Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
Abstract: (129 Views)
Background and objectives: Faba bean (Vicia faba L.) is grown world-wide as a protein source for food and feed. It is a very valuable legume crop that contributes to the sustainability of cropping systems by its ability of biological N2 fixation. Genetic control of yield is directly affected by parameters correlated with yield. Recognizing the correlation of yield and its components and finding the type of relationships between them can increase yield. The selection of genotypes based on multiple traits is a critical challenge in plant breeding and is important for improving stable crop varieties. In this study, the genotype × trait biplot (GT biplot) and the genotype × yield-trait biplot (GYT biplot) methods were used in combination with cluster analysis to investigate the relationships between grain yield and simultaneous improvement of quantitative traits and select the best faba bean genotypes. Also, the strengths and weaknesses of each genotype were determined by combining yield and other target traits with the GYT biplot method.
Materials and methods: To selection suitable genotypes, genotypes were evaluated in the field, based on simple lattice design (6 × 6) with two replications in Gorgan research stations in the 2021-2022 cropping season. Plant materials included 36 faba bean (Vicia faba L.) genotypes. The phonological traits, plant height (PH) and lowest pod height(HLP) was calculated before harvesting, in each plot were harvested by hand at harvest maturity stage and seed number/pod (NS), pod number/plant (NP) and hundred seed weight (100SW) measured on ten plants selected randomly from all plots. Data were analyzed using SAS software and the means were compared using LSD test at a 1% and 5% probability level of 5%. Also conducted two graphical multipurpose selection procedures GT biplot and GYT biplot in combination with cluster analysis for simultaneous improvement of quantitative traits. Clustering of genotypes and traits traits separately in each experiment using Ward method and Square Euclidean Distance were performed and the corresponding heatmap was plotted using metaboanalyst 3. 0 software.
Results: Based on the analysis of variance, there was a significant difference (P ≤ 0.01) in all parameters. Based on Clustering and Heat map graphical mapping assigned the faba bean genotypes into five groups. The different groups obtained can be useful for deriving the genotypes with diverse features and diversifying the heterotic pools. According to the mean grain yield of the genotypes, the maximum grain yield was obtained for, G25 (12TER-115-S2008, 058-4), G26 (12TER-124-S2009, 039-3) and G4 (ILB1814× WRB 1-5) genotypes with mean grain yield of 6251.7, 5965.6 and 5815.6 kgha-1, respectively. Results of the GT biplot in the present study indicated that G26, G25, G23, G21 and G16 genotypes were identified as superior genotypes. The GT biplot vector view indicate that there was a strong positive association between pod yield, number of branches, plant height and days to flowering with seed yield. The GT biplot vector view indicate that Number of seed per Pod, 100 seed weight, plant height and early maturity traits can be used as selection criterion for improving of seed yield in faba bean. Findings suggested that genotype by trait (GT) biplot explained less total variation (47%) as compared to GYT biplot (87.5%). The which-won-where view of GYT biplot divided the GYT polygon into five parts, out of which only two parts had combinations of traits. The first part harbored the combination of yield trait with phenological traits, plant height (PH), lowest pod height(HLP), pod number/plant (NP), biomass, harvest index and weight of 100 seeds, and nine genotypes (G4, G6, G13, G16, G21, G23, G25, G26 and G27) for which G25 and G26 were the winner genotypes. In the second parts of GYT polygon, genotype G32 (Feyz cultivar) were placed with Yield×number of grains per pod (NG) and Yield×lenght of pod (LP). Based on results of GYT biplot, G25 (12TER-115-S2008, 058-4) and G26 (12TER-124-S2009, 039-3) genotypes were the best genotypes in combining grain yield with valuable traits. Average tester coordinate (ATC) view of GYT biplot indentified genotypes G25, G26 and G4 with all positive yield-trait combinations as the best genotypes and genotypes G35, G7 and G12 as the weakest genotypes.
