Journal of
Plant Breeding and Crop Science

  • Abbreviation: J. Plant Breed. Crop Sci.
  • Language: English
  • ISSN: 2006-9758
  • DOI: 10.5897/JPBCS
  • Start Year: 2009
  • Published Articles: 401

Full Length Research Paper

Evaluation of the performance of advanced generation soybean [Glycine max (L.) Merr.] genotypes using GGE biplot

Clever Mukuze
  • Clever Mukuze
  • Department of Agricultural Production, School of Agricultural Sciences, College of Agriculture and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda.
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Phinehas Tukamuhabwa
  • Phinehas Tukamuhabwa
  • Department of Agricultural Production, School of Agricultural Sciences, College of Agriculture and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda.
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Mcebisi Maphosa
  • Mcebisi Maphosa
  • Department of Crop and Soil Science, Faculty of Agriculture, Lupane State University, P. O. Box 170, Lupane, Zimbabwe.
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Shorai Dari
  • Shorai Dari
  • Department of Crop Science, Faculty of Agriculture, University of Zimbabwe, P. O. Box MP167, Mt Pleasant, Harare, Zimbabwe.
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Tonny Obua
  • Tonny Obua
  • Department of Agricultural Production, School of Agricultural Sciences, College of Agriculture and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda.
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Hellen Kongai
  • Hellen Kongai
  • Department of Agricultural Production, School of Agricultural Sciences, College of Agriculture and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda.
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Patrick Rubaihayo
  • Patrick Rubaihayo
  • Department of Agricultural Production, School of Agricultural Sciences, College of Agriculture and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda.
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  •  Received: 27 May 2020
  •  Accepted: 03 August 2020
  •  Published: 30 September 2020

Abstract

Soybean is an important food and cash crop in Uganda. Despite the importance of soybean in Uganda’s economy, its performance is highly affected by genotype × environment interaction making it difficult to select and recommend new superior soybean genotypes for diverse growing environments. The objectives of this study were to examine the nature of G × E interaction for soybean grain yield, to identify stable and high yielding soybean genotypes with desirable percentage protein and oil content for production in diverse environments and to determine ideal test location for future soybean breeding activities in Uganda. The experiment was conducted at six locations for two consecutive seasons of year 2018 (2018A and 2018B). Twenty-three newly advanced generation soybean lines and two commercial varieties were evaluated in a randomized complete block design replicated three times. Combined analysis of variance over locations and seasons was carried out for grain yield, protein and oil (%) content. The results for grain yield showed significant (p<0.05) differences for all the sources of variation except genotypes × season interaction. Percentage protein and oil content showed non-significant (p>0.05) for all the sources of variation except location. The genotype main effect plus G × E interaction biplot explained 65.74% of the total interaction sum of squares for grain yield and showed that the advanced generation soybean lines BSPS 48A-28; Mak 3N × 1N and NGDT 8.11×3N-2 were high yielding and stable and had other desirable agronomic traits. Nakabango was the most discriminating and representative test location.

Key words: Soybean, stability, GGE, ideal testing location, mega-environment.