Genetic variability, heritability and genetic advance for yield and yield-contributing traits in promising rice (Oryza sativa L.) hybrids

Introduction

Rice (Oryza sativa L., 2n = 24) is the primary dietary staple for over half of the global population. Global rice production during the 2025/26 cycle was estimated at approximately 545.51 million metric tons of milled grain (USDA, 2025) [1] . Although India commands the largest acreage and contributes roughly 28% to global production, its average productivity (~4.39 t ha -1 ) remains substantially lower than leading producers like China (~7.19 t ha -1 ) (USDA, 2025) [1] . This yield gap highlights the critical need to design highyielding varieties and experimental F 1 hybrids. In the high-rainfall Konkan ecosystem of Maharashtra, rice serves as a socio-economic anchor; however, production is constrained by fragmented landholdings, escalating labor scarcity, and minimal mechanization, necessitating the development of robust, high-yielding hybrids tailored to local agro-ecologies. The phenotypic expression of complex quantitative traits is an interactive function of the genotype and prevailing environmental parameters. Effective selection requires partitioning total phenotypic variance into genotypic (GCV) and phenotypic (PCV) components to gauge the relative environmental influence. While broad-sense heritability (h 2 bs) quantifies the proportion of phenotypic variance attributable to genetic variations, it lacks predictive accuracy regarding absolute selection gain when confounded by non-additive gene action (epistasis and dominance). Consequently, the concurrent estimation of heritability and genetic advance as a percentage of mean (GAM) serves as a superior index to predict the response to directional selection, confirming whether a trait is governed by additive or non-additive genetic components. This investigation evaluates the genetic architecture, heritability parameters, and expected genetic gain for fifteen morphophysiological and biochemical parameters in twelve promising experimental rice hybrids under the agro-climatic conditions of Karjat, Maharashtra.

Materials and methods

Experimental plant material

The experimental germplasm consisted of sixteen genotypes: twelve experimental F 1 hybrids developed via a three-line breeding system utilizing the cytoplasmic male-sterile (CMS) line IR-58025A crossed with distinct restorer lines, to get the respective hybrids. The checks included two hybrid checks (Sahyadri 3 and Sahyadri 4) and two varietal checks (Karjat 7 and Konkan Sanjay), procured from the Regional Agricultural Research Station, Karjat. The experimental lines evaluated were designated as KJTRH

Field layout and crop management

The field trial was conducted in a Randomized Block Design (RBD) with three replications during the Kharif 2025 season at RARS, Karjat, Raigad, Maharashtra. Seedlings were transplanted at a standard spacing of 15 cm × 15 cm. Agronomic interventions, crop protection protocols and fertilizer applications were executed uniformly across all plots as per standard package of practices.

Phenotypic and biochemical phenotyping

Quantitative and qualitative measurements were recorded from five randomly selected competitive plants per genotype per replication. Observations were recorded for fifteen distinct traits viz days to 50% flowering (DFF), plant height (PH, cm), panicle length (PL, cm), number of tillers per plant (NTP), number of productive tillers per plant (NPP), spikelet fertility (SF, %), test weight (TW, g), grain yield per plant (GYP, g), straw yield per plant (SYP, g), harvest index (HI, %), hulling percentage (HLP, %), milling percentage (MLP, %), protein content (PC, %), amylose content (AC, %), and length-to-breadth ratio (LBR). Biochemical analyses for grain protein content (via total nitrogen determination) and amylose concentration were executed using standard colorimetric and analytical biochemistry methodologies.

Statistical and biometrical computations

Raw field data were subjected to Analysis of Variance (ANOVA) using standard linear models for RBD. Genotypic and phenotypic variances were estimated utilizing the mean expectation values according to Weber et al. (1952) [2] . The genotypic (GCV) and phenotypic (PCV) coefficients of variation were calculated following Burton et al. (1953) [3] and classified as low (< 10%), moderate (10-20%), and high (> 20%) based on Sivasubramanian and Madhava Menon (1973) [4] . Broad-sense heritability (h 2 bs) was derived using the genetic-tophenotypic variance ratio. Genetic advance (GA) and genetic advance as a percentage of mean (GAM) were computed according to Johnson et al. (1955) [5] . All biometrical analyses were processed via R software platforms.