Conclusion: The study showed that GYT biplot is a very good technique, the ideal and stable genotypes can be detected visually with it, and it can be used to define the best candidate based on combining yield and traits selection in breeding programs. Overall, these findings indicated that the genotypes G25 (12TER-115-S2008, 058-4), G26 (12TER-124-S2009, 039-3) and G4 (ILB1814× WRB 1-5) had the right combination of traits of interest required to produce higher yield and hence are potentially valuable candidates to be tested in multi-location trials for stable performance prior to release as new commercial faba bean cultivars.
Materials and methods: To selection suitable genotypes, genotypes were evaluated in the field, based on simple lattice design (6 × 6) with two replications in Gorgan research stations in the 2021-2022 cropping season. Plant materials included 36 faba bean (Vicia faba L.) genotypes. The phonological traits, plant height (PH) and lowest pod height(HLP) was calculated before harvesting, in each plot were harvested by hand at harvest maturity stage and seed number/pod (NS), pod number/plant (NP) and hundred seed weight (100SW) measured on ten plants selected randomly from all plots. Data were analyzed using SAS software and the means were compared using LSD test at a 1% and 5% probability level of 5%. Also conducted two graphical multipurpose selection procedures GT biplot and GYT biplot in combination with cluster analysis for simultaneous improvement of quantitative traits. Clustering of genotypes and traits traits separately in each experiment using Ward method and Square Euclidean Distance were performed and the corresponding heatmap was plotted using metaboanalyst 3. 0 software.
Results: Based on the analysis of variance, there was a significant difference (P ≤ 0.01) in all parameters. Based on Clustering and Heat map graphical mapping assigned the faba bean genotypes into five groups. The different groups obtained can be useful for deriving the genotypes with diverse features and diversifying the heterotic pools. According to the mean grain yield of the genotypes, the maximum grain yield was obtained for, G25 (12TER-115-S2008, 058-4), G26 (12TER-124-S2009, 039-3) and G4 (ILB1814× WRB 1-5) genotypes with mean grain yield of 6251.7, 5965.6 and 5815.6 kgha-1, respectively. Results of the GT biplot in the present study indicated that G26, G25, G23, G21 and G16 genotypes were identified as superior genotypes. The GT biplot vector view indicate that there was a strong positive association between pod yield, number of branches, plant height and days to flowering with seed yield. The GT biplot vector view indicate that Number of seed per Pod, 100 seed weight, plant height and early maturity traits can be used as selection criterion for improving of seed yield in faba bean. Findings suggested that genotype by trait (GT) biplot explained less total variation (47%) as compared to GYT biplot (87.5%). The which-won-where view of GYT biplot divided the GYT polygon into five parts, out of which only two parts had combinations of traits. The first part harbored the combination of yield trait with phenological traits, plant height (PH), lowest pod height(HLP), pod number/plant (NP), biomass, harvest index and weight of 100 seeds, and nine genotypes (G4, G6, G13, G16, G21, G23, G25, G26 and G27) for which G25 and G26 were the winner genotypes. In the second parts of GYT polygon, genotype G32 (Feyz cultivar) were placed with Yield×number of grains per pod (NG) and Yield×lenght of pod (LP). Based on results of GYT biplot, G25 (12TER-115-S2008, 058-4) and G26 (12TER-124-S2009, 039-3) genotypes were the best genotypes in combining grain yield with valuable traits. Average tester coordinate (ATC) view of GYT biplot indentified genotypes G25, G26 and G4 with all positive yield-trait combinations as the best genotypes and genotypes G35, G7 and G12 as the weakest genotypes.
Conclusion: The study showed that GYT biplot is a very good technique, the ideal and stable genotypes can be detected visually with it, and it can be used to define the best candidate based on combining yield and traits selection in breeding programs. Overall, these findings indicated that the genotypes G25 (12TER-115-S2008, 058-4), G26 (12TER-124-S2009, 039-3) and G4 (ILB1814× WRB 1-5) had the right combination of traits of interest required to produce higher yield and hence are potentially valuable candidates to be tested in multi-location trials for stable performance prior to release as new commercial faba bean cultivars.
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