Legume Res., 37 (3) : 253-258, 2014 doi:10.5958/j.0976-0571.37.3.038 AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com IDENTIFICATION OF STABLE GENOTYPES UNDER VARYING ENVIRONMENTS IN MUNGBEAN Tejbir Singh* and Amitesh Sharma Department of Genetics and Plant Breeding Kisan P.G. College, Simbhaoli-245 207, India Received: 06-12-2012 Accepted: 04-09-2013 ABSTRACT Forty indigenous genotypes of mungbean collected from different institute/organizations were evaluated under eight artificially created environments for stability analysis for seed yield and its components using Eberhart and Russell s (1966) model. Pooled analysis of variance indicated significant differences among the genotypes for all the characters except number of seeds per pod. The linear component of GxE was significant only for days to 50% flowering, plant height, number of seeds per pod and 100 seed weight suggesting that the prediction of performance of genotypes were possible across the environments for these characters. On the basis of stability parameters, genotypes KM 2194, KM 2224, KMU 41, KMU 42, and KMU 55 were identified as desirable for seed yield. Key words: GxE interaction, Mungbean, Seed yield, Stability. INTRODUCTION A specific genotype may not exhibit the same phenotypic performance across the series of environments. The relative ranking and values of different genotypes varies with environments. One of the major objectives in any plant breeding programme has been to develop stable varieties which minimize the effects of environment on performance. Allard and Bradshaw (1964) suggested that a variety may achieve stability through individual buffering or population buffering. The importance of G X E interaction in mungbean has been recognized by several workers (Verma et al., 1972; Zekeb and Zehran, 1976; Imrie et al., 1981; Rao and Suryavanshi, 1988). The genotypes x environment interaction play an important role in the expression of various plant characters. It creates problem for plant breeders to select the genotypes with wide adaptability and to get precise estimates of genetic parameters. It is, therefore, necessary to characterize the linear response of genotype to varying environmental conditions. For this purpose, several methods have been proposed based on conventional analysis of various techniques (Sprague and Federer, 1951) and univariate stability parameters (Plaisted and Peterson, 1957; Allard, 1961; Griffing and Langridge, 1963). These * Corresponding author s e-mail: drtejbir@yahoo.com methods, however do not provide preci se information on adaptation responses of individual genotype. The regression analysis originally suggested by Yates and Cochran (1938) and developed by Finlay and Wilkinson (1963). Eberhart and Russell (1966); Perkins and Jinks (1968) and Freeman and Perkins (1971) have been extensively used for characterizing the genotypic responses in crop plants. Eberhart and Russell (1966) model has been extensively used in different crop plants. In this model, regression coefficient (b) is considered as parameter of response and S 2 d 1 as parameter of stability. The present study was undertaken to estimate GxE interaction and identifying stable genotypes under