8个燕麦品种在甘肃的产量稳定性及试点代表性研究

doi:10.11733/j.issn.1007-0435.2016.05.026

草地学报 ›› 2016, Vol. 24 ›› Issue (5): 1100-1107.DOI: 10.11733/j.issn.1007-0435.2016.05.026

8个燕麦品种在甘肃的产量稳定性及试点代表性研究

柴继宽, 慕平, 赵桂琴

甘肃农业大学, 甘肃兰州 730070

收稿日期:2015-11-10 修回日期:2016-03-12 出版日期:2016-10-15 发布日期:2017-01-13
通讯作者: 慕平
作者简介:柴继宽(1983-),男,甘肃陇西人,博士,讲师,主要从事牧草种质资源及育种,E-mail:cjk_100@163.com
基金资助:
现代农业产业体系（nycytx-14）资助

Study on Yield Stability and Test Site Representativeness of Eight Oat Varieties in Gansu Province

CHAI Ji-kuan, MU Ping, ZHAO Gui-qin

Gansu Agricultural University, Lanzhou, Gansu Province 730070, China

Received:2015-11-10 Revised:2016-03-12 Online:2016-10-15 Published:2017-01-13

摘要/Abstract

摘要：

为了客观、准确地评价燕麦品种的稳定性和适应性，本研究采用GGE双标图对2012年甘肃省燕麦（Avena sativa）种植区域5个试点中的8个燕麦品种试验数据进行分析。结果表明：在燕麦种植区的大环境下，品种与环境互作效应对产量变异的影响约为品种效应的4.02倍。‘陇燕2号’和‘陇燕3号’属于高产、稳产性好的品种；‘青引1号’具有特殊适应性，在局部地区有推广价值。5个燕麦区试点可划分为2个不同的类型区，其中在甘肃中部半干旱地区表现最好的品种是‘陇燕1号’，在甘肃高寒阴湿区表现最好的品种是‘陇燕3号’。从环境代表性和对品种鉴别能力两方面分析，5个试点中代表性最好的是通渭，鉴别力最好的是天祝。

关键词: 燕麦, GGE双标图, 基因型×, 环境交互作用, 产量稳定性

Abstract:

In this study, GGE-biplot method was used to analyze the regional trial data of eight oat varieties from five sites in 2012, aiming to evaluate the yield stability and adaption of oat varieties objectively and accurately in Gansu province. The results showed that in oat planting region, the effect of interaction between variety and environment on yield variation were about 4.02 times as high as that of variety effects.‘Longyan No.2’ and ‘Longyan No.3’ had higher yield and better yield stability than other varieties, while ‘Qingyin No.1’ was deserved to promote in local areas for its idioadaptation. These five test sites were broadly classified into two environments. ‘Longyan No.1’ was the best genotypes for semi-arid regions of central Gansu province, and ‘Longyan No.3’ was the best genotypes for chilling and humid region of high-elevation of Gansu province. As for environment representativeness and identification varieties capacity, Tongwei was the best representative in the five test sites, and Tianzhu had the best discrimination capacity.

Key words: Oat, GGE biplot, Genotype×, Environment interaction, Yield stability

中图分类号:

S338
S543.7

柴继宽, 慕平, 赵桂琴. 8个燕麦品种在甘肃的产量稳定性及试点代表性研究[J]. 草地学报, 2016, 24(5): 1100-1107.

CHAI Ji-kuan, MU Ping, ZHAO Gui-qin. Study on Yield Stability and Test Site Representativeness of Eight Oat Varieties in Gansu Province[J]. Acta Agrestia Sinica, 2016, 24(5): 1100-1107.

0
/ / 推荐

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://manu40.magtech.com.cn/Jweb_cdxb/CN/10.11733/j.issn.1007-0435.2016.05.026

