Applying advanced molecular biology, metabolomics and image analysis using machine-learning technology to improve wheat resistance against Fusarium head blight

小麦是一种主要作物，也是加拿大经济的组成部分，为生产者提供收入，为加拿大人提供就业机会。加拿大是世界第六大小麦生产国和第二大小麦出口国（约占世界市场的20%）。加拿大小麦产业，包括面包和硬粒小麦，经常受到真菌疾病的威胁，如镰刀菌头枯病（FHB），每年在加拿大造成数亿美元的损失。典型的FHB症状包括小穗过早漂白，轴变色和镰刀菌损害的籽粒（FDK）。FDK的重量轻，甚至商业小麦作物中的少量FDK都可能导致严重的产量和质量损失。FHB也是一个食品和饲料安全问题，因为谷物被真菌毒素脱氧雪腐镰刀菌烯醇（DON）污染。农民可能会经历等级损失，限制营销机会，增加成本，并因FHB而损失收入。与化学杀菌剂相比，培育抗性小麦品种是控制赤霉病最有效、最环保、也是最经济的策略。利用先进的分子生物学，基因组学，代谢组学和各种自动化成像工具，拟议的项目旨在全面了解小麦赤霉病抗性的分子机制，表征赤霉病抗性类型的遗传基础，开发有用的分子标记，为育种计划鉴定抗性种质，并开发支持这些进步所需的高通量成像和深度学习工具。最终，该项目产生的知识、种质、分子标记和表型分析工具将加速育种周期，使小麦产业受益。

Wheat is a staple crop and an integral part of the Canadian economy, providing income for producers and jobs for Canadians. Canada is the sixth largest producer of wheat in the world and the second largest exporter (~20% of the world market). The Canadian wheat industry, including both bread and durum wheat, is frequently threatened by fungal diseases, such as Fusarium head blight (FHB), which causes hundreds of millions of dollars in losses every year in Canada. Typical FHB symptoms include premature bleaching of spikelets, discolouration of the rachis, and Fusarium damaged kernels (FDK). The light weight of FDKs and even a small amount of FDKs within a commercial wheat crop can result in severe yield and quality losses. FHB is also a food and feed safety concern due to the contamination of grain by the mycotoxin deoxynivalenol (DON). Farmers will likely experience grade loss, restricted marketing opportunities, added costs, and lost income as a result of FHB. Compared to chemical fungicides, cultivation of resistant wheat varieties is the most efficient, eco-friendly and often the most economic strategy to control FHB. With advanced molecular biology, genomics, metabolomics and diverse automated imaging tools, the proposed project aims to provide a comprehensive understanding of the molecular mechanism of FHB resistance in wheat, characterize the genetic basis of the types of FHB resistance, develop useful molecular markers, identify resistant germplasm for breeding programs, and develop the high-throughput imaging and deep-learning tools required to support these advancements. Eventually, the knowledge, germplasm, molecular markers and phenotyping tools generated from this project will accelerate breeding cycles and benefit the wheat industry.