作物学报 ›› 2015, Vol. 41 ›› Issue (02): 214-227.doi: 10.3724/SP.J.1006.2015.00214
罗俊1,许莉萍1,邱军2,张华1,袁照年1,邓祖湖1,陈如凯1,阙友雄1,*
LUO Jun1,XU Li-Ping1,QIU Jun2,ZHANG Hua1,YUAN Zhao-Nian1,DENG Zu-Hu1,CHEN Ru-Kai1,QUE You-Xiong1,*
摘要:
采用遗传力校正的GGE双标图(heritability adjusted GGE, HA-GGE), 分析基因型(G)、环境(E)、基因型与环境互作效应(GE)对产量变异的影响, 对14个试验点的分辨力、代表性和理想指数进行分析, 并对这些试验点的生态区进行划分。结果表明, 甘蔗试验环境对产量变异的影响大于基因型和基因型与环境互作; 互作因素中以环境×基因型的互作效应最大, 基因型×年份的互作效应最小。广东遂溪(E3)和广西崇左(E6)为最理想试验环境, 对筛选广适性新品种和鉴别理想品种的效率最高; 福建福州(E1)、福建漳州(E2)、广东湛江(E4)、云南保山(E11)、云南临沧(E13)、云南瑞丽(E14)为理想试验环境;广西百色(E5)、广西河池(E7)、海南临高(E10)、云南开远(E12)为较理想试验环境; 广西来宾(E8)、广西柳州(E9)为不太理想的试验环境。根据HA-GGE双标图分析结果, 可将我国甘蔗生态区划分为3个, 即以广西百色、河池、来宾和柳州为代表的华南内陆甘蔗品种生态区, 以云南保山、开远、临沧、瑞丽为代表的西南高原甘蔗品种生态区, 涵盖福建福州、漳州、广东湛江、遂溪、广西崇左等试点的华南沿海甘蔗品种生态区。
| [1]罗俊, 张华, 邓祖湖, 阙友雄. 用GGE双标图分析甘蔗品种性状稳定性及试点代表性. 应用生态学报, 2012, 23: 1319–1325Luo J, Zhang H, Deng Z H, Que Y X. Trait stability and test site representativeness of sugarcane cultivars based on GGE-biplot analysis. Chin J Appl Ecol, 2012, 23: 1319–1325[2]罗俊, 张华, 邓祖湖, 许莉萍, 徐良年, 袁照年, 阙友雄. 应用GGE双标图分析甘蔗品种(系)的产量和品质性状, 作物学报, 2013, 39: 142–152Luo J, Zhang H, Deng Z H, Xu L P, Xu L N, Yuan Z N, Que Y X. Analysis of yield and quality traits in sugarcane cultivars (lines) with GGE-biplot. Acta Agon Sin, 2013 39: 142–152 (in Chinese with English abstract)[3]Giauffret C, Lothrop J, Dorvillez D, Gouesnard B, Derieux M. Genotype × environment interactions in maize from temperate or high land tropical origin. Crop Sci, 2000, 40: 1004–1012[4]Haussmann B I, Hess D E, Reddy B V, Mukuru S Z, Kayentao M, Welz H G, Geiger. Pattern analysis of genotype × environment interaction for striga resistance and grain yield in African sorghum trials. Genetic Res Crop Evol, 2001, 122: 297–308[5]许乃银, 张国伟, 李健, 周治国. 基于GGE双标图的棉花品种生态区划分. 应用生态学报, 2013, 24: 771–776Xu N Y, Zhang G W, Li J, Zhou Z G. Ecological regionalization of cotton varieties based on GGE biplot. Chin J Appl Ecol, 2013, 24: 771–776 (in Chinese with English abstract)[6]Gauch H G, Zobel R W. AMMI analysis of yield trails. In: Kang M S, Gauch G H, eds. Genotype-by-Environment Interaction. Boca Raton Florida: CRC Press, 1996. pp 85–122[7]Romagosa I, Fox P N. Genotype×environment interaction and adaptation. In: Hayward M D, Bosemark N O, Romagosa I, eds. Plant Breeding: Principle and Prospects. London: Chapman and Hall, 1993. pp 373–390[8]Epinat-Le Signor C, Dousse S, Lorgeou J, Denis J B, Bonhomme R, Carolo P, Charcosset A. Interpretation of genotype × environment interactions for early maize hybrids over 12 years. Crop Sci, 2001, 41: 663–669[9]Gauch H G, Zobel R W. Identifying mega-environments and targeting genotypes. Crop Sci, 1997, 37: 311–326[10]许乃银, 张国伟, 李健, 周治国. 基于HA-GGE 双标图的长江流域棉花区域试验环境评价. 