QTL Mapping of Seed Quality Traits in Crops, 2nd Edition
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 27
Special Issue Editor
Interests: plant genetics, genomics, and biotechnology; QTL mapping of important agronomic traits especially seed composition traits in soybean and other crops
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Seeds of major crops are rich in valuable compounds that are essential for the food and feed industries. The nutritional and health benefits of animal feed and human diets rely heavily on seed-derived proteins, amino acids, oils, fatty acids (such as palmitic, stearic, oleic, linoleic, linolenic acids), sugars (including glucose, galactose, sucrose, raffinose), isoflavones (daidzein, genistein, glycitein), vitamins, minerals, secondary metabolites, and other nutrients. Understanding the genetic basis of these beneficial compounds is critical. Over the past three decades, numerous studies have been conducted to identify and map the quantitative trait loci (QTL) associated with these traits. However, many of these QTL regions remain poorly characterized, with most candidate genes still unidentified.
This Special Issue of Plants aims to advance the field by focusing on the genetic and QTL mapping of seed quality traits in crops, utilizing both traditional mapping populations (such as recombinant inbred lines (RILs), F2, doubled haploid, etc.) and genome-wide association studies (GWAS). Submissions that identify candidate genes within the identified QTL regions are especially encouraged.
We also welcome papers that integrate artificial intelligence (AI) and machine learning (ML) techniques in the analysis of genetic and QTL data. AI and ML offer powerful tools for uncovering hidden patterns, predicting trait outcomes, and enhancing the precision of QTL mapping and candidate gene identification. Studies leveraging these advanced computational approaches to gain new insights into seed quality traits are highly welcomed. We look forward to receiving your valuable contributions to this Special Issue.
Prof. Dr. Abdelmajid Kassem
Guest Editor
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Keywords
- crops
- QTL mapping
- seed quality traits
- GWAS
- seed protein
- oil
- fatty acids
- amino acids
- sugars
- isoflavones
- AI
- ML
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