Enhancing Sorghum Genetic Diversity for Agronomic Traits
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".
Deadline for manuscript submissions: closed (29 March 2021) | Viewed by 429
Special Issue Editor
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The identification and evaluation of genetically diverse sorghum germplasm are imperative for the sustained success of breeding programs. Today, most sorghum breeding programs are based on a narrow genetic diversity that might be limiting the development of new varieties. The large size of several sorghum germplasm collections has hampered the screening and identification of germplasm with important agronomic traits, and as a result, most sorghum genetic diversity is enclosed in these collections. Nevertheless, the integration and use of genomics and phenomics approaches are providing new insight into how to preserve and make the most adequate use of these sorghum germplasm collections. At the same time, the genomic dissection of important traits present in these sorghum germplasm collections is providing the knowledge and genomic tools necessary for its immediate use in breeding programs.
This Special Issue of Agronomy focusses on the study of genetic and phenotypic diversity present in germplasm collections, as well as among sorghum breeding varieties. We would like to include several articles or reviews that relate to the screening, phenotypic and genetic characterization, and the inheritance of agronomic important traits present in collections and breeding materials. Certainly, this Special Issue is a new opportunity to recognize the importance of germplasm collections, to increase genetic diversity in sorghum breeding programs, and the development of new varieties.
Dr. Hugo E. Cuevas
Guest Editor
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Keywords
- germplasm collection
- next-generation sequencing
- genotype-by-sequence
- GWAS
- germplasm screening
- phenomics
- genome mapping
- marker assistant selection
- crop evolution
- allele mining
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