Analysis of combining ability in maize inbred lines from line X tester mating design under stress situation

Introduction

Maize (Zea mays L.) is one of the most important cereal crops worldwide because of its high productivity, broad adaptability, and diverse utilization It belongs to the family Poaceae, tribe Maydeae, and has a chromosome number ofn = 20. The crop originated in Central America and wa domesticated nearly 9,years ago from its wild ancestor, teosinte (Zea mays ssp. parviglumis). As a monoecious and predominantly cross pollinated species, maize possesses enormous genetic diversity, making it suitable for cultivation under a wide range of agro-climatic conditions Globally, maize is cultivated for food, feed, fodder, and industrial purposes. The grain is extensively utilized in the manufacture of starch, ethanol, biofuels, pharmaceuticals, and numerous processed food products. The development of specialty maize types, including Quality Protein Maize (QPM), sweet corn, baby corn, popcorn, and waxy corn, has further enhanced its economic importance. Owing to its high genetic yield potential and versatility, maize continues to play a significant role in ensuring food, nutritional, and livelihood security. According to recent estimates, maize is cultivated on approximately 199 million hectares worldwide, producing about 1.13 billion tonnes of grain with an average productivity of 5.82 t ha ¹⁻ (Anonymous, 2024) [1] . In India, maize occupies approximately 12.84 million hectares, producing 46.15 million tonnes with an average productivity of 3.60 t ha ¹⁻. Karnataka is one of the leading maize-producing states, where the crop is grown on nearly 1.90 million hectares, yielding 6.35 million tonnes with an average productivity of 3.34 t ha ¹⁻ (Anonymous, 2025-26).

Among the various abiotic constraints affecting maize productivity, drought is considered the most severe, particularly in tropical and subtropica regions where the crop is largely cultivated under rainfed conditions. Water deficit during flowering and grain-filling stages significantly reduces pollination efficiency, kernel set, and ultimately grain yield (CIMMYT, 1999; Edmeades et al., 2001) [2,3] . Global estimates indicate that drought account for yield losses ranging from 15-20% annually, depending on the severity and duration of moisture stress. Therefore, the development of droughttolerant maize hybrids remains a major objective of modern breeding programmes. The development of superior inbred lines forms the foundation of successful hybrid breeding. Wellcharacterized base populations possessing broad genetic diversity are essential for developing elite inbred lines with enhanced yield potential and tolerance to environmental stresses (Prashanth, 2008) [4] . The success of hybrid breeding largely depends on the identification of parents with superior combining ability capable of producing highly productive and stable hybrids Combining ability analysis is an effective breeding tool for understanding the genetic control of economically important traits and for identifying desirable parental combinations. The line × tester mating design proposed by Kempthorne (1957) is widely employed to estimate general combining ability (GCA) and specific combining ability (SCA) effects. General combining ability primarily reflects additive gene action, whereas specific combining ability is associated with non-additive gene effects, including dominance and epistasis (Falconer, 1964) [5] . Knowledge of GCA and SCA facilitates the selection of superior parental lines and efficient hybrid combinations for exploitation in maize improvement programmes. The exploitation of heterosis through single-cross hybrids has substantially enhanced maize productivity worldwide. Single-cross hybrids generally exhibit superior vigour, greater uniformity, higher yield potential, and improved adaptability compared with open-pollinated varieties and composite populations. Their enhanced physiological efficiency and genetic constitution enable them to tolerate adverse environmental conditions, particularly drought stress, more effectively than conventional cultivars (Anonymous, 2009) [6] . Consequently, the identification of high-performing hybrids with desirable combining ability under both stress and non-stress environments is essential for developing resilient maize cultivars. Keeping these considerations in view, the present investigation was undertaken to evaluate the combining ability of 30 maize inbred lines and five testers using a line × tester mating design under stress and nonstress conditions. The study aimed to identify superior general and specific combiners for grain yield and its associated traits, and to identify promising hybrid combinations suitable for future maize hybrid development programmes.