https://manu40.magtech.com.cn/Jweb_cdxb/CN/Y2016/V24/I5/1100

参考文献

[1] 余懋群,马欣荣,张庆勤. 三种燕麦的核型研究[J]. 武汉植物学研究,1995,13(2):177-179
[2] Gabriel K R. The biplot graphic display of matrices with application to principal component analysis[J]. Biometrika,1971,58:453-467
[3] 王磊,C G Mclaren,杨仕华. 利用双标图分析基因型和环境交互作用[J]. 科技通报,1997,13(5):281-286
[4] 张泽,鲁成,向仲怀. 基于AMMI模型的品种稳定性分析[J]. 作物学报,1998,24(3):304-309
[5] Yan W K. Methodology of cultivar evaluation based on yield trial data with special reference to winter wheat in Ontario[M]. Guelph:University of Guelph,Canada,1999:87
[6] Yan W K, Hunt L A, Sheng Q, et al. Cultivar evaluation and mega-environment investigation based on the GGE biplot[J]. Crop Science,2000,40:597-605
[7] 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,2001,93:1111-1118
[8] Yan W K,Hant L A. Biplot analysis of diallel data[J]. Crop Science,2002,42:21-30
[9] Yan W, Rajcan I. Biplot analysis of test sites and trait relations of soybean in Ontario[J]. Crop Science,2002,42:11-20
[10] 张海娟,王化俊,马小乐,等. 基于GGE双标图的北方大麦区试品种稳产性及试点代表性评价[J]. 麦类作物学报,2015,35(9):1250-1256
[11] 王磊,程本义,鄂志国,等. 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
[12] 许乃银,李健,张国伟,等. 基于GGE双标图和马克隆值选择的棉花区域试验环境评价[J]. 中国生态农业学报,2013,21(10):1241-1248
[13] 尚毅,李少钦,李殿荣,等. 用双标图分析油菜双列杂交试验[J]. 作物学报,2006,32(2):243-248
[14] 张志芬,付晓峰,刘俊青,等. 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
[15] 张勇,何中虎,张爱民. 应用GGE双标图分析我国春小麦的淀粉峰值粘度[J]. 作物学报,2003,29(2):245-251
[16] 陈四龙,李玉荣,程增书,等. 用GGE双标图分析种植密度对高油花生生长和产量的影响[J]. 作物学报,2009,35(7):1328-1335
[17] Yan W K. Optimal use of biplots in analysis of multi-location variety test data[J]. Acta Agronomica Sincia,2010,36(11):1805-1819
[18] Gauch H G. Identifying mega-environments and targeting genotypes[J]. Crop Science,1997,37:311-326
[19] Yan W K, Kang M S. GGE biplot analysis:A graphical tool for breeders, geneticists, and agronomists[M]. Boca Raton,Florida:CRC Press,2003:25
[20] 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,2001,93:1111-1118
[21] 严威凯,盛庆来,胡跃高,等. GGE盈图法-分析品种×环境互作模式的理想方法[J]. 作物学报,2001,27(1):22-28
[22] Kempton R A. The use of biplots in interpreting variety by environment interactions[J]. Agricultural Science,1984,103:123-135
[23] Wamatu J N, Thomas E. The influence of genotype-environment interaction on the grain yields of 10 Pigeonpea cultivars grown in Kenya[J]. Jounal of Agonomy and Crop Science,2002,188(1):25-33
[24] 马洪文,王昕,殷延勃,等. 基因型与环境互作下粳稻农艺性状的遗传效应分析[J]. 西北农业学报,2009,18(2):74-78
[25] 焦伟红,刘景辉,齐冰洁,等. 用GGE双标图分析燕麦品种(系)农艺与品质性状[J]. 中国农学通报,2011,27(01):24-29
[26] 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
[27] Yan W, Hunt L A. Genetic and environment causes of genotype by environment interaction for winter wheat yield in Ontario[J]. Crop Science,2001,41:19-25
[28] Yan W, Cornelius P L, Crossa J, et al. Two types of GGE biplot for analyzing multi-environmenttrial data[J]. Crop Science,2001,41:656-663
[29] 罗俊,张华,邓祖湖,等. 用GGE双标图分析甘蔗品种性状稳定性及试点代表性[J]. 应用生态学报,2012,23(5):1319-1325
[30] 慕平,赵桂琴,柴继宽. 基于GGE-Biplot的甘肃省不同生态区燕麦生产性能及适应性分析[J]. 中国生态农业学报,2015,23(6):705-712
[31] 孙艳,王益权,仝瑞强. 土壤紧实胁迫对黄瓜叶片光合作用及叶绿素荧光参数的影响[J]. 植物营养与肥料学报,2009,15(3):638-642
[32] Adams D B, Adams Ⅲ W W. Photoprotection and other responses of plants to high light stress[J]. Ann Rev Plant Physiol Plant MolBiol,1992,43:599-626
[33] Demmig B, Winter K, Krüger A, et al. Photoinhibition and zeaxanthin formation in intact leaves. A possible role of the xanthophyII cycle in the dissipation of excess light energy[J]. Plant Physiology,1987,84:218-224
[34] Yan W, Hunt L A. Biplot analysis of Diallel data[J]. Crop Science,2002,42:21-30
[35] 李本贵,阎俊,何中虎,等. 用AMMI模型分析作物区域试验中的地点鉴别力[J]. 作物学报,2004,30(6):593-596

