Exploring and Understanding the Association between Yield and its Components in Sesame using Correlation Analysis

Sesame (Sesamum indicum L.) is an ancient oilseed crop belonging to the family Pedaliaceae (Abdipour et al., 2018; Pathak et al., 2017). This family includes 31 species distributed across Africa, Southeast Asia, Melanesia and Australia (IPGRI and NBPGR, 2004; POWO, 2019). Sesame can be grown in both tropical and subtropical regions and is rich in genetic diversity. It is renowned for its high-quality seed oil and numerous nutritional health benefits, often being referred to as the “queen of oil seeds.”(Sudha sundari et al., 2024). Sesame is suitable for dryland farming due to its drought tolerant nature and adaptability to high temperature (Tripathi et al., 2013).

In 2018, global sesame production was recorded to be 12.22 million tons (Girmay, 2018), with Sudan, Myanmar and India being the leading producers worldwide (Tripathi et al., 2023). India alone accounts for more than 40% of the world’s sesame cultivation area and 27% of its production (UNSD, 2017; FAOSTAT, 2022), with an average productivity of around 441 kg/ha. The major sesame grown areas of India are Maharashtra, Rajasthan, Odisha andhra Pradesh, Tamil Nadu, West Bengal, Gujarat and Karnataka (Anishetra and Kalaghatagi, 2021). Since sesame is often grown on poor and marginal lands, increasing yield appears to be essential and a challenging task for breeder. So, the primary goal of any breeding program is yield improvement. Genetically, crop yield is controlled by polygenes and is quantitative in nature, making it complex to dissect and directly enhance the yield. Therefore, the present study aims to identify and analyze the most reliable yield-attributing traits through correlation and path coefficient analysis. By partitioning traits into direct and indirect effects via path coefficient analysis, researchers can uncover the true relationship prevailing between the yield and its component traits. For years, plant breeders have employed correlation and path coefficient analysis as one of the valuable tools to assist in the selection process of crop improvement.

The experiment was conducted at Pandit Jawaharlal Nehru college of Agriculture and Research Institute, Karaikal during summer, 2023. Forty sesame genotypes listed in Table 1 were collected from various research institutes such as National Bureau of Plant Genetic Resources, New Delhi (36) and Regional Research Station, Virudachalam (VRI), Tamil Nadu Agricultural University (10) and Tamil Nadu Agricultural University, Coimbatore (1), Regional Agricultural Research Station, Polasa, Jagital (2) and one local type from Puducherry (PY). The experiment was laid out in completely Randomized Block Design with three replications. These forty genotypes were raised by adopting a row spacing of 30 cm and plant spacing of 15 cm. Standard agronomy practices were adopted throughout the study.  From each genotype five plants were randomly selected to record the biometrical data for the following characters viz., plant height (cm), days to 50% flowering (DF), number of primary branches per plant (NPB), number of capsules per plant (NCP), days to maturity (DM), number of seeds per capsule (NSC), capsule length (CL) (cm), 1000 seed weight (TSW) (g) and seed yield per plant (SYP) (g). All these data were recorded during physiological maturity except days to fifty percent flowering which was recorded from the date of onset of flowering to the extent of fifty percent of plants started flowering. However, the number of seeds per capsule, capsule length (CL) (cm), 1000 seed weight (TSW) (g) and seed yield per plant were measured after harvest. Statistical analysis was performed using STAR package of IRRI, version 2.0.1, (2014). The correlation between the quantitative traits were estimated and also the direct and indirect effects by path coefficient analysis were studied using the method suggested by Dewey and Lu (1959).

Correlation coefficient analysis is a valuable tool for determining the strength of the linear relationship between yield and yield-supporting traits in sesame. The genotypic correlation coefficients of seed yield per plant with other traits are presented in Table 2. Understanding the degree of association between these traits are crucial for identifying key components in selection processes aimed at yield improvement.



Among the traits studied, the number of capsules per plant exhibited the highest significant positive correlation with single plant yield (r = 0.731, p<0.01), indicating its strong influence on yield improvement. This was followed by plant height (r = 0.605), the number of primary branches (r = 0.524), thousand seed weight (r = 0.498) and capsule length (r = 0.492). As shown in Fig 1, the correlation aligns with findings of Bharati et al. (2014), who reported positive correlations for the number of primary branches, thousand seed weight and the number of capsules per plant. Similarly, Vanishree et al., (2013) confirmed the positive correlation between the number of capsules per plant, thousand seed weight and capsule length, further supporting the present study’s results.



