Combining ability analysis for yield and its components in Indian mustard [Brassica juncea (L.) Czern & Coss] using half diallel

Introduction

India, as the largest agrarian subcontinent, supports 26% of the world's agricultural population on just 12% of the global arable land. It is the fifth largest vegetable oil economy, contributing 7.4% to global oilseed production, 5.8% to oil production, 6.1% to oil meal production, and accounting for 9.3% of the world's edible oil consumption (Jat et al., 2019) [6] . Oilseeds represent the second most significant segment of India's agricultural economy, following cereals, with an annual growth rate of 4.1% over the past three decades. Among oilseeds, brassica species cover 23.5% of the cultivation area and contribute 24.2% to the total oilseed production in the country (Jha et al., 2012) [11] . Despite being the third largest producer of oilseed brassica globally, after Canada and China, India relies on imports for 57% of its domestic edible oil needs and ranks as the seventh largest importer of edible oils. Although oilseed brassica production has seen considerable growth in India, productivity remains low due to extensive rainfed cultivation, biotic and abiotic stresses, and resource limitations (Sharma, 2014) [16] . The regions where mustard is cultivated in India exhibit a vast range of agro-climatic conditions, with different species of rapeseed-mustard grown across various parts of the country (Kumar et al., 2023) [8] . Indian mustard (Brassica juncea) is a naturally autogamous species, yet in this crop frequent outcrossing occurs which varies from 5 to 30% depending upon the environmental conditions and frequency of pollinating insects. Cytologically Indian mustard is an amphidiploid (2n=36), derived from interspecific cross of Brassica rapa (2n=20) and Brassica nigra (2n=16). Seed quality, seed yield and other yield related parameters of Brassica oil seed crop has been tried to improve by several researchers for international acceptance, erucic acid content should be <2%. As applied different strategies for improving seed yield and quality attributed of Brassica. Gami and Chauhan (2013) [4] and Patel et al. (2013) [15] have also reported difference types of gene action and combining abilities in different sets of material studies.

The limited and steadily declining natural resources (land and water), and competition from agriculture and nonagricultural sector, jeopardized the scope to increase the acreage under oilseeds (Fischer and Connor, 2018) [3] . In such a situation, increase in yield levels through translational scientific interventions is a conceivable alternative to increase the production and edible oil availability (Joshi, 2004; Kumar et al., 2022) [12,10] . To investigate the inheritance of quantitative traits and evaluate various breeding procedures in the context of heterosis, a comprehensive study of combining ability is crucial (Vaghela et al., 2011; Kumar et al., 2018; Kaur et al., 2019) [22, 9, 19] . Combining ability refers to the capacity of parental genotypes to combine during hybridization and transmit desirable genes to their offspring. It is categorized into general combining ability (GCA) and specific combining ability (SCA). GCA reflects the average performance of a genotype across a series of hybrid combinations, while SCA pertains to cases where certain hybrid combinations perform better or worse than expected based on the average performance of the parental inbred lines. Studies on combining ability have highlighted the predominance of GCA effects on yield and most yield components, underscoring the importance of additive gene action. Conversely, provided evidence for significant SCA effects on yield and yield components, indicating the relevance of non-additive gene action. Singh (2005) [20] noted that both additive and non-additive genetic effects contribute to yield heterosis. The diallel mating design has been extensively utilized to analyze combining ability effects in B. napus L. genotypes, offering insights into the genetic mechanisms controlling seed yield and other traits. This approach can be leveraged for hybrid development, and populations can be studied through intensive selection in segregating generations. In light of the described situation, the present study aimed to evaluate: a) the mean performance of parental genotypes and their F1 hybrids, b) the general and specific combining ability effects in parental genotypes and their specific F1 hybrids.

Materials and Methods

Breeding material consisted of eight varieties of Indian mustard namely, Rohini, Vardan, PM-22, Pusa Tarak, PM-26, RLM-619, CS-54, and RH-749 along with two checks viz., GM-2 and Vardan. These varieties of Indian mustard were subjected to diallel fashion mating design (excluding reciprocals) during Rabi 2021-22. The experimental material comprising of 38 treatments viz., (8 parents + 28 F1's and 2 checks) was evaluated in RBD with three replications during Rabi 2022-23. Each parent and F1's planted in one row of 5 m long 45cm apart; plant to plant distance was maintained 15 cm by thinning. All the recommended agronomic practices were adopted for raising a healthy crop. Uniform cultural practices, as recommended, were applied throughout the growing season to all genotypes to minimize field variations and environmental influences.

Traits Measurement and Statistical Analysis

Data were collected on 10 randomly selected plants from the central two rows on a single plant basis for plant height and yield traits, including main raceme length, 1000-seed weight, and seed yield per plant. All recorded data were subjected to analysis of variance (ANOVA) to test the null hypothesis of no differences between parental means and their F1 populations. Upon finding significant differences among the parental genotypes and their F1 hybrids for various traits, the data were further analyzed for combining ability as outlined by (Jinks and Hayman. 1953) [22] , Griffing's approach-Griffing (1956) [23] Method-I, based on Eisenhart's Model-II, to assess genetic variances due to general combining ability (GCA) and specific combining ability (SCA).

