Clustering and Principal Component Analysis of Genetic Diversity in Elite Sugarcane Clones Over Pooled Crop Cycles

Abstract

The experiment was conducted from January, 2021 to December, 2023 (3 years) at the Regional Agricultural Research Station (RARS), Anakapalle, Andhra Pradesh, India, to evaluate the genetic diversity among 25 elite sugarcane clones for cane yield and juice quality traits. The experiment followed a randomized block design with three replications across three crop cycles, and pooled data were used for analysis. A total of eight quantitative and qualitative traits were recorded for phenotyping. K-means clustering effectively classified the genotypes into two distinct clusters, with Cluster 1 comprising 16 genotypes and Cluster 2 containing 9 genotypes. The first four principal components (PCs) were retained in the Principal Component Analysis (PCA) based on eigenvalues (≥ 1), explaining 87.52% of the total variation. PC1 accounted for 42.5% of the variation, followed by PC2 (17.61%), PC3 (14.58%), and PC4 (12.82%). Pearson correlation coefficient showed nine significant positive correlations and one significant negative correlation among the assessed traits. These findings provided valuable insights into genetic diversity, facilitating the selection of superior parental lines for sugarcane breeding programs.