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Studies on Components of Genetic Variance, Combining Ability and Heterotic Response in Rice (Oryza sativa L.) Through Morphological and Molecular SSR Markers

S
Siddheshwar Ravsaheb Korake1
S
Shiv Prakash Shrivastav1,*
H
Harmanpreet Kaur1
R
Rahul Singh1
Y
Yashpal Singh B. Yadav2
1Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Phagwara-144 001, Punjab, India.
2Department of Genetics and Plant Breeding, College of Agriculture Saralgaon, Murbad, Thane-421 401, Maharashtra, India.

ABSTRACT

Background: The experiment was conducted to evaluate the potential and limitations of using variance components and combining ability in establishing heterotic patterns in rice (Oryza sativa L.). Understanding genetic variability, heterosis and combining ability effects is crucial for identifying suitable parental lines and hybrids that can contribute to sustainable hybrid rice breeding programmes.

Methods: Thirteen quantitative and qualitative traits were studied in parents and their twenty-four F1 hybrids. Analysis of variance was performed to assess genetic variability. General combining ability (GCA) and specific combining ability (SCA) were estimated to identify promising parents and crosses. Heterobeltiosis and standard heterosis were measured relative to PR-26 (SV1) and Pusa Basmati 1121 (SV2). A total of seventy-one SSR markers were employed to assess parental polymorphism among the crosses, with polymorphic markers identified for molecular validation.

Result: Highly significant variations were observed among parents and hybrids, indicating broad genetic variability and the potential for genetic improvement in rice. For most traits, SCA variance exceeded GCA variance, suggesting the predominance of non-additive gene action. Parents such as PUSA 1509, HUR 105 and Sambha-Sub-1 showed significant and positive GCA effects for grain yield per plant and yield-contributing traits, highlighting their usefulness in hybridization. Among the twenty-four F1s, three crosses displayed positive and significant SCA effects for grain yield per plant. Wide variation in heterobeltiosis and standard heterosis, both positive and negative, was noted across traits. The top five F1s identified for heterotic potential were PUSA 1509 × IR-64-Sub-1, Sambha-Sub-1 × HUR 105, JGL 384 × HUR 105, PUSA 1509 × HUR 105 and Sarjoo-52 × HUR 105. Out of seventy-one SSR markers tested, six showed polymorphism supporting parental diversity assessment. These findings demonstrate the usefulness of combining ability and heterosis analysis in establishing heterotic patterns essential for hybrid rice improvement.

INTRODUCTION

Rice (Oryza sativa L.) is the most important staple food crop in the world. Asia is the leading region in rice production, accounting for about 90% of global output. India has the largest area under rice cultivation, covering 46.38 million hectares, which constitutes 28.26% of the world’s rice-growing area and ranks second in total production with 130.29 million tonnes, next to China, with an average productivity of 2,809 kg ha-1 (Anonymous, 2021-22). About 75% of the world’s rice supply is consumed by people in Asian countries; thus, rice is of immense importance to Asia’s food security. The demand for rice is expected to increase continuously with the growth of the global population.
       
The development of hybrid rice varieties in India faces several obstacles, including insufficient genetic diversity, unstable heterosis, difficulties in maintaining seed purity, high production costs and limited farmer adoption. In addition, regulatory constraints, resource limitations and intellectual property issues pose significant challenges. To overcome these problems, coordinated efforts are required to strengthen research, innovation and adoption of hybrid rice technology.
       
To address the above-mentioned issues, a thorough understanding of gene action, combining ability and heterotic response is essential in rice hybrid breeding. Therefore, there is a strong need to conduct integrated studies using both conventional and biotechnological approaches in rice improvement. These include selective breeding to elucidate gene action and select desirable traits, hybridization to exploit heterosis and develop superior progenies and marker-assisted selection to accelerate the breeding process by identifying plants carrying genes of interest. Furthermore, genome-editing tools enable precise manipulation of gene expression, while quantitative trait loci (QTL) mapping helps identify genomic regions associated with complex traits. Screening of diverse germplasm and the application of genomic selection enhance breeding programs by broadening genetic diversity and improving predictive accuracy, ultimately leading to the development of high-yielding, resilient rice varieties suited to sustainable agricultural production and global food security.

MATERIALS AND METHODS

Experimental site and development of materials
 
The study was conducted at the main experimental station of Lovely Professional University, Punjab, India (31°14′ 29.6″N, 75°41′46.9″E). The experimental material consisted of a line × tester set comprising twenty-four F1 hybrids developed by crossing eight female lines (HUR 1309, PR 121, PUSA 1509, PR 13, JGL 384, Sarjoo 52, Sambha Sub-1 and Pusa Basmati 1) with three male testers (IR-64-Sub-1, Sabhagi and HUR-105) during Kharif 2022. In total, thirty-seven genotypes, including twenty-four F1s, eleven parents and two standard checks (PR-26 and Pusa Basmati 1121), were evaluated in Kharif 2023 using a randomized complete block design with three replications. The objective was to estimate gene action, genetic variance components, combining ability and heterosis in rice.
       
Observations were recorded for thirteen morphological traits: days to 50% flowering, flag leaf area, plant height, panicle-bearing tillers per plant, panicle length, spikelets per panicle, grains per panicle, spikelet fertility, biological yield per plant, harvest index, L/B ratio, thousand-grain weight and grain yield per plant.
       
For molecular characterization, seventy-one SSR markers were initially screened to assess parental polymorphism and ensure genome-wide coverage. Only six markers exhibited clear and reproducible polymorphism and were selected for hybrid purity testing. The low polymorphism percentage reflects the narrow genetic base of elite rice germplasm. However, hybrid purity testing requires only parent-specific polymorphic loci rather than genome-wide diversity assessment; thus, a limited number of informative SSR markers is sufficient. The six selected markers, distributed across different chromosomes, produced distinct co-dominant banding patterns that enabled differentiation between male and female parents. The presence of both parental alleles in F1 plants confirmed their hybrid status. Previous studies have similarly reported that a small set of highly informative SSR markers is adequate for reliable hybrid purity testing in rice (Table 1).

Table 1: List of primers used in fingerprinting of hybrids with their information.


 
Statistical analysis
 
Line × tester analysis was performed following the method of Kempthorne (1957) and further elaborated by Arunachalam (1974) to estimate general combining ability (GCA) and specific combining ability (SCA) variances and effects. Heterosis was calculated as the percentage deviation of F1 means over the better parent (heterobeltiosis) as per Fonseca and Patterson (1968) and over the standard variety (economic heterosis) following Meredith and Bridge (1972). Significance was tested using critical difference values corresponding to heterosis estimates.
       
Genomic DNA was extracted from 10-15-day-old seedlings using the CTAB method of Doyle et al. (1990) with minor modifications. DNA was diluted to 40 ng/µL and stored at 4°C, with stock samples preserved at -20°C.
       
