Research Insight

Utilizing Sweet Potato Genetic Diversity and Molecular Breeding Techniques for Resistance Breeding and Quality Improvement  

Gongkai Chen , Hong Wang , Lingli Wang , Yong’an Liu , Fanglei Hong , Hongshuang Yang
Wenzhou Vocational College of Science and Technology, Wenzhou, 325006, Zhejiang, China
Author    Correspondence author
Molecular Plant Breeding, 2024, Vol. 15, No. 6   
Received: 03 Nov., 2024    Accepted: 05 Dec., 2024    Published: 13 Dec., 2024
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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.
Abstract

This study comprehensively explores the importance of genetic diversity in sweet potato breeding and crop improvement. As a globally significant crop, sweet potato offers abundant genetic resources for developing high-yielding, stress-tolerant, and nutritionally enhanced varieties. By evaluating genetic variation and population structure in sweet potato germplasm across different geographical regions, the study identifies key traits associated with yield, disease resistance, and nutritional quality. Modern breeding techniques, including marker-assisted selection and gene editing, were applied to accelerate the development of superior sweet potato varieties. Additionally, case studies, such as the identification of disease-resistant germplasm and the development of biofortified varieties, demonstrate the critical role of genetic diversity in addressing food security and sustainable agriculture. The findings highlight that integrating advanced molecular techniques with traditional breeding approaches can maximize the genetic potential of sweet potato, effectively tackling agricultural challenges posed by climate change, and support global agricultural innovation and socio-economic development.

Keywords
Sweet potato; Genetic diversity; Molecular breeding; Disease resistance; Biofortification; Climate adaptability; Genetic resource utilization
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. Gongkai Chen
. Hong Wang
. Lingli Wang
. Yong’an Liu
. Fanglei Hong
. Hongshuang Yang
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