黄淮海夏玉米品种籽粒产量基因型与环境互作分析
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摘要
为客观准确评价多点鉴定试验中玉米新品种丰产性、稳产性和适应性以及试点辨别力和代表性,探明适合黄淮海夏玉米多点鉴定试验基因型与环境互作分析方法。本研究借助AMMI模型和GGE双标图分析方法对2017年黄淮海夏玉米新品种多点鉴定试验中10个不同基因型品种在15个不同生态环境下的品种丰产性和稳定性进行分析,并对试点环境辨别力和代表性进行综合评价。结果表明:基因型效应、环境效应和基因型与环境互作均达到了极显著差异,基因型与环境互作是产量变异的主要来源。‘衡玉1587’和‘衡玉321’综合表现较好,属于丰产性、稳定性和适应性均较好的品种。‘伟科702’稳定性较好但丰产性较差,‘浚单20’丰产性较好且具有较强的适应性,可以在适宜地区推广种植。河北深州和山东德州具有较强辨别力和代表性,‘衡玉1587’和山东德州分别是理想品种和理想试点。AMMI模型和GGE双标图分析结果基本一致,两种方法优势互补,可以用来作为分析基因型与环境互作的理想工具。
In order to evaluate the high yield, stability and adaptability objectively and accurately of the new maize cultivars during the multi-environment trials, as well as the discrimination and representativeness of testing sites, to identify the appropriate analytical method for analyzing the genotype and environment interaction of the multi-environment trials of Huanghuaihai summer maize cultivars. In this study, AMMI model and GGE biplot analysis method were used to analyze the yield and stability of 10 different genotypes in 15 different ecological environments in the multi-environment trials of Huanghuaihai summer maize new cultivars in 2017, and comprehensive evaluation of the discriminative and representativeness of the testing sites. The results showed that genotype effects, environment effects and genotype and environment interactions all reached extremely significant differences, and genotype and environment interactions was the main sources of yield variation. 'Hengyu1587' and'Hengyu321' had a good overall performance, and are among the cultivars with high yield, stability and adaptability. 'Weike702' had good stability but poor yield, whereas 'Xundan20' had good yield and strong adaptability, and could be planted in suitable environments. Shenzhou of Hebei Province and Dezhou of Shandong Province had strong discrimination and representativeness. 'Hengyu1587' and Dezhou of Shandong Province were ideal cultivar and ideal location, respectively. The results of AMMI model and GGE biplot analysis were basically the same, and the two methods had complementary advantages and should be used as an ideal tool for analyzing genotype and environment interaction.
In order to evaluate the high yield, stability and adaptability objectively and accurately of the new maize cultivars during the multi-environment trials, as well as the discrimination and representativeness of testing sites, to identify the appropriate analytical method for analyzing the genotype and environment interaction of the multi-environment trials of Huanghuaihai summer maize cultivars. In this study, AMMI model and GGE biplot analysis method were used to analyze the yield and stability of 10 different genotypes in 15 different ecological environments in the multi-environment trials of Huanghuaihai summer maize new cultivars in 2017, and comprehensive evaluation of the discriminative and representativeness of the testing sites. The results showed that genotype effects, environment effects and genotype and environment interactions all reached extremely significant differences, and genotype and environment interactions was the main sources of yield variation. 'Hengyu1587' and'Hengyu321' had a good overall performance, and are among the cultivars with high yield, stability and adaptability. 'Weike702' had good stability but poor yield, whereas 'Xundan20' had good yield and strong adaptability, and could be planted in suitable environments. Shenzhou of Hebei Province and Dezhou of Shandong Province had strong discrimination and representativeness. 'Hengyu1587' and Dezhou of Shandong Province were ideal cultivar and ideal location, respectively. The results of AMMI model and GGE biplot analysis were basically the same, and the two methods had complementary advantages and should be used as an ideal tool for analyzing genotype and environment interaction.