PCR amplification using six SSR markers was performed  in a 10 µL reaction mixture containing template DNA, primers, Taq polymerase, MgCl‚  with buffer, dNTPs and nuclease-free water. The thermal profile included initial denaturation at 95°C (5 min), followed by 35 cycles of denaturation (94°C, 1 min), annealing (55°C, 1 min) and extension (72°C, 1 min), with final extension at 72°C for 7 min. Amplified products were resolved on 5% polyacrylamide gels stained with ethidium bromide and visualized under UV light. Product sizes were determined using 50 bp and 100 bp DNA ladders.

RESULTS AND DISCUSSION

Estimates of components of genetic variance
 
The estimates of combining ability variances, average degree of dominance, predictability ratio, additive and dominance variances, heritability in narrow sense and genetic advance in percent of mean have been presented (Table 2). Estimates of sca variance were higher than the corresponding estimates of gca variance for all the thirteen traits except flag leaf area, plant height and panicle bearing tillers in F1s. For each attribute, the average level of dominance varied from 0.31 to 2.43. Values less than unity (<1) imply partial dominance or additive gene activity, while values greater than unity (>1) show the predominance of over-dominance. A number of economically significant traits, including days to 50% flowering (1.04), panicle length (1.31), grains per panicle (1.11), spikelet fertility (1.74), harvest index (2.43) and 1000-grain weight (1.12), showed over-dominance, indicating that non-additive gene effects are important in the inheritance of these traits. This explains why a number of F1 hybrids showed a high heterotic response to these features. A number of economically significant traits, including days to 50% flowering (1.04), panicle length (1.31), grains per panicle (1.11), spikelet fertility (1.74), harvest index (2.43) and 1000-grain weight (1.12), showed over-dominance, indicating that non-additive gene effects are important in the inheritance of these traits. This explains why a number of F1 hybrids showed a high heterotic response to these features. Similar findings have also been reported by earlier researchers AL Mamun (2011); Rajpoot et al. (2017); Singh et al. (2019); Bhattacharjee et al. (2020) and Shrivastav et al. (2022).

Table 2: Components of genetic variance, average degree of dominance, predictability ratio, heritability in narrow sense and genetic advance in per cent of mean for 13 characters in rice.


       
The predictability ratio was less than 0.50 for most traits, including days to 50% flowering (0.48), grains per panicle (0.45), spikelet fertility (0.25), harvest index (0.14) and 1000-grain weight (0.44), confirming the predominance of non-additive gene action for these traits. However, comparatively higher predictability ratios were recorded for panicle bearing tillers per plant (0.91), plant height (0.89) and flag leaf area (0.76), indicating a greater role of additive genetic variance. These traits are therefore amenable to improvement through selection in early generations. The L/B ratio exhibited a predictability ratio greater than unity (1.40), which may be attributed to sampling error or low variance estimates, suggesting instability in additive variance estimation for this trait.
       
Heritability in narrow sense [h2(ns)] have been classified by Johnson et al., (1955) into three categories viz., high (>30%), medium (10-30%) and low (<10%). Some characteristics demonstrated moderate to high narrow-sense heritability, while having more SCA variance than GCA variance, which suggests non-additive gene action predominates. The GCA-SCA comparison shows the relative amount of additive and non-additive effects in particular cross combinations, while heritability assesses the fraction of additive variation compared to overall phenotypic variance, hence this seeming contradiction is not contradictory. Thus, it is possible for both dominant and additive effects to function concurrently. Higher SCA variance suggests the significance of dominance and epistasis for heterosis expression, whereas significant additive variance explains the moderate to high heritability. Consequently, a combination of selection and hybrid breeding techniques can enhance these characteristics. Among the traits ranging from -30.31% to 88.56%. High heritability estimates were recorded for panicle bearing tillers per plant (88.56%), plant height (86.42%), flag leaf area (73.74%), biological yield per plant (56.77%), spikelets per panicle (52.59%), grain yield per plant (50.27%), days to 50% flowering (46.44%), grains per panicle (44.29%) and 1000-grain weight (41.43%), indicating a substantial contribution of additive genetic variance and effectiveness of selection for these traits. Moderate heritability was observed for spikelet fertility (23.98%), panicle length (18.66%) and harvest index (13.40%), suggesting that selection for these traits should be practiced in later generations. The negative narrow-sense heritability observed for L/B ratio (-30.31%) was due to negative additive genetic variance (σ2A = -0.02) and very low gca variance (σ2g = -0.01). Such negative estimates are generally considered as zero heritability and arise from environmental effects or sampling errors rather than true negative inheritance, indicating limited scope for improvement of this trait through direct selection. Similar results have been reported by Yadav et al. (2011); Rajpoot et al., (2017); Yadav et al. (2020); Kumar et al., (2020) and Kumar et al. (2026).
 
Estimates of combining ability effects
 
The estimates of general combining ability (gca) effects in respect of eleven parents (eight lines and three testers) for the thirteen characters have been set out (Table 3). The lines, PUSA 1509 (4.75) and Sambha Sub-1 (2.19) in F1s possessed significant and positive gca effects for grain yield per plant. Similar results have been reported Sankar et al., (2008); Latha et al. (2013); Kargbo et al. (2019); Ghidan et al. (2019) and Abd El-Aty (2022). The lines, Pusa basmati 1 (-5.91) in F1s recorded negative and significant gca effects for grain yield per plant. Among the testers HUR 105 (2.81) recorded significant and positive gca effects, whereas Sabhagi (-2.80) exhibited significant and negative gca effect in F1s for grain yield per plant and IR-64-Sub-1 (-0.01) had negative and non-significant gca effect in F1s.

Table 3: Estimates of general combining ability (gca) effects of F1s parents (lines and testers) for 13 characters in rice.


       
The estimates of specific combining ability effects for twenty-four crosses of line×tester set for thirteen characters are presented (Table 4). Three crosses emerged with positive and significant sca effects for grain yield per plant viz., PUSA 1509 × IR-64-Sub-1 (7.12), Sambha Sub-1× Sabhagi (4.13) and Pusa basmati 1 × IR-64-Sub-1 (3.79). The undesirable negative and significant sca effects for grain yield per plant were exhibited by four crosses in F1s. Similar observations were made by Sai et al. (2025).

Table 4: Estimates of specific combining ability (sca) effects of crosses (F1s) for 13 characters in rice.


