河北省春播玉米品种产量稳定性及试点辨别力综合分析
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摘要
为全面评价河北省春播玉米品种产量的稳定性、适应性以及各试点的代表性和辨别力,本研究采用GGE双标图和AMMI模型对2011-2012年河北省北部春播区试14个品种和西部春播区试13个品种分别在10个试点和9个试点进行玉米品种产量分析。结果表明,2011年北部春播区试中地175、XBS688和鲲鹏7074丰产性较好,唐08-72最差;农大108、蠡试2975、农单906、中地175稳定性较好,唐08-72最差;裕丰、张家口、宽城和涞源试点代表性较好,丰润和抚宁试点辨别力较弱,蔚县、裕丰和固安3个试点较其他试点有较强的辨别力;2012年西部春播区试科试787和中地175丰产性较好,农大108、粟1754、科试787和中地175等品种稳定性较好,阜玉201号丰产性和稳定性均最差;涉县、平山、邢台县将军墓等试点代表性较好;行唐和涉县试点较其他试点有较强的辨别力。2年试验结果表明,中地175属于丰产性和稳产性均较好的品种,农大108(对照)属于稳产性较好、丰产性一般的品种,唐08-72和阜玉201号属于丰产性和稳产性均较差的品种,裕丰和涉县试点属于代表性和辨别力均较好的试点。GGE双标图和AMMI模型对品种产量稳定性和试点辨别力分析结果差异不大,说明这2种方法均可作为区域试验分析的理想工具。本研究为玉米品种合理布局提供了理论依据。
In order to comprehensively evaluate the stability and adaptability of spring sowing maize varieties and the representativeness and discrimination of each testing sites in Hebei province,GGE-biplot and AMMI model were used to analyze the variety yield from the regional trials for maize from 2011 to 2012. Fourteen maize varieties were tested in 10 testing sites in northern Hebei Province,and 13 maize varieties were tested in 9 sites in western Hebei Province. The results showed that the varieties of Zhongdi175,XBS688,and Kunpeng7074 had a higher yield than other varieties,and Tang08-72 was the worst. Nongda108,Lishi2975,Nongdan906,and Zhongdi175 had better yield stability than other varieties,while Tango8-72 had the lowest yield. In addition,Yufeng,Zhangjiakou,Kuancheng,and Laiyuan were more representative than other testing sites. Fengrun and Funing had weaker discrimination,while Yuxian,Yufeng,and Guan had stronger discrimination than other testing sites in Northern spring sowing regional trials of Hebei Province in 2011. In Western spring sowing regional trials of Hebei Province in 2012,Keshi787 and Zhongdi175 had a higher yield than other varieties,Nongda108,Su1754,Keshi787,and Zhongdi175 had better yield stability than the other varieties,with the poor yield and stability of Fuyu201. Shexian,Pingshan,Jiangjunmu of Xingtai County were more representative than other testing sites,of which Xingtang and Shexian had stronger discrimination than the other testing sites. The 2-years test results showed that Zhongdi175 had the best performance with high yield and stability,the control variety Nongda108 belongs to the high stability with average yield,Tang 08-72 and Fuyu201 belong to lower yield and weaker stability,Yufeng and Shexian had better representative and stronger discrimination than other testing sites. Little difference between GGE-biplot and AMMI model were found in the stability analysis of maize varieties and discrimination of testing sites. The two methods can be used as the ideal tools for analysis in regional test. The results provide a theoretical basis on rational distribution of maize varieties.
In order to comprehensively evaluate the stability and adaptability of spring sowing maize varieties and the representativeness and discrimination of each testing sites in Hebei province,GGE-biplot and AMMI model were used to analyze the variety yield from the regional trials for maize from 2011 to 2012. Fourteen maize varieties were tested in 10 testing sites in northern Hebei Province,and 13 maize varieties were tested in 9 sites in western Hebei Province. The results showed that the varieties of Zhongdi175,XBS688,and Kunpeng7074 had a higher yield than other varieties,and Tang08-72 was the worst. Nongda108,Lishi2975,Nongdan906,and Zhongdi175 had better yield stability than other varieties,while Tango8-72 had the lowest yield. In addition,Yufeng,Zhangjiakou,Kuancheng,and Laiyuan were more representative than other testing sites. Fengrun and Funing had weaker discrimination,while Yuxian,Yufeng,and Guan had stronger discrimination than other testing sites in Northern spring sowing regional trials of Hebei Province in 2011. In Western spring sowing regional trials of Hebei Province in 2012,Keshi787 and Zhongdi175 had a higher yield than other varieties,Nongda108,Su1754,Keshi787,and Zhongdi175 had better yield stability than the other varieties,with the poor yield and stability of Fuyu201. Shexian,Pingshan,Jiangjunmu of Xingtai County were more representative than other testing sites,of which Xingtang and Shexian had stronger discrimination than the other testing sites. The 2-years test results showed that Zhongdi175 had the best performance with high yield and stability,the control variety Nongda108 belongs to the high stability with average yield,Tang 08-72 and Fuyu201 belong to lower yield and weaker stability,Yufeng and Shexian had better representative and stronger discrimination than other testing sites. Little difference between GGE-biplot and AMMI model were found in the stability analysis of maize varieties and discrimination of testing sites. The two methods can be used as the ideal tools for analysis in regional test. The results provide a theoretical basis on rational distribution of maize varieties.
