GENETIC DIVERSITY AND PRINCIPLE COMPONENT ANALYSIS (PCA) OF FABA BEAN LANDRACES BASED ON YIELD......

During the growing seasons 2018/19 and 2019/20, this study was conducted at Bahteem farm Genetic resources research department, field crop research institution, Agricultural Research Center, Giza, Egypt. Twenty landraces were planted in a Randomized Complete Block Design (RCBD) with three replications to investigate genetic variability, morphological variety, and relationships between these landraces for agromorphological and biochemical properties. With respect to all agronomic and protein characteristic characteristics evaluated, analysis of variance demonstrated substantial heterogeneity across all tested genotypes. The first principal component (PC1) described 54.40 percent and 37.90 percent of the total variation for morphological and biochemical variables, respectively, while the second principle component (PC2) explained 14.30 percent and 24.90 percent of the total variation. All differences in total variance were explained by the cumulative ratio of the first six major components. By cluster or heat-map analysis, the investigated faba bean landraces were distributed across PC biplot and clustered suggested distribution of examined material (matched with measured checks). Based on physical and biochemical features, the results clustered or distributed differentially. The GT biplot was then utilised to highlight the link between the examined faba bean traits and landraces, revealing that the most positive effective traits in faba bean seed yield were quantity of seeds and pods, resulting in the highest harvest index. The landraces G16 and G19 with the highest check Giza716 had the largest seed output, number of seeds, number of pods, and harvest index, according to the results. GT biplot graph is a good recommended alternate approach for each of correlation and cluster analyses, and it is considered a useful tool for facilitating the interpretations in addition to or instead of cluster analysis. This research has yielded helpful data for the development of strategies for the conservation and long-term management of improved genetic source material, as well as genetic improvement of Vicia faba.

Please see the link :- https://www.ikprress.org/index.php/JOGAE/article/view/7506