varying environments. MATERIALS AND METHODS The experimental material comprised of forty indigenous genotypes collected from different institutes including some released varieties (Table 2). The material was grown in a randomized block design with three replications at research farm of Kisan P.G. College, Simbhaoli (Hapur) under eight environments { two years (2008 & 2009) x two season (summer & kharif) x two dates of sowing (early & late)}. Each genotype was assigned to a single row plot of 3m length with a distance of 30 cm and 15 cm between rows and plants,
254 LEGUME RESEARCH- An International Journal TABLE 1: Joint regression analysis for yield and yield components in mungbean (Eberhart and Russell, 1966). *,** = Significant at P = 0.05 and P = 0.01 levels, respectively. respectively. The observations were recorded on five randomly selected plants in each plot on twelve characters (listed in Table 1) and data were subjected to stability analysis as suggested by Eberhart and Russell (1966) model. RESULTS AND DISCUSSION In the present investigation, one regression approach (Eberhart and Russell, 1966) has been applied to understand the stability of forty genotypes of mungbean grown in eight different environments (two seasons, two dates of sowing and two years). The pooled analysis of variance was carried out as per Eberhart and Russell (1966) model to determine the differences among genotypes, environments and genotype x environment interaction. The results showed significant differences among the genotypes for all the characters except number of seeds per pod indicating the presence of considerable amount of genetic variability. Mean squares due to environments were also highly significant for all the characters except days to maturity which indicated that the environments were diverse (Table 1). Genotypes showed variable performance as mean square due to genotype x environment was highly significant for all the characters which indicated that the genotypes interacted consi derably to environmental conditions and the relative rankings of genotypes were different in different environments. Further, the mean squares due to environment (linear) were also significant for all the characters thus indicated that the environments influenced the characters differently due to larger envi ronmental differences among the eight environments. Similar to the present results significant mean squares for genotype, environment and genotype x environment interaction were also reported by Rao and Suryawanshi (1988), Patel and Narkhede (1989) in urdbean; Raje and Rao (2001) and Parmar et al.(2005) in mungbean, Sood et al. (2000), Kumar et al. (2005) in chickpea; Phad et al. (2005), Patel et al. (2005) in pigeonpea and Chauhan et al. (2005) in rajmash. The mean squares due to genotype x environment (linear) were also significant for days to 50% flowering, plant height, number of seeds per pod and 100-seed weight indicated the presence of predictable genotype x environment interaction. It is further suggested that major portion of G x E interaction was attributed to linear
