Soybeans represent a major oilseed and protein crop in Ethiopia, contributing substantially to food security, income generation, and soil fertility improvement. Optimal production relies on refined cultivation practices, including effective land preparation, appropriate plant spacing, and timely weed management, all of which maximize genetic yield potential. Genetic variability remains essential for crop improvement and breeding initiatives. However, the efficiency of soybean breeding in Ethiopia is constrained by several factors, including limited application of molecular breeding techniques, a narrow genetic base of germplasm, environmental variability, and inadequate research infrastructure. Opportunities exist to advance soybean improvement through the adoption of modern genomic tools such as marker-assisted selection and genomic selection, expansion of multi-environment trials, and participatory plant breeding strategies. This review synthesizes findings from genetic variability studies conducted in Ethiopia over the past decade, with a focus on parameters such as genotypic and phenotypic coefficients of variation, heritability, genetic advance, and trait associations. The evidence consistently demonstrates significant variability among soybean genotypes across diverse agro-ecological zones. High heritability coupled with high genetic advance for yield-related traits indicates the predominance of additive gene action, facilitating effective selection. Persistent challenges include limited molecular breeding, environmental variability, and a restricted genetic base. While Ethiopia has begun to implement Marker-Assisted Selection (MAS), integration of multi-omics data and high-throughput phenomics remains limited. There is considerable potential to modernize the sector by adopting precision breeding approaches, emphasizing climate resilient ideotypes and industrial quality traits, such as reduced anti-nutritional factors, which are currently under represented in the national research agenda.
| Published in | Science Discovery Plants (Volume 1, Issue 3) |
| DOI | 10.11648/j.sdplants.20260103.11 |
| Page(s) | 111-122 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2026. Published by Science Publishing Group |
Challenges, Genetic Variability, Opportunities, Review, Soybeans
| [1] | Abdeta, T. M., Biratu, W., & Yadesa, L. (2022). Genomic Mapping, Molecular Marker and Marker Assisted Selection in Rice: A Review. Agro Bali: Agricultural Journal, 5(3), 422-433. |
| [2] | Al Mamun, S. A., Rezve, M., Sorker, M. B. A., Shoun, M. M. H., Sultana, M. S., Pandit, A. A., & Islam, M. M. (2026). MGIDI selection and machine learning reveal harvest index driving traits in sodium induced rice mutants with SSR-based genetic diversity. Bio Rxiv, 2026-02. |
| [3] | Amadou, A., Song, X., Huang, S., Song, A., Tang, Z., Dong, W.,. & Fan, F. (2021). Effects of long-term organic amendment on the fertility of soil, nodulation, yield, and seed quality of soybean in a soybean-wheat rotation system. Journal of Soils and Sediments, 21(3), 1385-1394. |
| [4] | Arega Woldemariam, A. (2016). genetic progress for yield and yield components of soybean varieties [glycine max (l.) merrill] at bako, western ethiopia (doctoral dissertation, haramaya university). |
| [5] | Athoni and Basavaraja (2025). Genetic diversity and population structure of soybean (Glycine max (L.) Merril) germplasm, 1-17. |
| [6] | Berhanu, H., Tesso, B., & Lule, D. (2021). Correlation and path coefficient analysis for seed yield and yield related traits in soybean (Glycine max (L.)) genotypes. |
| [7] | Begna, T. (2020). Major challenging constraints to crop production farming system and possible breeding to over-come the constraints. International Journal of Research Studies in Agricultural Sciences (IJRSAS), 6(7), 27-46. |
| [8] | Beyene, C. (2019). genetic variability and association of traits in white lupin (lupinus albus l.), genotypes at holeta, central ethiopia (Doctoral dissertation, Haramaya university). |
| [9] | Dalle, D., Gecho, Y., & Bedeke, S. B. (2026). Drivers and barriers of climate change adaptation among smallholder farmers in the Wolaita Zone, Southern Ethiopia. Discover Sustainability, 7(1), 170. |
