Xuebing Ying ¹ , Yanjun  Lu ¹ , Shaoping  Shi ¹ , Lin Zhao ² , Jiang  Shi ²

1 Lin’an District Agricultural and Forestry Technology Promotion Center, Hangzhou, 310000, Zhejiang, China
2 Crop (Ecology) Research Institute of Hangzhou Academy of Agricultural Sciences, Hangzhou, 310000, Zhejiang, China
Author    Correspondence author
Molecular Plant Breeding, 2025, Vol. 16, No. 1   doi: 10.5376/mpb.2025.16.0008
Received: 11 Jan., 2025    Accepted: 17 Jan., 2025    Published: 25 Feb., 2025

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.

Ying X.B., Lu Y.J., Shi S.P., Zhao L., and Shi J., 2025, Case study on molecular breeding for drought-resistant sweet potato varieties, Molecular Plant Breeding, 16(1): 73-81 (doi: 10.5376/mpb.2025.16.0008)

This study clarifies the importance of drought resistance in sweet potato cultivation and systematically evaluates the application of molecular techniques, such as marker-assisted selection (MAS), genomic selection (GS), and quantitative trait loci (QTL) mapping, in enhancing drought tolerance in sweet potatoes. Several candidate genes associated with water retention, abscisic acid (ABA) signaling pathways, and key transcription factors were identified, which play a crucial role in improving drought resistance. Field trials validated that newly developed drought-resistant sweet potato varieties exhibited significantly enhanced water-use efficiency, optimized root architecture, and stable yield performance, outperforming traditional breeding methods. By focusing on molecular breeding for drought-resistant sweet potatoes, this study provides both technical support for breeding resilient varieties and essential insights for improving agricultural adaptability to climate change, thus contributing to food security.

Drought resistance; Molecular breeding; Marker-assisted selection (MAS); Genomic selection (GS); Quantitative trait loci (QTL)