GENETIC DIVERSITY AND PRINCIPLE COMPONENT ANALYSIS (PCA) OF FABA BEAN LANDRACES BASED ON YIELD-TRAITS AND PROTEIN SDS-PAGE
Abstract: This investigation was carried out at Bahteem farm Genetic resources research department ,field crop research institute , Agricultural Research Center ,Giza , Egypt during two growing seasons 2018/19 and 2019/20. Twenty landraces with two faba bean check landraces were grown in Randomized Complete Block Design (RCBD) with 3 replications to determine the genetic variability, morphological diversity and relationships among these landraces for agro-morphological and biochemical characteristics. Analysis of variance revealed high variability among all measured genotypes with respect to all agronomic and protein characteristic studied traits. Principle Component Analysis (PCA) was performed; the first principal component had 54.40% and 37.90% of the total variation (PC1) and the second principle component (PC2) explained 14.30% and 24.90% of the total variation for morphological and biochemical traits, respectively . The cumulative ratio of the first six primary components explained all variations of total variation. The studied faba bean landraces were distribution among PC biplot and clustered indicated distribution of studied material (matched with measured checks) by cluster or heat-map analysis. The results clustered or distributed differently based on morphological and biochemical traits. Then, GT biplot used to clear the relationship among the studied faba bean traits and landraces, showing that number of seeds and pods were the most positive effective traits in faba bean seed yield, causing highest harvest index. Results revealed that landrace G16 and G19 with the highest check Giza716 recorded the highest values of seed yield, number of seeds, number of pods and harvest index. GT biplot graph is a good preferred alternative procedure for each of correlation and cluster analyses and considered an effective technique beside or instead of cluster analysis for facility the interpretations. From all results, this work has provided useful data for elaboration of strategies for the conservation and sustainable management of the better genetic source germplasm and for Vicia faba improvement genetically
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Publication year 2022
Pages 1-16
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Author(s) from ARC
Publication Type Journal
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