Genetic parameters and their role in selection for yield traits in coriander (Coriandrum sativum L.)

Introduction

Genetic parameters, particularly variability, heritability, and genetic advance, constitute the cornerstone for understanding the inheritance of quantitative traits and play a decisive role in determining the efficiency of selection in crop improvement programmes (Singh et al., 2019;Sharma et al., 2020;Moharana et al., 2023; Ali et al., 2024) [5] . These parameters enable plant breeders to quantify, how different the plants are from one another within a group of plants and to estimate how they will improve when you select the best ones under varying environmental conditions (Yadav et al., 2022;Verma et al., 2020; Choudhary et al., 2021) [9] . In self-pollinated crops such as coriander (Coriandrum sativum L.), rapid attainment of homozygosity enhances the effectiveness of selection, provided sufficient additive genetic variance exists within the population (Meena et al., 2017; Patel et al., 2019; Rai et al., 2024) [4] . The success of any crop improvement programme largely depends on the availability and effective utilization of genetic variability, which provides the basic foundation for selection and genetic improvement in coriander (Moharana et al., 2023;Basol et al., 2024;Rai et al., 2024).The partitioning of phenotypic variance into genotypic and environmental components provides a scientific basis for finding superior genotypes and formulating effective breeding strategies (Verma et al., 2020;Yadav et al., 2022;Basol et al., 2024) [9] . Phenotypic coefficient variation (PCV) and genotypic coefficient variation (GCV) are widely used to assess the magnitude of variability, where higher values indicate greater scope for improvement genetically through the process of selection (Singh et al., 2019;Patel et al., 2019;Rai et al., 2024) [4, 5] . In coriander, substantial variability has been reported for important yield-attributing traits such as height of the plant, umbels number per plant, seeds number per umbel, and seed yield per plant, indicating the presence of exploitable genetic diversity within available germplasm (Meena et al., 2017;Yadav et al., 2022;Moharana et al., 2023; Ali et al., 2024) [9] .