The characters days to fifty percent flowering, days to maturity and number of seeds per capsule recorded non-significant positive correlation as similar to the result concluded by Kumhar et al., (2020). Though these characters recorded non-significant positive correlation, it is considered to be an important while selecting the lines for early maturation.

In addition to examining how other traits are directly associated with yield, studying the intercorrelation among these traits and seed yield per plant is crucial for understanding their relationship and establishing appropriate selection criteria to improve the yield. The trait plant height showed a high significant positive inter-correlation with the number of capsules per plant, followed by capsule length, thousand seed weight, days to fifty percent flowering and days to maturity as reported by Goudappagoudra et al., (2011) and Akbar et al., (2011). Interestingly, days to fifty percent flowering exhibited a significant positive inter correlation with days to maturity as reported by Roy and Pal (2019) and the number of capsules per plant, whereas non-significant negative correlation with number of seeds per capsule and seed thousand weight. This implies that days to fifty percent flowering does not influence the seed yield parameter.  

Moreover, the number of primary branches was significantly positively inter correlated with the number of capsules per plant, capsule length and thousand seed weight. It also displayed a non-significant positive correlation with days to maturity. Similar observations were reported by Solanki and Gupta (2001); Vidhayavathi et al., (2005), confirming the association between these traits and their collective impact on yield.

Notably, the number of seeds per capsule registered a negative correlation with thousand seed weight (r = -0.215), indicating seed weight and number are not directly proportionated. Conversely, it showed a positive significant correlation with capsule length, suggesting the complex interplay between these traits.

According to Bhatt (1973) correlation analysis might not be adequate to completely explicate the strength of interactions. Hence path analysis was used in this study to delineate the direct and indirect effects of each trait towards the correlated variable. The key important traits such as plant height, thousand seed weight, number of capsules per plant recorded positive direct effect towards seed yield per plant as corroborated by Yingzhong and Yishnu (2002) and Srikanth and Ghodke (2022). The diagonal values in the Table 3 represents the positive direct effect over single plant yield. These traits should be prioritized in selection strategies for yield enhancement. In contrast, days to fifty per cent flowering demonstrated a negative direct effect on yield (path coefficient = -0.285), which is in concordance with the report of Abate and Mekbib (2015). This finding suggests that selecting for earlier flowering genotypes may not always favor yield improvement and underscores the importance of balancing flowering time with other traits.



Indirect effects reveal additional layers of complexity. Plant height, for instance, exerted a positive indirect effect on yield through its influence on the number of primary branches, the number of capsules per plant, capsule length and thousand seed weight. Fazal et al., (2015); Sumathi and Muralidharan (2011) reported similar interactions, highlighting the importance of considering both direct and indirect pathways in plant breeding programs.

The indirect effect of days to fifty percent flowering on seed yield, primarily mediated through days to maturity, indicated a potential interaction between these phenological traits that warrants further exploration. Meanwhile, thousand seed weight demonstrates a positive indirect effect via plant height, number of primary branches, number of capsules per plant and capsule length suggesting its multifaceted role in contribution to yield.

The study reported a residual effect of 0.21, indicating that 79% of the traits were included in the study to understand the component characters contributing to seed yield per plant. Overall, the combination of correlation and path analysis underscores the importance of selecting sesame genotypes with traits such as more number of capsules with increase in primary branches, thousand seed weight and plant height to enhance the yield of the crop.

Sesame is widely cultivated in marginal and poor lands with low input technologies. Increasing the productivity is the major issue for the plant breeder who desires to bring notable improvement in the yield. Hence it is worthwhile to understand the relationship of independent variables along with its magnitude on dependent trait. In this background the present study revealed the strong associations of the characters such as plant height, number of primary branches, thousand seed weight and capsule length with seed yield. Further to explore the correlated responses between variables, the cause and its effect were studied through path coefficient analysis. Some of the traits are discerned to create large impact on seed yield directly via plant height, number of primary branches, number of capsules per plant, capsule length and thousand seed weight and also indirectly via days to maturity. Thus, the characters, number of capsules per plant, plant height, number of primary branches and thousand seed weight were identified as selection criteria for improving yield in sesame genotypes, as these traits recorded positive correlation as well as high positive direct effect with seed yield.

The present study was not funded by any project work. The authors sincerely thank National Bureau of Plant Genetic Resources (NBPGR) New Delhi, Regional Agriculture Research Station (RRS) Jagital and Regional Research Station (RRS) Virudachalam, Tamil Nadu Agricultural University (TNAU), for providing the seed materials to  conduct the experiment.
 
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The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
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All animal procedures for experiments were approved by the Committee of Experimental Animal care and handling techniques were approved by the University of Animal Care Committee.

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.