APPLICATION OF AMMI MODEL FOR EVAULATION SPRING BARLEY GENOTYPES IN MULTI-ENVIRONMENT TRIALS

The aim of study was to evaluate the yield performance of genotypes and stability, environments and G × E interaction of 12 spring barley genotypes in multi-environment trials. The trials were implemented in respect to a integrate arrangement complex style with four replications. The AMMI (Additive main effects and multiplicative interaction) analysis was made to estimate grain yield and understand G × E interaction patterns. Analysis indicated that the major contributions to treatment sum of squares were environments (81.4%), GE (10.3%) and genotypes (8.3%), respectively; suggesting that grain yield of genotypes was effected environmental conditions. PCA 1 and PCA 2 axes (Principal component) were significant (0.01) and supplied to 68.30% of the complete G × E interaction. The AMMI analysis revealed that E3 and E5 were more stable and high productive; mean while E6 and E7 were unstable and nominal efficient environments. According to stability variance, the genotypes (G1, G3, G6 and G9) were the productive and more stable; meanwhile G4 and G5 were low productive and stable genotypes. Moreover, G2 were the best productive to all environments without E2. The G × E model exposed according to AMMI analysis recommended that G2 shown candidates and registered as Kendal, because of wide adaptability with high performances in all environments. Introduction Barley (Hordeum vulgare L.) is important for cereal crop of Turkey and accounted for nearly 20% of the total cereal production. Barley has been cultivated for many years and has a significant role in South-Eastern Anatolia. It is also grown mainly on rainfall conditions, but genotype × environment interaction (GEI) restricts the progress in yield improvement under rain fed and unpredictable climatic conditions (Kilic 2014). Therefore, G × E interaction is of major importance, because of provides information about the effect of test environments on genotype performance and plays an important key role for assessment of performance yield stability of the breeding genotype (Mohammadi et al. 2013). Increasing genetic gain in yield performance is possible in part from narrowing the adaptation of genotypes and so maximizing yield in particular environments are described by GE interaction (Sabaghnia et al. 2012b). Yield is highly affected by many genetic factors as well as environmental fluctuations, because it is a complicated marker which is dependent on somewhat other markers (Akter et al. 2014). The model of AMMI is a complex model including both two way data structure and additive multiplicative components which enabled a breeder to get precise prediction on genotypic potentiality and environmental influences on it. The impact of AMMI method has been clearly showed by different researchers using multi-environment. This method is very effective for studying GEI interaction (Tarakanovas and Ruzgas 2006), provide the correlative size and significant affects of GEI and its interaction (Asfaw et al. 2009), display more informative in different genotype response over environments, describing specific and non-specific resistance of *Author for correspondence: . GAP International Agricultural Research and Training Centre, 21100, Diyarbakır, Turkey. 614 KENDAL AND TEKDAL genotypes, identifying most discriminating environments (Mnukherjee et al. 2013), demonstrates the presence of GE interactions, and shows highly significant differences for environment, genotype and their interactions (Rad et al. 2013), is important for testing promising lines under across environments to estimate stability and performance (Hagos and Abay 2013), reveals the efficiency performances of genotypes under the different effect of conditions and effects of GE interaction (Kilic 2014) and thus, it is useful for breeders and supporting breeding program decisions. The major objective of study reveal adaptation of barley genotypes using AMMI analysis to estimate the importance of GE interaction on yield, define mega-environments, identity the best acting genotype for every mega-environment and debate the containment of the GE interaction to barley breeding. Materials and Methods The experimental material comprising of 12 barley genotypes (Ten new promising lines and two cultivars (Sahin 91-regional and Vamıkhoca 98-national check) were used (Table 1). Table 1. The information’s about varieties, used in experiment. Code Pedigree of line and cultivar name Origin IPCAg [1] IPCAg [2] 01 CARDO/QUIB. /3/ROB. //GLORIA-BAR/COPAL . C B S S 96 W M 0 0 2 7 3 T-C-1 M1Y2M0Y ICARDA –119.521 158.962 02 LENT/BLLU//PINON -CBSS97M00698T-C-2M-1Y-0M " –112.673 881.421 03 CAB. /4/GLOR. /COPAL//BEN.4D/3/S.PB/5 /ABETO/ /GLORIA-BAR/CBSS97Y00819T-D-2Y-1M-0Y " 803.197 490.963 04 WI2269/Espe/3/WI2291/Bgs//Hml-02 ICB97-0152-0AP-13AP-0AP " 338.692 –542.972 05 ŞAHİN-91(Local Check) GAPIARTC 576.233 –468.294 06 Kv/ /Alger /Ceres.3621-1/3/ WI2 269/4 /Sara I C B 9 3-0727F7SSD92AP -0AP ICARDA 133.104 160.698 07 Mo . B1337 / WI2291 / / Mo. B1337 / WI2291 I C B 9 2-00450AP20AP0AP0AP " –680.955 –474.860 08 77s409/ Akrash-01 I C B 94-8140AP7AP0AP0AP " –884.913 –0.15904 09 Kv/ /Alger/ Ceres 362-1-1/ 3 /WI2269/6/ Zanbaka /5 / I C B 9 4629-0AP7AP0AP0AP " –377.964 0.37109 10 VAMIKHOCA-98(National check) AARI 170.038 –314.086 11 PATTY/ 3 /WEEAH 11/ / WI 2291/ BGS S E A 92-33963S-0S7S-0 " –159.308 297.823 12 PATTY / 3/ WEEAH 11 // WI 2291 / BGS SEA 9233962S0S15S0 ICARDA 314.070 –210.861 ICARDA: International Center for Agricultural Research in the Dry Areas. GAPIARTC: GAP International Agricultural Research and Training Center. AARI: Aegean Agricultural Research Institute The barley multi-environmental trials were conducted at seven test environment and different years (Table 2). Test environments shown different growing season and the conditions regions characterized by differences in climatic conditions. The location of Suruc was chosen as a very drought location APPLICATION OF AMMI MODEL FOR EVAULATION SPRİNG BARLY 615 and Adiyaman for heat stress. Also there were different climatic conditions among years. The trial carried out in a randomized block design with four replications and 450 seeds were used for m. Plot magnitude was 7.2 m (1.2 × 6 m) occurring in 6 rows spaced with 20 cm separate. Sowing was done by Wintersteiger drill. The fertilization rates for all plots were used 60 kg N/ha and 60 kg P/ha with sowing time and 60 kg N/ha was applied to plots at the early stem elongation. Harvest was done using Hege 140 harvester up on 6 m. Table 2. Years, the status of environment and long term of precipitation. Years Sites Code of sites Altitude (m) Latitude Longitude Annual rainfall (mm) 2007-08 Adiyaman E1 685 37° 46' N 38 17' E 554 2008-09 Adiyaman E2 685 3746' N 38 17' E 654 2008-09 Diyarbakir E3 499 36 97' N 38° 42' E 429 2009-10 Adiyaman E4 685 37 46’ N 38 17' E 56