8个燕麦品种在甘肃的产量稳定性及试点代表性研究

Study on Yield Stability and Test Site Representativeness of Eight Oat Varieties in Gansu Province

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	宋词, 黄小涛, 石国玺, 周华坤, 王芳萍, 姚步青. 播期对青藏高原燕麦生长和饲草品质的影响[J]. 草地学报, 2021, 29(S1): 121-127.
[2]	吴海艳, 曲珍, 刘昭明, 拉巴顿珠, 同桑措姆, 曲尼, 尼玛卓嘎, 马玉寿. 基于主成分分析的燕麦品种生产性能的比较研究[J]. 草地学报, 2021, 29(9): 1967-1973.
[3]	朱海霞. 多孢木霉HZ-31菌株胁迫下野燕麦内参基因的选择[J]. 草地学报, 2021, 29(8): 1666-1674.
[4]	陈彩锦, 张尚沛, 师尚礼, 曾燕霞, 吴娟, 尚继红, 高婷, 张蓉. 基于GGE双标图对苜蓿品种丰产性和稳定性综合评价[J]. 草地学报, 2021, 29(5): 912-918.
[5]	童永尚, 鱼小军, 徐长林, 汪鹏斌, 宋建超, 李珍, 李颖. 天祝高寒区播期对7个燕麦品种饲草产量及品质的影响[J]. 草地学报, 2021, 29(5): 1094-1106.
[6]	梁国玲, 刘文辉, 马祥. 590份皮燕麦种质资源穗部性状遗传多样性分析[J]. 草地学报, 2021, 29(3): 495-503.
[7]	刘备, 宋玉梅, 孙铭, 毛培胜. 燕麦劣变种子吸胀过程中线粒体AsA-GSH循环的生理响应[J]. 草地学报, 2021, 29(2): 211-219.
[8]	贾志锋, 马祥, 琚泽亮, 刘凯强, 赵桂琴. 施氮量和播种量对燕麦光合特性、激素含量及种子产量的影响[J]. 草地学报, 2021, 29(2): 293-302.
[9]	张琦, 魏臻武, 闫天芳, 耿小丽. 燕麦种质资源农艺性状遗传多样性的鉴定评价[J]. 草地学报, 2021, 29(2): 309-316.
[10]	李文, 魏廷虎, 阿保地, 永措巴占, 才仁塔次, 周玉海, 李文浩, 郭卫兴, 张雁平. 化肥减施配合有机肥对高寒区燕麦营养品质和土壤养分的影响[J]. 草地学报, 2021, 29(12): 2878-2886.
[11]	胡佳燕, 刘畅, 李志坚, 周帮伟, 白静. 不同类型皮燕麦在吉林省西部的产量与农艺性状的比较研究[J]. 草地学报, 2021, 29(10): 2247-2257.
[12]	汪雪, 刘晓静, 赵雅姣, 王静. 紫花苜蓿/燕麦间作对燕麦碳、氮代谢及其物质积累的影响研究[J]. 草地学报, 2021, 29(10): 2258-2264.
[13]	周磊, 王璐, 赵宝平, 米俊珍, 王凤梧, 刘景辉, 张丹, 刘烨焜. 北方农牧交错区不同播期和刈割期对燕麦饲草产量和品质的影响[J]. 草地学报, 2021, 29(10): 2355-2363.
[14]	付东青, 王彦超, 宋磊, 王旭哲, 张凡凡, 马春晖. 施氮量和种植密度对石河子复播早熟饲用燕麦生产性能的影响[J]. 草地学报, 2021, 29(10): 2364-2371.
[15]	贾志锋, 马祥, 琚泽亮, 刘凯强, 赵桂琴. 氮肥和种植密度对燕麦叶片衰老特性及细胞结构的影响[J]. 草地学报, 2021, 29(1): 80-87.