Genetic variability provides the basic foundation for crop improvement because selection becomes effective only when sufficient heritable variation is present within the population. Estimation of genetic parameters such as genotypic coefficient of variation, phenotypic coefficient of variation, heritability, and genetic advance helps breeders identify superior genotypes and predict the efficiency of selection for economically important traits. Heritability is major key genetic parameter that measures the total proportion of phenotypic variation attributable to genetic factors and provides insight into the transmissibility of traits across generations (Sharma et al., 2020;Verma et al., 2020;Choudhary et al., 2021). High heritability means that the visible traits of the plant are mostly controlled by its genes, so selecting plants based on what you can observe is likely to give good results. On the other hand, low heritability suggests that the environment has a stronger effect on how the trait appears, making selection less reliable (Singh et al., 2019;Yadav et al., 2022; Rai et al., 2024) [5, 9] . However, heritability alone is insufficient to predict any kind of response to selection, as it does not consider the magnitude of genetic variation or selection intensity (Moharana et al., 2023;Ali et al., 2024). Because of this, genetic advance an estimate of how much improvement can be achieved through selection is studied along with heritability to identify traits mainly controlled by genes that respond well to selection (Patel et al., 2019;Sharma et al., 2020; Meena & Sharma, 2025) [4] . When both heritability and genetic advance are high, it usually means these traits are strongly influenced by such genes, making selection more effective and reliable (Meena et al., 2017;Moharana et al., 2023;Rai et al., 2024). Yield is one of the complex trait controlled by many genes and also affected by environmental conditions, so selecting plants based only on yield is often less efficient and not always reliable (Singh et al., 2019;Sharma et al., 2020;Yadav et al., 2022) [5] . Consequently, indirect selection based on contribution of yield traits exhibiting high heritability and genetic advance is widely adopted in plant breeding programmes (Verma et al., 2020;Choudhary et al., 2021;Ali et al., 2024). In coriander, traits like the number of umbels per plant, seeds per umbel, number of primary branches, and seed weight are strongly and positively related to seed yield (Moharana et al., 2023;Rai et al., 2024). Correlation and path coefficient analyses both serve as important statistical tools for understanding the interrelationships among traits and for partitioning the direct and indirect effects of yield components (Verma et al., 2020; Yadav et al., 2022; Rai et al., 2024) [9] . While correlation analysis indicates the degree and direction of association between traits, path analysis provides a more precise estimation of cause-and-effect relationships by separating direct and indirect contributions (Singh et al., 2019;Sharma et al., 2020; Choudhary et al., 2021) [5] . These analytical approaches facilitate the identification of key yield-contributing traits that can be effectively utilized as selection indices in coriander breeding programmes (Patel et al., 2019;Moharana et al., 2023;Ali et al., 2024) [4] . The nature of gene action governing yield and its component traits significantly influences the choice of breeding strategy (Sharma et al., 2020;Moharana et al., 2023;Rai et al., 2024). Traits controlled predominantly by additive gene action respond well to simple selection methods, whereas traits governed by non-additive gene action require alternative approaches such as hybridization and heterosis breeding (Singh et al., 2019;Verma et al., 2020; Meena & Sharma, 2025) [5] . In coriander, several studies have reported high heritability along with high genetic advance for key yield traits, indicating the predominance of additive gene effects and the effectiveness of direct selection (Meena et al., 2017;Yadav et al., 2022;Moharana et al., 2023) [9] . Coriander (Coriandrum sativum L.) is an important seed spice from the Apiaceae family, widely grown for both its seeds and fresh leaves, which are used in cooking as well as in medicinal and industrial applications (Singh et al., 2021;Mishra et al., 2019;Varshney et al., 2021) [3, 6, 7] . India is the leading producer, consumer, and exporter of coriander, playing a major role in the global spice market ( [6, 9] . Despite its economic importance, coriander productivity remains relatively low due to limited genetic improvement, narrow genetic base, and strong environmental influence on yield expression (Patel et al., 2019;Sharma et al., 2020;Moharana et al., 2023) [4] . The absence of stable, highyielding genotypes adapted to diverse agro-climatic conditions further constrains its yield potential [9] . In coriander, considerable genetic variability has been documented for yield and its contributing traits, indicating the presence of ample scope for genetic improvement (Meena et al., 2017; Patel et al., 2019; Choudhary et al., 2021) [4] . The effective exploitation of this variability through selection based on genetic parameters can significantly enhance breeding efficiency and genetic gain (Singh et al., 2019;Verma et al., 2020; Ali et al., 2024) [5] . Recent advances in plant breeding have integrated conventional quantitative genetic approaches with genomicassisted breeding methods to improve selection efficiency and accelerate genetic gain. Technologies such as markerassisted selection and genomic selection are increasingly used in crop improvement programmes for precise identification of superior genotypes and prediction of complex quantitative traits (Crossa et al., 2017;Varshney et al., 2021;Xu et al., 2017) [1, 7, 8] . However, the practical application of these molecular breeding tools in coriander is still limited, and most coriander improvement programmes continue to rely primarily on phenotypic selection based on genetic parameters (Moharana et al., 2023;Basol et al., 2024). Despite considerable research on genetic variability and trait association in coriander, there remains a gap in integrating genetic parameters with modern breeding strategies across diverse environments. Furthermore, the limited utilization of genomic tools highlights the need for a more comprehensive and integrated approach to coriander improvement. Therefore, the present review aims to provide a comprehensive understanding of genetic parameters and their role in selection for yield traits in coriander, with special emphasis on integrating classical quantitative genetics with recent advances in plant breeding to enhance selection efficiency and develop high-yielding, stable cultivars (

Methodology of Review

Literature included in the present review was collected from scientific databases such as Google Scholar, Scopus, Web of Science, ScienceDirect, and ResearchGate. Research articles published mainly between 2015 and 2025 related to genetic variability, heritability, genetic advance, correlation analysis, path coefficient analysis, genetic divergence, and breeding approaches in coriander (Coriandrum sativum L.) were critically reviewed. Relevant keywords including "coriander genetic variability", "heritability in coriander", "yield traits in coriander", "path coefficient analysis", "genetic divergence", and "molecular breeding in coriander" were used during literature searches. Priority was given to peer-reviewed research articles, review papers, and recent advancements in plant breeding and quantitative genetics.