| [10] | Derso, E. (2017). Agricultural research for Ethiopian renaissance: challenges, opportunities and directions. |
| [11] | CSA (Central Statistical Agency). (2025). Report on Area and Production of Major Crops (Private Peasant Holdings, Meher Season). Statistical Bulletin, Addis Ababa, Ethiopia. |
| [12] | FAOSTAT. (2025). World Food and Agriculture - Statistical Data for Oil crops. Food and Agriculture Organization of the United Nations. |
| [13] | Fikre, A., Shiferaw, T., & Tekalign, A. (2016). A Review of Five Decades of Legumes Improvement Program in Ethiopia: the Transition in Breeding Practices and Product Delivery. |
| [14] | Gao, H., & Li, H. (2025). Marker-assisted selection (MAS) in soybean breeding. Molecular Plant Breeding, 16. |
| [15] | Lin, F., Chhapekar, S. S., Vieira, C. C., Da Silva, M. P., Rojas, A., Lee, D., & Nguyen, H. T. (2022). Breeding for disease resistance in soybean: a global perspective. Theoretical and Applied Genetics, 135(11), 3773-3872. |
| [16] | Gebre, M. G., Rajcan, I., & Earl, H. J. (2022). Genetic variation for effects of drought stress on yield formation traits among commercial soybean [Glycine max (L.) Merr.] cultivars adapted to Ontario, Canada. Frontiers in Plant Science, 13, 1020944. |
| [17] | Gemada, A. R. (2021). Soil acidity challenges to crop production in Ethiopian highlands and management strategic options for mitigating soil acidity for enhancing crop productivity. Agriculture, Forestry and Fisheries, 10(6), 245-261. |
| [18] | Getahun, A. (2021). Estimating genetic variability, gene effect, heritability, and genetic advance of yield component agronomic traits: towards the improvement of peanut agronomic traits. agriRxiv, (2021), 20210234086. |
| [19] | Hailemariam, M., Asfaw, E., Tesfaye, A., & Assen, M. (2021). Demonstration of maize-soybean (Glycine max (L) Merrill) rotations in promotion for sustainable cropping system in Southwest Ethiopia. Journal of Genetic and Environment Conservation. |
| [20] | Kebede, E. (2020). Grain legumes production and productivity in Ethiopian smallholder agricultural system, con-tribution to livelihoods and the way forward. Cogent Food &Agriculture, 6(1), 1722353. |
| [21] | Khojely et al. (2021). History, current status, and prospects of soybean production and research in sub-Saharan Africa. Crop. J. 2018, 6, 226-235., (November). |
| [22] | Kumar, R., Das, S. P., Choudhury, B. U., Kumar, A., Prakash, N. R., Verma, R., & Mishra, V. K. (2024). Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing. Biological Research, 57(1), 80. |
| [23] | Lukanda, M. M.; Dramadri, I. O.; Adjei, E. A.; Arusei, P.; Gitonga, H. W.; Wasswa, P.; Edema, R.; Ssemakula, M. O.; Tukamuhabwa, P.; Tusiime, G. Genetic Diversity and Population Structure of Ugandan Soybean (Glycine max L.) Germplasm. |
| [24] | Maitra, S., Mondal, T., Hossain, A., Kalasare, R. S., Praharaj, S., Joy, J. M. M.,. & Sairam, M. (2022). Impact of climate change on growth and productivity of major field crops. |
| [25] | McGee, R., Zaleski‐Cox, M., Jayawardana, M. A., Tillman, B. L., Wally, O., Esquivel‐Garcia, L.,. & Hoyos‐Villegas, V. (2025). Breeding for quantitative disease resistance: Case studies, emerging approaches, and exploiting pathogen variation. Crop Science, 65(6), e70202. |
| [26] | Mindaye, T. T., Mace, E. S., Godwin, I. D., & Jordan, D. R. (2015). Genetic differentiation analysis for the identi-fication of complementary parental pools for sorghum hybrid breeding in Ethiopia. Theoretical and applied genetics, 128(9), 1765-1775. |
| [27] | Molla, H. S., Ayele, Z. A., & Zeleke, M. A. (2024). Trends, opportunities, and challenges of the Ethiopian soybean Export Market in the past two decades (2004-2022). Advances in Agriculture, 2024(1), 9979892. |
| [28] | Mossie, T., Biratu, K., & Endale, T. (2020). Effect of feeding quality protein maize (Zea mays L.) on egg production and quality in Bovans Brown layers. Cogent Food & Agriculture, 11(1), 2588879. |
| [29] | Murithi, H. M., Beed, F., Tukamuhabwa, P., Thomma, B. P., & Joosten, M. H. (2016). Soybean production in eastern and southern Africa and threat of yield loss due to soybean rust caused by Phakopsora pachyrhizi. Plant pathology, 65(2), 176-188. |
