Indian Journal of Agricultural Research

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Indian Journal of Agricultural Research, volume 56 issue 1 (february 2022) : 7-11

Combining Ability of Selected Soybean [Glycine max (L.) Merrill] Parental Lines

Gbemisola O. Otusanya1,2,*, G. Chigeza1, S. Chander1,3, A.T. Abebe1, O.O. Sobowale2, D.K. Ojo1,2, M.O. Akoroda4
1International Institute of Tropical Agriculture, PMB 5320, Ibadan 200 001, Nigeria.
2Department of Plant Breeding and Seed Technology, Federal University of Agriculture, PMB 2240, Abeokuta, Nigeria.
3Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar-125 004, Haryana, India.
4Department of Crop Production, University of Ibadan, Nigeria.
Cite article:- Otusanya O. Gbemisola, Chigeza G., Chander S., Abebe A.T., Sobowale O.O., Ojo D.K., Akoroda M.O. (2022). Combining Ability of Selected Soybean [Glycine max (L.) Merrill] Parental Lines . Indian Journal of Agricultural Research. 56(1): 7-11. doi: 10.18805/IJARe.A-638.
Background: The success of hybridization programme depends on the combining ability of parental lines.

Methods: Seven soybean genotypes and all their partial diallel crosses in the F2 generation were evaluated in a randomized complete block design at two locations in Nigeria, during the 2017-2018 growing season. 

Result: Analysis of variance showed that both environments and genotypes were significantly different for all measured traits. The genotype TGx 1988-5F was the best general combiner for earliness in flowering and poding, while TGx 1448-2E was the best general combiner for number of pods/plant and seed yield/plant. Crosses having significant and positive specific combining ability effect for number of pods/plant and seed yield/plant were TGx 1485-1D × TGx 1448-2E and TGx 1988-5F × TGx 1989-19F, respectively. Genotypes TGx 1988-5F and TGx 1448-2E exhibiting good general combining ability for earliness and seed yield/plant, are thus, promising for utilization in the future hybridization programme for soybean improvement.
Soybean [Glycine max (L.) Merrill] is one of the most important leguminous and oilseed crop in the world (Mikic and Peric, 2013). According to Agarwal et al., (2013), soybean contributes to about 26.7% of the global vegetable oil production and about two thirds of the world’s protein concentrate for livestock feeding. Its richness in oil (20%) and protein (40%) content makes it an ideal crop to alleviate protein malnutrition in developing world (Bhartiya et al., 2018). Parent selection is one of the most critical aspects of any breeding programme, as its success depends directly on this step (deAlmeidaLopes et al., 2001).
Diallel analysis formulated by Griffing (1956) helps breeders to evaluate newly developed cultivars for their parental usefulness and to assess gene action controlling inheritance of yield and its contributing traits in order to formulate efficient breeding programme (Susanto, 2018). Also, diallel crossing analysis is an excellent tool, which provide breeders with information on general and specific combining ability of parents and their hybrids (Nassar, 2013). According to Kearsey (1965), half diallel which involves a set of progeny and their parents have advantage over the other diallel techniques, because it provides the maximum information about genetic architecture of parents and traits. The use of Diallel analysis, excluding reciprocals for analyzing combining ability of soybean for yield and its related traits across environments have been reported by various authors (Paschal and Wilcox, 1975; Kaw and Menon, 1981; Cho and Scott, 2000).
Combining ability analysis is used to identify better parents, which can be hybridized to select better crosses for further breeding work (Murtadha et al., 2018). Combining ability study in soybean revealed significant estimated general and specific combing ability for yield and related traits (Agrawal et al., 2005; Gaviloli and Perecin, 2008; Abd El and Nassar, 2013). Aims of the study were to identify the best general combiners in soybean for measured traits and estimate the extent of additive and non-additive gene actions in-order to derive implications for further improvement of the populations generated from the crosses across environments.
Seven soybean parental lines (TGx 1989-19F, TGx 1987-10F, TGx 1988-5F, TGx 1987-62F, TGx 1835-10E, TGx 1448- 2E, TGx 1485-1D) obtained from the soybean breeding program of the International Institute of Tropical Agriculture (IITA) selected for various desirable traits (Table 1) were used for the crossing. To generate the F1s, crossing was attempted among the seven selected parental lines (all are released varieties) in all possible combinations without reciprocals (partial diallel). The resulting 21 F1 populations were further advanced to F2. All the F2s along with their parents were planted in the field at IITA, Ibadan (Longitude 7°30'N, Latitude 3°54'E) and Fashola (Longitude 6°49'N, Latitude 3°16'E) in Oyo State, Nigeria, during 2017 and 2018 growing season in a randomized complete block design (RCBD) with three replications. Each block was divided into 28 plots each measuring 2 m × 0.75 m and a distance of 0.75 m was allocated between blocks and plots. The number of rows for each plot was four rows with two harvestable middle rows and an intra and inter-row spacing of 10 cm and 75 cm, respectively.

