Ten varieties of bread wheat, Triticum aestivum L. Thell, namely, Raj 3077, CPAN 3004, HD 2428, Lok-1, Durgapura 65, Raj 1972, Sonalika, HD 2329, HD 2285 and WH 157 were crossed in all possible combinations excluding reciprocals. The 10 parents and their resulting 45 F1's and 45 F2's were grown in a randomized block design with three replications under early (El: 25th October), normal (E2: 20th November) and late (E3: 20th December) sown conditions at Agricultural Research Sub-Station, Tabiji, Ajmer, Rajasthan, India. Plots of parents and F1's consisted of four rows of 3 m length while each plot of F2 consisted of eight rows with the spacing of 30 cm between rows and 15 cm between plants. Twenty competitive plants in parents and F1's and 60 plants in F2 progenies were selected randomly for recording observations on twelve characters viz, days to heading (75%), days to maturity (75%), plant height (cm), flag leaf area (cm2), Tillers per plant, spike length (cm), grain yield per spike (g), grains per spike, 1000-grain weigh (g), harvest index (%), grain yield per plant (g) and protein content (%) under each environment, separately. Six random samples of seeds from each parent and from every cross in both the generations in all the three environments were ground and powder was taken for protein estimation. Nitrogen percent of grain was estimated by micro-Kjeldhal's method and percentage of protein was obtained by multiplying percent nitrogen by the factor 6.25.
The mean of each plot was used for statistical analysis. The
data were first subjected to the usual analysis followed for a randomized block
design for pooled environments as well as for individual environment (Panse
and Sukhatme 1967). The combining ability analysis was done following Method
2, Model 1 of Griffing (1956).
Results and discussion
The mean values for grain yield per plant and protein content of the parents exhibited variability among the parents under all the three environments (Table 1). Similarly, yield contributing traits also exhibited variability over environments indicated that diverse parents were used for present study. The pooled analysis of variance data revealed that in both the F1 and F2 generations significant differences among the genotypes existed and the genotypes also interacted significantly with environments for all the characters studied (Table 2). Significant differences between the environments were also observed, indicating the differences in the effects of environments on the expression of characters in both the generations. Genotype x environment interaction was significant for each of the character in both F1 and F2 generations, indicating existence of non-linear response of genotypes of the varying environments. This is in conformity with the earlier reports of Allard and Bradshow (1964). In view of significant genotype x environment interaction for all the characters, the analysis of variance for individual environment was done for all the characters in all the three environments. The environment wise analysis of variance data revealed that significant differences existed among the parents as well as F1's and F2's for all the characters in all the three environments (sowing dates). The mean squares for parents vs F1's and parents vs F2's were also significant for most of the traits in different environments.Combining ability analysis depicted that both general combining ability (gca) and specific combining ability (sca) variances were significant for all the characters in both the generations indicating the importance of additive and non-additive gene effects on the character expression (Table 3). The ratio between gca and sca variances titled in favor of general combining ability indicating the preponderance of additive gene effects in the genetic control for all the characters, except for flag leaf area (F1 E3), number of tillers per plant (F2 E2), grains per spike (F1 E3), and 1000-grain weight (F1 E1; F1 and F2 E2), which indicated that these characters were primarily controlled by non-additive components of genetic variance. Results further exhibited that both gca and sca effects were not very consistent in different environments for most of characters in both the generations. The findings of Singh and Rana (1987), Pokhrel et al. (1993), Menon and Sharma (1995), Bhavasar et al. (1996) and Menon and Sharma (1997) are in agreement with the present results.
Both gca and sca exhibited highly significant interaction with the environments for grain yield and its components in both non-segregating (F1) and segregating (F2) generations, indicating the role of environment in influencing the gene effects, which further complicated the problem of identification of promising parents and crosses. Other studies (Dasgupta and Mandol 1988; Menon and Sharma 1994, 1997) substantiate this point. However, gca x environment interaction variances were higher than sca x environment variances for almost all the traits, further signifying the importance of additive genetic variance for yield components. Thus, it may be concluded that the variances due to gca is by and large more important in a crop like wheat.