Materials and Methods

The present investigation was conducted at the Main Agricultural Research Station (MARS), Dharwad, Karnataka, India (15°25′ N latitude, 70°25′ E longitude; 678 m above mean sea level) during the kharif, rabi, and summer seasons of 2011-12, 2012-13, and 2013-14. Meteorological data, including rainfall and minimum and maximum temperatures recorded throughout the crop growth period, were obtained from the station's meteorological observatory and are presented in Appendix I. During the evaluation period (rabi 2013-14), the mean minimum and maximum temperatures ranged from 16.00 to 30.87 °C, and a total rainfall of 11.40 mm was recorded.

Development of Experimental Hybrids

Early-generation screening of inbred lines was undertaken to identify suitable parental material for combining ability analysis using the line × tester mating design. A total of 200 maize inbred lines were initially evaluated, and the best 30 lines were selected based on superior grain yield (mean + 1 SD), reduced anthesis-silking interval (ASI; mean -1 SD), and a higher number of cobs per plant (mean + SD). These selected inbred lines were crossed with five testers during the summer season (3 April 2013), resulting in the development of 150 F₁ single-cross hybrids. After harvest, hybrid seeds were properly processed, dried, and stored under suitable conditions until field evaluation.

Field Evaluation

The 150 F hybrids, together with 35 parental lines and standard commercial checks, were evaluated during early spring 2013 (11 December 2013)₁ under drought stress conditions. The experiment was laid out in a Restricted Randomized Block Design (RBD) with two replications. Each experimental plot consisted of a single 4 m row with an inter-row spacing of 75 cm and a plant-to-plant spacing of 20 cm. To impose moisture stress, all experimental entries received irrigation only up to 30 days after sowing. Thereafter, irrigation was withheld unti harvest, allowing the crop to experience water deficit during the critical flowering and grain-filling stages. All other recommended agronomic and crop management practices were followed uniformly throughout the experimental period.

Data Recording

Observations were recorded from five healthy and competitive plants selected at random in each replication for every genotype. Data were collected for the following traits: days to 50% anthesis, days to 50% silking, anthesis-silking interval (ASI), plant height (cm), ear height (cm), days to maturity, cob length (cm), cob girth (cm), number of cobs per plant, number of kernel rows per cob, number of kernels per row, shelling percentage, 100-grain weight (g), grain yield per plant (g), relative water content (RWC), and chlorophyll content. The mean value of each trait for every genotype was used for statistical analysis.

Statistical Analysis

The experimental data were subjected to line × tester analysis following the method proposed by Kempthorne (1957). The total genetic variation among the hybrids was partitioned into components attributable to general combining ability (GCA) and specific combining ability (SCA) to estimate the relative importance of additive and non-additive gene effects governing the studied traits. All statistical analyses were performed using WINDOSTAT version 8.0 software.

Results and Discussion

The ANOVA in respect of all the characters studied on hybrids under stress situation are presented in Table 1. The mean sum of squares for crosses were significant for four traits viz. chlorophyll at 90 days, relative water content at 60 days, number of kernel rows per cob and grain yield per plant under stress. Further, under stress condition, lines showed significant differences for days to 50 per cent anthesis, days to 50 per cent silking, chlorophyll at 90 days, relative water content at 60 days, relative water content at 90 days, plant height, ear height, cob length, number of kernels per row and 100-seed weight. The testers under stress situation, they revealed significant differences for chlorophyll at 60 days, relative water content at 90 days, plan height, ear height, number of kernel rows per cob, grain yield per plant and grain yield kg/ha. The interaction between lines and testers under stress situation the interaction was significant for number of kernel rows per cob and grain yield per plant. under stress situation SCA variance was higher than the GCA variance for most of the traits except days to 50 per cent anthesis, days to 50 per cent silking, anthesis to silking interval (ASI), chlorophyll at 60 days, relative water content at 60 days, relative water content at 90 days, plant height, ear height, Number of cobs per plant and 100-seed weight. This revealed the preponderance of non-additive gene effects over the additive gene effects as most of the GCA/SCA ratios were less than unity for all traits under stress situation. The proportional contribution of lines to total variation was higher than the testers in all of the traits under stress situation. The results of the interaction between line x tester were higher fo all the traits under stress situation.