Literature Review

In Coriandrum sativum L., substantial variability has been reported for yield and its contributing traits across diverse environments, indicating the presence of exploitable genetic diversity ( [6] . The global cultivation area and production of coriander have steadily increased due to rising demand for its seeds and leaves, firmly establishing it as a commercially valuable crop (Basol et al., 2024; Singh et al., 2021) [6] . The present review synthesizes recent information on genetic variability, heritability, correlation, and divergence into a unified framework for selection. By emphasizing consistently important traits across studies and integrating recent advancements, this review provides a more comprehensive and application-oriented approach to coriander improvement, offering new insights for future breeding programmes (Ali et al., 2024; Rai et al., 2024; Kumar et al., 2021). In general, higher estimates of genotypic and phenotypic coefficients of variation for yield-related traits indicate wider genetic diversity among coriander genotypes. Traits showing high variability provide greater opportunities for effective selection and genetic improvement. However, differences in variability estimates across studies also indicate the influence of environmental conditions and genotype × environment interactions on trait expression. [1, 2] . The identification of genetically diverse parents is important for broadening the genetic base and improving heterosis in breeding programmes. Multivariate techniques such as principal component analysis and cluster analysis help classify genotypes into distinct groups based on multiple traits, thereby assisting breeders in selecting suitable parents for hybridization.

Modern Breeding Approaches in Coriander

Over the last decade, research in coriander has increasingly focused on integrating classical breeding methods with modern statistical and genomic tools to improve selection efficiency. Multi-environment trials have gained importance for identifying stable and high-yielding genotypes, while advanced analytical methods have improved the accuracy of genetic parameter estimation (Basol et al., 2024; Heffner et al., 2019) [2] . However, the adoption of genomic tools and marker-assisted selection in coriander breeding is still in its early stages, representing a critical gap between available technologies and their practical application (Crossa et [1, 7, 8] . The integration of molecular breeding tools with conventional selection approaches can significantly improve breeding efficiency in coriander. Marker-assisted selection enables early identification of superior genotypes, while genomic selection improves prediction accuracy for complex quantitative traits. Despite their potential, these advanced breeding technologies remain underutilized in coriander improvement programmes.

Genotype × Environment Interaction

Genotype × environment interaction plays an important role in the expression of quantitative traits in coriander. The performance of genotypes often varies under different environmental conditions due to climatic and soil differences. Therefore, multi-location and multi-season testing are essential for identifying stable and adaptable genotypes suitable for wider cultivation. Stability analysis helps breeders select genotypes with consistent performance across environments and improves the reliability of selection programmes. [5] .

Research Gaps and

In addition, correlation and path coefficient studies help identify which traits contribute most to yield. [3, 6] .

References

1. Crossa J, Pérez-Rodríguez P, Cuevas J, MontesinosLópez O, Jarquín D, de Los Campos G, et al. Genomic selection in plant breeding: Methods, models, and perspectives. Trends Plant Sci. 2017;22(11):961-975.
2. Heffner EL, Sorrells ME, Jannink JL. Genomic selection for crop improvement. Crop Sci. 2009;49(1):1-12. DOI:10.2135/cropsci2008.08.0512.
3. Mishra BK, Dubey PN, Mishra PK. Coriander: Production, processing and value addition. Int J Seed Spices. 2019;9(2):1-8.
4. Patel NB, Patel AI, Desai DT. Genetic variability, correlation and path analysis studies in coriander (Coriandrum sativum L.). Int J Chem Stud. 2019;7(4):2345-2349.
5. Singh D, Meena RS, Kumar S. Genetic variability, heritability and genetic advance studies in coriander (Coriandrum sativum L.). J Pharmacogn Phytochem. 2019;8(3):1450-1454.
6. Singh H, Sharma A, Verma S. Importance and medicinal properties of coriander (Coriandrum sativum L.): A review. Pharma Innov J. 2021;10(5):123-128.
7. Varshney RK, Sinha P, Singh VK, Kumar A, Zhang Q, Bennetzen JL. 5Gs for crop genetic improvement. Curr Opin Plant Biol. 2020;56:190-196. DOI:10.1016/j.pbi.2019.102015.
8. Xu Y, Li P, Zou C, Lu Y, Xie C, Zhang X, et al. Enhancing genetic gain in the era of molecular breeding. J Exp Bot. 2017;68(11):2641-2666. DOI:10.1093/jxb/erx135.
9. Yadav R, Meena SS, Choudhary R. Genetic variability and character association studies in coriander (Coriandrum sativum L.). Biol Forum Int J. 2022;14(2):120-125.