INTRODUCTION The common oat (Avena sativa L.) is cereal crop grown primarily for its green fodder and grains. Oats grain are suitable for human consumption whereas green and dry fodder is used as livestock feed. It belongs to family Poaceae and has three naturally occurring ploidy levels namely; diploid (2n=2x=14 having A and C genome), tetraploid (2n=4x= 28 with AB and AC genome) and hexaploid (2n=6x=42 containing ACD genome) (Loskutov, 2008). Oat is grown in 25.3 m ha area of the world producing 49.6 mt. of grains globally with a productivity of 1963 kg per hectare. The country's total oat-growing area is estimated to be around 5,000 acres. Uttar Pradesh has the most area under cultivation (34 percent), followed by Punjab (20 percent), Bihar (16 percent), Haryana (9 percent), and Madhya Pradesh (6 percent) (IGFRI, 2019).Whole (unhusked) oats produce/feeds have a high protein (12%), fat (5%), fibre (12–15%), and carbohydrate content when compared to other grains (about 64 percent).Oat green fodder contains 20 % dry matter, 10 % crude protein and 91 % organic matter. Oat straw is more nutritious and palatable than wheat straw as well as an important supplementary feed. It contains high amount of important vitamins and minerals such as vitamin E, Vitamins B, calcium, phosphorus, magnesium and potassium. The amino acid profile of proteins in oats kernel is considered to be in perfect proportion (Nanda et al., 2017). Oat protein is nearly equivalent in quality to soy protein, meat, milk and egg proteins which has been reported by WHO. The protein content of the hull-less oat kernel ranges from 12 to 24 per cent, which is the highest among cereals (Lasztity, 1999). Oat is also an important winter forage crop in many parts of the world. It includes total dietary fibre, including the soluble fibre -glucan, and is high in antioxidants such as -tocotrienol, -tocopherol, and avenanthramides, unlike other cereal grains such as wheat and barley (Oliver et al., 2010). Animal feeding systems are primarily based on grazed native grasslands, which are declining in terms of productivity and quality, as well as varying seasonally, resulting in poor animal performance. Despite the importance of livestock, poor animal nutrition is a prevalent problem in developing nations and a key stumbling block to the development of viable livestock industry. In India, the available feed supply is only one-third of what animals require (Younas and Yaqoob 2005). In order to harness potential production of oat, it is facing number of constraints including biotic, abiotic and agronomic stress. The study was conducted to vanquish all these hurdles and provide all necessary information regarding character association present in germplasm for researchers to speedup breeding programme for both fodder and seed production. MATERIAL AND METHODS The current study was conducted during the rabi seasons of 2021 at the CSAUA&T, Kanpur, student instructional farm plot No. 41. The 38 genotypes were obtained from the Jhansi-based Indian Grassland and Fodder Research Institute. The experiment was set up in a three replication using randomized block design, with a plot size of 3 × 1 m2 and row-to-row and plant-to-plant spacing of 30 and 5 cm, respectively. Observations were recorded for: Days to 50% flowering, plant height (cm), tillers per plant, leaves per plant, leaf length (cm), leaf width (cm), fresh plant weight (g), leaf area (cm2), leaf area index, dry weight/plant (g), HI (percent), and grain yield per plant were all measured on three randomly selected competitive plants in each replication (g). The phenotypic, genotypic, and environmental coefficients of correlation were calculated using Al-Jibouri et al. (1958) technique. The significance of the phenotypic coefficient of correlation at (g–2) degrees of freedom and the environmental coefficient of correlation at [(r–1) (g–1) –1] degrees of freedom, where r and g stand for number of replication and genotypes, respectively, was tested against the table (r) values of correlation coefficients at a 5% level of significance (Fisher and Yates 1963). The path coefficient is a standardized partial regression coefficient that allows the direct and indirect effects of a set of variables (component characters) on a dependent variable to be partitioned. As recommended by Dewey and Lu (1959), direct and indirect effects of component characters on green forage yield were calculated using appropriate correlation coefficients of distinct component characters. RESULT AND DISCUSSION The following are some of the components of the current study that have been discussed: correlation studies, and path coefficient analyses, with list of potential genotypes for each character. On the basis or mean performance of all 38 genotypes for all 12 features the observed potential genotype can be used for breeding programs are given in Table 1. The efficiency of any breeding or selection programme is determined by the type and relationship between yield and other characteristics. The coefficients of correlation