Aims: 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. 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 Research ArticleAmerican Journal of Experimental Agriculture, 3(4): 977-987, 2013 978 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.
Cowpea is an important food crop with high nutritional and socio-economical values in South Sudan. However, the lack of improved varieties is one of the main production constraints. This study was undertaken to assess the yield stability performance of improved cowpea genotypes across six environments in South Sudan in 2014 and 2015. Nine genotypes were evaluated in a randomized complete block design with three replications. Genotype and genotype x environment biplot analysis method was used to determine yield stability. Highly significant (p less than 0.001) genotype x environment interaction effect was detected for seed yield. IT90K-277-2 had the highest while ACC004 had the lowest grain yield. Palotaka was as highly discriminating and repeatable environment compare to the other testing sites. IT07K-211-1-8 and Mading Bor II were the most responsive genotypes, while IT90K-277-2 was the most stable high yielding genotype across the test environments and can be grown by farmers across the region.
Twenty-five cowpea (Vigna unguiculata L) genotypes were evaluated across six contrasting environments for phenotypic yield stability. Combined analysis of variance revealed significant differences among the genotypes and the main effects. A1B×D, BC×M, L1B×M, A1B×M, and BA×I were the best performing and stable genotypes. The non-parametric analysis showed that genotype IT93K-503-1 had the highest yield and BC×D had the lowest yield. Shukla stability analysis revealed Beledi A and Dan lla as the most stable across test environments and genotypes A1B×D, BC×M and BA×I were good performers. The coefficient of variability graphical approach showed that genotypes BC×I, A1B×M, A1B×D, Dan lla, TA×M, Mouride, L1B×I, BC×M and L1B×D were high yielding. This implies they would do well across the testing sites. However, genotype IT93K-503-1 should be promoted for cultivation in drought-prone environments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.