Analysis of Genetic Variability and Association for Yield Traits in Rice (Oryza sativa L.) Germplasm Lines

As an essential staple crop, rice (Oryza sativa L.) contributes >50% of total food production worldwide. It is classified as part of the Poaceae family and is cultivated effectively in diverse environments, including lowland flooded fields, rainfed uplands and coastal areas, in a wide range of agroclimatic zones. Besides its economic and nutritional importance, rice also has considerable cultural, religious and heritage significance, for instance in Asia, where it is omnipresent in the life of people. Rice is a major source of carbohydrates and is essential to the world’s dietary needs and food safety. (Yu et al., 2024). But global rice production is not without challenges: climate change, soil erosion, water scarcity and shifting weather patterns. The food and agriculture organization (FAO) has information indicating rice production around the world increased from about 509 million tonnes in 2020 to almost 520 million tonnes in 2023. Asia continues to be the epicenter for rice production, with both China and India among its top contributors. Rice production in India registered an increase, from 118.87 million tonnes in 2019-20 to130.29 million tonnes in 2022-23, according to the Department of Agriculture  and Farmers Welfare. Tamil Nadu in particular is one of India’s major rice-growing states, producing between 8 to 10 million tonnes every year. The yield of rice varies considerably depending on the variety and agro-climatic conditions, ranging from 3.5 to 4.2 tonnes per hectare (Naik et al., 2021).
       
Rice production productivity has also improved significantly through rice mechanization, high-yielding varieties and advanced irrigation systems. But now, sustainable rice production is increasingly threatened by unpredictable monsoon patterns, increased insect pest invasions and deteriorating soil health. As such, it will require innovative practices and policies that address these issues for the future of rice agriculture. India serves as a significant reservoir of rice diversity, with several traditional rice landraces with unique adaptability to local climate and resistance to various stresses, besides being highly nutritious (Shoba et al., 2021; Naik et al., 2021). Recent studies highlight the need to safeguard these landraces for future breeding programs to create nutrient-enriched and climate-resilient rice (Shoba et al., 2019; Ramesh et al., 2024). Karuppu Kavuni (Rajan et al., 2019) reacts to a rich source of antioxidant anthocyanins and Mappillai Samba (Selvi et al., 2023) is rich in iron and zinc and promotes strength and endurance are examples of such rice varieties. Kumar et al.,(2024) recommended consumption of Poongar, a drought resistant medicinal rice, especially for expectant mothers because of its excellent nutritional profile. Kattuyanam is an important flood- resistant race; Seeraga Samba is well known for its unique flavor and pest resilience to reduce chemical input (Arunkumar et al., 2020).
       
To protect genetic diversity and enhance future food security, it is crucial to implement comprehensive conservation and documentation strategies for traditional rice. Advances in genetic research methods, such as genetic variability and correlation analysis, can significantly enhance our understanding of the breeding potential of these landraces. With increasing demands for climate adaptation and improved nutrition, interest in traditional rice continues to grow. Therefore, integrating traditional rice varieties into mainstream breeding efforts will be essential for fostering sustainable rice farming and ensuring global food security. A collaborative approach that emphasizes expanded research, supportive policies and dedicated conservation initiatives will be pivotal in maintaining biodiversity and securing the future of rice agriculture.

The yield and yield components of 130 lines (Table 1) of genetic material were observed in a field. These rice genotypes were sown in an augmented design at SRM College of Agricultural Sciences during Kharif 2024. Each rice genotype was sown in three rows with a 30 cm × 30 cm spacing. Yield and yield component data at maturity were recorded from five randomly tagged plants per genotype for each replication. Data on eleven agronomic characteristics were: plant height (PH), length of flag leaf (LFL), weight of the leaf (WL), length of the panicle (LP), internode length (INL), productive tillers per plant (PTP), grains per panicle (GP), weight of thousand grain (WTG), yield per plant (YP) and for every genotype in every replication, morphological data for days to maturity (DM) and days to fifty per cent flowering (DFF) were observed on plot basis.

The evaluation of the genetic variability parameters of association, mean, range, genetic variability, heritability, genetic advance for the 130 rice genotypes in each of the 11 yield attributing traits is required (Singh et al., 2024 and Sheshnath et al., 2017) for the selection of successful breeding programme (Table 2).


       
Plant height, days to 50% flowering and days to maturity was not suitable for selection, since it is indicating moderate GCV and PCV which is influenced by the environment on these traits (Upadhyaya et al., 2010). For days to 50% flowering, Rajkumar and Ibrahim (2025) obtained similar results. It is possible that the environment influences these traits because internode length has a little genotypic coefficient of variation (GCV) and a high phenotypic coefficient of variation (PCV).
       
The traits of length of flag leaf, weight of the leaf, productive tillers per plant, length of the panicle, weight of thousand grain, grains per panicle, yield per plant had high PCV and GCV. This suggests significant variations for these traits (Maurya et al., 2022; Divya et al., 2018 Ranjani et al., 2018).
 