| [30] | Nigatu, D. (2022). Genetic Varability and Assosation of Traits in Groundnut (Arachis Hypogaea L.) Genotypes at Pawe North Western Ethiopia (Doctoral dissertation, Ethiopian Institute of Agricultural Research, Debre Markos University). |
| [31] | Qu, X., Lamlom, S. F., Ren, G., Sang, Y., Ren, H., Wang, Y., & Zhou, R. (2026). Evaluation of Germplasm Re-sistance in Several Soybean Accessions Against Soybean Fusarium Root Rot in Harbin, Heilongjiang Province, China. Plants, 15(3), 379. |
| [32] | Raya, S. R., Majid, A., Waza, S. A., & Islam, A. K. M. A. (2025). Plant breeding approaches for enhancing abiotic stress tolerance in crops: A review. Madras Agric J, 112, 7-9. |
| [33] | Tadesse, W., Zegeye, H., Debele, T., Kassa, D., Shiferaw, W., Solomon, T.,. & Assefa, S. (2022). Wheat production and breeding in Ethiopia: retrospect and prospects. Crop Breeding, Genetics and Genomics, 4(3). |
| [34] | Taku, M., Debbarma, P., Kumar, R., Saini, M., Ramlal, A., & Talukdar, A. (2026). Soybean Genetics Emphasizing Chromosome and Genome Organization. In Soybeans (pp. 3-14). Apple Academic Press. |
| [35] | Sebsibe Belete, H. (2017). genetic variability and associations among yield, yield components and quality traits in advanced bread wheat (triticum aestivum l.) genotypes at sinana, south eastern ethiopia (doctoral disserta-tion, haramaya university). |
| [36] | Sinclair et al., 2020). Field Crops Research Genotype x environment interaction analysis of soybean (Glycine max (L.) Merrill) grain yield across production environments in Southern Africa. Field Crops Research, 256(May), 107922. |
| [37] | Shurtleff, W., & Aoyagi, A. (2009). History of soybeans and soyfoods in Africa (1857-2009): extensively annotated bibliography and sourcebook. In Soyinfo Center. |
| [38] | Umeta, T., Mendesil, E., Bayissa, W., & Abebe, A. T. (2026). Evaluation of soybean varieties for resistance to adzuki bean beetle (Collosobruchus chinenesis L.)(Coleoptera: bruchidae) by the no-choice method. Journal of Stored Products Research, 115, |
| [39] | USDA. (2025). World Agricultural Supply and Demand Estimates (WASDE). United States Department of Agri-culture, Office of the Chief Economist. |
| [40] | Wang, T., Qin, P., & Luo, Y. (2022). A review on plant-based proteins from soybean: Health benefits and soy product development. Journal of Agriculture and Food Research, 7. |
APA Style
Tesiso, M., Getachew, E. (2026). Review on Genetic Variability Studies of Soybean (Glycine Max L.) in Ethiopia: Challenges and Opportunities. Science Discovery Plants, 1(3), 111-122. https://doi.org/10.11648/j.sdplants.20260103.11
ACS Style
Tesiso, M.; Getachew, E. Review on Genetic Variability Studies of Soybean (Glycine Max L.) in Ethiopia: Challenges and Opportunities. Sci. Discov. Plants 2026, 1(3), 111-122. doi: 10.11648/j.sdplants.20260103.11
AMA Style
Tesiso M, Getachew E. Review on Genetic Variability Studies of Soybean (Glycine Max L.) in Ethiopia: Challenges and Opportunities. Sci Discov Plants. 2026;1(3):111-122. doi: 10.11648/j.sdplants.20260103.11
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Download@article{10.11648/j.sdplants.20260103.11,
author = {Mohammed Tesiso and Essubalew Getachew},
title = {Review on Genetic Variability Studies of Soybean
(Glycine Max L.) in Ethiopia: Challenges and Opportunities},
journal = {Science Discovery Plants},
volume = {1},
number = {3},
pages = {111-122},
doi = {10.11648/j.sdplants.20260103.11},
url = {https://doi.org/10.11648/j.sdplants.20260103.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sdplants.20260103.11},
abstract = {Soybeans represent a major oilseed and protein crop in Ethiopia, contributing substantially to food security, income generation, and soil fertility improvement. Optimal production relies on refined cultivation practices, including effective land preparation, appropriate plant spacing, and timely weed management, all of which maximize genetic yield potential. Genetic variability remains essential for crop improvement and breeding initiatives. However, the efficiency of soybean breeding in Ethiopia is constrained by several factors, including limited application of molecular breeding techniques, a narrow genetic base of germplasm, environmental