Combining ability analysis for grain yield and its contributing traits in Chickpea (Cicer arietinum L.) under variable environmental conditions

Introduction

Chickpea (Cicer arietinum L.) is one of the oldest domesticated pulse crops, an annual diploid legume ( 2𝑛 = 2𝑥 = 16) of the family Fabaceae that originated in the Fertile Crescent of the Near East (Gowda et al., 2015) [1] . It has two major groups: desi (Microsperma) with small, angular, dark seeds and pigmented plants, and kabuli (Macrosperma) with large, cream-coloured seeds and unpigmented plants (Admas et al., 2021) [2] . Chickpea contains about 22% protein along with minerals, vitamins and dietary fibre, and its regular consumption is associated with benefits against cardiovascular diseases, gastrointestinal disorders, type 2 diabetes and certain cancers (Zhang et al., 2024) [3] . Chickpea contributes about 50% of India's total pulse production. The leading producing states are Maharashtra (25.97%), Rajasthan (20.65%), Madhya Pradesh (18.59%) and Gujarat (10.10%) (Praween et al., 2024) [4] . Combining ability analysis helps identify promising parents and desirable cross combinations for developing improved varieties (Sindhu et al., 2000; Patil et al., 2004) [6,5] , and also reveals the nature of gene action. The present study was therefore undertaken to identify superior parents and cross combinations and to understand the gene action governing grain yield and its contributing traits under different environments.

Materials and methods

The experiment was conducted at the Agricultural Research Station, Sriganganagar, Rajasthan. Eight chickpea genotypes (GNG-1958, GNG-1581, CSG-8962, KWR-108, GNG-1488, H-82-2, Pant G-186 and DCP-92-3) were crossed in an 8 × 8 half diallel without reciprocals. The 36 genotypes (8 parents and 28 F 1 crosses) were evaluated in a randomized block design with three replications during rabi 2025-26 in three environments: timely sown irrigated (E 1 , 1 November), late sown irrigated (E 2 , 25 November) and timely sown under conserved moisture (E 3 , 1 November). Each plot was a single row of 2 m length with 30 cm × 10 cm spacing, and all recommended agronomic practices were followed. Observations were recorded on five randomly selected competitive plants for days to 50% flowering, days to maturity, plant height (cm), primary and secondary branches per plant, pods per plant, seeds per pod, 100-seed weight (g), grain yield per plant (g), harvest index (%) and protein content (%). Combining ability analysis followed Griffing (1956a) [7] , Model I, Method 2.

Results and discussion

Analysis of variance for combining ability (Table 1) showed that GCA and SCA variances were highly significant for all characters in all three environments, except SCA for pods per plant in E 1 and harvest index in E 3 . This indicated the importance of both additive and non-additive gene action in the inheritance of these characters. Environmental effects were significant for all characters. GCA × environment interaction was significant for days to maturity, primary branches per plant, seeds per pod and protein content, and SCA × environment interaction for primary branches per plant. Similar involvement of additive and non-additive gene effects in chickpea was reported by Lakhote et al. (2020) [8] , Malge et al. (2021) [9] , Choudhary et al. (2023a, b) and Quatadath et al. (2024) [10] . The ratio σ 2 gca/σ 2 sca was less than unity for days to 50% flowering (0.27-0.39), days to maturity (0.06-0.29), plant height (0.24-0.68), primary branches per plant (0.07-0.14), grain yield per plant (0.56-0.66) and protein content (0.13-0.51), indicating predominance of non-additive gene action. It exceeded unity for secondary branches per plant (1.35-2.36), pods per plant (1.46-2.52) and 100-seed weight (2.57-2.87), indicating predominance of additive gene action. For seeds per pod (1.27, 0.37 and 0.66) and harvest index (0.37, 0.63 and 1.55), the relative importance of additive and non-additive effects changed from one environment to another. Similar trait-wise differences were reported by Bhardwaj et al. (2009) [11] , Jha et al. (2019) [12] and Saba et al. (2020) [13] . Estimates of GCA effects (Tables 2 and3) showed that no parent was a good general combiner for all the characters studied. GNG-1958 was the most promising general combiner for grain yield per plant (0.74, 0.80 and 0.70 in E 1 , E 2 and E 3 , respectively) and showed significant desirable GCA effects in all environments for days to 50% flowering, secondary branches per plant, pods per plant (3.52, 4.61 and 3.89), 100-seed weight (6.12, 5.86 and 5.74) and harvest index (1.02, 1.01 and 1.13), but it had poor GCA for seeds per pod and protein content. GNG-1488 was a good general combiner for days to maturity, plant height (shorter), primary and secondary branches, pods per plant, seeds per pod, grain yield per plant (0.38, 0.39 and 0.39) and harvest index. Pant G-186 showed desirable GCA for pods per plant, 100-seed weight, grain yield per plant (0.55, 0.43 and 0.47) and harvest index; CSG-8962 for secondary branches and grain yield per plant; and GNG-1581 for primary and secondary branches, pods per plant and seeds per pod, although it was poor for 100-seed weight and protein content. KWR-108 had significant negative GCA effects for days to 50% flowering (-1.82, -1.48 and -2.23), days to maturity and plant height (-6.77, -4.79 and -4.46) and significant positive effects for protein content (0.47, 0.49 and 0.33) in all environments. It can therefore serve as a source of earliness, reduced plant height and protein content, although it was a poor combiner for grain yield and most yield components. DCP-92-3 was a good combiner for early flowering, seeds per pod and protein content, whereas H-82-2 showed no desirable GCA for any character and had significantly negative GCA for grain yield per plant, pods per plant and harvest index. The three best crosses for each character on the basis of SCA effects are given in Table 4, along with the GCA status of their parents; none of the crosses ranked high for all characters. For grain yield per plant, Pant G-186 × GNG-1488 (1.76, 1.83 and 1.83; good × good) and GNG-1958 × GNG-1581 (1.34, 1.76 and 1.18, good × average) recorded positive and significant SCA effects in all three environments. These two crosses were also among the best for pods per plant, secondary branches per plant and harvest index. Pant G-186 × GNG-1488 (5.89, 6.33 and 6.76) and CSG-8962 × Pant G-186 (4.89, 4.51 and 4.44) were significant for pods per plant in all environments, while GNG-1958 × Pant G-186 (3.83, 3.66 and 2.26) and GNG-1958 × GNG-1581 (3.32, 2.53 and 2.68) were the best for harvest index. For 100-seed weight, GNG-1958 × GNG-1581 (2.12, 2.47 and 1.95) and GNG-1958 × H-82-2 (2.53, 1.93 and 1.61) were significant in all environments, and all three best crosses involved the good combiner GNG-1958 with a poor combiner. For earliness, Pant G-186 × H-82-2 had significant negative SCA effects for days to 50% flowering in all environments (-6.24, -3.98 and -4.89), while GNG-1958 × GNG-1581 and GNG-1581 × DCP-92-3 were best for days to maturity. GNG-1958 × KWR-108 and CSG-8962 × DCP-92-3 showed significant negative SCA effects for plant height; GNG-1581 × KWR-108 was the only cross with significant positive SCA for primary branches per plant in all environments (0.56, 0.44 and 0.50); KWR-108 × Pant G-186 was best for protein content (0.85, 0.78 and 0.61); and GNG-1581 × Pant G-186 for seeds per pod (significant in E 2 and E 3 ). Most of the top SCA crosses for grain yield per plant, pods per plant, secondary branches per plant, 100-seed weight and harvest index had at least one good general combiner as a parent (Table 4), indicating the role of additive × additive or additive × dominance interaction in their high SCA effects. In contrast, the best crosses for earliness and plant height mostly involved average × average or poor combiners, pointing to dominance and epistatic (non-additive) effects. The best cross combinations for yield and its components can thus be obtained by crossing at least one parent with good GCA (Lakhote et al., 2020) [8] . Table 1. Analysis of variance (mean squares) for general (GCA) and specific (SCA) combining ability and the ratio σ 2 gca/σ 2 sca in three environments for yield and its contributing traits.