The GCA effects of 30 lines and 5 testers for various characters is presented in Table 2. GCA effects of lines for days to 50 per cent anthesis ranged from -2.87 (Rajkumar × CML446 Inbredline 3) to 1.73 (NK6240 × CI4 Inbredline 18) and -0.22 (HS4) to 0.16 (HS10) for testers, three out of 30 parents showed significant GCA effects, two parents viz., Rajkumar × CML446 Inbredline 38 (-1.77) and Rajkumar × CML446 Inbredline 3 (-2.87) showed GCA effects in negative direction. GCA effects of lines for days to 50 per cent silking ranged from -2.3 (Rajkumar × CML446 Inbredline 3) to 2.1 (NK6240 × CI4 Inbredline 18) and -0.10 (HS4) to 0.16 (HS10) fo testers, four out of 30 parents showed significant GCA effects, three parents viz., Rajkumar × CML446 Inbredline 38 (-1.60), G57 × NAC6002 Inbredline 25 (-1.80) and Rajkumar × CML446 Inbredline 3 (-2.30)

showed GCA effects in negative direction. GCA effects of lines for ASI ranged from -0.53 (Allrounder × HS17 Inbredline 21) to 0.77 (NK6240 × HS17 Inbredline 20) and -0.18 (HS7) to 0.13 (CI4) for testers. One out of 30 parents showed significant GCA effects viz., NK6240 × HS17 Inbredline 20 (0.77) in positive direction. GCA effects of lines for days to maturity ranged from -2.55 (NK6240 × CI4 inbredline 37) to 2.35 (NK6240 × HS17 Inbredline 22) and -0.25(HS7) to 0.18 (HS10) for testers, three out of 30 parents showed significant GCA effects, one parent viz., NK6240 × HS17 Inbredline 22 (2.35) showed positive GCA effects, whereas two parents viz., NK6240 × CI4 Inbredline 35 (-1.85) and NK6240 × CI4 inbredline 37 (-2.55) showed GCA effects in negative direction. GCA effects of lines for chlorophyll content at 60 days ranged from -2.49 (Rajkumar × CML446 Inbredline 46) to 2.56 (Allrounder × HS17 Inbredline 25) and -1.73(KDMI16) to 1.61 (HS4) for testers, two out of 30 parents showed significant GCA effects one parent viz., Allrounder × HS17 Inbredline 25 (2.56) showed positive GCA effects, Among the testers, HS4 (1.61) exhibited significant positive GCA effects. GCA effects of lines for chlorophyll content at 90 days ranged from -5.34 (G57 × NAC6002 Inbredline 25) to 6.10 (Parbhat × CI4 Inbredline 5) and -1.47 (HS7) to 0.40 (HS10) for testers, seven out of 30 parents showed significant GCA effects, three parents viz., Allrounder × HS17 Inbredline 39 (3.41), Rajkumar × CML446 Inbredline 18 (3.60) and Parbhat × CI4 Inbredline 5 (6.10) showed positive GCA effects. GCA effects of lines for relative water content at 60 days ranged from -0.113 (G57 × NAC6002 Inbredline 25) to 0.075 (Rajkumar × CML446 Inbredline 1) and -0.009 (KDMI16) to 0.011 (HS7) for testers, six out of 30 parents showed significant GCA effects, two parents viz., NK6240 × HS17 Inbredline 20 (0.068) and Rajkumar × CML446 Inbredline 1 (0.075) showed positive GCA effects. GCA effects of lines for relative water content at 90 days ranged from -0.086 (Rajkumar × CML446 Inbredline 8) to 0.072 (Allrounder × HS17 Inbredline 34) and -0.022 (CI4) to 0.036 (HS7) for testers, two out of 30 parents showed significant GCA effects, one parent viz., Allrounder × HS17 Inbredline 34 (0.072) showed positive GCA effects. Among testers HS7 (0.036) showed significant positive GCA effects. GCA effect of lines and testers for plant height ranged from -23.41 (Rajkumar × CML446 Inbredline 8) to 20.33 (Rajkumar × CML446 Inbredline 1) and -5.95 (CI4) to 4.31 (HS10), respectively. three out of 30 parents exhibited significant GCA effect among them, two is in positive direction viz., NK6240 × HS17 Inbredline 10 (12.28) and Rajkumar × CML446 Inbredline 1 (20.33) and one are in negative direction viz., Rajkumar × CML446 Inbredline 8 (-23.41). Among testers CI4 (-5.95) exhibited significant GCA effect in negative direction. GCA effect of lines and testers for ear height ranged from -17.42 (Rajkumar × CML446 Inbredline 8) to 10.87 (NK6240 × HS17 Inbredline 14) and -5.44 (CI4) to 6.91 (HS10), respectively. one of the line viz., NK6240 × HS17 Inbredline 14 (10.87) showed GCA effect in positive direction, The lines viz., Rajkumar × CML446 Inbredline 38 (-10.87) and Rajkumar × CML446 Inbredline 8 (-17.42) showed GCA effect in negative direction However, among testers, HS10 (6.91) showed significant GCA effect in positive direction and CI4 (-5.44) showed significant GCA effect in negative direction.

