USING BIPLOT ANALYSIS OF F1 FABA BEAN DIALLEL DATA TO PREDICT COMBINING ABILITY
Abstract: This study was carried out under insect cages during 2017/18 and 2018/19 seasons at Giza Research Station, ARC, Egypt to investigate the combining ability possibility prediction and relationship between biplot graph and Griffing of half diallel data, and to identify promising genotypes. Six parental faba bean genotypes and their half diallel crosses (15 F1’s) were evaluated under a randomized complete block design in three replications. The results reflected significant differences for both GCA and SCA in most traits, indicating the important role of both additive and dominant components in the inheritance. Meanwhile, Baker’s ratio emphasized the preponderant role of additive gene action in controlling the most studied traits. Simple correlation results showed that seed yield may be raised through selecting most pods and seeds per plant, which recorded the highest heritability in broad and narrow sense (hb2 and hn2%) estimates coupled with highest genetic advance (GA %) in faba bean. Biplot graph (innovative) and Griffing (traditional) analysis exhibited equivalent results for gca and sca effects and are meaningful for identifying Giza 843 (P1), Misr 1 (P2) and Giza 40 (P6) as the best parents and Giza 843 x Misr 1 (C12), Giza 843 x Nubaria 1 (C15), Misr 1 x Giza 3 (C24), Giza 716 x Nubaria 1 (C35) and Nubaria 1 x Giza 40 (C56) as promising five crosses. Then, GT-biplot method is considered as the best alternative analysis for giving a complete picture about the interrelationships among genotypes and traits (for relative comparing genotypes based on multiple traits). Hence, number of pods and seeds per plant traits could be used for the improvement of seed yield. Besides, five faba bean crosses were distinguished which possess genetic factors for high yield and highly promising to be employed in the development of high yielding populations of faba bean breeding programs.
Publication year 2020
Pages 251 –271
Organization Name
Author(s) from ARC
Publication Type Journal
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