African Journal of
Plant Science

  • Abbreviation: Afr. J. Plant Sci.
  • Language: English
  • ISSN: 1996-0824
  • DOI: 10.5897/AJPS
  • Start Year: 2007
  • Published Articles: 780

Full Length Research Paper

Genotype by environment interaction in sesame (Sesamum indicum L.) cultivars in Uganda

Walter Okello-Anyanga
  • Walter Okello-Anyanga
  • Department of Agricultural Production, School of Agricultural Sciences, Makerere University, Kampala, P.O. Box. 7062, Kampala, Uganda.
  • Google Scholar
Patrick Rubaihayo
  • Patrick Rubaihayo
  • Department of Agricultural Production, School of Agricultural Sciences, Makerere University, Kampala, P.O. Box. 7062, Kampala, Uganda.
  • Google Scholar
Paul Gibson
  • Paul Gibson
  • Department of Agricultural Production, School of Agricultural Sciences, Makerere University, Kampala, P.O. Box. 7062, Kampala, Uganda.
  • Google Scholar
Patrick Okori
  • Patrick Okori
  • Department of Agricultural Production, School of Agricultural Sciences, Makerere University, Kampala, P.O. Box. 7062, Kampala, Uganda.
  • Google Scholar


  •  Received: 10 May 2016
  •  Accepted: 04 August 2016
  •  Published: 31 October 2016

Abstract

Sesame (Sesamum indicum L.) is an important and ancient oilseed crop cultivated in hot, dry climates for its oil and protein rich seeds. On the African continent, Uganda ranks seventh in sesame production. The improvement of new genotypes with the desired yield stability and performance in different environments is an important issue in breeding programs. In order to identify high yielding and stable sesame genotypes across environments, field experiments were conducted with 16 genotypes for four seasons (2011-2013) at three locations, viz. Serere, Kaberamaido and Ngetta. The objective of the study was to use additive main effects and multiplicative interaction (AMMI) and genotype by genotype environment interaction (GGE) biplot statistical analysis to identify the stability and yield potential of sixteen sesame genotypes.   The results of  AMMI analysis of variance for seed yield (kg/ha) showed that all the sources of variations that included treatments, genotypes, environments, blocks, interactions, IPCA1 and IPCA 2 were highly significant (P<0.001). The combined analysis of variance indicated that season, season x location, genotype and location x genotype had highly significant (P<0.001) variation. The GGE biplot suggested the existence of only one sesame mega-environment with genotype G9 (Local 158-1) best adapted in that mega-environment followed by G1 (Ajimo A1-6//7029)-1-1. The mega-environment had environments K2011B, K2012A, K2012B, N2012B and K2013B. The vertex genotypes which indicated that they were the most responsive in their respective environments were G2 (Ajimo A1-6//7029)-1-9, G3 (Local 158//6022)-1-2-1, G8 (EM15-3-2), G9 (Local 158-1), G12 (Renner 1-3-1-16) and G14 (Renner 1-3-1-17-1). Genotypes G2 and G12 performed poorly in poor environments. Genotypes were categorized into stable and high yielding, stable but poor yielding, unstable but good yielding and unstable and poor yielding. Environment K2013B was the most discriminating environment. According to the ideal-genotype biplot, genotype G9 (Local 158-1) was the best performing genotype and Kaberamaido was the nearest to ideal environment. It was officially released as Sesim 3 variety for commercial production because of its yield, stability, tolerance to pests and high oil content.

 

Key words: Adaptation, additive main effects and multiplicative interaction (AMMI), genotype environment interaction (GGE) biplot, principal component analysis, stability.