Skip to content
Research Article Open access CC BY 4.0

Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies

Ramesh Sunagar, Manoj Kumar Pandey

Journal of Advances in Biology & Biotechnology · pp. 174–185 · Published 8 May 2024

10.9734/jabb/2024/v27i6877

Abstract

Mustard, a vital oilseed crop, plays a significant role in global agriculture due to its versatile applications in food, feed, and biofuel industries. However, meeting the increasing demands for yield and quality traits poses a substantial challenge to mustard breeders. In response, genomic approaches have emerged as powerful tools to expedite mustard breeding programs by unraveling the genetic basis of key agronomic traits. This review provides a comprehensive overview of genomic strategies aimed at enhancing yield and quality traits in mustard. Beginning with an exploration of traditional breeding methods and their limitations, we delve into the advancements in genomics, including next-generation sequencing technologies, marker-assisted selection (MAS), and genome editing techniques. We discuss how these tools are leveraged to identify yield-related genes, quantitative trait loci (QTLs), and markers for efficient trait selection. Furthermore, we examine genomic approaches for improving oil content, nutritional profiles, and phytochemical composition, crucial for enhancing mustard quality. Case studies demonstrating the successful integration of genomics into breeding programs are highlighted, along with discussions on challenges such as regulatory concerns and technical hurdles. Finally, we outline future directions and the potential of genomic approaches to revolutionize mustard breeding, paving the way for sustainable crop improvement. This study offers valuable insights into the application of genomics in mustard breeding and underscores its importance in addressing the evolving needs of agriculture in the 21st century.

Mustard genomic approaches yield quality breeding Marker-assisted Selection (MAS)

Cited by 1

1 citation reported by external sources — individual citing-article records aren't available to list yet.

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

1

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.