 
Gene action
 
The grain yield per plant (g) for various rice crosses was analyzed, with significant specific combining ability (SCA) effects observed. The cross PUSA 1509 × IR-64-Sub-1 exhibited the highest SCA effect of 7.12 and a mean performance of 47.33 g per plant, categorized under high × low (H×L) general combining ability (GCA) effects. Another notable cross, Sambha Sub-1 × Sabhagi, showed an SCA effect of 4.13 with a mean performance of 39.00 g per plant, falling under low × low (L×L) GCA effects. Similarly, the cross Pusa Basmati 1 × IR-64-Sub-1 recorded an SCA effect of 3.79 and a mean performance of 34.67 g per plant, also categorized under L×L GCA effects are presented (Table 5). Earlier studies have found in similar result Fasahat et al. (2016); Nyombe (2017) and Bhattacharjee et al. (2020).

Table 5: Most promising cross combinations for different characters along with their mean performance, sca effects and gca effects of parents in F1s.


 
Estimates of heterosis over better-parent and standard variety
 
Heterosis was estimated as a per cent increase or decrease of F1 value over better-parent (BP) and standard variety (SV) viz., PR 26 (SV1) Pusa basmati 1121 (SV2). The estimates of heterobeltiosis and standard heterosis for thirteen characters are presented (Table 6). For grain yield per plant, the heterosis over better-parent varied from -28.23% (Pusa basmati 1 × Sabhagi) to 91.89% (PUSA 1509 × IR-64-Sub-1). Eighteen crosses showed positive and significant heterosis over BP and the best five among them were PUSA 1509 × IR-64-Sub-1 (91.89%), PUSA 1509 × HUR 105 (83.03%), Sarjoo 52 × HUR 105 (68.25%), Pusa basmati 1 × HUR 105 (58.46%) and JGL 384 × HUR 105 (48.15%). The standard heterosis for grain yield per plant ranged from -7.73% (Pusa basmati 1 × Sabhagi) to 107.97% (PUSA 1509 × IR-64-Sub-1) over SV1 and from -8.87% (Pusa basmati 1 × Sabhagi) to 105.41% (PUSA 1509 × IR-64-Sub-1) over SV2. Eighteen crosses showed positive heterosis and the top five were PUSA 1509 × IR-64-Sub-1 (105.41%), Sambha Sub-1x HUR 105 (85.16%), JGL 384 × HUR 105 (73.59%), PUSA 1509 × HUR 105 (72.14%) and Sarjoo 52 × HUR 105 as well as Sambha Sub-1 × Sabhagi (69.25%). Earlier studies have found similar results Sankar et al., (2008); Sai et al. (2025) and Chintala et al. (2026).

Table 6: Extent of per cent heterosis over better parent (BP) and two standard varieties (SV1 and SV2) of F1s for 13 characters in rice.


 
Hybrid purity testing of rice using SSR molecular markers
 
Only six of the seventy-one SSR markers showed polymorphism among the parental lines, indicating low molecular diversity due to the narrow genetic base of elite rice germplasm. Similar low to moderate polymorphism has been reported in earlier rice studies. Despite limited variability, these informative markers were sufficient for parental discrimination and reliable F1 hybrid purity confirmation. A list of six polymorphic markers is presented. These polymorphic markers were used to check the true F1 hybrids of the crosses (Fig 1). SSR marker RM122 showed polymorphism on the cross HUR 1309 × IR-64-Sub-1, PR 121 × IR-64-Sub-1, PUSA 1509 × IR-64-Sub-1, Sarjoo 52 × IR-64-Sub-1 and Pusa basmati 1 × IR-64-Sub-1. SSR marker RM6887 exhibited polymorphism in the crosses HUR 1309 × Sabhagi, PR 121 × Sabhagi, PR 13 × Sabhagi, Sarjoo 52 × Sabhagi and Sambha Sub-1 × Sabhagi. Polymorphism was observed with SSR marker RM3253 in the combinations JGL 384 × HUR-105, Sarjoo 52 × HUR-105 and Sambha-Sub-1 × HUR-105. The crosses PUSA 1509 × IR-64-Sub-1, JGL 384 × IR-64-Sub-1 and Sambha-Sub-1 x IR-64-Sub-1 displayed polymorphism with SSR marker RM168. SSR marker RM3271 revealed polymorphism across the crosses HUR 1509 × Sabhagi, JGL 384 × Sabhagi and Pusa basmati 1 × Sabhagi. In the crosses HUR 1309 x HUR-105, PR 121 x HUR-105, PUSA 1509 × HUR-105, PR 13 × HUR-105 and Pusa basmati 1 × HUR-105 SSR marker RM3291 showed polymorphic patterns and true F1 hybrids of these crosses. Similar results of genetic purity testing of rice were reported by Shashibhushan et al. (2021).

Fig 1: Molecular profiling of rice hybrids.


       
The prevalence of non-additive gene action was suggested by the larger SCA variance than GCA variance for the majority of variables, indicating that hybrid breeding would be more successful than direct selection for increasing rice grain production. While crosses like PUSA 1509 × IR-64-Sub-1 and Sambha Sub-1 × HUR 105 shown strong heterosis and SCA effects, making them ideal candidates for hybrid creation, parents like PUSA 1509, HUR 105 and Sambha Sub-1 emerged as good general combiners. Through selective breeding, traits like plant height and tiller number that are controlled by additive effects can be enhanced. These findings support previous research showing the significance of heterosis and non-additive gene activity in increasing rice production, demonstrating the value of combining ability analysis to find superior parents and hybrids. Similar findings were reported by Kumar et al. (2026).

CONCLUSION

The present investigation highlighted the significance of genetic variance components, combining ability and heterotic response in rice improvement. The predominance of non-additive gene action indicated by higher SCA variance suggests the potential of hybrid breeding in enhancing yield and related traits. Promising parents such as PUSA 1509, HUR 105 and Sambha Sub-1 exhibited strong GCA effects, while crosses like PUSA 1509 × IR-64-Sub-1 and Sambha Sub-1 × HUR 105 showed high heterotic potential. The SSR markers further validated parental polymorphism and hybrid purity. Overall, this study provides valuable insights for establishing heterotic patterns, thereby strengthening strategies for sustainable hybrid rice breeding.

ACKNOWLEDGEMENT

The School of Agriculture and the experimental facilities at Lovely Professional University, Punjab, India, are much appreciated by the authors for carrying out this study. The authors express their gratitude to all academic members, technical staff and colleagues for their invaluable advice, support and help with data processing, laboratory work and field experiments. The assistance obtained for statistical analysis and molecular analysis is also appropriately recognized.
 
Disclaimer
 
The opinions and findings presented in this study are entirely the authors’ own and may not represent the official positions of the associated organizations or institutions. The integrity and correctness of the data used in this study are the responsibility of the authors. If there are any mistakes or omissions, they are not deliberate. The writers or their institutions do not advocate or encourage the use of trade names, commercial goods, or particular equipment.
 
