Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits
To evaluate genetic variability of five soybean genotypes, and assess genotype × environment effect on seed yield and yield related traits. Study Design: Split-plot, replicated three times. Genotypes were fixed effect while plots (main 60 m² and subplot 12 m²) were random effects. The sub-plot consi...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10568/76435 |
| _version_ | 1855543549148266496 |
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| author | Ngalamu, T. Ashraf, M. Meseka, S. |
| author_browse | Ashraf, M. Meseka, S. Ngalamu, T. |
| author_facet | Ngalamu, T. Ashraf, M. Meseka, S. |
| author_sort | Ngalamu, T. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | To evaluate genetic variability of five soybean genotypes, and assess genotype × environment effect on seed yield and yield related traits. Study Design: Split-plot, replicated three times. Genotypes were fixed effect while plots (main 60 m² and subplot 12 m²) were random effects. The sub-plot consists of 4 rows 5 m
long with 60 cm and 10 cm inter and intra-row spacing. Place and Duration: El Gantra, Range and Pasture Farm in Sennar State of the Sudan during 2009 and 2010 cropping season. Methodology: Five soybean genotypes NA 5009 RG; TGx 1904-6F, TGx 1740-2F, TGx 1937-1F and Soja were evaluated. A strain of Rhizobium japonicum was used for inoculation at a rate of 10 g per kg of soybean seed using a sugary solution in 2009. Inoculation was not carried out due to the assumption that the field had the remnant of inoculum effect in 2010. All the recommended soybean agronomic practices were equally applied. Number of days to 50% flowering was recorded on plot basis when almost half of the sub-plot flowers. Ten plants were randomly selected on plot basis to quantify these traits: Plant height was measured as from ground surface to the base of meri-stem of the mother plant. Number of branches was computed as an average count of branches per plant. Leaf area was computed using Iamauti [12] empirical relationship. The first pod height was measured at full bloom. Number of seeds per pod was counted at physiological maturity of the crop. 100-seed weight was determined randomly from a seed bulk using a digital weighing machine. Seed yield was quantified after harvest and converted into kg/hectare. Results: The effect of genotype (G), environment (E) and G × E interactions on pod number per plant; plant height, first pod height, number of branches per plant, leaf area, number of days to 50% flowering and seed yield were found significant at P=0.05. The
highest mean seed yield was obtained from TGx 1937-1F (0.98 t/ha). Beside TGx 1740-2F, TGx 1904-6F and Soja were significantly higher than NA 5009 RG in all environments for seed yield. TGx 1937-1F was an intermediate maturing and best in terms of number of pods per plant, number of branches per plant, and leaf area. Correlation coefficient for seed yield showed significant association with days to 50% flowering and leaf area. Conclusion: The best genotype for seed yield across the environments was TGx 1937-1F and TGx 1740-2F, TGx1904-6F and Soja were intermediate and NA 5009 RG was the least. Thus, partitioning G × E into adaptability and phenotypic stability will positively address the information gap on association of traits to yield. |
| format | Journal Article |
| id | CGSpace76435 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| record_format | dspace |
| spelling | CGSpace764352025-11-11T11:08:42Z Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits Ngalamu, T. Ashraf, M. Meseka, S. soyabean genetic variability yield To evaluate genetic variability of five soybean genotypes, and assess genotype × environment effect on seed yield and yield related traits. Study Design: Split-plot, replicated three times. Genotypes were fixed effect while plots (main 60 m² and subplot 12 m²) were random effects. The sub-plot consists of 4 rows 5 m long with 60 cm and 10 cm inter and intra-row spacing. Place and Duration: El Gantra, Range and Pasture Farm in Sennar State of the Sudan during 2009 and 2010 cropping season. Methodology: Five soybean genotypes NA 5009 RG; TGx 1904-6F, TGx 1740-2F, TGx 1937-1F and Soja were evaluated. A strain of Rhizobium japonicum was used for inoculation at a rate of 10 g per kg of soybean seed using a sugary solution in 2009. Inoculation was not carried out due to the assumption that the field had the remnant of inoculum effect in 2010. All the recommended soybean agronomic practices were equally applied. Number of days to 50% flowering was recorded on plot basis when almost half of the sub-plot flowers. Ten plants were randomly selected on plot basis to quantify these traits: Plant height was measured as from ground surface to the base of meri-stem of the mother plant. Number of branches was computed as an average count of branches per plant. Leaf area was computed using Iamauti [12] empirical relationship. The first pod height was measured at full bloom. Number of seeds per pod was counted at physiological maturity of the crop. 100-seed weight was determined randomly from a seed bulk using a digital weighing machine. Seed yield was quantified after harvest and converted into kg/hectare. Results: The effect of genotype (G), environment (E) and G × E interactions on pod number per plant; plant height, first pod height, number of branches per plant, leaf area, number of days to 50% flowering and seed yield were found significant at P=0.05. The highest mean seed yield was obtained from TGx 1937-1F (0.98 t/ha). Beside TGx 1740-2F, TGx 1904-6F and Soja were significantly higher than NA 5009 RG in all environments for seed yield. TGx 1937-1F was an intermediate maturing and best in terms of number of pods per plant, number of branches per plant, and leaf area. Correlation coefficient for seed yield showed significant association with days to 50% flowering and leaf area. Conclusion: The best genotype for seed yield across the environments was TGx 1937-1F and TGx 1740-2F, TGx1904-6F and Soja were intermediate and NA 5009 RG was the least. Thus, partitioning G × E into adaptability and phenotypic stability will positively address the information gap on association of traits to yield. 2013-08 2016-08-12T06:27:42Z 2016-08-12T06:27:42Z Journal Article https://hdl.handle.net/10568/76435 en Open Access application/pdf Ngalamu, T., Ashraf, M., & Meseka, S. (2013). Soybean (Glycine max L) Genotype and Environment Interaction Effect on Yield and Other Related Traits. American Journal of Experimental Agriculture, 3(4):977-987. |
| spellingShingle | soyabean genetic variability yield Ngalamu, T. Ashraf, M. Meseka, S. Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title | Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title_full | Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title_fullStr | Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title_full_unstemmed | Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title_short | Soybean (Glycine max L) genotype and environment interaction effect on yield and other related traits |
| title_sort | soybean glycine max l genotype and environment interaction effect on yield and other related traits |
| topic | soyabean genetic variability yield |
| url | https://hdl.handle.net/10568/76435 |
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