INTRODUCTION Green gram [Vigna radiata (L.) Wilczek] is considered as the most consequential legume crop in India. Green gram is a self-pollinating pulse crop that belongs to the Fabaceae family and has a 2n=22 somatic chromosomal number. Green gram had supposed to be originated from Indian subcontinent. It is a warm season and frost intolerant crop and suitable for cultivation in temperate, tropical and sub-tropical regions. It is widely cultivated in India, Bangladesh, Pakistan, Thailand, Sri Lanka, Malaysia and Indonesia. India is one of the world’s leading grower and user of green gram. Green gram is a popular legume crop because to its short growing season, minimal input requirements and great digestibility due to reduced gas generation (Shil and Bandopadhya 2007). It works well in intense crop rotations since it has a short growing season. In some sections of country, the crop is also farmed for fodder. Green gram is recognized for their magnificent nutritive values. It is a good source of proteins, fats, vitamins and several minerals viz., calcium, magnesium, iron, manganese, phosphorus, potassium and zinc and is great source of antioxidants like flavonoids, phenolic acid, cinnamic acid and caffeic acid. These nutritive properties have great health benefits and reduce risk of chronic diseases such as heart diseases, cancers and diabetes. Green gram also helps in atmospheric nitrogen fixation in soil making it suitable for green manure and cover crop. Despite of such an important crop the average productivity of green gram is quite low as expected due to several reasons. Narrow genetic base and insufficient knowledge of genetics of crop is a major drawback. Yield is a complicated attribute that is influenced by several attributing characters either directly or indirectly. In developing a breeding program, understanding the genetic relationship of yield and its contributing factors is critical. Correlation analysis helps a breeder to perform both direct and indirect selection of yield attributing traits. Path coefficient analysis provides the information whether the relationship of yield attributing traits with yield is due to direct effect on yield or due to their indirect effect via some other component traits. The present investigation was carried out to evaluate the relationship between seed yield and its contributing traits in 44 genotypes of green gram. MATERIALS AND METHODS The present study was carried out during kharif 2020, at Research Farm of Sri Karan Narendra College of Agriculture, Jobner, Jaipur (Rajasthan). Forty four green gram genotypes were evaluated in Randomized Block Design (RBD) with three replications (Table 1). Each genotype was sown in two rows in a plot of 2.50 m length, with a row to row and plant to plant distance of 30 and 10 cm, respectively, in each replication. The experimental material was assembled from All India Coordinated Research Project on MULLaRP, Rajasthan Agriculture Research Institute, Durgapura, Jaipur (Rajasthan). The observations for thirteen quantitative traits were observed on ten arbitrarily picked plants from each genotype in each replication for all the following characters namely, plant height (cm), branches per plant, clusters per plant, pods per cluster, pods per plant, pod length (cm), seeds per pod, seed yield per plant (g), protein content (%) and chlorophyll content (SPAD meter reading) with the exception of days to 50% flowering, days to maturity and 1000-seed weight (g) which were reported on plot basis. The genotypic and phenotypic correlation coefficients were determined using the formulas provided Johnson et al., (1955); Singh and Choudhary (1985). Path coefficient analysis was used to assess the direct and indirect effects of various factors on seed yield, as stated by Wright (1921); Dewey and Lu (1959). RESULT AND DISCUSSION Correlation analysis. Knowing the interrelationships between different traits and seed yield is critical for formulating a rewarding breeding program. To determine the magnitude of both environmental and genetic impacts, the correlation coefficients must be evaluated at both phenotypic and genotypic levels. Genotypic coefficient of correlation is considered as the true estimate of correlation as it eliminates the environmental factor. The genotypic coefficient of correlation was greater than the phenotypic coefficient of correlation in the current study, suggested that there was a significant degree of correlation between traits at the genotypic level and its phenotypic expression was depleted by the environmental factors. The traits showing high genotypic correlation with each other and with seed yield are regarded crucial for applying selection pressure to improve seed yield genetically. The genotypic correlation coefficient between 13 traits in 44 genotypes of green gram are shown in Table 2. Days to 50% flowering exhibited positive and significant correlation with days to maturity (0.684) and plant height (0.475), whereas a negative significant correlation with protein content (-0.388). Similar findings were observed by Varma et al., (2018) for days to maturity and plant height. Days to maturity revealed positive significant correlation with plant height (0.272), clusters per plant (0.183), seeds per pod (0.204) and chlorophyll content (0.193). Plant