Informed consent
 
Informed consent was not applicable for this study as it did not involve human participants or animals. The research was conducted on plant materials under field and laboratory conditions in accordance with institutional and ethical guidelines.

CONFLICT OF INTEREST

Regarding the publishing of this research work, the authors affirm that they have no conflicts of interest. The authors attest that the study, data analysis and paper preparation were not impacted by any financial or personal ties.

REFERENCES


  1. Abd El-Aty, M.S., Abo-Youssef, M.I., Galal, A.A., Salama, A.M., Salama, A.A., El-Shehawi, A.M. and El-Tahan, A.M. (2022). Genetic behavior of earliness and yield traits of some rice (Oryza sativa L.) genotypes. Saudi Journal of Biological Sciences. 29(4): 2691-2697.

  2. AL Mamun, S.A. (2011). Characterization and Genetic Diversity for Agronomic Traits in Exotic Rice (Doctoral Dissertation, Bangabandhu Sheikh Mujibur Rahman Agricultural University).

  3. Anonymous. (2021-22). Director of Economics and Statistics, Department of Agriculture, Cooperation and Farmers Welfare (DAC and FW).

  4. Arunachalam, V. (1974). The fallacy behind the use of modified line × tester design. Indian Journal of Genetics and Plant Breeding. 34(2): 200-207.

  5. Bhattacharjee, M., Majumder, K., Kundagrami, S. and Dasgupta, T. (2020). Evaluation of recombinant inbred lines for higher iron and zinc content along with yield and quality parameters in rice (Oryza sativa L.). Indian Journal of Agricultural Research. 54(6): 724-730. doi: 10.18805/IJARe.A-5454.

  6. Chintala, S., Babu, P.R., Babu, J.D.P., Rao, V.S., Jayalalitha, K. and Siva, M. (2026). Identification of elite parents and study of heterosis for important yield traits in rice: Combining ability and heterosis in rice. Oryza-An International Journal of Rice. 63(1). https://epubs.icar.org.in/index. php/OIJR/article/view/147012.

  7. Doyle, J.J., Doyle, J.L., Brown, A.H. and Grace, J.P. (1990). Multiple origins of polyploids in the Glycine tabacina complex inferred from chloroplast DNA polymorphism. Proceedings of the National Academy of Sciences. 87(2): 714-717.

  8. Fasahat, P., Rajabi, A., Rad, J.M. and Derera, J.J.B.B.I.J. (2016). Principles and utilization of combining ability in plant breeding. Biometrics and Biostatistics International Journal. 4(1): 1-24.

  9. Fonseca, S. and Patterson, F.L. (1968). Hybrid vigor in a seven parent diallel cross in common winter wheat (Triticum aestivum L.). Crop Science. 8(1): 85-88.

  10. Ghidan, W.F., El-Agoury, R.Y. and Hussein, F.A. (2019). Utilization of combining ability and genetic components for yield and its contributing traits of some rice (Oryza sativa L.) genotypes. Journal of Agricultural Chemistry and Biotechnology. 10(12): 257-267.

  11. Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in soybeans. Agronomy Journal. 47: 314-318.

  12. Kargbo, S.S., Showemimo, F., Akintokun, P. and Porbeni, J. (2019). Combining ability analysis and gene action for yield and yield related traits in rice (Oryza sativa L.) under saline conditions. Journal of Plant Breeding and Genetics. 7(2): 63-74.

  13. Kempthorne, O. (1957). The contributions of statistics to agronomy. Advances in Agronomy. 9: 177-204.

  14. Kumar, J., Chand, P., Singh, S.K., Khilari, K. and Kumar, M. (2020). Genetic variability, heritability and genetic advance for yield and its contributing traits in rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry. 9(2): 385-387.

  15. Kumar, S., Jayasudha, S. and Singh, S.K. (2026). Genetic variability, heritability and genetic advance for yield and quality traits in rice (Oryza sativa L.). Indian Journal of Agricultural Research. 60(2): 183-190. doi: 10.18805/IJARe.A-6402.

  16. Latha, S., Sharma, D. and Sanghera, G.S. (2013). Combining ability and heterosis for grain yield and its component traits in rice (Oryza sativa L.). Notulae Scientia Biologicae. 5(1): 90-97.

  17. Meredith, J.W.R. and Bridge, R.R. (1972). Heterosis and gene action in cotton, Gossypium hirsutum L. Crop Science. 12(3): 304-310.

  18. Nyombe, M.M.L. (2017). Genetic Improvement of Grain Yield and Quality in rice (Oryza sativa L.) in South Sudan (Doctoral Dissertation).

  19. Rajpoot, P., Singh, P.K., Verma, O.P. and Tripathi, N. (2017). Studies on genetic variability and heritability for quantitative characters in rice (Oryza sativa L.) under sodic soil. Journal of Pharmacognosy and Phytochemistry. 6(4): 1162-1165.

  20. Sai, R.K., Saraswathi, R., Kumar, M., Raveendran, M. and Robin, S. (2025). Estimation of combining ability and heterosis in TGMS based two-line hybrids of rice (Oryza sativa). The Indian Journal of Agricultural Sciences. 95(2): 133- 139.

  21. Sankar, P.D., Subbaraman, N. and Narayanan, S.L. (2008). Heterosis, combining ability and gene action studies in TGMS based rice hybrids under normal and salt affected environments. Indian J. Agric. Res. 42(3): 177-182.

  22. Shashibhushan, D., Muchanthula, A.R. and Pradeep, T. (2021). Molecular finger printing and genetic purity assessment of a rice hybrid using microsatellite markers. Pharma Innovation. 10(6): 926-929.

  23. Shrivastav, S.P., Verma, O.P., Jakhar, D.S., Singh, V. and Lal, K. (2022). Studies on component of genetic variance and heterotic response in rice (Oryza sativa L.) for high yield with quality and sodicity tolerance. Indian Journal of Genetics and Plant Breeding. 82(4): 419-429.

  24. Singh, S.K., Bindal, S., Singh, A. and Srivastava, S. (2019). Combining ability effects for yield traits in rice (Oryza sativa L.) under sodic soil. Journal of Pharmacognosy and Phytochemistry. 8(1): 281-283.

  25. Yadav, S.K., Pandey, P., Kumar, B. and Suresh, B.G. (2011). Genetic architecture, inter-relationship and selection criteria for yield improvement in rice (Oryza sativa L.). Pakistan Journal of Biological Sciences. 14(9): 540-545.

