Hangming Lin¹ , Xiaoxi Zhou²

1 Tropical Legume Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China
2 Institute of Life Sciences, Jiyang Colloge of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
International Journal of Horticulture, 2026, Vol. 16, No. 3   doi: 10.5376/ijh.2026.16.0014
Received: 19 Apr., 2026    Accepted: 23 May, 2026    Published: 10 Jun., 2026

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Lin H.M., and Zhou X.X., 2026, Marker-assisted selection in soybean breeding: achievements and limitations, International Journal of Horticulture, 16(3): 149-163 (doi: 10.5376/ijh.2026.16.0014)

Soybean is a globally important crop for both food and oil production. However, traditional breeding relies heavily on phenotypic selection, which is time-consuming, inefficient, and highly influenced by environmental factors, making it difficult to achieve the coordinated improvement of high yield, superior quality, and stress resistance. This study systematically reviews the application progress of marker-assisted selection (MAS) in soybean breeding, including resistance to diseases and pests, tolerance to abiotic stresses, optimization of agronomic traits, and improvement of seed quality. It also analyzes the practical value of MAS in gene pyramiding and backcross breeding. The results indicate that MAS has clear advantages in tracking, introgressing, and pyramiding major genes and large-effect quantitative trait loci (QTL), thereby improving selection efficiency and shortening breeding cycles. However, for complex quantitative traits such as yield and wide adaptability, its effectiveness is still constrained by factors including minor-effect QTL, gene–environment interactions, and cost inputs. MAS serves as a fundamental technology for precision breeding in soybean. In the future, it should be integrated with genomic selection, multi-omics approaches, and gene editing technologies to enhance the improvement of complex traits and support the development of climate-resilient soybean varieties.

Soybean; Marker-assisted selection; Gene pyramiding; Quality improvement; Genomic selection