Genotype by Environment Interaction in Soybean and its Implications for Crop Improvement

Adediran, B. O. and Ayo-Vaughan, M. A. and Ariyo, O. J. and Sakariyawo, O. S. and Aremu, C. O. and Ibitoye, D. O. (2023) Genotype by Environment Interaction in Soybean and its Implications for Crop Improvement. International Journal of Plant & Soil Science, 35 (18). pp. 162-173. ISSN 2320-7035

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Abstract

Adequate production of soybean [Glycine max (L.) Merr.] in Nigeria depends on selection of varieties combining high grain yield with stability. Soybean farmers are recurrently faced with the limitation of selecting the best genotype for available environments at their disposal for the production of this crop. Soybean genotypes (23) and two landraces were therefore evaluated in three environments: Abeokuta, Ibadan upland and Ibadan in-land valley in 2017 to select genotype that combines high yield and stability. The experiment in each environment was arranged in a randomized complete block design with three replicates. Data were collected on grain yield and yield component characters. The grain yield data were analyzed using genotype + genotype x environment interaction (GGE) biplot to select desirable genotypes for grain yield and stability; the yield component data were also analyzed using analysis of variance (ANOVA). The variation attributable to G by E interaction was significant except number of branches per plant. Abeokuta was identified as the most representative environment for soybean production. The genotypes TGX 2007-4F, TGX 2016-2E and TGX 2007-1F were the best yielding genotypes in the most discriminating environment – Ibadan upland, thus highly recommended for that specific location. Genotype TGX 2027-7E (G25) was the most stable genotype but was low yielding. Genotypes TGX 2027-3E, TGX 2016-2E, TGX 2007-4F, TGX 2009-1F and TGX 2027-4E, which combined high yield and stability, can be recommended to growers in these three (or similar) environments.

Item Type: Article
Subjects: South Archive > Agricultural and Food Science
Depositing User: Unnamed user with email support@southarchive.com
Date Deposited: 17 Jul 2023 05:56
Last Modified: 22 Jun 2024 09:18
URI: http://ebooks.eprintrepositoryarticle.com/id/eprint/1330

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