Assessing genotype-by-environment interactions and trait associations in forage sorghum using GGE biplot analysis

被引:19
作者
Aruna, C. [1 ]
Rakshit, S. [1 ]
Shrotria, P. K. [2 ]
Pahuja, S. K. [3 ]
Jain, S. K. [4 ]
Kumar, S. Siva [5 ]
Modi, N. D. [6 ]
Deshmukh, D. T. [7 ]
Kapoor, R. [8 ]
Patil, J. V. [1 ]
机构
[1] Directorate Sorghum Res, Hyderabad, Andhra Pradesh, India
[2] GB Pant Univ Agr & Technol, Pantnagar, Uttar Pradesh, India
[3] CCS Haryana Agr Univ, Hisar, Haryana, India
[4] Sardarkrushinagar Dantiwada Agr Univ, Deesa, India
[5] Tamil Nadu Agr Univ, Coimbatore 641003, Tamil Nadu, India
[6] Navsari Agr Univ, Surat, India
[7] PDKV, Akola, India
[8] Punjab Agr Univ, Ludhiana 141004, Punjab, India
关键词
STATISTICAL-ANALYSIS; GRAPHIC ANALYSIS; YIELD STABILITY; TRIAL DATA; AMMI; IMPROVEMENT; HYBRIDS; WHEAT;
D O I
10.1017/S0021859615000106
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Forage sorghum is an important component of the fodder supply chain in the arid and semi-arid regions of the world because of its high productivity, ability to utilize water efficiently and adaptability to a wide range of climatic conditions. Identification of high-yielding stable genotypes (G) across environments (E) is challenging because of the complex G x E interactions (GEI). In the present study, the performance of 16 forage sorghum genotypes over seven locations across the rainy seasons of 2010 and 2011 was investigated using GGE biplot analysis. Analysis of variance revealed the existence of significant GEI for fodder yield and all eight associated phenotypic traits. Location accounted for a higher proportion of the variation (0.72-0.91), while genotype contributed only 0.060.21 of total variation in different traits. Genotype-by-location interactions contributed 0.02-0.13 of total variation. Promising genotypes for fodder yield and each of the associated traits could be identified effectively using a graphical biplot approach. The majority of test locations were highly correlated. A 'Which-won-where' study partitioned the test locations into two mega-environments (MEs): ME1 was represented by five locations with COFS 29 as the best genotype, while ME2 had two locations with S 541 as the best genotype. The existence of two MEs suggested a need for location-specific breeding. Genotype-by-trait biplots indicated that improvement for forage yield could be achieved through indirect selection for plant height, leaf number and early vigour.
引用
收藏
页码:73 / 86
页数:14
相关论文
共 39 条
[1]   Fodder yield and quality in forage sorghum: scope for improvement through diverse male sterile cytoplasms [J].
Aruna, C. ;
Shrotria, P. K. ;
Pahuja, S. K. ;
Umakanth, A. V. ;
Bhat, B. Venkatesh ;
Devender, A. Vishala ;
Patil, J. V. .
CROP & PASTURE SCIENCE, 2012, 63 (11-12) :1114-1123
[2]   TESTS FOR CROSSOVER GENOTYPE-ENVIRONMENTAL INTERACTIONS [J].
BAKER, RJ .
CANADIAN JOURNAL OF PLANT SCIENCE, 1988, 68 (02) :405-410
[3]   Error variation in multienvironment peanut trials: Within-trial spatial correlation and between-trial heterogeneity [J].
Casanoves, F ;
Macchiavelli, R ;
Balzarini, M .
CROP SCIENCE, 2005, 45 (05) :1927-1933
[4]  
Cooper M., 1996, P5
[5]   Biplot analysis of genotype by environment interaction for barley yield in Iran [J].
Dehghani, H ;
Ebadi, A ;
Yousefi, A .
AGRONOMY JOURNAL, 2006, 98 (02) :388-393
[6]   Graphic analysis of trait relations of rapeseed using the biplot method [J].
Dehghani, Hamid ;
Omidi, Heshmat ;
Sabaghnia, Naser .
AGRONOMY JOURNAL, 2008, 100 (05) :1443-1449
[7]   Yield stability of maize hybrids evaluated in multi-environment trials in Yunnan, China [J].
Fan, Xing-Ming ;
Kang, Manjit S. ;
Chen, Hongmei ;
Zhang, Yudong ;
Tan, Jing ;
Xu, Chuxia .
AGRONOMY JOURNAL, 2007, 99 (01) :220-228
[8]   BIPLOT GRAPHIC DISPLAY OF MATRICES WITH APPLICATION TO PRINCIPAL COMPONENT ANALYSIS [J].
GABRIEL, KR .
BIOMETRIKA, 1971, 58 (03) :453-+
[9]  
Gauch H G., 1992, Genotype-by-environment interaction, P1
[10]   Identifying mega-environments and targeting genotypes [J].
Gauch, HG ;
Zobel, RW .
CROP SCIENCE, 1997, 37 (02) :311-326