Results and discussion

Analysis of variance (ANOVA)

The structured analysis of variance (Table 1) demonstrated highly significant differences (p < 0.01) among the sixteen evaluated genotypes across all fifteen traits. This confirms the presence of extensive genetic variability within the breeding material, establishing the empirical validity for further partitioning into genotypic and phenotypic components.

Genetic variability parameters

Phenotypic coefficients of variation were uniformly higher than their corresponding genotypic counterparts across all parameters, signaling environmental interactions, though the margins remained minimal for most characters. Low-to-moderate variability coupled with narrow GCV-PCV margins were observed for days to 50% flowering (GCV = 6.22%, PCV = 6.36%), plant height (GCV = 9.13%, PCV = 10.05%), panicle length (GCV = 8.85%, PCV = 10.75%), harvest index (GCV = 7.19%, PCV = 7.93%), and L/B ratio (GCV = 9.22%, PCV = 9.65%). These findings align with Nithya et al. (2020) [6] and Sala et al. (2016) [7] , confirming rigorous genetic control over these expressions. In contrast, the number of tillers per plant (GCV = 10.26%, PCV = 15.42%) and number of productive tillers per plant (GCV = 10.69%, PCV = 16.90%) exhibited wider GCV-PCV disparities, echoing the findings of Ullah et al. (2023) [8] and Savitha et al. (2015) [9] , which point to environmental vulnerability regarding tillering processes. Economically vital parameters such as grain yield per plant manifested moderate coefficients of variation (GCV = 12.33%, PCV = 14.04%), matching the conclusions of Babu et al. (2024) [10] . Grain milling properties, specifically hulling percentage (1.79%, 2.91%) and milling percentage (3.44%, 5.01%), presented the narrowest variation parameters, consistent with Binodh et al. (2006) [11] .

Heritability and genetic advance as a percent of mean

Broad-sense heritability values exhibited wide variations, extending from 37.65% (hulling percentage) to a peak of 97.13% (grain protein content). In structural alignment with Ojha et al. (2018) [12] , biochemical profiling demonstrated that protein content combined high heritability (97.13%) with high genetic advance (GAM = 23.29%). This highly favorable genetic framework was similarly recorded for grain yield per plant (h 2 bs = 77.07%, GAM = 22.30%), plant height (h 2 bs = 82.49%, GAM = 17.08%), and amylose content (h 2 bs = 78.81%, GAM = 18.98%). These traits are governed by additive gene action, as documented by Akter et al. (2019) [13] and Akshay et al.

(2022) [14] , indicating that direct phenotypic selection will be highly effective. Conversely, traits like days to 50% flowering (95.45%), L/B ratio (91.26%), and harvest index (82.12%) yielded high broad sense heritability but only low-to-moderate genetic advance values (12.51%, 18.14%, and 13.42%, respectively). This dynamic reflects the influence of non-additive gene actions (dominance/epistasis) and environmental interactions, corroborating Meena et al. (2020) [15] and Gour et al. (2017) [16] . Furthermore, tillering parameters (NTP, NPP), spikelet fertility, and grain-recovery values (HLP, MLP) displayed low-to-moderate heritability integrated with limited genetic gains, matching the trends discovered by Divya et al. (2018) [17] and Kurmanchali et al. (2019) [18] . Heterosis breeding or multi-locational progeny tests across temporal scales remain necessary to bypass these genotype × environment blocks, as advanced by Fentie et al. (2021) [19] and Shrivastava et al. (2015) [20] .

Conclusion

Extensive genetic variability was successfully characterized across the sixteen evaluated rice genotypes for all fifteen parameters. Traits such as grain yield per plant, protein content, plant height and amylose content exhibited high broad-sense heritability coupled with high expected genetic advance, indicating substantial genetic variability and good scope for effective selection among the evaluated hybrids. Conversely, tillering and milling parameters showed greater environmental influence and complex genetic control, emphasizing the need for multi-environment evaluation to assess hybrid stability and consistency. Overall, grain yield per plant, harvest index and protein content emerged as important traits for identifying superior hybrids and advancing promising rice hybrids under the agro-ecological conditions of Karjat, Maharashtra.

References

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