height showed positive and significant correlation with branches per plant (0.560), clusters per plant (0.364), pods per clusters (0.225), pods per plant (0.406) and seed yield per plant (0.221), on the contrary it showed negative significant correlation with pod length (-0.180). Ramakrishnan et al. (2018) also got related results. Branches per plant showed positive and significant correlation with clusters per plant (0.804), pods per plant (0.550), chlorophyll content (0.253) and seed yield per plant (0.592) whereas a negative significant correlation was found with pods per cluster (-0.547), pod length (-0.234), seeds per pod (-0.830), 1000-seed weight (-0.230) and protein content (-0.207). Clusters per plant showed positive and significant correlation with pods per plant (0.847), chlorophyll content (0.336) and seed yield per plant (0.758) while negative significant correlation with pods per cluster (-0.338), pod length (-0.520), seeds per pod (-0.903) and 1000-seed weight (-0.281). Pods per cluster exhibited positive and significant correlation with pods per plant (0.292) and seeds per pod (0.325) while it showed negative and significant correlation with pod length (-0.269). Pods per plant showed positive and significant correlation with chlorophyll content (0.315) and seed yield per plant (0.708) while negative significant correlation with pod length (-0.687), seeds per pod (-0.842) and 1000-seed weight (-0.284). These results were in accordance with findings of Makeen et al., (2007); Narasimhulu et al., (2013) and Ramakrishnan et al., (2018). Pod length revealed positive and significant correlation with seeds per pod (1.428) and 1000-seed weight (0.363) while negative and significant correlation with chlorophyll content (-0.278) and seed yield per plant (-0.234). These findings were in correspondence with investigations of Varma et al. (2018). Seeds per pod exhibited positive and significant correlation with 1000-seed weight (0.341) and protein content (0.568) while negative significant correlation with chlorophyll content (-0.244) and seed yield per plant (-0.289). 1000-seed weight showed positive and significant correlation with protein content (0.179). Protein content exhibited negative and significant correlation with chlorophyll content (-0.322). Chlorophyll content exhibited positive and significant correlation with seed yield per plant (0.233). The highest positive and significant correlation with seed yield per plant was exhibited by the branches per plant, clusters per plant and pods per plant. Such associations were also reported by Biradar et al. (2007); Tabasum et al., (2010); Narasimhulu et al. (2013); Garje et al., (2014); Anand et al. (2016); Bhutia et al. (2016); Sandhiya and Saravanan (2018). This implies that selecting these traits will eventually boost the seed yield per plant. Patel et al., (2014) reported positive and significant association for plant height, 1000-seed weight and protein content and Kate et al. (2017) for days to maturity. Path analysis. Correlation analysis merely reveals the nature and degree of association between two characters, whereas, path analysis helps in understanding the direct and indirect association of characters as well as the relative contribution of different traits with respect to seed yield. As a result, the correlation coefficients were subdivided into direct and indirect effects at both genotypic and phenotypic levels. The seed yield per plant was used as the dependent character and others were considered independent in the present path analysis. Path coefficient values among 13 traits in 44 green gram genotypes are presented in Table 3. Path diagram as shown in Fig. 1 in which seed yield is considered as dependent trait and other traits as independent traits. Direct effect. Pods per plant (1.954) revealed highest direct and positive effect on seed yield per plant followed by branches per plant (1.526), protein content (0.767), pod length (0.427), days to 50% flowering (0.348) and chlorophyll content (0.293). These findings were agreed with those of Haritha et al. (2002); Makeen et al. (2007); Biradar et al., (2007); Thippani et al., (2013); Eswaran and Senthilkumar (2015); Jyothsna et al. (2016); Varma et al. (2018); Mohammed et al. (2020). These results indicate that for yield improvement direct selection for these traits would be rewarding. Whereas clusters per plant (-1.906), plant height (-0.949), pods per cluster (-0.213), seeds per pod (-0.106), 1000-seed weight (-0.047) and days to maturity (-0.032) exhibited negative and direct effect on seed yield per plant. Indirect effect. Seeds per pod (1.721), pods per cluster (0.644) via clusters per plant; clusters per plant (1.654), branches per plant (1.075), plant height (0.793) via pods per plant; clusters per plant (1.227), plant height (0.854), pods per plant (0.839) via branches per plant; seeds per pod (0.61) via pod length had high indirect and positive effect on seed yield per plant. However, seeds per pod (-1.266), pods per cluster (-0.834) via branches per plant; pods per plant (-1.614), branches per plant (-1.533), plant height (-0.694) via clusters per plant; seeds per pod (-1.645), pod length (-1.342) via pods per plant; branches per plant (-0.531) via plant height had high negative indirect effect on seed yield per plant.