Satyanarayana et al., Biological Forum – An International Journal 15(11): 329-335(2023) 329 ISSN No. (Print): 0975-1130 ISSN No. (Online): 2249-3239 Association Studies for Identifying the Selection Criteria Among Early varieties of Rice in North Coastal Zone of Andhra Pradesh P.V. Satyanarayana, K. Madhu Kumar, P. Uday Babu, T. Srinivas and Duppala Manojkumar * Agricultural Research Station, Ragolu, Acharya N G. Ranga Agricultural University (ANGRAU) (Andhra Pradesh), India. (Corresponding author: Duppala Manojkumar * ) (Received: 07 September 2023; Revised: 07 October 2023; Accepted: 19 October 2023; Published: 15 November 2023) (Published by Research Trend) ABSTRACT: Rice yields were affected by various heritable and non-heritable components, the present investigation was undertaken to study the variability, heritability, genetic advance, character associations, path coefficients, principal component analysis of yield component traits along with principal component analysis study in early duration varieties of rice for identification of effective selection criteria for grain yield improvement. A notable observation was made regarding the high phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV), accompanied by elevated heritability and genetic advance as a percentage of the mean for traits such as filled grains per panicle, total grains per panicle, test weight, and grain yield per plant. This suggests the viability of direct phenotypic selection for enhancing these characteristics. Principal component analysis revealed that four principal components with eigenvalues exceeding 1 accounted for 86.5% of the variability in PC1. Filled grains per panicle and total grains per panicle contributed significantly to this variability, with filled grains per panicle showing a positive direct effect and a noteworthy positive correlation with grain yield per plant. Consequently, filled grains per panicle is identified as a promising selection criterion for improving grain yield in the early stages of rice crop cultivation. Keywords: Rice, Correlation Analysis, Genetic Advance, Heritability, Path Analysis, Principal component analysis. INTRODUCTION Rice serves as the fundamental food source for over 100 countries globally and plays a vital role in nourishing nearly 70% of the world's population. It holds significant dietary and food security importance, particularly in numerous Asian nations. India, ranking second globally in rice production, contributes 22% to the total global rice output (Duppala et al., 2023), following China. However, the direct phenotypic selection for grain yield poses challenges due to its complex nature, relying on multiple traits, often being polygenic, and heavily influenced by environmental factors. As a result, such direct selection methods are frequently ineffective. Therefore, the identification of effective criteria for enhancing grain yield becomes a top priority. In this context, the exploration of heritability and genetic advance of yield component traits emerges as a crucial area of study. An analysis of the association of yield component traits with grain yield and their inter-associations is also important for formulation of effective breeding strategy to improve grain yield (Awad et al., 2022; Bakya et al., 2020; Priyanka et al., 2019; Rao et al., 2021). Further, to detect the traits, having high influence on grain yield, path analysis is commonly applied to elucidate information on the relative direct and indirect contribution of each component character towards yield and help the breeders in formulation of effective selection criteria for grain yield improvement. Principal Component Analysis (PCA), a reduction approach for multivariate data, is increasingly utilized to evaluate the relevance and contribution of each factor to the overall variance as well as to provide information on the impact of a particular attribute on the total variance was employed (Bhargavi et al., 2023; Prasanth et al., 2023; Ratnam et al., 2022 and Sharma et al., 2021). In this context, the study was initiated using advanced breeding lines of rice having desirable characters to have a variety which is high yielding combined with early duration to cater the farmer needs from the states of Andhra Pradesh and Telangana. The present study, reports the extent of genetic variability, inter- relationships and path coefficients, principal component analysis for grain yield and yield contributing traits in the advanced breeding lines of rice. MATERIAL AND METHODS The current study was conducted at the Agricultural Research Station, Ragolu, situated in the North-Coastal districts of Andhra Pradesh. Sixteen genetically pure seeds from improved breeding lines, developed by Acharya NG Ranga Agricultural University Biological Forum – An International Journal 15(11): 329-335(2023)