引文
[1]张勇强,宋航,薛志伟,牛平平,介领军,李潮海.施用锌肥和硼肥对玉米穗粒性状和品质的影响[J].核农学报,2017,31(2):371-378
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[6]张群远,孔繁玲.作物品种区域试验统计分析模型的比较[J].中国农业科学,2002,35(4):365-371
[7]胡希远,尤海磊,宋喜芳,李建平,Joachim S.作物品种稳定性分析不同模型的比较[J].麦类作物学报,2009,29(1):110-117
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[12]温振民,张永科.用高稳系数法估算玉米杂交种高产稳产性的探讨[J].作物学报,1994,20(4):508-512
[13]Gauch J H G.Model selection and validation for yield trials with interaction[J].Biometrics,1988,44(3):705-715
[14]冀建华,刘光荣,李祖章,侯红乾,刘秀梅,李絮花,罗奇祥.基于AMMI模型评价长期定位施肥对双季稻总产量稳定性的影响[J].中国农业科学,2012,45(4):685-696
[15]孙日彦,王照红,杜建勋,梁明芝.基于AMMI模型的桑品种产量性状稳定性分析[J].蚕业科学,2008,34(1):101-105
[16]查宏波,黄韡,胡启贤,黄跃辉,王崇玉,方再龙,周芸,石建兴,赵声春,郑丽华.应用AMMI模型评价烤烟品种产量适宜性[J].中国烟草学报,2012,18(2):17-20
[17]王志强,刘声锋,郭守金,于蓉,田梅,董瑞.用AMMI双标图分析西瓜品种的产量稳定性及试点分辨力[J].干旱地区农业研究,2013,13(4):89-93
[18]Yan W K,Hunt L A,Sheng Q,Szlavnics Z.Cultivar evaluation and mega-environment investigation based on the GGE biplot[J].Crop Science,2000,40(3):597-605
[19]Yan W K.GGE biplot A windows application for graphical analysis of multi-environment trial data and other types of two way data[J].Agronomy Journal,2001,93(5):111-1118
[20]杨锦忠,郝建平,姚宏亮,姚先伶.基于AMMI模型的玉米区域试验地点鉴别力的重演性研究[J].玉米科学,2011,19(4):145-148
[21]吕泽文,张友君,钟育海,李求文,秦光才,杨险峰,龙艳.区域试验玉米品种(系)产量稳定性和适应性的GGE双标图分析[J].湖北农业科学,2014,53(15):3487-3491
[22]唐启义.DPS数据处理系统:实验设计、统计分析及数据挖掘[M].北京:科学出版社,2010
[23]张志芬,付晓峰,刘俊青,杨海顺.用GGE双标图分析燕麦区域试验品系产量稳定性及试点代表性[J].作物学报,2010,36(8):1377-1385
[24]Jalata Z.GGE-biplot analysis of multi-enviroment yieldtrails of Barley(Hordeium vulgare L.)genotypes in Southeastern Ethiopia highlands[J].International Journal of Plant Breeding and Genetics,2011,5(1):59-75
[25]Yan W,Holland J B.A heritability-adjusted GGE Biplot for test environment evaluation[J].Euphytica,2010,171(3):355-369
[26]Ramburan S,Zhou M,Labuschagne M T.Investigating test site similarity,trait relations and causes of genotype x environment interactions of sugarcane in the Midlands region of South Africa[J].Field Crops Research,2012,129(10):71-80
[27]Nzuve F,Githiri S,Mukunya D M,Gethi J.Analysis of genotype x environment interaction for grain yield in maize hybrids[J].Journal of Agricultural Science,2013,5(11):75-85
[28]Reza Mohammadi,Ezatollah Farshadfar,Ahmed Amri.Interpreting genotype×environment interactions for grain yield of rainfed durum wheat in Iran[J].The Crop Journal,2015,3(6):526-535
[29]严威凯.双标图分析在农作物品种多点试验中的应用[J].作物学报,2010,36(11):1805-1819