引文
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Abakemal D.,Shimelis H.,and Derera J.,2016,Genotype-by-environment interaction and yield stability of quality protein maize hybrids developed from tropical-highland adapted inbred lines,Euphytica,209(3):757-769
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Imtiaz M.,Malhotra R.S.,Singh M.,and Arslan S.,2013,Identifying high yielding,stable chickpea genotypes for spring sowing:specific adaptation to locations and sowing seasons in the Mediterranean region,Crop Sci.,53(4):1472-1480
Kendal E.,and Tekdal S.,2016,Application of AMMI model for evaulation spring barley genotypes in multi-environment trials,Bangl.J.Bot.,45(3):613-620
Laurie S.M.,and Booyse M.,2015,Employing the GGE SREGmodel plus Elston index values for multiple trait selection in sweetpotato,Euphytica,204(2):433-442
Luo J.,Zhang H.,and Que Y.X.,2012,Genotype,environment and their interactive effects on main traits of sugarcane varieties,Redai Yaredai Zhiwu Xuebao(Journal of Tropical and Subtropical Botany),20(5):445-454(罗俊,张华,阙友雄,2012,甘蔗品种主要性状的基因型与环境及其互作效应分析,热带亚热带植物学报,20(5):445-454)
Mohammadi R.,Haghparast R.,Amri A.,and Ceccarelli S.,2010,Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials,Crop Pasture Sci.,61(1):92-101
Mortazavian S.M.M.,Nikkhah H.R.,Hassani F.A.,Sharif-Al-Hosseini M.,Taheri M.,and Mahlooji M.,2014,GGE biplot and AMMI analysis of yield performance of barley genotypes ac ross different environments in Iran,J.Agr.Sci.Tech.,16(3):609-622
Muthoni J.,Shimelis H.,and Melis R.,2015,Genotype×environment interaction and stability of potato tuber yield and bacterial wilt resistance in Kenya,Am.J.Potato Res.,92(3):367-378
Peyman S.,and Akbar E.A.,2018,Relationships of rice yield and quality based on genotype by trait(GT)biplot,Anais da A-cademia Brasileira de Ciências,90(1):343-356
Ramburan S.,Zhou M.,and Labuschagne M.T.,2012,Investigating test site similarity,trait relations and causes of genotype×environment interactions of sugarcane in the Midlands region of South Africa,Field Crop Res.,129(10):71-80
Rodrigues P.C.,Malosetti M.,Gauch H.G.,and Eeuwijk F.A.V.,2014,A wei ghted AMMI algorithm to study genotype-byenvironment interaction and QTL-by-environment interaction,Crop Sci.,54(4):1555-1570
Sabaghnia N.,Dehghani H.,Alizadeh B.,Mohghaddam M.,Sabaghnia N.,and Mohghaddam M.,2010,Genetic analysis of oil yield,seed yield,and yield components in rapeseed using additive main effects and multiplicative interaction biplots,Agron.J.,102(5):1361-1368
Sabaghnia N.,Sabaghpour S.H.,and Dehghani H.,2008,The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials,J.Agr.Sci.,146(5):571-581
Shahriari Z.,Heidari B.,and Dadkhodaie A.,2018,Dissection of genotype×environment interactions for mucilage and seed yield in Plantago species:application of AMMI and GGE biplot analyses,PLoS One,13(5):e0196095
Ssemakula G.,Dixon A.G.O.,and Maziyadixon B.,2008,Stability of total carotenoid concentration and fresh yield of selected yellow-fleshed cassava(Manihot esculenta Crantz),J.Trop.Agric.,45(1):14-20
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Ullah I.,Ayub M.,Khan M.,Ashraf M.,Mirza M.,and Yousaf M.,2007,Graphical analysis of multi-environment trial(MET)data in sunflower(Helianthus annuus L.)through clustering and GGE biplot technique,Pak.J.Bot.,39(5):1639-1646
Vlachostergios D.N.,and Roupakias D.G.,2008,Response to conventional and organic environment of thirty-six lentil(Lens culinaris Medik.)varieties,Euphytica,163(3):449-457