GCA effect of lines and testers for cob length ranged from -1.98 (G57 × NAC6002 Inbredline 17) to 1.87 (Rajkumar × CML446 Inbredline 3), -0.43 (KDMI16) to 0.43 (HS7), respectively. Six of the lines viz., Rajkumar × CML446 Inbredline 18 (1.20), NK6240 × HS17 Inbredline 5 (1.27), NK6240 × CI4 Inbredline 12 (1.40), NK6240 × HS17 Inbredline 22 (1.45) and Rajkumar × CML446 Inbredline 3 (1.87) showed GCA effect in positive direction. The GCA effect of lines and testers for cob girth ranged from -0.24 (Rajkumar × CML446 Inbredline 25) to 0.24 (Allrounder × HS17 Inbredline 25) and -0.05 (KDMI16) to 0.05 (HS7), respectively. Two of the lines viz., NK6240 × HS17 Inbredline 14 (0.20) and Allrounder × HS17 Inbredline 25 (0.24) showed GCA effect in positive direction. The GCA effect of lines and testers for number of kernel rows per cob ranged from -0.89 (NK6240 × HS17 Inbredline 22) to 1.18 (Rajkumar × CML446 Inbredline 38) and -0.45 (HS7) to 0.27 (CI4), respectively. Three lines viz., NK6240 × CI4 inbredline 37 (0.78), G57 × NAC6002 Inbredline 25 (0.92) and Rajkumar × CML446 Inbredline 38 (1.08) showed GCA effects in positive direction. The GCA effect of lines and testers for number of kernels per row ranged from -3.80 (G57 × NAC6002 Inbredline 17) to 3.56 (NK6240 × CI4 Inbredline 12) and -0.24 (HS10) and 0.41 (HS7), respectively. Five out of 30 lines viz., Rajkumar × CML446 Inbredline 18 (2.92), Rajkumar × CML446 Inbredline 3 (3.42), NK6240 × HS17 Inbredline 22 (3.526), NK6240 × HS17 Inbredline 5 (3.529) and NK6240 × CI4 Inbredline 12 (3.56) showed positive GCA effect. The GCA effect of lines and testers for Number of cobs per plant ranged from -0.07 (Parbhat × CI4 Inbredline 5) to 0.16 (Rajkumar × CML446 Inbredline 8) and -0.006 (HS10) and 0.007 (KDMI16), respectively. Two out of 30 lines viz., NK6240 × HS17 Inbredline 22 (0.161) and Rajkumar × CML446 Inbredline 8 (0.162) showed positive GCA effect. The GCA effect of lines and testers for 100-seed weight ranged from -3.06 (Rajkumar × CML446 Inbredline 25) to 2.33 (NK6240 × CI4 Inbredline 12) and -0.22 (HS10) to 0.56 (HS7), respectively. Two out of 30 lines viz., NK6240 × CI4 inbredline 37 (2.15) and NK6240 × CI4 Inbredline 12 (2.33) showed positive GCA effect. The GCA effect of lines and testers for grain yield per plant ranged from -11.37 (Rajkumar × CML446 Inbredline 8) to 13.93 (Rajkumar × CML446 Inbredline 18) and -7.79 (HS10) to 6.98 (HS7), respectively. One out of 30 lines viz., Rajkumar × CML446 Inbredline 18 (13.93) showed positive GCA effect. Among testers HS7 (6.98) showed significant GCA