ADAPTABILITY ANALYSIS OF PROMISING GENOTYPES OF BREAD WHEAT IN NWPZ OF INDIA USING ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION C N Mishra*, Satish Kumar, Amit Kumar#, Vikas Gupta, Ravish Chatrath, Vinod Tiwari and Indu Sharma Directorate of Wheat Research (DWR), Karnal Haryana #ICAR NEH Region Umiam, Meghalaya ADAPTABILITY ANALYSIS OF PROMISING GENOTYPES OF BREAD WHEAT IN NWPZ OF INDIA USING ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION C N Mishra*, Satish Kumar, Amit Kumar#, Vikas Gupta, Ravish Chatrath, Vinod Tiwari and Indu Sharma Directorate of Wheat Research (DWR), Karnal Haryana #ICAR NEH Region Umiam, Meghalaya India is the second largest producer of wheat in world with a record harvest of million tonnes during For the last five years there has a record harvest of wheat. The major factor further contributing to record produce were the development of high yielding genotypes, management of losses due to diseases and cool climate at grain formation stages. Apart from this the successes achieved in case of wheat can be contributed to a well established varietal evaluation system. Indian wheat programme has been quoted as one of the best in the world. For the purpose of varietal evaluation the country is divided into six major wheat growing zones, on the basis of agro-climatic conditions i.e. Northern Hills Zone (NHZ), North Western Plains Zone (NWPZ), North Eastern Plains Zone (NEPZ), Central Zone (CZ), Peninsular Zone (PZ) and Southern Hills Zone (SHZ). In the North western Plains zone wheat occupies an area of 11.3 m ha ( ̴ 41%) with highest productivity of 4.5 tonnes is the most productive zone of the country. With the primary goal of identifying superior cultivars multilocation trials are conducted annually throughout the zone and the best genotypes are identified for release as variety. The trials are conducted at a number of locations in the zone and average performance of the genotypes over the locations determines its release as a variety. The data generated through coordinated trials can be utilized for studying the stability of promising lines in the zone. Introduction Anonymous (2011) Progress Report of All India Coordinated Wheat &Barley Improvement Project Vol. I, p.312 Gauch HG (1992) Statistical Analysis of Regional Trials: AMMI Analysis of Factorial Designs. Elsevier, Amsterdam, The Netherlands Manrique K. and Hermann M. (2001) Effect of GxE Interaction on root yield and Beta carotene content of selected sweet potato (Ipomea batatas L.) varieties and breeding clones. In CIP Program Report , Lima, peru. pp Ortiz R, Wagoire WW, Hill J, Chandra S, Madsen S and Stolen O. (2001) Heritability and correlations among genotype by environment stability statistics for grain yield in Bread Wheat. Theor. Appl. Genet., 103: References Methodology The results of AMMI analysis for GxE interaction showed that the first three principal components cumulatively contributed defining per cent of GxE interaction variation. However the first two components were more descriptive and accounted for 71.9 per cent of G x E interaction variation and were considered for ease of interpretation (Fig. 1.). Among the 17 genotypes tested WH 1105, PBW 651, and HD 3058 were found as stable genotypes as they were located near the cross section in biplot with lower PCA 2 value. WH 1105 with the highest yield and better stability could be regarded as a genotype with wide adaptability in the zone The contribution of PBW 648, Raj 4229, HD 3055, HUW 640, PBW 343 and DBW 17 towards GxE interaction was more. However, the contribution of PBW 651, WH 1105 and HD 3058 were low and showed a degree of stability at six major locations of the zone. Among the six locations Delhi, Hisar and Ludhiana were major contributors to the GxE interaction. The AMMI method for studying the stability of genotypes has also been used by various researchers (Ortiz et al. 2001, Manrique and Hermann 2001) in different crops. The results also indicated that AMMI is an informative method for stability and adaptation analysis to be employed in practical plant breeding. The Additive Main effect and Multiplicative Interaction (AMMI) method proposed by Gauch (1992) is a statistical tool which leads to identification of stable genotypes with their adaptation behaviour in an easy manner. In this method main effects are initially accounted for a regular analysis of variance and then the interaction is analysed through principal component analysis. Seventeen advance wheat breeding lines viz., PBW 648(1), PBW 651(2), WH 1105(3), WH 1107(4), Raj 4228(5), Raj 4229(6), Raj 4230(7), HD 3055(8), HD 3058(9), HD 3059(10), JAUW 548(11), HUW 640(12) along with five checks viz., PBW 343(13), DBW 17(14), PBW 550(15), HD 2967(16) and identified variety DPW (17) were evaluated during the year under irrigated timely sown condition of Advance Varietal Trial (AVT) for North Western Plains Zone of India (Anonymous 2011). The grain yield data of these promising genotypes from six major locations, which are representative of the zone (Delhi, Karnal, Hisar, Ludhiana, Durgapura and Pantnagar), was subjected to AMMI analysis to find out the satbility of promising genotypes. The analysis of variance (ANOVA) for the genotypes and locations revealed that the main effects of genotype, location and interaction effect of genotype x location were highly significant. In spite of the location, the genotype WH 1105 was the highest yielder followed by the identified variety HD These two genotypes were followed by PBW 651 and WH The maximum location yield was observed from Ludhiana followed by Hisar, Pantnagar, Delhi, Karnal and Durgapura. Results and Discussion Fig: 1. Interaction Biplot Graph for AMMI model.