Wang R.H.,Hu D.H.,Zheng H.Q.,Yan S.,and Wei R.P.,2016,Genotype×environmental interaction by AMMI and GGEbiplot analysis for the provenances of Michelia chapensis in South China,J.Forestry Res.,27(3):659-664
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Abakemal D.,Shimelis H.,and Derera J.,2016,Genotype-by-environment interaction and yield stability of quality protein maize hybrids developed from tropical-highland adapted inbred lines,Euphytica,209(3):757-769
Abamu F.J.,and Alluri K.,2010,AMMI analysis of rainfed lowland rice(Oryza sativa)trials in Nigeria,Plant Breed.,117(4):395-397
Adugna A.,2010,Assessment of yield stability in sorghum using univariate and multivariate statistical approaches,Hereditas,145(1):28-37
Ashraful Alam M.D.,Farhad M.D.,Abdul Hakim M.D.,Deb Barma N.C.,Kumar Malaker P.,Mostofaali Reza M.D.,and Amir Hossain M.D.,and Li M.,2017,AMMI and GGE biplot analysis for yield stability of promising bread wheat genotypes in Bangladesh,Pak.J.Bot.,49(3):1049-1056
Badu-Apraku B.,Oyekunle M.,Obeng-Antwi K.,Osuman A.S.,and Didjeira A.,2012,Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis,J.Agr.Sci.,150(4):473-483
Bashir E.M.A.,Ali A.M.,Ismail M.I.,Parzies H.K.,and Haussmann B.I.G.,2014,Patterns of pearl millet genotype-by-environment interaction for yield performance and grain iron(Fe)and zinc(Zn)concentrations in Sudan,Field Crop Res.,166:82-91
Bose L.,Namdeorao Jambhulkar N.,Pande K.,and Nath Singh O.,2014,Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions,Chil.J.Agr.Res.,74(1):3-9
Campanelli G.,Acciarri N.,Campion B.,Delvecchio S.,Leteo F.,Fusari F.,Angelini P.,and Ceccarelli S.,2015,Participatory tomato breeding for organic conditions in Italy,Euphytica,204(1):179-197
Chang L.,and Chai S.X.,2010,Application of GGE biplot in spring wheat yield stability analysis in rainfed areas of China,Zhongguo Shentgai Nongye Xuebao(Chinese Journal of Eco-Agriculture),18(5):988-994(常磊,柴守玺,2010,GGE双标图在我国旱地春小麦稳产性分析中的应用,中国生态农业学报,18(5):988-994)
Dehghani H.,Feyzian E.,Jalali M.,Rezai A.,and Dane F.,2012,Use of GGE biplot methodology for genetic analysis of yield and related traits in melon(Cucumis melo L.),Can.J.Plant Sci.,92(1):77-85
Dehghani M.R.,Majidi M.M.,Mirlohi A.,and Saeidi G.,2016,Study of genotype by environment interaction in tall fescue genotypes and their polycross progenies in Iran based on AMMI model analysis,Crop Pasture Sci.,67:792-799
Fan X.M.,Kang M.S.,Chen H.,Zhang Y.,Tan J.,and Xu C.,2007,Yield stability of maize hybrids evaluated in multi-en vironment trials in Yunnan,China,Agron.J.,99(1):220-228
Farshadfar E.,Farshadfar M.,and Sutka J.,2000,Combining ability analysis of drought tolerance in wheat over different water regimes,Acta Agronomica Hungarica,48(4):353-361
Gauch H.G.,1988,Model selection and validation for yield trials with interaction,Biometrics,44(3):705-715
Gauch H.G.,2013,A simple protocol for AMMI analysis of yield trials,Crop Sci.,53(5):1860-1869
Gauch H.G.,and Zobel R.W.,1988,Predictive and postdictive success of statistical analyses of yield trials,Theor.Appl.Genet.,76(1):1-10
Guerra E.P.,Oliveira R.A.D.,Daros E.,Zambon J.L.C.,Ido O.T.,and Bespalhok Filho J.C.,2009,Stability and adaptability of early maturing sugarcane clones by AMMI analysis,Crop Breed.Appl.Biot.,9(3):260-267
Haile J.K.,Sarial A.K.,and Assefa S.,2007,AMMI analysis for stability and locations effect on grain protein content of durum wheat genotypes,Cereal Res.Commun.,35(4):1661-1673
Hristov N.,Mladenov N.,Djuric V.,Kondic-Spika A.,Marjanovic-Jeromela A.,and Simic D.,2010,Genotype by environment interactions in wheat quality breeding programs in southeast Europe,Euphytica,174(3):315-324