effect in positive direction. The GCA effect of lines and testers for grain yield (kg/ha) ranged from -682 (Allrounder × HS17 Inbredline 21) to 515.05 (Rajkumar × CML446 Inbredline 18) and -254.05 (KDMI16) to 261.30 (HS7), respectively. None of the lines showed GCA effect in positive direction among testers HS7 (261.30) showed significant GCA effect in positive direction. The GCA effect of lines and testers for shelling percentage ranged from -6.31 Allrounder × HS17 Inbredline 25) to 4.57 (Rajkumar × CML446 Inbredline 25) and -0.77 (KDMI16) and 1.29 (HS7), respectively. One out of 30 lines viz., Rajkumar × CML446 Inbredline 25 (4.57) showed GCA effect in positive direction. The specific combining ability effects of 150 crosses are presented in Table16. SCA effects for days to 50 per cent anthesis ranged from -3.86 (Allrounder × HS17 Inbredline 21) × HS7 to 3.73 (NK6240 × CI 4 Inbredline 18) × HS7. Two hybrids viz. compared to that of variance due to GCA for all the characters under stress. The ratio of GCA to SCA variance was much below unity indicating preponderance of nonadditive gene effects in the inheritance of all traits under study for stress situation. The predominance of non-additive gene action for most of the growth and productivity traits have been reported by Sharma et al. (2004) [12] , Sandhu et al. (2006) [13] , Singh et al. (1983) [14] , Paul and Duara (1991) [15] , Sedhom (1994) [16] , Mohammad (1993) [17] and Satyanarayana et al. (1994) [18] . Whereas, Olaoye (2005) [19] and Aminu and Izge (2013) [10] reported predominance of both GCA and SCA for most of the traits under stress and non-stress situations. These results also in agreement with Rojas and Sprague (1952) [20] and Gama et al. (1995) who worked on millet and maize respectively. These results exhibited that parental lines would be utilized in the development of maize hybrids. Exploitation of hybrid vigour has gained much significance in view of enormous higher yield in hybrids, which is the only way to harness the predominant non-additive gene action The contribution of lines to total variances was higher than testers for most of the traits which signifies the prevalence of high diversity among the lines used for this investigation. This is mainly attributed to the enormous diversity in different source populations from which these lines have been derived. The contribution of either lines or tester revealed the importance of specific contribution for expression of all the traits studied in hybrids. Similar observations were also reported by Kadlubiec et al. (2000) [21]