Vol. 37, No. 3, 2014 255 TABLE 2: Estimates of stability parameters for seed yield and yield traits in forty genotypes of mungbean. Genotypes No. of seeds per pod Pod length (cm) S 2 d S 2 d X b X b IPM-3-3 10.25 0.53* 1.77 + 7.04 1.18 0.23 IPM-3-1 10.46 0.62* 0.99 7.69 1.02 1.83 IPM - 99-125 10.64 0.59* 2.71 + 7.10 3.70** 0.25 KM- 2194 11.10 0.47** 1.49 + 7.89 1.24 0.27 KM-2195 11.39 0.76 1.25 7.07-1.00* 1.37 + KM- 2197 11.48 0.85 2.40 6.69 0.18** 0.05 KM-2224 11.35 0.83 1.29 6.49 1.19 0.07 KM- 2239 10.26 0.70* 1.17 7.20 1.73* 0.63 KM- 2241 11.85 0.55* 2.88 + 6.60 0.54* 0.05 MUM-2 10.50 0.66 2.07 7.36 0.94 0.02 HUM-2 11.38 0.69 1.11 7.34 0.95 0.03 HUM-6 11.10 0.77 1.37 7.24 0.64 0.15 HUM-8 10.75 0.65* 1.99 7.08 1.64** 0.03 HUM-14 10.76 0.51** 1.11 6.45 1.52* 0.09 HUM-15 10.89 0.64 0.62 6.43 0.84-0.01 HUM-17 10.00 0.59* 0.63 6.27 1.11 0.11 PDM-11 11.00 0.62* 0.69 6.99 0.02** 0.06 PDM-54 11.08 0.74 1.45 6.76 1.06 0.02 PDM-139 9.23-0.04 13.61 + + 6.69 1.68** 0.24 + PM-5 10.14 1.01 1.60 6.68 0.62* -0.03 Samrat 10.54 0.83 1.44 7.43 0.97 0.45 Pusa-9531 9.27 0.94 2.52 + 6.72 1.47* 0.66 + + Pusa vishal 10.57 0.85 4.19 6.91 0.48** 0.30 KMU-27 11.00 0.87 2.85 7.05 0.42* 0.16 + KMU-32 11.72 0.97 2.32 6.83 0.66* 0.12 KMU-34 10.47 0.85 1.65 6.69 0.45* -0.04 KMU-36 10.57 0.98 1.02 7.14 0.99 0.11 KMU-38 9.42 0.85 0.59 6.88 1.22 0.11 KMU-41 10.33 0.94 2.17 8.23 0.02** 0.31 + + KMU-42 10.63 1.10 1.93 6.94 1.63* 0.07 KMU-55 11.07 1.08 2.28 7.96 1.89* 0.11 KMU-61 11.52 0.96 1.93 6.89 0.97 0.01 K-851 10.08 0.88 0.13 6.85 1.19 0.04 Type-44 9.04 0.92 1.09 6.64 2.79* 2.41 + + NDM-1 9.96 0.92 2.50 7.71 2.74** 1.12 + NDM-3-11 9.38 0.63* 2.01 6.58 0.14* 0.20 Pusa Ratna 9.00 0.27** 2.04 6.66 0.14** 0.10 S-9 9.92 0.51* 1.55 7.22 1.71* 0.35 PS-10 9.54 0.32** 1.09 6.59-0.40 0.51 + Pusa-105 8.75 0.39** 1.27 6.59-1.20 0.21 Population mean 10.67 6.96 S.E. of Mean 0.64 0.23 100-seed weight (g) S 2 d X b 5.06 0.67* 0.25 6.54 1.02 1.34 + + 5.98 0.98 2.77 + + 8.96 2.84** 3.76 + 6.55 1.28 1.61 + 4.65 0.20** 0.27 5.08 0.47* 2.20 + 5.87 0.92 8.15 + + 4.82 0.75 0.10 5.91 1.15 1.16 8.00 1.01 1.06 8.22 1.80* 0.98 5.65 0.75 4.20 + 6.39 1.38 0.41 5.29 1.10 3.53 + 6.23 1.36 1.04 7.18 1.18 4.57 6.87 1.57* 3.09 5.50 0.95 10.08 + + 6.79 1.81** 0.10 5.63 1.31 2.70 + 6.50 1.43* 1.02 8.21 1.79** 3.69 + 6.74 1.68* 0.62 7.40 0.90 0.55 5.98 1.31 2.23 + 7.38 1.46 12.20 6.77 1.57* 0.75 6.31 0.40** 6.13 + 7.16 1.12 0.67 7.67 0.62 2.35 + 4.35 0.43* 1.01 6.23 0.43* 1.56 4.23 0.59* 2.49 + 4.98 0.67* 6.11 6.21-0.17 11.96 + + 5.79 0.23** 8.32 7.00-0.20 16.65 + + 6.08 0.02** 12.24 + + 6.79 0.53* 11.89 + + Population mean 23.97 S.E. of Mean 3.24 Cont...
256 LEGUME RESEARCH- An International Journal Cont... Genotypes IPM-3-3 IPM-3-1 IPM - 99-125 KM- 2194 KM-2195 KM- 2197 KM-2224 KM- 2239 KM- 2241 MUM-2 HUM-2 HUM-6 HUM-8 HUM-14 HUM-15 HUM-17 PDM-11 PDM-54 PDM-139 PM-5 Samrat Pusa-9531 Pusa vishal KMU-27 KMU-32 KMU-34 KMU-36 KMU-38 KMU-41 KMU-42 KMU-55 KMU-61 K-851 Type-44 NDM-1 NDM-3-11 Pusa Ratna S-9 PS-10 Pusa-105 Population mean S.E. of Mean X b Seed yield (g) S 2 d 6.01 1.37 10.44 + 5.49 0.96 3.55 + 5.79 1.42* 7.04 + 8.59 1.18 7.73 6.11 0.91 13.31 + + 6.18 1.48* 7.71 8.38 1.02 16.51 5.22 1.28 1.33 5.58 1.11 5.28 5.60 2.88** 6.92 + 6.16 0.39* 9.20 + 6.10 1.35 4.92 6.96 2.20** 9.11 + 5.59 1.53* 8.29 4.73 0.93 3.16 4.35 0.85 3.61 6.03-1.15** 4.28 