<![CDATA[Abstract. Dulbari, Maulida D, Ahyuni D, Subarjo, Rahmadi R, Jaya MHIS. 2026. Multivariate analysis of yield and lodging traits in rice genotypes. Biodiversitas 27 (7): d270710. https://doi.org/10.13057/biodiv/d270710. Lodging is a major constraint affecting rice yield stability by reducing photosynthetic efficiency, increasing loss yield, and lowering grain quality. Integrating yield and lodging traits is therefore essential for effective multi-trait selection in rice breeding programs. This study aimed to evaluate phenotypic diversity, identify trait relationships, and determine potential parental genotypes using a multivariate approach. The experiment was conducted using a randomized complete block design with three replications and 20 rice genotypes. Quantitative traits were analyzed using Principal Component Analysis (PCA) after Z-score standardization. Hierarchical clustering and heatmap visualization were performed using Euclidean distance and Ward's method, while the integration of quantitative and qualitative traits was carried out using the Gower coefficient. The first two principal components explained 50.3% of the total variation (PC1 = 29.8%; PC2 = 20.5%). PC1 was associated with biomass-related traits, while PC2 represented structural traits and yield-loss indicators. Cluster analysis grouped genotypes into four distinct phenotypic clusters. Genotypes G12, G7, G8, and G15 were associated with yield-related traits, while G19, G6, and G13 were linked to structural traits related to plant stability. These findings indicate that multivariate analysis can effectively identify phenotypic diversity and support parent selection in rice breeding. However, direct measurements of lodging are required for further validation.]]>
