Linxia, and Zhang. The genotype and genotype with environment interactions of yield were analyzed by the combined analysis of variance and GGE biplot. The plot yield and plant height had no significant difference in genotype and environment interactions effect, all the other yield components had significant differences (P<0.01) in genotype effect, environmental effect, and genotype and environment interaction effect. There were very significant differences between genotype and year interaction on the number of branches, pods of per plant, grains per plant, and 100-weight grain (P<0.01) while there was no significant difference between plant height and grains of per plant. The correlation analysis showed that yield of per plot was significantly at P < 0.05 and positively correlated with pods of per plant, but negatively correlated with 100-grain weight. The GGE analysis demonstrated that the adaptability, yield, and stability of varieties (lines), as well as the ability of discrimination and the representativeness of pilots all had high GGE variation values, ranging from 78.54% to 97.38%. According to the adaptability analysis of faba bean varieties (lines), L3 had the highest yield adaptability in Kangle county, Jishishan county, Weiyuan county, Linxia county, and Hezheng county in 2018. According to the stability analysis, the varieties (lines) with the high yield in order were L3 > L2 > L6 > L4, and the varieties (lines) with the high stability in order were L4 > L1 > L5 > L3. The discriminating ability of the pilot was Kangle county in 2017, followed by Jishishan county in 2017 and 2018, and the representativeness of the pilot was Weiyuan county in 2017, followed by Kangle county in 2018 and Jishishan county in 2018. The lines with stable and high yield were L3 and L4. Combined with the ability of distinguishing and representativeness of the pilot, the most ideal mage-environment was Jishishan county. Based on GGE biplot data, faba bean with superior yield-trait components were identified in Gansu province and provided a reference base for comprehensive evaluation of faba bean varieties.

Key words: faba bean, GGE biplot, multi-years and sites, yield component traits, pilot evaluation

表1

蚕豆高代品系和主栽品种的外观性状"

品种(系)编号
Variety (line) number
品种(系)
Variety (line)
试验年份
Year
L1 0215-1-4 2017-2018
L2 0208-3-1 2017-2018
L3 0208-3-2 2017-2018
L4 0323-2-1 2017-2018
L5 0161-1 2017-2018
L6 (Control) 和政尕蚕豆Hezhengga candou 2017-2018

表2

试验点环境信息"

地点
Location
海拔
Altitude
(m)
年降雨量
Annual
precipitation
(mm)
年日照时数
Annual
sunshine
(h)
年均温度
Mean annual temperature (℃)
无霜期
Frostless period (d)
土壤类型
Soil type
土壤质地
Soil texture
和政县
Hezheng county
2340 628 2504.9 5.1 130 山地黑麻土
Montane black hemp soil
中壤土
Medium loam
康乐县
Kangle county
2200 600 2510.0 6.1 140 山地黑麻土
Montane black hemp soil
中壤土
Medium loam
积石山县
Jishishan county
2600 728 2504.9 5.0 126 山地黑麻土
Montane black hemp soil
中壤土
Medium loam
渭源县
Weiyuan county
2240 580 2421.0 5.7 131 山地黑麻土
Montane black hemp soil
中壤土
Medium loam
临夏县
Linxia county
2035 450 2323.5 7.2 155 黄土
Loess
中壤土
Medium loam
漳县
Zhang county
2600 640 2214.9 4.4 101 山地黑麻土
Montane black hemp soil
中壤土
Medium loam

图1

参试品系(种)不同试点农艺性状分析 HZ: 和政县; KL: 康乐县; JSS; 积石山县; WY: 渭源县; LX: 临夏县; ZX: 漳县。"

表3

蚕豆农艺性状方差分析"

性状
Trait
变异来源
Source of
variations
自由度
DF
平方和
Sum of square
均值
Mean value
F检验
F-test
显著性
Significance
小区产量
Plot yield
基因型G 5 17,215.189 3443.038 0.656 0.659
环境E 5 19,281.128 3856.226 0.735 0.602
互作G×E 25 5298.575 211.943 0.040 1.000
残差Residual 36 188,859.429 5246.095
总变异Total 71 230,654.322
株高
Plant height
基因型G 5 1478.344 295.669 5.443 0.001
环境E 5 2430.911 486.182 8.949 < 0.001
互作G×E 25 858.839 34.354 0.632 0.883
残差Residual 36 1955.730 54.326
总变异Total 71 6723.824
分枝数
Branch number
基因型G 5 22.934 4.587 256.008 < 0.001
环境E 5 0.296 0.059 3.301 0.015
互作G×E 25 2.032 0.081 4.536 < 0.001
残差Residual 36 0.645 0.018
总变异Total 71 25.907
株荚数
Pod number per plant
基因型G 5 977.703 195.541 118.430 < 0.001
环境E 5 11.863 2.373 1.437 0.235
互作G×E 25 157.559 6.302 3.817 < 0.001
残差Residual 36 59.440 1.651
总变异Total 71 1206.564
株粒数
Grain number per plant
基因型G 5 5924.452 1184.890 238.315 < 0.001
环境E 5 131.253 26.251 5.280 0.001
互作G×E 25 694.860 27.794 5.590 < 0.001
残差Residual 36 178.990 4.972
总变异Total 71 6929.555
百粒重
Hundred-
grain weight
基因型G 5 6539.353 1307.871 69,835.871 < 0.001
环境E 5 117.487 23.497 1254.678 < 0.001
互作G×E 25 624.980 24.999 1334.873 < 0.001
残差Residual 36 0.674 0.019
总变异Total 71 7282.494