are provided in Table 2. The phenotypic and genotypic path coefficient analysis is given Table 3 and 4 respectively. Correlation Analysis: The Correlation studies provide details about the nature and magnitude of the association of different component characters with grain yield. Ultimately this could help the breeder to design selection strategies to improve grain and green fodder yield. Genotypic correlation coefficient was generally higher than phenotypic correlation coefficient for all the traits combination. High genotypic correlation compared to its respective phenotypic correlation Kumar et al. (2016). Low phenotypic correlations can be explained due to masking or modifying effects of environment on genetic association between characters. These results are in accordance with reports of Krishna et al. (2014); Poonia et al. (2018); Negi et al. (2019); Gandahi et al. (2021); Altuner (2021). Correlation between grain yield and its associated traits: At genotypic level the grain yield per plant showed a positive and significant correlation with plant dry weight (0.538), harvest index (0.417). Negative non-significant correlation with grain yield is reported with tiller per plant (-0.205), leaf per plant (-0.111), leaf width (-0.296), leaf area (-0.165), leaf area index (-0.171) and non-significant positive correlation observed with leaf length (0.019), days of 50% flowering (0.011). Similar result were observed by Deep et al (2019); Tessema and Getinet (2020); Mecha et al. (2017); Baye et al. (2020) for harvest index. Bibi et al. (2012), Kumar et al. (2016) for tillers per plant. At phenotypic level the grain yield per plant showed a positive and significant correlation with plant dry weight (0.531), harvest index (0.412). Negative non-significant correlation with grain yield is reported with tiller per plant (-0.188), leaf per plant (-0.108), leaf width (-0.285), leaf area (-0.160), leaf area index (-0.168) and Non-significant positive correlation observed with leaf length (0.014), days of 50% flowering (0.007). The correlation result for one or more characters observed in study in accordance to the finding of Nehvi et al. (2000); Choubey et al. (2001; Tiwari and Pandey (2014); Kumar et al., (2004); Bibi et al. (2012) also reported same result for tiller per plant. Correlation between green fodder/fresh weight yield and its component traits: After grain yield green fodder yield is the second most important traits in which breeders are interested to improve. Oat as a fodder has more desirable in relation of its palatable and nutritional quality compared to the other crop straw. Fodder yield association studied on total six characters. At genotypic level for green fodder/fresh weight the positive and significant correlation were observed with plant height (0.655), tillers per plant (0.457) leaf per plant (0.812), leaf length (0.513) and leaf width (0.497). For tiller per plant similar result were observed by Gandahi et al. (2021). At phenotypic level for green fodder /fresh weight the positive and significant correlation were observed with plant height (0.639), tillers per plant (0.414), leaf per plant (0.726), leaf length (0.494), leaf width (0.461). At both genotypic and phenotypic level positive and significant correlation for green fodder /fresh weight, the similar result were observed by Bibi et al. (2012) for number of tillers per plant, Dubey et al. (2014) for tillers per plant, leaf per plant, Devi et al. (2018) for tillers per plant, leaf per plant, Choudhary et al. (2020) for plant height, Negi et al. (2019) for tillers per plant. Path Coefficient analysis: Path coefficient analysis Wright, (1921), Dewey and Lu, (1959) is useful for partitioning correlations into direct and indirect effects of a single causal factor, determining the degree of relationship between yield and its component effects, and examining specific factors that provide a given correlation. The direct genotypic effect on grain yield were exerted by leaf per plant (0.585), Leaf area index (1.417), dry weight (0.886), harvest index (0.895). The negative significant direct effect observed by fresh weight (-0.359), leaf area (-1.652). Positive non-significant direct effect observed for plant height (0.198), leaf width (0.037), Days of 50% flowering (0.118) and negative non-significant effect were observed for characters tillers per plant (-0.149), leaf length (-0.074). The result observed in study in accordance to the finding of Dubey et al. (2014); Krishna et al. (2014); Jaipal and Shekhawat (2016). At phenotypic level the direct positive significant effect on grain yield were observed by leaf area (0.447), dry weight (0.926), harvest index (0.840). The negative significant direct effect observed for leaf area index (0.440). The negative non-significant direct effect observed for character tiller per plant (-0.046), leaf length (-0.067), leaf width (-0.077), fresh weight (-0.016) and positive non- significant direct effect observed for plant height (0.080), leaf per plant (0.066), days of 50% flowering (0.068).