variability, and inadequate research infrastructure. Opportunities exist to advance soybean improvement through the adoption of modern genomic tools such as marker-assisted selection and genomic selection, expansion of multi-environment trials, and participatory plant breeding strategies. This review synthesizes findings from genetic variability studies conducted in Ethiopia over the past decade, with a focus on parameters such as genotypic and phenotypic coefficients of variation, heritability, genetic advance, and trait associations. The evidence consistently demonstrates significant variability among soybean genotypes across diverse agro-ecological zones. High heritability coupled with high genetic advance for yield-related traits indicates the predominance of additive gene action, facilitating effective selection. Persistent challenges include limited molecular breeding, environmental variability, and a restricted genetic base. While Ethiopia has begun to implement Marker-Assisted Selection (MAS), integration of multi-omics data and high-throughput phenomics remains limited. There is considerable potential to modernize the sector by adopting precision breeding approaches, emphasizing climate resilient ideotypes and industrial quality traits, such as reduced anti-nutritional factors, which are currently under represented in the national research agenda.},
year = {2026}
}
TY - JOUR T1 - Review on Genetic Variability Studies of Soybean (Glycine Max L.) in Ethiopia: Challenges and Opportunities AU - Mohammed Tesiso AU - Essubalew Getachew Y1 - 2026/09/29 PY - 2026 N1 - https://doi.org/10.11648/j.sdplants.20260103.11 DO - 10.11648/j.sdplants.20260103.11 T2 - Science Discovery Plants JF - Science Discovery Plants JO - Science Discovery Plants SP - 111 EP - 122 PB - Science Publishing Group SN - 3142-7421 UR - https://doi.org/10.11648/j.sdplants.20260103.11 AB - Soybeans represent a major oilseed and protein crop in Ethiopia, contributing substantially to food security, income generation, and soil fertility improvement. Optimal production relies on refined cultivation practices, including effective land preparation, appropriate plant spacing, and timely weed management, all of which maximize genetic yield potential. Genetic variability remains essential for crop improvement and breeding initiatives. However, the efficiency of soybean breeding in Ethiopia is constrained by several factors, including limited application of molecular breeding techniques, a narrow genetic base of germplasm, environmental variability, and inadequate research infrastructure. Opportunities exist to advance soybean improvement through the adoption of modern genomic tools such as marker-assisted selection and genomic selection, expansion of multi-environment trials, and participatory plant breeding strategies. This review synthesizes findings from genetic variability studies conducted in Ethiopia over the past decade, with a focus on parameters such as genotypic and phenotypic coefficients of variation, heritability, genetic advance, and trait associations. The evidence consistently demonstrates significant variability among soybean genotypes across diverse agro-ecological zones. High heritability coupled with high genetic advance for yield-related traits indicates the predominance of additive gene action, facilitating effective selection. Persistent challenges include limited molecular breeding, environmental variability, and a restricted genetic base. While Ethiopia has begun to implement Marker-Assisted Selection (MAS), integration of multi-omics data and high-throughput phenomics remains limited. There is considerable potential to modernize the sector by adopting precision breeding approaches, emphasizing climate resilient ideotypes and industrial quality traits, such as reduced anti-nutritional factors, which are currently under represented in the national research agenda. VL - 1 IS - 3 ER -
Department of Horticulture and Plant Sciences, Jimma University, Jimma, Ethiopia;Bedele Agricultural Research Center, Oromia Agricultural Research Institute, Bedele, Ethiopia
Department of Horticulture and Plant Sciences, Jimma University, Jimma, Ethiopia
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