5.48 0.62* 1.66 4.55 0.36** 3.42 4.88 2.12* 5.68 4.16 1.29 3.01 + 5.28-0.57* 4.28 6.19 1.33 0.50 7.29 1.24 0.07 8.44 1.09 3.97 5.66 2.36** 10.46 + 7.15 2.52** 15.41 + + 5.19 1.60* 1.93 8.46-0.15 5.05 7.47 1.12 2.64 7.36 0.63 2.65 5.37 0.37** 6.44 + 5.71-0.13 7.26 + + 3.07 0.74 0.64 5.00-0.03 3.90 + 5.96 0.24** 3.99 6.02-0.48* 10.73 + 6.21 0.02** 13.79 + + 3.85-1.02** 3.93 + 5.08 0.97 2.28 + 5.71 0.93 *,** = Significantly deviating from unity at P = 0.05 at P = 0.01 level, respectively. +,+ + = Significantly deviating from zero at P = 0.05 and P = 0.01 level, respectively. Biological yield (g) Harvest index (%) S 2 d S 2 d X b X b 23.15 1.36 93.50 + + 27.69 1.36* 61.32 + 26.30 1.37 65.61 22.57 1.13 41.38 + 25.03 1.90** 79.22 + + 24.59 0.18** 53.85 + 25.08 0.23** 102.11 + 26.63 0.50* 27.04 27.08 0.80 96.89 22.56 0.35** 45.87 + 28.63 0.93 109.15 22.46 0.98 22.43 25.21 1.25 131.09 + + 24.10 0.87 9.62 23.53 1.21 77.86 + 23.32 0.55* 7.09 27.33 1.08 114.08 21.58 0.82 11.29 23.25 1.97** 129.26 + + 26.44 1.03 53.92 + + 27.46 1.30 87.98 22.54 0.42* 23.22 30.84 2.17** 89.17 + + 22.24 1.42* 28.52 26.74 1.42* 82.34 + 25.89 0.26** 35.38 + + 23.98 0.94 29.56 + 24.45 0.80 114.75 + + 18.67-0.24 29.64 + 26.75 0.87 54.73 18.29 0.58* 47.49 + 25.28 0.76 66.47 + + 22.97 0.51* 52.93 + 27.48 0.76 82.04 + 22.56 0.36** 24.44 24.84 0.79 9.14 20.83 0.63* 68.77 + + 24.71 1.62* 44.50 19.27 0.32** 31.06 + 25.08 1.63** 25.83 + 20.60 0.07** 45.79 + + 21.76 1.27 49.13 + + 25.67-0.03 140.55 + + 22.41 0.90 37.38 + 27.88 1.09 9.30 23.67 1.46* 18.76 28.40 0.92 12.82 28.73 1.15 7.02 28.66 0.91 62.16 29.27 1.08 33.52 27.75 2.03** 197.86 22.74 1.96** 6.30 + 28.11 1.43* 64.24 25.33 1.60* * 44.36 + + 24.96 0.74 88.85 21.56 0.71 17.36 23.39 0.62* 74.36 28.32 0.97 3.55 28.21 1.17 19.41 29.10 1.08 68.00 25.49 0.86 33.64 29.92 0.98-0.13 21.54 0.43** 48.08 25.35 1.16 34.44 + + 20.84 1.16 79.4 27.87 1.06 3.16 13.99 0.58* 9.30 22.91 0.84 30.12 + 21.42 0.49** 45.96 23.66 0.77* 8.47 20.46 0.77 45.89 32.80 1.11 171.08 26.67 2.63** 202.27 28.93 0.08** 360.86 + + 21.20 1.39* 7.92 29.04 0.99 169.64 19.00 1.29 39.46 24.12 1.29 180.50 + + 25.00 3.07** 82.11 27.60 2.90** 18.79 + 23.97 25.35 3.24 2.93
component in respect to these traits although nonlinear component pooled deviation was also found to be significant. The predominance of linear component would help in predicting the performance of the genotypes across the environments. This also suggested that the prediction for these characters would be perfect. Variance due to pooled deviations from regression was highly significant for all the characters which indicated that the prediction of the response of the genotypes on the basis of regression analysis for these characters might not be very reliable. According to Eberhart and Russells criteria of stability, a stable genotype should have higher mean than population mean, b= 1 and S 2 d= 0, but for days to 50% flowering and maturity, the desirable and stable genotype could have low mean, b= 1 and S 2 d= 0. For days to 50% flowering and days to maturity the genotypes KM-2239 and KM-2241 respectively, were considered as desirable and stable. Considering high mean performance and stability parameters together