  26. Yadav, V.P., Singh, P.K. and Verma, O.P. (2020). Genetic variation and heritability for quantitative traits in rice (Oryza sativa L.) under sodic soil. The Indian Journal of Agricultural Sciences. 90(2): 316-319.
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    Full Research Article

    Studies on Components of Genetic Variance, Combining Ability and Heterotic Response in Rice (Oryza sativa L.) Through Morphological and Molecular SSR Markers

    S
    Siddheshwar Ravsaheb Korake1
    S
    Shiv Prakash Shrivastav1,*
    H
    Harmanpreet Kaur1
    R
    Rahul Singh1
    Y
    Yashpal Singh B. Yadav2
    1Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Phagwara-144 001, Punjab, India.
    2Department of Genetics and Plant Breeding, College of Agriculture Saralgaon, Murbad, Thane-421 401, Maharashtra, India.

    ABSTRACT

    Background: The experiment was conducted to evaluate the potential and limitations of using variance components and combining ability in establishing heterotic patterns in rice (Oryza sativa L.). Understanding genetic variability, heterosis and combining ability effects is crucial for identifying suitable parental lines and hybrids that can contribute to sustainable hybrid rice breeding programmes.

    Methods: Thirteen quantitative and qualitative traits were studied in parents and their twenty-four F1 hybrids. Analysis of variance was performed to assess genetic variability. General combining ability (GCA) and specific combining ability (SCA) were estimated to identify promising parents and crosses. Heterobeltiosis and standard heterosis were measured relative to PR-26 (SV1) and Pusa Basmati 1121 (SV2). A total of seventy-one SSR markers were employed to assess parental polymorphism among the crosses, with polymorphic markers identified for molecular validation.

    Result: Highly significant variations were observed among parents and hybrids, indicating broad genetic variability and the potential for genetic improvement in rice. For most traits, SCA variance exceeded GCA variance, suggesting the predominance of non-additive gene action. Parents such as PUSA 1509, HUR 105 and Sambha-Sub-1 showed significant and positive GCA effects for grain yield per plant and yield-contributing traits, highlighting their usefulness in hybridization. Among the twenty-four F1s, three crosses displayed positive and significant SCA effects for grain yield per plant. Wide variation in heterobeltiosis and standard heterosis, both positive and negative, was noted across traits. The top five F1s identified for heterotic potential were PUSA 1509 × IR-64-Sub-1, Sambha-Sub-1 × HUR 105, JGL 384 × HUR 105, PUSA 1509 × HUR 105 and Sarjoo-52 × HUR 105. Out of seventy-one SSR markers tested, six showed polymorphism supporting parental diversity assessment. These findings demonstrate the usefulness of combining ability and heterosis analysis in establishing heterotic patterns essential for hybrid rice improvement.

    INTRODUCTION

    Rice (Oryza sativa L.) is the most important staple food crop in the world. Asia is the leading region in rice production, accounting for about 90% of global output. India has the largest area under rice cultivation, covering 46.38 million hectares, which constitutes 28.26% of the world’s rice-growing area and ranks second in total production with 130.29 million tonnes, next to China, with an average productivity of 2,809 kg ha-1 (Anonymous, 2021-22). About 75% of the world’s rice supply is consumed by people in Asian countries; thus, rice is of immense importance to Asia’s food security. The demand for rice is expected to increase continuously with the growth of the global population.
           
    The development of hybrid rice varieties in India faces several obstacles, including insufficient genetic diversity, unstable heterosis, difficulties in maintaining seed purity, high production costs and limited farmer adoption. In addition, regulatory constraints, resource limitations and intellectual property issues pose significant challenges. To overcome these problems, coordinated efforts are required to strengthen research, innovation and adoption of hybrid rice technology.
           
    To address the above-mentioned issues, a thorough understanding of gene action, combining ability and heterotic response is essential in rice hybrid breeding. Therefore, there is a strong need to conduct integrated studies using both conventional and biotechnological approaches in rice improvement. These include selective breeding to elucidate gene action and select desirable traits, hybridization to exploit heterosis and develop superior progenies and marker-assisted selection to accelerate the breeding process by identifying plants carrying genes of interest. Furthermore, genome-editing tools enable precise manipulation of gene expression, while quantitative trait loci (QTL) mapping helps identify genomic regions associated with complex traits. Screening of diverse germplasm and the application of genomic selection enhance breeding programs by broadening genetic diversity and improving predictive accuracy, ultimately leading to the development of high-yielding, resilient rice varieties suited to sustainable agricultural production and global food security.

    MATERIALS AND METHODS

    Experimental site and development of materials
     
    The study was conducted at the main experimental station of Lovely Professional University, Punjab, India (31°14′ 29.6″N, 75°41′46.9″E). The experimental material consisted of a line × tester set comprising twenty-four F1 hybrids developed by crossing eight female lines (HUR 1309, PR 121, PUSA 1509, PR 13, JGL 384, Sarjoo 52, Sambha Sub-1 and Pusa Basmati 1) with three male testers (IR-64-Sub-1, Sabhagi and HUR-105) during Kharif 2022. In total, thirty-seven genotypes, including twenty-four F1s, eleven parents and two standard checks (PR-26 and Pusa Basmati 1121), were evaluated in Kharif 2023 using a randomized complete block design with three replications. The objective was to estimate gene action, genetic variance components, combining ability and heterosis in rice.
           
    Observations were recorded for thirteen morphological traits: days to 50% flowering, flag leaf area, plant height, panicle-bearing tillers per plant, panicle length, spikelets per panicle, grains per panicle, spikelet fertility, biological yield per plant, harvest index, L/B ratio, thousand-grain weight and grain yield per plant.
           
    For molecular characterization, seventy-one SSR markers were initially screened to assess parental polymorphism and ensure genome-wide coverage. Only six markers exhibited clear and reproducible polymorphism and were selected for hybrid purity testing. The low polymorphism percentage reflects the narrow genetic base of elite rice germplasm. However, hybrid purity testing requires only parent-specific polymorphic loci rather than genome-wide diversity assessment; thus, a limited number of informative SSR markers is sufficient. The six selected markers, distributed across different chromosomes, produced distinct co-dominant banding patterns that enabled differentiation between male and female parents. The presence of both parental alleles in F1 plants confirmed their hybrid status. Previous studies have similarly reported that a small set of highly informative SSR markers is adequate for reliable hybrid purity testing in rice (Table 1).

    Table 1: List of primers used in fingerprinting of hybrids with their information.


     
    Statistical analysis
     
    Line × tester analysis was performed following the method of Kempthorne (1957) and further elaborated by Arunachalam (1974) to estimate general combining ability (GCA) and specific combining ability (SCA) variances and effects. Heterosis was calculated as the percentage deviation of F1 means over the better parent (heterobeltiosis) as per Fonseca and Patterson (1968) and over the standard variety (economic heterosis) following Meredith and Bridge (1972). Significance was tested using critical difference values corresponding to heterosis estimates.
           