Heritability and genetic advance as per cent of mean
 
Heritability estimates demonstrate the patterns of trait inheritance. The advancement of genetics facilitates the development of selection strategies (Kaushik et al., 2007). Genetic advancement and heritability in leaf weight and internode length are minimal. This trait indicated non-additive gene action. Nath and Alam (2002) asserted that phenotypic selection for these traits was not likely to yield improvement.
       
Several traits showed high genetic advance and high heritability such as plant height, days to fifty percent flowering, days to maturity, length of the panicle, productive tillers per plant, length of the flag leaf, weight of thousand grain, grains per panicle and yield per plant. Hence, the aforementioned traits may be under the control of additive gene action. So, selection for these traits would be rewarding, immediately. This implied that additive gene activity primarily governs these traits, enabling improvement by direct selection. Divya et al., (2018) reported comparable findings regarding the weight of thousand grain, productive tillers per plant and number of grains per panicle while Shaili et al., (2022) observed the positive correlation between the number of grains per panicle and plant height.
 
Correlation among yield components
 
The data illustrated the relationships for correlation among yield components. This understanding will contribute towards improving yield traits and overall productivity in breeding programs (Table 3).


       
Days to 50% flowering exhibited positive correlation with days to maturity (DM), plant height (PH) and negative correlation with flag leaf length (FLL), leaf weight (LW), internode length (INL), number of productive tillers (NPT) and number of grains per panicle (NGP). According to Kamana et al., (2019), plant height and the number of days till 50% flowering were positively correlated.
       
Days to maturity had positive correlation with plant height and had negative correlation with flag leaf length (FLL), leaf weight (LW), internode length (INL), number of productive tillers (NPT) and number of grains per panicle (NGP). Plant height is significantly correlated with the flag leaf length (FLL), leaf weight (LW), panicle length (PL), internode length (INL). Flag leaf length had positive correlation with leaf weight (LW) and internode length (INL). Leaf weight had negative correlation with panicle length (PL) and internode length (INL). Panicle length was significantly positively correlated with internode length (INL) and negatively correlated with number of grains per panicle (NGP). These results were agreement with Iqbal et al., (2018).
       
Thousand grain weight is significantly negatively correlated with days to fifty percent flowering (DFF), plant height (PH), flag leaf length (FLL), panicle length (PL), internode length (INL), number of productive tillers (NPT), number of grains per panicle (NGP) and thousand grain weight (TGW). This result was in conformity with the earlier findings of Ramanjaneyulu et al., (2014).
       
Single plant yield (SPY) was positively correlated with number of productive tillers (NPT), number of grains per panicle (NGP) and thousand grain weight (TGW) and negatively correlated with days to fifty percent flowering (DFF), days to maturity (DM), plant height (PH) and flag leaf length (FLL). In selecting traits to enhance yield, it is suggested to prioritize these characteristics. Similar associations were previously reported by Pachauri et al., (2017).
               
The traits flag leaf length (FLL), leaf weight (LW), panicle length (PL), number of productive tillers (NPT), number of grains per panicle (NGP), thousand grain weight (TGW), single plant yield (SPY) exhibited a high magnitude of genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV), indicating potential for improvement through selection. A significant heritability was observed along with a substantial genetic advance as a percentage of the mean for the traits days to fifty percent flowering (DFF), days to maturity (DM), plant height (PH), flag leaf length (FLL), panicle length (PL), number of productive tillers (NPT), number of grains per panicle (NGP), thousand grain weight (TGW), single plant yield (SPY) suggests that these traits were predominantly controlled by additive gene action, indicating that selection for these characteristics would be more effective for achieving the desired genetic improvement.

The evaluation of 130 rice genotypes across 11 yield-attributing traits revealed significant genetic variability for several key characteristics, including flag leaf length, leaf weight, productive tillers per plant, panicle length, thousand grain weight, grains per panicle and yield per plant. These traits exhibited high PCV and GCV, suggesting substantial scope for genetic improvement through selection. Furthermore, traits like days to 50% flowering, days to maturity, plant height, flag leaf length, panicle length, productive tillers per plant, grains per panicle, thousand grain weight and single plant yield demonstrated high heritability coupled with high genetic advance as a percentage of the mean, indicating the predominance of additive gene action and the potential for effective improvement through direct selection. Conversely, plant height, days to 50% flowering and days to maturity showed moderate GCV and PCV, suggesting a greater environmental influence, while leaf weight and internode length displayed minimal heritability and genetic advance, implying non-additive gene action and limited improvement through phenotypic selection. Correlation analysis further highlighted significant relationships among yield components, providing valuable insights for developing effective breeding strategies aimed at enhancing yield and overall productivity in rice. Prioritizing traits such as productive tillers per plant, number of grains per panicle and thousand grain weight, which showed positive correlations with single plant yield, is recommended for achieving yield enhancement in breeding programs.

All authors declared that there is no conflict of interest.