作物学报, 2012, 38: 2229–2236Xu N Y, Zhang G W, Li J, Zhou Z G. Evaluation of cotton regional trial environments based on HA-GGE biplot in the Yangtze river valley. Acta Agon Sin, 2012, 38: 2229–2236 (in Chinese with English abstract)[11]Yan W K, Hant L A. Biplot analysis of diallel data. Crop Sci, 2002, 42: 21–30[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: 1?16Yan W K. Optimal use of biplots in the analysis of multi?environment variety trial data. Acta Agon Sin, 2010, 36: 1?16 (in Chinese with English abstract)[13]de Oliveira R L, Von Pinho R G, Ferreira D F, Pires L P M, Melo W M C. Selection index in the study of adaptability and stability in maize. Sci World J, 2014, http://dx.doi.org/10.1155/2014/360570[14]Yan W, Frégeau-Reid J A, Pageau D, Martin R, Mitchell-Fetch J, Etienne M, Rowsell J, Scott P, Price M, de Haan B, Cummiskey A, Lajeunesse J, Durand J, Sparry E. Identifying essential test locations for oat breeding in eastern Canada. Crop Sci, 2010, 50: 504?515[15]Crossa J, Fox P N, Pfeiffer W H, Rajaram S, Gauch Jr H G. AMMI adjustment for statistical analysis of an internal wheat yield trial. Theor Appl Genet, 1991, 81: 27–37[16]常磊, 柴守玺. AMMI模型在旱地春小麦稳定性分析中的应用. 生态学报, 2006, 26: 3677–3684Chang L, Chai S X. Application of AMM I model in the stability analysis of spring wheat in rainfed area. Acta Ecol Sin, 2006, 26: 3677–3684 (in Chinese with English abstract)[17]刘文江,李浩杰, 汪旭东, 周开达. 用AMMI模型分析杂交水稻基本性状的稳定性. 作物学报, 2002, 28: 569–573Liu W J, Li H J, Wang X D, Zhou K D. Stability analysis for elementary characters of hybrid rice by AMMI model. Acta Agon Sin, 2002, 28: 569–573 (in Chinese with English abstract)[18]刘旭云, 谢永俊, 杨德, 张锡顺. AMMI模型应用于油菜区域试验的分析研究. 西南农业学报, 2001, 14(2): 27–30Liu X Y, Xie Y J, Yang D, Zhang X S. Analysis and research of AMMI model for rape varieties regional trials. Southwest China J Agric Sci, 2001, 14(2): 27–30 (in Chinese with English abstract)[19]罗俊, 袁照年, 张华, 陈由强, 陈如凯.宿根甘蔗产量性状的稳定性分析. 应用与环境生物学报, 2009, 15: 488–494Luo J, Yuan Z N, Zhang H, Chen Y Q, Chen R K. Stability analysis on yield characters of sugarcane ratoon. Chin J Appl Environ Biol, 2009, 15: 488–494 (in Chinese with English abstract)[20]Gauch H G Jr, Piepho H P, Annicchiarico P. Statistical analysis of yield trials by AMMI and GGE: further considerations. Crop Sci, 2008, 48: 866?889[21]Yan W, 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[22]严威凯, 盛庆来, 胡跃高, Hun L A. GGE叠图法-分析品种×环境互作模式的理想方法. 作物学报, 2001, 27: 21–27Yan W K, Sheng Q L, Hu Y G, Hun L A. GGE biplot: all ideal tool for studying genotype by environment interaction of regional yield trial data. Acta Agon Sin, 2001, 27: 21–27 (in Chinese with English abstract)[23]Yan W, Hunt L A, Sheng Q L, Szlavnics Z. Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Sci, 2000, 40: 596?605[24]Yan W, Holland J B. A heritability-adjusted GGE biplot for test environment evaluation. Euphytica, 2010, 171: 355–369[25]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. 