Journal of Applied Biosciences (J. Appl. Biosci.) [ISSN 1997 - 5902]
Volume 43: 2924 - 2941. Published July 11, 2011.
Determination of yield stability of seven soybean (Glycine max) genotypes across diverse soil pH levels using GGE biplot analysis.
1Jandong E.A., 2Uguru M.I and 2*Oyiga B.C
1College of Agriculture, Jalingo, P.M.B. 1025 Jalingo, Taraba State, Nigeria
2Department of Crop Science, University of Nigeria, Nsukka, Nigeria
ABSTRACT
Objectives: The combined effects of genotype, environment and genotype x environment (GxE) interaction determine the yield of a crop. For the purpose of genotype evaluation, only genotype and GxE interactions are relevant to selection. This study was carried out to study adaptation and stability of soybean varieties over six soil pH regimes. Adaptability and stability are important breeding parameters under conditions of high rainfall and low soil pH.
Methodology and results: One improved and six local soybean genotypes were tested for two consecutive years (2004-2005) over a range of soil pH conditions of between 3.5 and 7.0. The experiments were conducted in a factorial design laid out in a completely randomized design with three replications. The genotypes were grown in the polythene bags at the research field of Department of Crop Science, University of Nigeria, Nsukka. The soil media were adjusted to the required pH levels using 1.0 N hydrochloric acid and calcium hydroxide. At harvest, data on some of the root and yield parameters were collected across all the soil pH conditions evaluated. The results showed high contributions of environment (E) to the total yield variation in the two planting seasons. ANOVA showed that genotype, soil pH and their interactions varied significantly (p<0.01) in both years. The GGE biplot explained 94.3 and 93.3% of the genotype main effect and GE interaction in 2004 and 2005, respectively. The genotypes, Kyado andTGX1448-2E were the most superior for seed yield per plant in 2004 and 2005 plantings, respectively while cultivar Gembu performed poorly in both years. Genotype Gembu was consistently poor in yield performance, hence the high stability observed. In the 2004 planting, soil pH between 5.5 and 6.5 were representative but non discriminating among the test environments. However, in 2005 planting, soil pH 7.0 was the most discriminating and representative of the test environments; and therefore useful for culling genotypes that performed poorly. The stability analysis showed that none of the high performing genotypes was stable for seed yield.
Conclusion and application of findings: Cultivation of the genotypes, Kyado and TGX1448-2E is likely to improve soybean production in the regions with high precipitation usually associated with low soil pH. Thus, Kyado andTGX1448-2E were selected as superior for improved seed yield based on their mean performance. These genotypes could be used in a breeding program to develop genotypes with high yield potential. None of the high performing genotypes evaluated was stable across the soil pH environments, suggesting that each genotype has specific soil pH requirements. Cultivar, TGX1448-2E has neutral response to varying soil pH; Kyado and Sebore performed well in soil pH 5.5 - 6.5, indicating that theyare relatively tolerant to moderately acidic soil and therefore are good candidates for breeding acid tolerant soybean genotypes. This study shows that GGE biplot analysis is appropriate for identifying and discriminating genotypes across soil pH environments.
Key words: Derived Savannah agro-ecology, Genotype x environment interaction, GGE Biplot analysis, Glycine max and Multi-environment trials
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