An experiment was conducted on 30 farmer's rice varieties collected from different districts of Madhya Pradesh to identify the genetic components contributing to phenophasic development, physiological, yield attributes and biochemical traits. Principal component analysis was performed to rank the farmer's varieties based on PC scores acquired as per the trait studied. Out of twenty one traits studied, only five principal components (PCs) exhibited more than 1.00 Eigen value and showed 84.24 % of total cumulative variability. The PC1 showed 42.46%, while PC 2, PC 3, PC 4 and PC 5, exhibited 20.97%, 9.60%, 6.18% and 5.02% variability, respectively. The PC1 which accounted for the highest variability (42.46%) was mostly associated with major physiological parameters and yield related traits. The PC 2 was dominated by biochemical traits, while PC3 was mostly dominated for some phenophases and yield related traits. The PC 4 was dominated by only one trait i.e. chlorophyll content index, and PC5 was dominated by test weight. Farmer's variety Pandu was superior for Chlorophyll content index (38.27), total dry matter production (38.15 g plant'), Leaf area index (4.09). Leaf area duration (17982 cm days) and crop growth rate (0.00282 g m² day), PCA revealed that the genotype Garudluchai (7.260) acquired highest positive value PCs followed by Navari (4.161), Vishnubhog (3.641) and Krishnabhog (3.063) respectively. Farmer’s varieties Garudluchai, Uraiboota, Karhani contributed their presence in maximum PCs of this investigation. The identified lines will be utilized in the rice breeding programme to develop improved rice varieties for high yield and maximum physiological efficiency

Principal component analysis, farmer’s varieties, rice, physiological parameter and morphological responses

In the present investigation the genotype Garudluchai (7.260) contributed highest PC score among all the genotypes included in this study. Similarly, genotype Navari (4.161) and Vishnubhog (3.641) from PC1 contributed highest positive value from all of the five PCs. Here, the genotypes contributing highest PC score (>5.0) could be considered for the best genotypes selection. PC1 was dominated with physiological parameters and yield attributing traits and selection of genotypes from these PCs will be helpful for the identification of donor for the transfer of physiological parameters and yield attributing traits. On the basis of PCA findings, among all genotypes contributing their presence in more than one PC with high PC score only three genotypes viz., Garudluchai, Uraiboota, Karhani confine with desirable physiological, yield associated traits. These lines might be utilized in hybridization programme the development of promising rice cultivars

Abhiraj, R. Shiv Ramakrishnan, Parikha Prakash Singh, Sakshi Mishra, Ayushi Dubey, Jhilick Banerjee, Madhana Keerthana S., Radheshyam Sharma, Ashish Kumar, Stuti Sharma, Sanjay Singh and G.K. Koutu (2025). Genetic Diversity Analysis to Identify Superior and Physiologically Efficient Farmers Varieties of Rice Collected from Madhya Pradesh. Biological Forum, 17(5): 41-49