GENETIC DIVERSITY OF THE BC2 POPULATION OF ALFALFA MULTIFOLIATE LEAVES BASED ON MORPHOLOGICAL TRAITS USING CORRELATION, PRINCIPAL COMPONENT, AND CLUSTERING ANALYSIS - OMER IDRIS MUSA OLOM; Zhenwu Wei; Liu Nana (Journal of Animal and Plant Sciences, 2023)
The current research aimed to assess the 179 BC2 population of alfalfa (Medicago sativa L. cv. Huaiyin) multifoliate leaves and their parents to select genotypes based on the morphological traits for future alfalfa breeding programs. A backcross breeding was carried out between the recurrent male parent and alfalfa PL34HQ as the non-recurrent female parent of alfalfa. In the pod setting stage, morphological traits were measured in the BC2 populations. Data were analyzed for descriptive statistics, correlation, principal component (PCA), and agglomerative hierarchical cluster analyses. The result of descriptive statistics revealed high variation in the means, minimum, and maximum values for most of the morphological traits. Therefore, high variability was observed in plant height (PH) 26-98 cm, number of branches per plant (NBP) 6-74, stem diameter (SD) 1.46-5.46 mm, second branch length SBL 0-62 cm, number of multifoliate leaves per plant (NMFLP) 0-95.7%, number of multifoliate leaves on the main branch (NMFLMB) 0-90.6%, number of nodes (NN) 12-24, fresh shoot weight (FSW) 3.10-359.4 g, and dry shoot weight (DSW) 0.40-108.6 g. The results showed that the comprehensive traits of the BC2 population tended to the recurrent parent, about 32.40% of the total population. However, many plants tended to the non-recurrent parent, about 67.40% of the total population, with a high multifoliate rate. Correlation analysis revealed a significant positive association of plant height with stem diameter, fresh shoot weight, dry shoot weight, second branch length, number of nodes, and branch number. Principal component analysis (PCA) discovered the first three components with an eigenvalue greater than one, contributing 78.98% of total variability for different traits. The PC1 showed favorable factor loading for all morphological traits. The contribution of dry shoot weight, fresh shoot weight, stem diameter, and plant height was highest in principal component 1. The average hierarchical cluster analysis method grouped all the genotypes into four main clusters. Alfalfa multifoliate leaf genotype clustering based on morphological traits would help identify potential genotypes for future breeding research and programs.
Keywords: Alfalfa multifoliate leaves; Principal component analysis; Correlation; Cluster analysis