Character

Parent

International Journal of Research in Agronomy

Table 4. Top three crosses for each character on the basis of SCA effects, along with the GCA status of their parents, in three environments. G = good, A = average, P = poor. A parent is good or poor when its GCA effect is significant in the desirable or undesirable direction in at least two environments, and average otherwise. *, ** significant at 5% and 1% levels, respectively. E 1 = timely sown irrigated, E 2 = late sown irrigated, E 3 = timely sown under conserved moisture. Crosses are ranked on the mean SCA effect in the desirable direction.

Character

GCA is attributed to additive gene action and additive × additive interaction, which are fixable, whereas SCA is attributed to non-additive, non-fixable gene action. The predominance of SCA for days to 50% flowering, days to maturity, plant height, primary branches per plant, grain yield per plant and protein content suggests that selection in early segregating generations may be less effective for these characters, whereas the higher GCA variance for secondary branches per plant, pods per plant and 100-seed weight offers greater scope for selection and fixation of desirable alleles. As chickpea is self-pollinated, exploitation of heterosis is not feasible; however, crosses with high SCA involving at least one good general combiner, such as Pant G-186 × GNG-1488 and GNG-1958 × GNG-1581, could produce transgressive segregants in advanced generations if the additive effects of the good combiner and complementary epistatic effects act in the same direction. The significant GCA × environment and SCA × environment interactions further emphasise the need to evaluate promising parents and crosses across environments to identify stable combinations.

Conclusion

Significant GCA and SCA effects for all traits showed that both additive and non-additive gene action govern grain yield and its contributing traits in chickpea, and their magnitude varied across environments. GNG-1958 was the most promising general combiner for grain yield per plant, pods per plant, secondary branches per plant, 100seed weight and harvest index, and KWR-108 for early flowering, early maturity, shorter plant height and protein content. Pant G-186, CSG-8962 and GNG-1488 also showed desirable GCA for several yield-related characters. GNG-1958 × GNG-1581 and Pant G-186 × GNG-1488 had consistently positive and significant SCA effects for grain yield per plant in all three environments. Pant G-186 × H-82-2 (early flowering), GNG-1958 × GNG-1581 and GNG-1581 × DCP-92-3 (early maturity) and KWR-108 × Pant G-186 (protein content) also performed consistently. Non-additive effects predominated for several traits, making early-generation selection less effective for them, whereas additive effects predominated for secondary branches per plant, pods per plant and 100-seed weight. These parents and crosses, evaluated across environments, can be exploited to develop stable, high-yielding and well-adapted chickpea genotypes.

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