    Genomic DNA was extracted from 10-15-day-old seedlings using the CTAB method of Doyle et al. (1990) with minor modifications. DNA was diluted to 40 ng/µL and stored at 4°C, with stock samples preserved at -20°C.
           
    PCR amplification using six SSR markers was performed  in a 10 µL reaction mixture containing template DNA, primers, Taq polymerase, MgCl‚  with buffer, dNTPs and nuclease-free water. The thermal profile included initial denaturation at 95°C (5 min), followed by 35 cycles of denaturation (94°C, 1 min), annealing (55°C, 1 min) and extension (72°C, 1 min), with final extension at 72°C for 7 min. Amplified products were resolved on 5% polyacrylamide gels stained with ethidium bromide and visualized under UV light. Product sizes were determined using 50 bp and 100 bp DNA ladders.

    RESULTS AND DISCUSSION

    Estimates of components of genetic variance
     
    The estimates of combining ability variances, average degree of dominance, predictability ratio, additive and dominance variances, heritability in narrow sense and genetic advance in percent of mean have been presented (Table 2). Estimates of sca variance were higher than the corresponding estimates of gca variance for all the thirteen traits except flag leaf area, plant height and panicle bearing tillers in F1s. For each attribute, the average level of dominance varied from 0.31 to 2.43. Values less than unity (<1) imply partial dominance or additive gene activity, while values greater than unity (>1) show the predominance of over-dominance. A number of economically significant traits, including days to 50% flowering (1.04), panicle length (1.31), grains per panicle (1.11), spikelet fertility (1.74), harvest index (2.43) and 1000-grain weight (1.12), showed over-dominance, indicating that non-additive gene effects are important in the inheritance of these traits. This explains why a number of F1 hybrids showed a high heterotic response to these features. A number of economically significant traits, including days to 50% flowering (1.04), panicle length (1.31), grains per panicle (1.11), spikelet fertility (1.74), harvest index (2.43) and 1000-grain weight (1.12), showed over-dominance, indicating that non-additive gene effects are important in the inheritance of these traits. This explains why a number of F1 hybrids showed a high heterotic response to these features. Similar findings have also been reported by earlier researchers AL Mamun (2011); Rajpoot et al. (2017); Singh et al. (2019); Bhattacharjee et al. (2020) and Shrivastav et al. (2022).

    Table 2: Components of genetic variance, average degree of dominance, predictability ratio, heritability in narrow sense and genetic advance in per cent of mean for 13 characters in rice.


           
    The predictability ratio was less than 0.50 for most traits, including days to 50% flowering (0.48), grains per panicle (0.45), spikelet fertility (0.25), harvest index (0.14) and 1000-grain weight (0.44), confirming the predominance of non-additive gene action for these traits. However, comparatively higher predictability ratios were recorded for panicle bearing tillers per plant (0.91), plant height (0.89) and flag leaf area (0.76), indicating a greater role of additive genetic variance. These traits are therefore amenable to improvement through selection in early generations. The L/B ratio exhibited a predictability ratio greater than unity (1.40), which may be attributed to sampling error or low variance estimates, suggesting instability in additive variance estimation for this trait.
           
    Heritability in narrow sense [h2(ns)] have been classified by Johnson et al., (1955) into three categories viz., high (>30%), medium (10-30%) and low (<10%). Some characteristics demonstrated moderate to high narrow-sense heritability, while having more SCA variance than GCA variance, which suggests non-additive gene action predominates. The GCA-SCA comparison shows the relative amount of additive and non-additive effects in particular cross combinations, while heritability assesses the fraction of additive variation compared to overall phenotypic variance, hence this seeming contradiction is not contradictory. Thus, it is possible for both dominant and additive effects to function concurrently. Higher SCA variance suggests the significance of dominance and epistasis for heterosis expression, whereas significant additive variance explains the moderate to high heritability. Consequently, a combination of selection and hybrid breeding techniques can enhance these characteristics. Among the traits ranging from -30.31% to 88.56%. High heritability estimates were recorded for panicle bearing tillers per plant (88.56%), plant height (86.42%), flag leaf area (73.74%), biological yield per plant (56.77%), spikelets per panicle (52.59%), grain yield per plant (50.27%), days to 50% flowering (46.44%), grains per panicle (44.29%) and 1000-grain weight (41.43%), indicating a substantial contribution of additive genetic variance and effectiveness of selection for these traits. Moderate heritability was observed for spikelet fertility (23.98%), panicle length (18.66%) and harvest index (13.40%), suggesting that selection for these traits should be practiced in later generations. The negative narrow-sense heritability observed for L/B ratio (-30.31%) was due to negative additive genetic variance (σ2A = -0.02) and very low gca variance (σ2g = -0.01). Such negative estimates are generally considered as zero heritability and arise from environmental effects or sampling errors rather than true negative inheritance, indicating limited scope for improvement of this trait through direct selection. Similar results have been reported by Yadav et al. (2011); Rajpoot et al., (2017); Yadav et al. (2020); Kumar et al., (2020) and Kumar et al. (2026).
     
    Estimates of combining ability effects
     
    The estimates of general combining ability (gca) effects in respect of eleven parents (eight lines and three testers) for the thirteen characters have been set out (Table 3). The lines, PUSA 1509 (4.75) and Sambha Sub-1 (2.19) in F1s possessed significant and positive gca effects for grain yield per plant. Similar results have been reported Sankar et al., (2008); Latha et al. (2013); Kargbo et al. (2019); Ghidan et al. (2019) and Abd El-Aty (2022). The lines, Pusa basmati 1 (-5.91) in F1s recorded negative and significant gca effects for grain yield per plant. Among the testers HUR 105 (2.81) recorded significant and positive gca effects, whereas Sabhagi (-2.80) exhibited significant and negative gca effect in F1s for grain yield per plant and IR-64-Sub-1 (-0.01) had negative and non-significant gca effect in F1s.

    Table 3: Estimates of general combining ability (gca) effects of F1s parents (lines and testers) for 13 characters in rice.


           
    The estimates of specific combining ability effects for twenty-four crosses of line×tester set for thirteen characters are presented (Table 4). Three crosses emerged with positive and significant sca effects for grain yield per plant viz., PUSA 1509 × IR-64-Sub-1 (7.12), Sambha Sub-1× Sabhagi (4.13) and Pusa basmati 1 × IR-64-Sub-1 (3.79). The undesirable negative and significant sca effects for grain yield per plant were exhibited by four crosses in F1s. Similar observations were made by Sai et al. (2025).

    Table 4: Estimates of specific combining ability (sca) effects of crosses (F1s) for 13 characters in rice.