图2

农艺性状适应性GGE分析 A: 小区产量; B: 株高; C: 分枝数; D: 株荚数; E: 株粒数; F: 百粒重。HZ: 和政县; KL: 康乐县; JSS; 积石山县; WY: 渭源县; LX: 临夏县; ZX: 漳县。"

图3

农艺性状稳定性GGE分析 A: 小区产量; B: 株高; C: 分枝数; D: 株荚数; E: 株粒数; F: 百粒重。HZ: 和政县; KL: 康乐县; JSS; 积石山县; WY: 渭源县; LX: 临夏县; ZX: 漳县。"

图4

试点的区分力和代表性GGE分析 A: 小区产量; B: 株高; C: 分枝数; D: 株荚数; E: 株粒数; F: 百粒重。HZ: 和政县; KL: 康乐县; JSS; 积石山县; WY: 渭源县; LX: 临夏县; ZX: 漳县。"

图5

蚕豆农艺性状相关性热图 MC: 小区产量; ZG: 株高; FZ: 分枝数; ZJS: 株荚数; ZLS: 株粒数; BLZ: 百粒重。*: P < 0.05; **: P < 0.01。"

[1] 张红岩, 郭兴莲, 杨涛, 刘荣, 黄宇宁, 季一山, 王栋, 宗绪晓. 利用SSR标记分析蚕豆品种(品系)与优异种质的遗传多样性. 中国蔬菜, 2018, (2): 34-41.
Zhang H Y, Guo X L, Yang T, Liu R, Huang Y N, Ji Y S, Wang D, Zong X X. Genetic diversity of faba bean varities (lines) and elite collections by SSR markers. China Veget, 2018, (2): 34-41. (in Chinese with English abstract)
[2] 李萍, 张雁霞, 刘玉皎. PEG胁迫下西北不同蚕豆种子萌发期的抗寒性鉴定. 四川农业大学学报, 2015, 33: 251-257.
Li P, Zhang Y X, Liu Y J. Drought tolerance of different faba beans during the germination stage under PEG stress in the northwest China. J Sichuan Agric Univ, 2015, 33: 251-257. (in Chinese with English abstract)
[3] Rakshit S, Ganapathy K N, Gomashe S S, Rathore A, Ghorade R B, Nagesh Kumar M V, Ganesmurthy K, Jain S K, Kamtar M Y, Sachan J S, Ambekar S S, Ranwa B R, Kanawade M, Balusamy D G, Kadam D, Sarkar A, Tonapi V A, Patil J V. GGE biplot analysis to evaluate genotype, environment, and their interactions in sorghum multi-location data. Euphytica, 2012, 185: 465-479.
doi: 10.1007/s10681-012-0648-6
[4] Cooper M, DeLacy I H. Relationships among analytical methods used to study genotypic variation and genotype-by-environment interaction in plant breeding multi-environment experiments. Theor Appl Genet, 1994, 88: 561-572.
doi: 10.1007/BF01240919 pmid: 24186111
[5] Crossa J, Cornelius P L, Sayre K, Iván Ortiz-Monasterio R J. A shifted multiplicative model fusion method for grouping environments without cultivar rank change. Crop Sci, 1995, 35: 54-62.
doi: 10.2135/cropsci1995.0011183X003500010010x
[6] 叶夕苗, 程鑫, 安聪聪, 袁剑龙, 余斌, 文国宏, 李高峰, 程李香, 王玉萍, 张峰. 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: 354-364.
doi: 10.3724/SP.J.1006.2020.94089
Ye X M, Cheng X, An C C, Yuan J L, Yu B, Wen G H, Li G F, Cheng L X, Wang Y P, Zhang F. Genotype × environment interaction and stability of yield components for potato lines. Acta Agron Sin, 2020, 46: 354-364. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2020.94089
[7] Aastveit A H, Martens H. ANOVA interactions interpreted by partial least squares regression. Biometrics, 1986, 42: 829-844.
doi: 10.2307/2530697
[8] Finlay K W, Wilkinson G N. The analysis of adaptation in a plant-breeding programmer. Aust J Agric Res, 1963, 14: 742-754.
doi: 10.1071/AR9630742
[9] Blouin D C, Webster E P, Bond J A. On the analysis of combined experiments. Weed Technol, 2015, 25: 165-169.
doi: 10.1614/WT-D-10-00047.1
[10] Wang R, Hu D, Zheng H, Shu Y, Wei R. Genotype × environmental interaction by AMMI and GGE biplot analysis for the provenances of michelia chapensis in south China. J For Res, 2016, 27: 659-664.
doi: 10.1007/s11676-015-0181-2
[11] Hugh G, Gauch J R. Statistical analysis of yield trials by AMMI and GGE. Crop Sci, 2006, 46: 1488-1500.
doi: 10.2135/cropsci2005.07-0193
[12] 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: 641-653.