, Ramesh et al. (2000) [22] , Rosa et al. (2000) [23] , Mandal et al. (2001) [24] and Sandhu et al. (2006) [13] . A high GCA effect for specific trait in a parent indicates presence of additive gene effects for that trait. When parents possessing high GCA effects were combined by hybridization, a large proportion of progenies would have high value for the trait concerned facilitating easy selection for that trait. In the present study, a score was given based on the GCA effects of the parents (Table 15). The total score of each parent across the characters was worked out for the classification of parents as high or best combiner and low or poor combiner (Thenmozhi, 1983) [25] under stress situation, among the lines, Rajkumar × CML446 inberdline 18 exhibited maximum positive GCA effect for quantitative traits with a pooled score for GCA effects of +4 and proved itself as a potential general combiner. this was followed by NK6240 × HS17 inberdline 22 with poo score of +and NK6240 × HS17 inberdline 20, NK6240 × HS17 inberdline 14, NK6240 × HS17 inberdline 5, NK6240 × CI4 inberdline 18, NK6240 × CI4 inberdline 12 with pool score of +for GCA effects. Among the testers, HS7 recorded pool score of +4 indicating its superiority for utilization in hybridization programme. Generral combining ability effects of selected triats. The results of these triats presented in (Table 2). Under stress none of the parents recorded significant GCA effects in desirable direction. Anthesis silking interval is a trait used mostly in screening genotypes for tolerance to stresses (EL-Hosary et al., 1994) [26] . It is a measure of nicking (synchronization) of pollen shed with silking as reported by Paul and Debenth (1999) [27] and (Olaoye et al., 2005) [19] . For number of cobs per plant three parents viz., NK6240 × CI4 inberdline 24, Allrounder × HS17 inberdline 34 and NK6240 × CI4 inberdline 12 exhibited significant GCA effects in desirable direction. Among testers, under stress situation, two parents viz., NK6240 × HSinberdline 22 and Rajkumar × CML446 inberdline 8 exhibited significant GCA effects in desirable direction The GCA effects for grain yield per plant Rajkumar × CML446 inberdline exhibited significant GCA effect in desirable direction under stress. Among testers HS7 exhibited significant GCA effect in desirable direction under stress situation. The parents with a high GCA effects for traits could produce superior segregants in F₂ as well as in later generations. Significant GCA effects in desirable direction for most of the quantitative traits Therefore, these parents could be utilized in a hybridization programme for selection of superior recombinants. These findings are in accordance with Mandal et al. (2001) [24] , Malik et al. (2004) [28] , Koinuma et al. (2004) [29] , Fan et al. (2004) [30] , kanta et al. (2005), Prashanth (2008) [4] , Kuchanur (2010) [31] , Premlatha and Kalamani (2010) [9] , Izge and Dugje (2011) [32] , Aminu and Izge (2013) [10] and Praveen Kumar et al. (2014) [33] The estimates of specific combining ability effects for traits in maize under stress situation are presented in Table 16. These estimates are used to identify the best crosscombinations for hybrids production (Izge et al., 2007) [34] Among 150 hybrids evaluated, 45 and 30 hybrid combinations recorded positive score under stress situation, across triats, indicating them as heterotic hybrids for these traits. under stress situation, among hybrids viz. (Allrounder × HS17 Inberdline 45) × HS10 and (Parbhat × CI4 Inberdline 5) × HSexhibited maximum positive GCA effect for quantitative traits with a pooled score for sca effects of +and (NK6240 × HS17 Inberdline 22) × KDMI16 (Allrounder × HS17 Inberdline 34) × HS7 and (Allrounder × HS17 Inberdline 25) × HS7 recorded a positive score of +for sca effects. However, under stress for chlorophyll content at 60 days, relative water content 90 days and shelling percentage 29 hybrid combinations were found to be inferior with negative score for sca effects across traits under stress. 91 hybrid combinations scored zero under stress, because of cancellation positive and negative significant sca effects for different characters. Such hybrids may also be considered as heterotic hybrids depending on the importance of productivity trait with positive significant sca effects (Table 16). The study revealed that hybrids with high SCA effects involved at least one or two of the several higher general combiners as parent. Gama et al. (1995), Kadams et al. (1999) [35] Asif et al. (2007) [8] , Kuchanur (2010) [31] , Premlatha and Kalamani (2010) [9] , Aminu and Izge (2013) [10] and Praveen Kumar et al. (2014) [33] reported similar result where a hybrid with high SCA effects involved one or both of the good general combiners as parents. Specific combining ability effects of selected triats. The results of these triats presented in (Table 2). Under stress situation, the hybrids viz. (Rajkumar × CML446 Inberdline 40) × KDMI16 and (NK6240 × CIInberdline 12) × CIexhibited significant sca effects in negative direction. Negativity of these traits is important, implying that these hybrids could mature earlier and could escape drought. Similar results were reported by Bello and Olaoye (2009) [36] , Kuchanur (2010) [31] and Aminu and Izge (2013) [10] . Under stress situation, the hybrid viz. (Allrounder

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