Trait Reduction in Chickpea (Cicer arietinum L.) Germplasm through Principal Component Analysis

Enhancing chickpea (Cicer arietinum L.) seed production can be achieved by selecting superior genotypes according to various yield and yield component characteristics. Yield is a multidimensional feature that is controlled by several circumstances; thus, principal component analysis, a well-established method, was used to discover and limit the number of characteristics necessary for effective selection. As a result, this experiment was conducted to analyze the genetic diversity of chickpea genotypes. The study involved 81 chickpea germplasm lines and 15 check varieties, totalling 96, assessed through an augmented block design with four blocks. Each experimental unit consisted of two rows per genotype, each 2 meters in length, with a 0.5-meter gap between rows and plants spaced 30 × 10 cm apart. Standard procedures were used to obtain data on 10 quantitative traits for every genotype. Among the ten principal components (PCs) analyzed, only three had eigenvalues exceeding 1.0, accounting for approximately 63.97% of the variability. PC 1 accounted for the largest portion of variability at 26.39%. This was followed by PC 2, which explained 21.79% of the variability with an eigenvalue of 2.17, and PC 3, which accounted for 15.79% with an eigenvalue of 1.57. The first three PCs—days to 50% pod setting, days to 50% flowering, and days to maturity—accounted for 63.97% of the overall variation and explained the characteristics. Genotypes frequently appearing in more PCs included ICC-16534, ICC-6816, ICC-12726, and CSJ-515. The current study revealed that chickpea germplasm exhibited significant genetic diversity across most of the traits examined.