[30]李艳艳,丰震,赵兰勇.用AMMI模型分析玫瑰品种产花量的稳定性[J].中国农业科学,2008,41(6):1761-1766
[31]周凤云,李伯群,余国东,马强,高志宏,杨明.小麦新品种渝麦13号丰产性、稳产性及适应性分析[J].西南农业学报,2013,26(3):894-898
[32]Baxevanos D,Goulas C,Rossi J.Separation of cotton cultivar testing sites based on representativeness and discriminating ability using GGE biplots[J].Agronomy Journal,2008,100(5):1230-1236
[33]石强,李亚杰,范士杰,张俊莲,白江平,王蒂.贵州省马铃薯区试品种产量与农艺性状的GGE双标图分析[J].干旱地区农业研究,2015,33(2):5-15
[34]李辛村,张恩和,董孔军,何继红,杨天育.用AMMI双标图分析糜子品种的产量稳定性及试点代表性[J].中国生态农业学报,2012,20(4):422-426
[35]何代元,胡宁,马兆锦,周联东,刘经纬,何琴.AMMI模型在玉米区域试验中的应用[J].玉米科学,2009,17(4):144-147,152
[36]常磊,柴守玺.GGE双标图在我国旱地春小麦稳产性分析中的应用[J].中国生态农业学报,2010,18(5):988-994
[37]史跃伟,郎胜勇,王志红,张吉顺,曹廷冒,邱萍.烤烟新品种(系)重要经济性状丰产性和稳定性评价研究[J].华北农学报,2013,28(S1):238-242
[38]汪洲涛,苏炜华,阙友雄,许莉萍,张华,罗俊.应用AMMI和HA-GGE双标图分析甘蔗品种产量稳定性和试点代表性[J].中国生态农业学报,2016,24(6):790-800
[39]聂迎彬,穆培源,桑伟,徐红军,庄丽.AMMI模型和GGE双标图法在新疆冬小麦区域试验产量分析上的应用[J].新疆农业科学,2012,49(9):1569-1575
[40]张宇君,赵丽丽,王普昶,陈超,康芙蓉.燕麦萌发期抗旱指标体系构建及综合评价[J].核农学报,2017,31(11):2236-2242
[41]郑桂萍,蔡永盛,赵洋,李丹丹,郑悦,潘世驹,刘丽华.利用AMMI模型进行寒地水稻品质分析[J].核农学报,2015,29(2):296-303
[2]孟建,韩江伟,杨林风,谷志平.河北省玉米生产省域尺度比较优势分析[J].中国农学通报,2010,26(15):343-348
[3]胡秉民,耿旭.作物稳定性分析法[M].北京:科学出版社,1993
[4]王磊,程本义,鄂志国,杨仕华.基于GGE双标图的水稻区试品种丰产性、稳产性和适应性评价[J].中国水稻科学,2015,29(4):408-416
[5]Romagosa I,Fox P N.Genotype×environment interaction and adaptation[M]//Hayward M D,Bosemark N O,Romagosa I.Plant Breeding:Principle and Prospects.London:Chapman and Hall,1993:373-390
[6]张群远,孔繁玲.作物品种区域试验统计分析模型的比较[J].中国农业科学,2002,35(4):365-371
[7]胡希远,尤海磊,宋喜芳,李建平,Joachim S.作物品种稳定性分析不同模型的比较[J].麦类作物学报,2009,29(1):110-117
[8]高金锋,高小丽,韩海,邱军,柴岩.秩次分析法评价甜荞品种产量性能及稳定性[J].干旱地区农业研究,2008,26(4):186-189
[9]潘家驹.作物育种学总论[M].北京:中国农业出版社,1994
[10]胡秉民,耿旭.作物稳定性分析法[M].北京:科学出版社,1993
[11]Eberhart S A,Russell W A.Stability parameters for comparing varieties[J].Crop Science,1966,6(1):36-40
[12]温振民,张永科.用高稳系数法估算玉米杂交种高产稳产性的探讨[J].作物学报,1994,20(4):508-512
[13]Gauch J H G.Model selection and validation for yield trials with interaction[J].Biometrics,1988,44(3):705-715
[14]冀建华,刘光荣,李祖章,侯红乾,刘秀梅,李絮花,罗奇祥.基于AMMI模型评价长期定位施肥对双季稻总产量稳定性的影响[J].中国农业科学,2012,45(4):685-696
[15]孙日彦,王照红,杜建勋,梁明芝.基于AMMI模型的桑品种产量性状稳定性分析[J].蚕业科学,2008,34(1):101-105
[16]查宏波,黄韡,胡启贤,黄跃辉,王崇玉,方再龙,周芸,石建兴,赵声春,郑丽华.应用AMMI模型评价烤烟品种产量适宜性[J].中国烟草学报,2012,18(2):17-20
[17]王志强,刘声锋,郭守金,于蓉,田梅,董瑞.用AMMI双标图分析西瓜品种的产量稳定性及试点分辨力[J].干旱地区农业研究,2013,13(4):89-93
[18]Yan W K,Hunt L A,Sheng Q,Szlavnics Z.Cultivar evaluation and mega-environment investigation based on the GGE biplot[J].Crop Science,2000,40(3):597-605