     
    Gene action
     
    The grain yield per plant (g) for various rice crosses was analyzed, with significant specific combining ability (SCA) effects observed. The cross PUSA 1509 × IR-64-Sub-1 exhibited the highest SCA effect of 7.12 and a mean performance of 47.33 g per plant, categorized under high × low (H×L) general combining ability (GCA) effects. Another notable cross, Sambha Sub-1 × Sabhagi, showed an SCA effect of 4.13 with a mean performance of 39.00 g per plant, falling under low × low (L×L) GCA effects. Similarly, the cross Pusa Basmati 1 × IR-64-Sub-1 recorded an SCA effect of 3.79 and a mean performance of 34.67 g per plant, also categorized under L×L GCA effects are presented (Table 5). Earlier studies have found in similar result Fasahat et al. (2016); Nyombe (2017) and Bhattacharjee et al. (2020).

    Table 5: Most promising cross combinations for different characters along with their mean performance, sca effects and gca effects of parents in F1s.


     
    Estimates of heterosis over better-parent and standard variety
     
    Heterosis was estimated as a per cent increase or decrease of F1 value over better-parent (BP) and standard variety (SV) viz., PR 26 (SV1) Pusa basmati 1121 (SV2). The estimates of heterobeltiosis and standard heterosis for thirteen characters are presented (Table 6). For grain yield per plant, the heterosis over better-parent varied from -28.23% (Pusa basmati 1 × Sabhagi) to 91.89% (PUSA 1509 × IR-64-Sub-1). Eighteen crosses showed positive and significant heterosis over BP and the best five among them were PUSA 1509 × IR-64-Sub-1 (91.89%), PUSA 1509 × HUR 105 (83.03%), Sarjoo 52 × HUR 105 (68.25%), Pusa basmati 1 × HUR 105 (58.46%) and JGL 384 × HUR 105 (48.15%). The standard heterosis for grain yield per plant ranged from -7.73% (Pusa basmati 1 × Sabhagi) to 107.97% (PUSA 1509 × IR-64-Sub-1) over SV1 and from -8.87% (Pusa basmati 1 × Sabhagi) to 105.41% (PUSA 1509 × IR-64-Sub-1) over SV2. Eighteen crosses showed positive heterosis and the top five were PUSA 1509 × IR-64-Sub-1 (105.41%), Sambha Sub-1x HUR 105 (85.16%), JGL 384 × HUR 105 (73.59%), PUSA 1509 × HUR 105 (72.14%) and Sarjoo 52 × HUR 105 as well as Sambha Sub-1 × Sabhagi (69.25%). Earlier studies have found similar results Sankar et al., (2008); Sai et al. (2025) and Chintala et al. (2026).

    Table 6: Extent of per cent heterosis over better parent (BP) and two standard varieties (SV1 and SV2) of F1s for 13 characters in rice.


     
    Hybrid purity testing of rice using SSR molecular markers
     
    Only six of the seventy-one SSR markers showed polymorphism among the parental lines, indicating low molecular diversity due to the narrow genetic base of elite rice germplasm. Similar low to moderate polymorphism has been reported in earlier rice studies. Despite limited variability, these informative markers were sufficient for parental discrimination and reliable F1 hybrid purity confirmation. A list of six polymorphic markers is presented. These polymorphic markers were used to check the true F1 hybrids of the crosses (Fig 1). SSR marker RM122 showed polymorphism on the cross HUR 1309 × IR-64-Sub-1, PR 121 × IR-64-Sub-1, PUSA 1509 × IR-64-Sub-1, Sarjoo 52 × IR-64-Sub-1 and Pusa basmati 1 × IR-64-Sub-1. SSR marker RM6887 exhibited polymorphism in the crosses HUR 1309 × Sabhagi, PR 121 × Sabhagi, PR 13 × Sabhagi, Sarjoo 52 × Sabhagi and Sambha Sub-1 × Sabhagi. Polymorphism was observed with SSR marker RM3253 in the combinations JGL 384 × HUR-105, Sarjoo 52 × HUR-105 and Sambha-Sub-1 × HUR-105. The crosses PUSA 1509 × IR-64-Sub-1, JGL 384 × IR-64-Sub-1 and Sambha-Sub-1 x IR-64-Sub-1 displayed polymorphism with SSR marker RM168. SSR marker RM3271 revealed polymorphism across the crosses HUR 1509 × Sabhagi, JGL 384 × Sabhagi and Pusa basmati 1 × Sabhagi. In the crosses HUR 1309 x HUR-105, PR 121 x HUR-105, PUSA 1509 × HUR-105, PR 13 × HUR-105 and Pusa basmati 1 × HUR-105 SSR marker RM3291 showed polymorphic patterns and true F1 hybrids of these crosses. Similar results of genetic purity testing of rice were reported by Shashibhushan et al. (2021).

    Fig 1: Molecular profiling of rice hybrids.


           
    The prevalence of non-additive gene action was suggested by the larger SCA variance than GCA variance for the majority of variables, indicating that hybrid breeding would be more successful than direct selection for increasing rice grain production. While crosses like PUSA 1509 × IR-64-Sub-1 and Sambha Sub-1 × HUR 105 shown strong heterosis and SCA effects, making them ideal candidates for hybrid creation, parents like PUSA 1509, HUR 105 and Sambha Sub-1 emerged as good general combiners. Through selective breeding, traits like plant height and tiller number that are controlled by additive effects can be enhanced. These findings support previous research showing the significance of heterosis and non-additive gene activity in increasing rice production, demonstrating the value of combining ability analysis to find superior parents and hybrids. Similar findings were reported by Kumar et al. (2026).

    CONCLUSION

    The present investigation highlighted the significance of genetic variance components, combining ability and heterotic response in rice improvement. The predominance of non-additive gene action indicated by higher SCA variance suggests the potential of hybrid breeding in enhancing yield and related traits. Promising parents such as PUSA 1509, HUR 105 and Sambha Sub-1 exhibited strong GCA effects, while crosses like PUSA 1509 × IR-64-Sub-1 and Sambha Sub-1 × HUR 105 showed high heterotic potential. The SSR markers further validated parental polymorphism and hybrid purity. Overall, this study provides valuable insights for establishing heterotic patterns, thereby strengthening strategies for sustainable hybrid rice breeding.

    ACKNOWLEDGEMENT

    The School of Agriculture and the experimental facilities at Lovely Professional University, Punjab, India, are much appreciated by the authors for carrying out this study. The authors express their gratitude to all academic members, technical staff and colleagues for their invaluable advice, support and help with data processing, laboratory work and field experiments. The assistance obtained for statistical analysis and molecular analysis is also appropriately recognized.
     
    Disclaimer
     
    The opinions and findings presented in this study are entirely the authors’ own and may not represent the official positions of the associated organizations or institutions. The integrity and correctness of the data used in this study are the responsibility of the authors. If there are any mistakes or omissions, they are not deliberate. The writers or their institutions do not advocate or encourage the use of trade names, commercial goods, or particular equipment.
     
