GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data

被引:110
作者
Rakshit, Sujay [1 ]
Ganapathy, K. N. [1 ]
Gomashe, S. S. [1 ]
Rathore, A. [2 ]
Ghorade, R. B. [3 ]
Kumar, M. V. Nagesh [4 ]
Ganesmurthy, K. [5 ]
Jain, S. K. [6 ]
Kamtar, M. Y. [7 ]
Sachan, J. S. [8 ]
Ambekar, S. S. [9 ]
Ranwa, B. R. [10 ]
Kanawade, D. G. [11 ]
Balusamy, M. [12 ]
Kadam, D. [13 ]
Sarkar, A. [14 ]
Tonapi, V. A. [1 ]
Patil, J. V. [1 ]
机构
[1] Directorate Sorghum Res, Hyderabad 500030, Andhra Pradesh, India
[2] Int Crops Res Inst Semi Arid Trop, Patancheru 502324, Andhra Pradesh, India
[3] Dr Panjabrao Deshmukh Krishi Vidyapeeth, Akola 444104, Maharashtra, India
[4] ANGRAU Reg Agr Res Stn, Palem 509215, Andhra Pradesh, India
[5] Tamil Nadu Agr Univ, Dept Genet & Plant Breeding, Coimbatore 641003, Tamil Nadu, India
[6] Sardarkrushinagar Dantiwada Agr Univ, Sorghum Res Stn, Deesa 385535, Gujarat, India
[7] Univ Agr Sci, Main Sorghum Res Stn, Dharwad 580005, Karnataka, India
[8] Chandra Shekhar Azad Univ Agr & Technol, Crop Res Stn AICRP, Jhansi 284204, Uttar Pradesh, India
[9] Marathwada Agr Univ, Parbhani 431402, Maharashtra, India
[10] Maharana Pratap Univ Agr & Technol, Udaipur 313001, Rajasthan, India
[11] Agr Res Stn PDKV, Buldana 443001, Maharashtra, India
[12] Agr Res Stn TNAU, Bhavanisagar 638451, Tamil Nadu, India
[13] Agr Res Stn MPKV, Karad, Maharashtra, India
[14] Natl Acad Agr Res Management, Hyderabad 500030, Andhra Pradesh, India
关键词
Sorghum bicolor; Multi-location data; GE interaction; GGE biplot; Stability; Mega-environment; STATISTICAL-ANALYSIS; YIELD TRIALS; GRAPHIC ANALYSIS; TRAIT RELATIONS; AMMI; STABILITY; LOCATIONS;
D O I
10.1007/s10681-012-0648-6
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Sorghum [ (L.) Moench] is a very important crop in the arid and semi-arid tropics of India and African subcontinent. In the process of release of new cultivars using multi-location data major emphasis is being given on the superiority of the new cultivars over the ruling cultivars, while very less importance is being given on the genotype x environment interaction (GEI). In the present study, performance of ten Indian hybrids over 12 locations across the rainy seasons of 2008 and 2009 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (59.3-89.9%), while genotype contributed only 3.9-16.8% of total variation. Genotype x location interaction contributed 5.8-25.7% of total variation. We could identify superior hybrids for grain yield, fodder yield and for harvest index using biplot graphical approach effectively. Majority of the testing locations were highly correlated. 'Which-won-where' study partitioned the testing locations into three mega-environments: first with eight locations with SPH 1606/1609 as the winning genotypes; second mega-environment encompassed three locations with SPH 1596 as the winning genotype, and last mega-environment represented by only one location with SPH 1603 as the winning genotype. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. We did not observe any correlation of these mega-environments to their geographical locations. Existence of extensive crossover GEI clearly suggests that efforts are necessary to identify location-specific genotypes over multi-year and -location data for release of hybrids and varieties rather focusing on overall performance of the entries.
引用
收藏
页码:465 / 479
页数:15
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