Advances in Soybean Genetics and Breeding
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Genetics, Genomics and Breeding".
Deadline for manuscript submissions: closed (25 January 2024) | Viewed by 3690
Special Issue Editors
Interests: soybean genetics; functional genomics; genomic selection; molecular breeding and computational breeding
Special Issue Information
Dear Colleagues,
Soybean, a wealthy source of edible oil and protein, is cultivated globally. In the last century, conventional breeding has made significant progress in soybean breeding; however, considering its limitations of time-consuming variety development, low genetic gain per unit time, and environment sensitiveness, it is not able to maintain pace with the current population growth and climate change. In this context, molecular breeding has emerged as a potential approach to overcome this limitation and accelerate the crop production. Recent technological advances in the field of genome sequencing, “omics”, genome editing, and artificial intelligence-based approaches (e.g., machine learning and deep learning) have allowed to us explore the in-depth genetic mechanism at high accuracy underlying the important traits of soybean and to further deploy these results for the improvement of soybean yield, quality, and stress tolerance to achieve self-sufficiency in soybean production.
For this Special Issue, we seek the submission of research and review articles related to both basic research and technological advancements in soybean genetics and breeding. Authors are welcome to submit articles in the areas of genetic mapping, gene identification, genomic selection, gene editing, genetic engineering, marker-assisted breeding, omics-assisted breeding, high-throughput phenotyping, and other related areas. It is emphasized that papers submitted in this Special Issue are required to possess novel results and/or new plausible and testable models for the integrative analysis of the different approaches applied to soybean breeding.
Prof. Dr. Xianzhong Feng
Prof. Dr. Piwu Wang
Guest Editors
Manuscript Submission Information
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Keywords
- soybean
- genetic mapping
- functional genomics
- yield and quality improvement
- biotic and abiotic stress resistance
- omics
- molecular breeding
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