[13] Nzuve F, Githiri S, Mulunya D M, Gethi J. Analysis of genotype × environment interaction for grain yield in maize hybrids. J Agric Sci, 2013, 5: 75-85.
doi: 10.1002/jsfa.v5:2
[14] Bednarz C W, Bridges D C, Brown S M. Analysis of cotton yield stability across population densities. Agron J, 2000, 92: 128-135.
doi: 10.2134/agronj2000.921128x
[15] Yan W K, Rajcan I. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Sci, 2002, 42: 11-20.
pmid: 11756248
[16] 崔顺立, 何美敬, 侯名语, 杨鑫雷, 穆国俊, 刘立峰. 利用GGE双标图分析花生品质性状的基因型-环境互作. 中国油料作物学报, 2021, 43: 617-626.
Cui S L, He J M, Hou M Y, Yang X L, Mu G J, Liu L F. Genotype × environment interactions for the quality traits of peanut varieties based on GGE biplot analysis. Chin J Oil Crop Sci, 2021, 43: 617-626. (in Chinese with English abstract)
doi: 10.19802/j.issn.1007-9084.2021039
[17] Frankham R. Introduction to quantitative genetics (4th edn). Trends Genet, 1996, 12: 280-280.
doi: 10.1016/0168-9525(96)81458-2
[18] Burgueño J, de los Campos G, Weigel K, Crossa J. Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers. Crop Sci, 2012, 52: 707-719.
doi: 10.2135/cropsci2011.06.0299
[19] Phuke R M, Anuradha K, Radhika K, Jabeen F, Anuradha G, Ramesh T, Hariprasanna K, Mehtre S P, Deshpande S P, Anil G, Das R R, Rathore A, Hash T, Reddy B V S, Kumar A A. Genetic variability, genotype × environment interaction, correlation, and GGE biplot analysis for grain iron and zinc concentration and other agronomic traits in RIL population of sorghum (Sorghum bicolor L. Moench). Front Plant Sci, 2017, 8: 712.
doi: 10.3389/fpls.2017.00712
[20] Shahriari Z, Heidari B, Dadkhodaie A, Chen Z H. Dissection of genotype × environment interactions for mucilage and seed yield in planta go species: application of AMMI and GGE biplot analyses. PLoS One, 2018, 13: e0196095.
doi: 10.1371/journal.pone.0196095
[21] 陆宏园, 张林杰, 李梅, 胡伟民, 关亚静, 胡晋. 蚕豆栽培品种综合性状的比较与分析. 浙江农业科学, 2015, 56: 993-997.
Lu H Y, Zhang L J, Li M, Hu W M, Guan Y J, Hu J. Comparison and analysis of comprehensive characters of faba bean cultivars. Zhengjiang Agric Sci, 2015, 56: 993-997. (in Chinese with English abstract)
[22] 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. pp 28-137.
Yan W K. Crop Variety Test Data Management and Analysis. Beijing: China Agricultural Science and Technology Press, 2015. pp 28-137. (in Chinese)
[23] 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. Application of biplot analysis in multi-point experiment of crop varieties. Acta Agron Sin, 2010, 36: 1805-1819. (in Chinese with English abstract)
[24] 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. Annu Rev Ecol Evol Syst, 2013, 44: 5-29.
doi: 10.1146/ecolsys.2013.44.issue-1
[25] 李本贵, 阎俊, 何中虎, 李仲来. 用AMMI模型分析作物区域试验中的地点鉴别力. 作物学报, 2004, 30: 593-596.
Li B G, Yan J, He Z H, Li Z L. The AMMI model was used to analyze site discrimination in crop regional experiments. Acta Agron Sin, 2004, 30: 593-596 (in Chinese with English abstract).
[26] 李艳花, 陈红, 王萍, 杜成章, 张继君. 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.
Li Y H, Chen H, Wang P, Du C Z, Zhang J J. Correlation and path analysis between yield per plant and agronomic traits of faba bean high-generation material. Jiangsu Agric Sci, 2018, 46(20): 79-81. (in Chinese with English abstract)
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