Results and Discussion

Analysis of variance

The analysis of variance was carried out with respect to all the characters to test the significance of differences among various treatments is depicted in Table 1. The mean squares due to treatments were found highly significant for all the thirteen traits. The variance due to replications were found non-significant for all the traits. The results were in accordance with Patel et al. (2013) [15] and Arifullah (2013) [1] . Highly significant differences were recorded among the treatments for all the characters namely, days to flowering, days to maturity, plant height, number of siliquae per plant, number of branches per plant, seed yield per plant, test weight, harvest index and oil content (Table 1).

GCA and SCA Effects

The analysis of variance for combing ability indicated that variances due to GCA and SCA were highly significant for all the characters. The general combining ability (gca) effects of the parents are presented in Table 2, 3 and 4, which revealed that possibilities to pick out a good general combiner for all the traits was lesser because the combining ability effects of the parents were not consistent for all the yield contributing traits. For days to 50 percent flowering, general combining ability effects (gca) with negative values are desirable. Among parents, P3 (-2.08), P4 (-2.73), P5 (-1.58) and P7 (-3.67) exhibited significant and negative gca effects for days to 50 percent; P3 (-11.46), P4 (-12.00), P5 (-7.66) and P7 (-3.93) found to be a good general combiner for days to maturity; P2 (0.18), P4 (0.69) and P7 (0.48) for 1000 seed weight; P1 (1.16), P5 (1.2), P6 (1.05), P7 (0.43) and P8 (0.67) for biological yield; P2 (2.86) and P8 (2.42) for harvest index; P1 (0.60 and P7 (0.64) for oil content; P4 (0.25), P5 (0.16) and P6 (0.49) for primary branches per plant; P2 (0.07), P4 (0.18), P6 (0.55) and P7 (0.42) for secondary branches per plant; P1 (3.51), P2 (2.68), P6 (4.13) and P8 (3.47) for plant height; P3 (0.28), P5 (0.72) and P6 (1.91) for seeds per siliqua; P2 (0.33), P4 (35.63), P5 (0.34) and P7 (0.07) for number of siliqua per plant; P3 (0.34), P7 (2.31) and P8 (3.92) for siliqua on main raceme and P3 (0.34), P7 (2.31) and P8 (3.92) for seed yield per plant. The gca and SCA ratio was less than unity for all the traits except days to flowering, plant height and harvest index. This indicated that non-additive component played more roles in inheritance of these characters. The non-additive type of gene action was also found in mustard by Gami and Chauhan (2013) [4] . The parents mentioned above had high general combining ability and fixable component of gene action additive could be successfully exploited by developing homozygous line have used for improved character for which improvement was desired. These parental lines might be utilized for producing the intermatting population in order to get desirable recombinants in Indian mustard. In mustard Singh et al. (2005) [20] , Kirti et al., (2022) [7] , Patel et al. (2013) [15] and Gami and Chauhan (2013) [4] also reported result in this fashion with different parent. The promising direct crosses exhibiting significant SCA effects in desirable direction maybe incorporated in future mustard improvement programme. The specific combining ability is associated with interaction effects, which may be due to dominance and epistatic components of genetic variation that are non-fixable in nature. The maximum significant and positive sca effects in desirable direction are presented in Table 3. SCA effect is an estimate for making selection of best cross combinations. High SCA denotes, undoubtedly a high heterotic response, however this, does not mean high performance of the hybrids as well. However, it can say that in majority of cases, the crosses revealing high sca effects were found to have one or both of the parents as good general combiner for the traits under study.

The results are in agreement with the findings by different authors viz., Vaghela et al. (2011) [22] , Maurya et al. (2012) [13] , Gami and Chauhan (2014) [5] and Thanmichon et al. (2018) [20] , Singh et al. (2019) [18] and Choudhary et al. (2020) [2] . These hybrids could be further evaluated to exploit the heterosis after identifying suitable hybrid seed production technology and in future breeding programme by utilizing biparental mating or recurrent selection breeding approaches to obtain desirable segregants for development of further superior genotypes for seed yield and its component traits.

Conclusion

The present investigation employed a half-diallel crossing design to explore the potential for improving yield and related traits in Indian mustard (Brassica juncea L.). The analysis of variance revealed significant variations among treatments for all studied traits, highlighting the presence of substantial genetic diversity within the parental lines. The mean performance data further emphasized this point, demonstrating a wide range of variation for each trait across parents and their hybrids. GCA analysis identified specific parental lines with consistently positive effects for various traits. These lines, such as P3, P4, P5, and P7 for early flowering and maturity or P2, P4, and P7 for increased seed weight, can be employed strategically in breeding programs to enhance specific traits in offspring. SCA analysis revealed promising cross combinations exhibiting significant positive effects for several traits. These crosses, like P1 X P7 for earlier flowering, P1 X P4 for increased seed weight, and P4 X P5 for enhanced biological yield, represent valuable breeding material for exploiting heterosis and developing superior mustard varieties.

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