Case Study

Genetic Enhancement of Wheat for Pasta Production  

Zhengqi  Ma , Wei  Wang
Institute of Life Sciences, Jiyang College of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Triticeae Genomics and Genetics, 2025, Vol. 16, No. 1   
Received: 27 Dec., 2024    Accepted: 10 Feb., 2025    Published: 26 Feb., 2025
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This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

High-quality wheat is the core raw material for pasta production, and its key quality traits play a decisive role in the cooking and processing quality of pasta. However, the complex genetic basis, multi-gene regulation mode and significant gene-environment interaction of these traits pose great challenges to breeding. This study reviews the key quality requirements and genetic basis of high-quality pasta wheat, discusses in detail the application progress of genetic improvement technology in wheat quality improvement, and focuses on the research results in the fields of molecular marker development, gene editing and multi-omics data integration. At the same time, the technical bottlenecks and challenges in the current genetic improvement of high-quality wheat are analyzed, including the complexity of phenotypic measurement, gene-environment interaction in multi-environment experiments, and the need for variety development to adapt to climate change conditions. Future breeding strategies based on the comprehensive utilization of genetic and environmental factors are proposed, and the potential value of genomics and multi-omics technologies in promoting pasta-specific wheat breeding is envisioned. This study provides an important scientific reference for global food security and the sustainable development of the pasta industry.

Keywords
Pasta wheat; Quantitative trait loci (QTL); Marker-assisted selection; Gene editing; Multi-omics integration; precision breeding
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