作物学报, 2010, 36: 1377–1385Zhang Z F, Fu X F, Liu J Q, Yang H S. Yield stability and testing-site representativeness in national regional trials for oat variety based on GGE-biplot analysis. Acta Agon Sin, 2010, 36: 1377–1385 (in Chinese with English abstract)[26]陈四龙, 李玉荣, 程增书, 刘吉生. 用GGE双标图分析种植密度对高油花生生长和产量的影响. 作物学报, 2009, 35: 1328–1335Chen S L, Li Y R, Cheng Z S, Liu J S. GGE-biplot analysis of effects of planting density n growth and yield components of high oil peanut. Acta Agon Sin, 2009, 35: 1328–1335 (in Chinese with English abstract)[27]尚毅, 李少钦, 李殿荣. 用双标图分析油菜双列杂交试验. 作物学报, 2006, 32: 243?248Shang Y, Li S Q, Li D R. GGE biplot analysis of diallelcross of B. napus L. Acta Agon Sin, 2006, 32: 243?248 (in Chinese with English abstract)[28]周长军, 田中艳, 李建英. 双标图法分析大豆多点试验中品系产量稳定性及试点代表性. 大豆科学, 2011, 30: 318?322Zhou C J, Tian Z Y, Li J Y. GGE-biplot analysis on yield stability and testing-site representativeness of soybean lines in multi-environment trials. Soybean Sci, 2011, 30: 318?322 (in Chinese with English abstract)[29]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. 中国生态农业学报, 2010, 18: 988?994Chang L, Chai S X. Application of GGE biplot in spring wheat yield stability analysis in rainfed areas of China. Chin J Eco-Agric, 2010, 18: 988?994 (in Chinese with English abstract)[30]许乃银, 金石桥. 应用GGE双标图筛选理想棉花区域试验点. 江西棉花, 2010, 32(3): 7?12Xu N Y, Jin S Q. Identifying discriminating and representative locations in cotton regional trials using GGE biplot. Jiangxi Cotton, 2010, 32(3): 7?12 (in Chinese with English abstract)[31]孙敏, 蒋文敏, 李慧英, 刘壮. 应用GGE双标图进行向日葵杂交种产量稳定性分析. 黑龙江农业科学, 2010, (9): 11?13Sun M, Jiang W M, Li H Y, Liu Z. Analysis of stable-production character by GGE biplot on sunflower hybrids. Heilongjiang Agric Sci, 2010, (9): 11?13 (in Chinese with English abstract)[32]Tang Q Y, Zhang C X, Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research. Insect Sci, 2013, 20: 254?260[33]唐启义, 冯明光. DPS数据处理系统----实验设计、统计分析及数据挖掘. 北京: 科学出版社, 2010Tang Q Y, Feng M G. DPS Data Processing System: experimental design, statistical analysis, and data mining. Beijing: Science Press, 2010[34]金石桥, 许乃银. GGE双标图在中国农作物品种试验中应用的必要性探讨. 种子, 2012, 31(12): 89?92Jin S Q, Xu N Y. The discuss of necessity about GGE double labeling chart applied in crop variety experiment in china. Seed, 2012, 31(12): 89?92 (in Chinese with English abstract)[35]Luo J, Pan Y B, Xu L P, Zhang H, Yuan Z N, Deng Z H, Chen R K, Que Y X. Cultivar evaluation and essential test locations identification for sugarcane breeding in China. Sci World J, 2014, http://dx.doi.org/10.1155/2014/302753[36]Luo J, Que Y X, Zhang H, Xu L P. Seasonal variation of the canopy structure parameters and its correlation with yield-related traits in sugarcane. Sci World J , 2013, http://dx.doi.org/10.1155/2013/801486 |
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