Variability Parameters, Correlation Studies and Path Analysis of Yield and Yield-Related Traits in Rice (Oryza sativa L.): A Comprehensive Review

Abstract

Rice, a staple food crop of global importance exhibits substantial diversity in terms of yield and other agronomic traits, influenced by genetic, environmental, and management factors. Variability parameters, including genotypic and phenotypic coefficients of variation, heritability, correlation, and path analysis provide crucial insights into the extent of trait variation and their potential for improvement through breeding programs. Furthermore, correlation studies unveil the interdependencies between different traits, shedding light on potential connections influencing yield. This analysis uncovers important trait associations, guiding breeders and researchers in the pursuit of crop improvement strategies. By identifying both positive and negative correlations, this research offers a deeper understanding of trait interplay and informs targeted trait selection efforts. Path analysis, a pivotal aspect of this review, describes the underlying causal relationships between traits and their direct and indirect effects on yield. This analysis facilitates the ranking of trait contributions and guides decisions for trait prioritization in breeding programs. By illuminating the pathways through which traits influence yield, path analysis enhances the precision of trait selection for improved rice cultivars. The synergy of variability parameters, correlation studies, and path analysis presents a holistic framework for unraveling the complexities of rice yield determination. Understanding these parameters enhances our ability to select and develop high-yielding and resilient rice varieties, contributing to food security and sustainable agriculture. This abstract delves into the significance of variability parameters in unraveling the complexities of rice yield and trait dynamics, guiding effective crop improvement strategies for the future. This review provides a valuable synthesis of existing knowledge, offering insights that can aid researchers, breeders, and agronomists in their pursuit of enhancing rice yield and overall agricultural sustainability.