KM-2194, KM-2224, KMU-27, KMU-32, KMU-41, KMU-42 and KMU-55 were considered as desirable and stable for seed yield. (Table 2). Genotypes having lower mean values than the population mean with below average stability were KM-2197, PDM-11 and PM-5. Another group of genotypes with lower mean than the population mean with above average stability are PDM-54, PDM-139, Pusa-9531 and NDM-3-11. These Vol. 37, No. 3, 2014 257 genotypes can be used in hybridization programme to develop high yielding and stable variety of mungbean. These genotypes with lower mean values on one hand and higher mean values on the other show two genetically diverse groups of stable genotypes which can be used as genetically diverse and stable parents in hybridization programme to develop high yielding and stable variety of mungbean. It was concluded from the results that the genotypes, IPM-99-125, KM-2241, HUM-8, KMU-34, Type-44 for number of primary branches and the genotypes KM-2241, PDM-11 and Pusa Ratna for number of pods per cluster were screened as desirable and stable genotypes. Similarly, the genotypes KM-2224, KM-2239, HUM-8 and PDM- 54 for number of pods per plant and genotypes IPM- 3-1, KM-2194, MUM-2, HUM-2 and Samrat for pod length were screened as desirable and stable genotypes. Likewise KM-2197, KM-2241, HUM-2, Pusa Vishal, KMU-27, KMU-32 and KMU-42 were screened desirable and stable genotypes for biological yield. Similar to the present results Yadav and Kumar (1983), Patel and Narkhede, 1995 and Patel et al., 1998 also arrived at similar conclusion regarding the stability of seed yield and its component characters. On the basis of their mean performance (mean± S.E.), certain genotypes have been identified as important genetic donors (Table 3) which can be used in further breeding programme. Further, Characters TABLE 3: Important genetic donor identified from germplasm for different characters. Important genetic donors Days to 50% flowering (< 48.75 days) KM-2239, PM-5, IPM-3-3, KMU-41, NDM-1, IPM-3-1, KM-2241, KM-2224, NDM- 3-11, HUM-15, K-851. Days to maturity (< 58.42 days) HUM-8, KM-2241, KMU-55, KMU-41, HUM-2, HUM-2, HUM-6, KM-2197. Plant height (cm) (> 65.21 cm) PDM-139, PDM-11, Pusa-9531, NDM-1, Type-44, KM-2197, KM-2241 No. of primary branches (> 2.17) KM-2195, IPM-99-125, KMU-34, Type-44, HUM-8, HUM-6, KM-2224, PDM-139, KM-2241 No. of pods per cluster (> 4.96) HUM-8, KMU-36, KM-2241, HUM-6, HUM-2, PDM-11, Pusa Ratna, HUM-14, KMU-32 No. of pods per plant (> 10.23) KM-2197, KM-2239, KM-2224, KMU-42, Pusa-9531, Pusa Ratna, HUM-8, HUM- 14, PDM-54, KMU-38, KMU-36 No. of seeds per pod (> 8.75) KM-2241, KMU-32, KMU-61, KM-2197, KM-2195, HUM-2, KM-2224 Pod length (cm) (> 6.27 cm) KMU-41, KMU-55, KM-2194, NDM-1, IPM-3-1, Samrat, MUM-2, HUM-2, HUM-6, S-9, KM-2239 100 seed weight (> 4.23 g) KM-2194, HUM-6, Pusa Vishal, HUM-2, KMU-55, KMU-32, KMU-36, PDM-11, KMU-42 Seed yield (> 3.07 g) KM-2194, KMU-41, KMU-32, KM-2224, KMU-42, KMU-55, KMU-27, KMU-36, HUM-8 Biological yield (> 13.99 g) HUM-6, KMU-32, KM-2197, KMU-27, KMU-42, KMU-36, Pusa Vishal, KMU-34, HUM-2, KM-2241 Harvest index (> 21.56 %) NDM-3-11, KMU-55, KMU-32, KMU-42, S-9, Pusa Ratna, KMU-27, KMU-44
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