    Informed consent
     
    Informed consent was not applicable for this study as it did not involve human participants or animals. The research was conducted on plant materials under field and laboratory conditions in accordance with institutional and ethical guidelines.

    CONFLICT OF INTEREST

    Regarding the publishing of this research work, the authors affirm that they have no conflicts of interest. The authors attest that the study, data analysis and paper preparation were not impacted by any financial or personal ties.

    REFERENCES


    1. Abd El-Aty, M.S., Abo-Youssef, M.I., Galal, A.A., Salama, A.M., Salama, A.A., El-Shehawi, A.M. and El-Tahan, A.M. (2022). Genetic behavior of earliness and yield traits of some rice (Oryza sativa L.) genotypes. Saudi Journal of Biological Sciences. 29(4): 2691-2697.

    2. AL Mamun, S.A. (2011). Characterization and Genetic Diversity for Agronomic Traits in Exotic Rice (Doctoral Dissertation, Bangabandhu Sheikh Mujibur Rahman Agricultural University).

    3. Anonymous. (2021-22). Director of Economics and Statistics, Department of Agriculture, Cooperation and Farmers Welfare (DAC and FW).

    4. Arunachalam, V. (1974). The fallacy behind the use of modified line × tester design. Indian Journal of Genetics and Plant Breeding. 34(2): 200-207.

    5. Bhattacharjee, M., Majumder, K., Kundagrami, S. and Dasgupta, T. (2020). Evaluation of recombinant inbred lines for higher iron and zinc content along with yield and quality parameters in rice (Oryza sativa L.). Indian Journal of Agricultural Research. 54(6): 724-730. doi: 10.18805/IJARe.A-5454.

    6. Chintala, S., Babu, P.R., Babu, J.D.P., Rao, V.S., Jayalalitha, K. and Siva, M. (2026). Identification of elite parents and study of heterosis for important yield traits in rice: Combining ability and heterosis in rice. Oryza-An International Journal of Rice. 63(1). https://epubs.icar.org.in/index. php/OIJR/article/view/147012.

    7. Doyle, J.J., Doyle, J.L., Brown, A.H. and Grace, J.P. (1990). Multiple origins of polyploids in the Glycine tabacina complex inferred from chloroplast DNA polymorphism. Proceedings of the National Academy of Sciences. 87(2): 714-717.

    8. Fasahat, P., Rajabi, A., Rad, J.M. and Derera, J.J.B.B.I.J. (2016). Principles and utilization of combining ability in plant breeding. Biometrics and Biostatistics International Journal. 4(1): 1-24.

    9. Fonseca, S. and Patterson, F.L. (1968). Hybrid vigor in a seven parent diallel cross in common winter wheat (Triticum aestivum L.). Crop Science. 8(1): 85-88.

    10. Ghidan, W.F., El-Agoury, R.Y. and Hussein, F.A. (2019). Utilization of combining ability and genetic components for yield and its contributing traits of some rice (Oryza sativa L.) genotypes. Journal of Agricultural Chemistry and Biotechnology. 10(12): 257-267.

    11. Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in soybeans. Agronomy Journal. 47: 314-318.

    12. Kargbo, S.S., Showemimo, F., Akintokun, P. and Porbeni, J. (2019). Combining ability analysis and gene action for yield and yield related traits in rice (Oryza sativa L.) under saline conditions. Journal of Plant Breeding and Genetics. 7(2): 63-74.

    13. Kempthorne, O. (1957). The contributions of statistics to agronomy. Advances in Agronomy. 9: 177-204.

    14. Kumar, J., Chand, P., Singh, S.K., Khilari, K. and Kumar, M. (2020). Genetic variability, heritability and genetic advance for yield and its contributing traits in rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry. 9(2): 385-387.

    15. Kumar, S., Jayasudha, S. and Singh, S.K. (2026). Genetic variability, heritability and genetic advance for yield and quality traits in rice (Oryza sativa L.). Indian Journal of Agricultural Research. 60(2): 183-190. doi: 10.18805/IJARe.A-6402.

    16. Latha, S., Sharma, D. and Sanghera, G.S. (2013). Combining ability and heterosis for grain yield and its component traits in rice (Oryza sativa L.). Notulae Scientia Biologicae. 5(1): 90-97.

    17. Meredith, J.W.R. and Bridge, R.R. (1972). Heterosis and gene action in cotton, Gossypium hirsutum L. Crop Science. 12(3): 304-310.

    18. Nyombe, M.M.L. (2017). Genetic Improvement of Grain Yield and Quality in rice (Oryza sativa L.) in South Sudan (Doctoral Dissertation).

    19. Rajpoot, P., Singh, P.K., Verma, O.P. and Tripathi, N. (2017). Studies on genetic variability and heritability for quantitative characters in rice (Oryza sativa L.) under sodic soil. Journal of Pharmacognosy and Phytochemistry. 6(4): 1162-1165.

    20. Sai, R.K., Saraswathi, R., Kumar, M., Raveendran, M. and Robin, S. (2025). Estimation of combining ability and heterosis in TGMS based two-line hybrids of rice (Oryza sativa). The Indian Journal of Agricultural Sciences. 95(2): 133- 139.

    21. Sankar, P.D., Subbaraman, N. and Narayanan, S.L. (2008). Heterosis, combining ability and gene action studies in TGMS based rice hybrids under normal and salt affected environments. Indian J. Agric. Res. 42(3): 177-182.

    22. Shashibhushan, D., Muchanthula, A.R. and Pradeep, T. (2021). Molecular finger printing and genetic purity assessment of a rice hybrid using microsatellite markers. Pharma Innovation. 10(6): 926-929.

    23. Shrivastav, S.P., Verma, O.P., Jakhar, D.S., Singh, V. and Lal, K. (2022). Studies on component of genetic variance and heterotic response in rice (Oryza sativa L.) for high yield with quality and sodicity tolerance. Indian Journal of Genetics and Plant Breeding. 82(4): 419-429.

    24. Singh, S.K., Bindal, S., Singh, A. and Srivastava, S. (2019). Combining ability effects for yield traits in rice (Oryza sativa L.) under sodic soil. Journal of Pharmacognosy and Phytochemistry. 8(1): 281-283.

    25. Yadav, S.K., Pandey, P., Kumar, B. and Suresh, B.G. (2011). Genetic architecture, inter-relationship and selection criteria for yield improvement in rice (Oryza sativa L.). Pakistan Journal of Biological Sciences. 14(9): 540-545.

    26. Yadav, V.P., Singh, P.K. and Verma, O.P. (2020). Genetic variation and heritability for quantitative traits in rice (Oryza sativa L.) under sodic soil. The Indian Journal of Agricultural Sciences. 90(2): 316-319.
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