Food Legume Genomics
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Plant Genetics and Genomics".
Deadline for manuscript submissions: closed (15 February 2021) | Viewed by 36090
Special Issue Editors
Interests: population genomics; evolution; plant genetic resources; plant breeding; legumes
Special Issue Information
Dear Colleagues,
Recently, we assisted to an ever-increasing interest for food legumes due to the fact that they represent a valuable source of proteins, lipids, and fiber, and an alternative source of these compounds in human consumption. In particular, pulses, a crucial source of protein in less developed countries, are also becoming increasingly important in developed countries, where they can be used as alternative sources of food protein over animal products, and for their health benefits related to regular consumption.
A general lack of systematic breeding efforts to increase yield capacity, adaptation to different agro-ecosystems and quality of food legumes was the rule during the past decades. Thus, a breeding effort to broad the genetic bases of elite germplasm of these crops is required to improve agronomic performances, resistance to biotic and abiotic stresses, nutritional and technological quality of seeds. This Special Issue in Genes on “Food Legume Genomics” will contribute to increase the knowledge of food legume plant genetic resources by deep genomic and phenotypic characterization (e.g. omics technologies) of underutilized and underexploited genetic diversity present in available wild and domesticated germplasm, along with the parallel characterization of mapping populations to identify, by applying the most recent population genomics, linkage and association mapping approaches, the genetic control of important phenotypic traits. The new results will be the starting point of breeding programs aimed to improve food legume varieties.
Dr. Elena Bitocchi
Dr. Monica Rodriguez
Guest Editors
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Keywords
- genomics
- molecular phenotyping
- phenomics
- association mapping
- population genomics
- nutritional quality
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