[19]Yan W K.GGE biplot A windows application for graphical analysis of multi-environment trial data and other types of two way data[J].Agronomy Journal,2001,93(5):111-1118
[20]杨锦忠,郝建平,姚宏亮,姚先伶.基于AMMI模型的玉米区域试验地点鉴别力的重演性研究[J].玉米科学,2011,19(4):145-148
[21]吕泽文,张友君,钟育海,李求文,秦光才,杨险峰,龙艳.区域试验玉米品种(系)产量稳定性和适应性的GGE双标图分析[J].湖北农业科学,2014,53(15):3487-3491
[22]唐启义.DPS数据处理系统:实验设计、统计分析及数据挖掘[M].北京:科学出版社,2010
[23]张志芬,付晓峰,刘俊青,杨海顺.用GGE双标图分析燕麦区域试验品系产量稳定性及试点代表性[J].作物学报,2010,36(8):1377-1385
[24]Jalata Z.GGE-biplot analysis of multi-enviroment yieldtrails of Barley(Hordeium vulgare L.)genotypes in Southeastern Ethiopia highlands[J].International Journal of Plant Breeding and Genetics,2011,5(1):59-75
[25]Yan W,Holland J B.A heritability-adjusted GGE Biplot for test environment evaluation[J].Euphytica,2010,171(3):355-369
[26]Ramburan S,Zhou M,Labuschagne M T.Investigating test site similarity,trait relations and causes of genotype x environment interactions of sugarcane in the Midlands region of South Africa[J].Field Crops Research,2012,129(10):71-80
[27]Nzuve F,Githiri S,Mukunya D M,Gethi J.Analysis of genotype x environment interaction for grain yield in maize hybrids[J].Journal of Agricultural Science,2013,5(11):75-85
[28]Reza Mohammadi,Ezatollah Farshadfar,Ahmed Amri.Interpreting genotype×environment interactions for grain yield of rainfed durum wheat in Iran[J].The Crop Journal,2015,3(6):526-535
[29]严威凯.双标图分析在农作物品种多点试验中的应用[J].作物学报,2010,36(11):1805-1819
[30]李艳艳,丰震,赵兰勇.用AMMI模型分析玫瑰品种产花量的稳定性[J].中国农业科学,2008,41(6):1761-1766
[31]周凤云,李伯群,余国东,马强,高志宏,杨明.小麦新品种渝麦13号丰产性、稳产性及适应性分析[J].西南农业学报,2013,26(3):894-898
[32]Baxevanos D,Goulas C,Rossi J.Separation of cotton cultivar testing sites based on representativeness and discriminating ability using GGE biplots[J].Agronomy Journal,2008,100(5):1230-1236
[33]石强,李亚杰,范士杰,张俊莲,白江平,王蒂.贵州省马铃薯区试品种产量与农艺性状的GGE双标图分析[J].干旱地区农业研究,2015,33(2):5-15
[34]李辛村,张恩和,董孔军,何继红,杨天育.用AMMI双标图分析糜子品种的产量稳定性及试点代表性[J].中国生态农业学报,2012,20(4):422-426
[35]何代元,胡宁,马兆锦,周联东,刘经纬,何琴.AMMI模型在玉米区域试验中的应用[J].玉米科学,2009,17(4):144-147,152
[36]常磊,柴守玺.GGE双标图在我国旱地春小麦稳产性分析中的应用[J].中国生态农业学报,2010,18(5):988-994
[37]史跃伟,郎胜勇,王志红,张吉顺,曹廷冒,邱萍.烤烟新品种(系)重要经济性状丰产性和稳定性评价研究[J].华北农学报,2013,28(S1):238-242
[38]汪洲涛,苏炜华,阙友雄,许莉萍,张华,罗俊.应用AMMI和HA-GGE双标图分析甘蔗品种产量稳定性和试点代表性[J].中国生态农业学报,2016,24(6):790-800
[39]聂迎彬,穆培源,桑伟,徐红军,庄丽.AMMI模型和GGE双标图法在新疆冬小麦区域试验产量分析上的应用[J].新疆农业科学,2012,49(9):1569-1575
[40]张宇君,赵丽丽,王普昶,陈超,康芙蓉.燕麦萌发期抗旱指标体系构建及综合评价[J].核农学报,2017,31(11):2236-2242
[41]郑桂萍,蔡永盛,赵洋,李丹丹,郑悦,潘世驹,刘丽华.利用AMMI模型进行寒地水稻品质分析[J].核农学报,2015,29(2):296-303