Hu Z.H.,Wang P.Q.,Yang J.,Guo L.F.,Wu Y.Q.,Hu X.L.,and Liu X.Y.,2018,Analysis of the interaction between genotypes of the yield traits of safflower petals and environment by AMMI model,Fenzi Zhiwu Yuzhong(Molecular Plant Breeding),16(9):2931-2938(胡尊红,王沛琦,杨谨,郭丽芬,吴郁青,胡学礼,刘旭云,2018,利用AMMI模型分析红花花瓣产量性状的基因型与环境互作,分子植物育种,16(9):2931-2938)
Imtiaz M.,Malhotra R.S.,Singh M.,and Arslan S.,2013,Identifying high yielding,stable chickpea genotypes for spring sowing:specific adaptation to locations and sowing seasons in the Mediterranean region,Crop Sci.,53(4):1472-1480
Kendal E.,and Tekdal S.,2016,Application of AMMI model for evaulation spring barley genotypes in multi-environment trials,Bangl.J.Bot.,45(3):613-620
Laurie S.M.,and Booyse M.,2015,Employing the GGE SREGmodel plus Elston index values for multiple trait selection in sweetpotato,Euphytica,204(2):433-442
Luo J.,Zhang H.,and Que Y.X.,2012,Genotype,environment and their interactive effects on main traits of sugarcane varieties,Redai Yaredai Zhiwu Xuebao(Journal of Tropical and Subtropical Botany),20(5):445-454(罗俊,张华,阙友雄,2012,甘蔗品种主要性状的基因型与环境及其互作效应分析,热带亚热带植物学报,20(5):445-454)
Mohammadi R.,Haghparast R.,Amri A.,and Ceccarelli S.,2010,Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials,Crop Pasture Sci.,61(1):92-101
Mortazavian S.M.M.,Nikkhah H.R.,Hassani F.A.,Sharif-Al-Hosseini M.,Taheri M.,and Mahlooji M.,2014,GGE biplot and AMMI analysis of yield performance of barley genotypes ac ross different environments in Iran,J.Agr.Sci.Tech.,16(3):609-622
Muthoni J.,Shimelis H.,and Melis R.,2015,Genotype×environment interaction and stability of potato tuber yield and bacterial wilt resistance in Kenya,Am.J.Potato Res.,92(3):367-378
Peyman S.,and Akbar E.A.,2018,Relationships of rice yield and quality based on genotype by trait(GT)biplot,Anais da A-cademia Brasileira de Ciências,90(1):343-356
Ramburan S.,Zhou M.,and Labuschagne M.T.,2012,Investigating test site similarity,trait relations and causes of genotype×environment interactions of sugarcane in the Midlands region of South Africa,Field Crop Res.,129(10):71-80
Rodrigues P.C.,Malosetti M.,Gauch H.G.,and Eeuwijk F.A.V.,2014,A wei ghted AMMI algorithm to study genotype-byenvironment interaction and QTL-by-environment interaction,Crop Sci.,54(4):1555-1570
Sabaghnia N.,Dehghani H.,Alizadeh B.,Mohghaddam M.,Sabaghnia N.,and Mohghaddam M.,2010,Genetic analysis of oil yield,seed yield,and yield components in rapeseed using additive main effects and multiplicative interaction biplots,Agron.J.,102(5):1361-1368
Sabaghnia N.,Sabaghpour S.H.,and Dehghani H.,2008,The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials,J.Agr.Sci.,146(5):571-581
Shahriari Z.,Heidari B.,and Dadkhodaie A.,2018,Dissection of genotype×environment interactions for mucilage and seed yield in Plantago species:application of AMMI and GGE biplot analyses,PLoS One,13(5):e0196095
Ssemakula G.,Dixon A.G.O.,and Maziyadixon B.,2008,Stability of total carotenoid concentration and fresh yield of selected yellow-fleshed cassava(Manihot esculenta Crantz),J.Trop.Agric.,45(1):14-20
Tang Q.Y.,and Zhang C.X.,2013,Data processing system(DPS)software with experimental design,statistical analysis and data mining developed for use in entomological research,Insect Sci.,20(2):254-260
Ullah I.,Ayub M.,Khan M.,Ashraf M.,Mirza M.,and Yousaf M.,2007,Graphical analysis of multi-environment trial(MET)data in sunflower(Helianthus annuus L.)through clustering and GGE biplot technique,Pak.J.Bot.,39(5):1639-1646
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