Table 1: Characteristics of soybean varieties used in the study.

Standard agronomic practices, like weeding, fertilizer application and pest management were done during the entire growing period. Data for five quantitative traits viz. days to flowering, days to poding, plant height, number of pods/plant and seed yield/plant were measured on forty randomly selected plants. Harvesting and threshing were done manually. Combining ability analysis after Griffing (1956) Method II, Model I using DIALLEL-SAS (Zhang and Kang, 1997) was performed.
Combined analysis of variance of partial diallel crosses of soybean for yield and yield-related traits across locations revealed that the two environments were significantly different from each other (Table 2). Entries (parents and crosses) were significantly different from each other for all the traits studied, indicating sufficient genetic variability among the parents and crosses generated (Kose, 2019). Significant interaction between environment and entries was observed in all the measured traits, except for number of pods/plant and seed yield/plant. There were significant general combining ability (GCA) effects across environments for almost all the measured traits, except for days to poding. Similarly, the specific combining ability (SCA) effects across environments were significant for days to poding, number of pods/plant and seed yield/plant, exhibiting that variability in the breeding material can be attributed to both additive and non-additive gene effects. Highly significant GCA × environment interactions for almost all the measured traits showed that the performance of parents used in the study was influenced by environment and thus, testing under different environments will ensure selection of stable parents that can perform to the potential of that environment (Machado et al., 2009).

Table 2: Pooled analyses of variance of soybean for yield and yield-related traits in Ibadan and Fashola.

Greater magnitude of GCA compared to SCA was observed for all measured traits, which reveals the prevalence of additive gene action, indicating and that selection will be effective to improve the traits (Gravina et al., 2004; Nazim et al., 2014). The GCA: SCA ratio close to unity for all measured traits showed that the parents contributed mostly to the performance of the crosses observed, and influence of the environment was minimal and thus, there is preponderance of additive gene action controlling traits studied (Murtadha et al., 2018). Adsul et al., 2016 reported that additive gene action was found predominant in the inheritance of 100-seed weight and yield/plant in segregating population of soybean. Also, Umar et al., (2017) reported the importance of additive gene action in inheritance of days to 50% flowering, days to maturity, number of pods/plant and 100-seed weight. Nassar (2013) also observed high GCA: SCA ratio for earliness and number of pods/plant in soybean.
The estimates of GCA effects of parental lines used in the study across Ibadan and Fashola (Table 3), revealed that TGx 1988-5F had desirable negative and significant GCA effect for days to flowering and poding. The parent TGx 1448-2E gave significant and positive GCA effect for number of pods/plant and seed yield/plant, showing the importance of this parent in improving these traits. Soybean parental lines with significant GCA have been reported by Durai and Subbalakshmi (2009). Good GCA in soybean for yield and its related traits have also been reported earlier by Srivastava et al., (1978) and Sharma and Phul (1994).

Table 3: Pooled GCA effects of parental genotypes used in partial diallel crosses of soybean for yield and yield-related traits across Ibadan and Fashola.

The SCA effects of the cross TGx 1835-10E × TGx 1989-10F was negative and significant and desirable for days to flowering (Table 4). Two crosses, TGx 1988-5F × TGx 1989-19F and TGx 1485-1D × TGx 1835-10E exhibited significant and positive SCA effects for days to poding. Significant good specific combining ability for reduced plant height was observed in cross TGx 1987-62F × TGx 1988-5F. Crosses having positive and significant SCA effects for number of pods/plant are TGx 1988-5F × TGx 1987-10F and TGx 1485-1D × TGx 1448-2E. Significant and positive SCA effect for seed yield/plant was observed in the cross TGx 1988-5F × TGx 1989-19F. Datt et al., (2011) have also reported crosses with good SCA for earliness and grain yield/plant in soybean. Crosses showing good specific combining ability for traits studied have either parent as good or average combiners. According to Kenga et al., (2004), cross combinations with favorable SCA estimates and involving at least one of the parents with good GCA estimate would likely enhance the concentration of favorable alleles to improve traits of interest.

Table 4: Estimates of SCA effects of soybean crosses for yield and yield-related traits across Ibadan and Fashola.

Parental varieties of soybean used in the study had higher GCA than SCA showing preponderance of additive gene action controlling seed yield and its related traits. Hence, selection for measured traits at early growth of segregating populations might be effective. As evidenced by their significant GCA effects, the parental line TGx 1988-5F can be used to improve earliness, while TGx 1448-2E can be used to improve seed yield in soybean breeding program.
Authors thank the technical staff of soybean breeding unit, IITA, Ibadan, Nigeria.

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