Triticeae crops, such as wheat, barley, and rye, are staple foods for more than 40% of the world's population and account for more than 20% of calorie intake. Given the predicted growth in global population, it is expected that worldwide demand for Triticeae crops would rise sharply in the next years. However, multiple diseases (stripe rust, powdery mildew, Fusarium head blight, etc.), harsh weather (cold and heat, etc.), and limited resources (water, nutrients, etc.) make their production unpredictable. To address the rising demand for these Triticeae crops, high-yielding varieties with good resistance and tolerance should be developed. However, existing staple varieties have been artificially selected for their adaptation performance for the special environment, resulting in poor yield stability and massive losses in response to abnormal climate extremes or novel pathogens. Although, in recent years, with the publication of genomic and pan-genomic sequencing information for Triticeae crops, the successive development of various gene chips, and the maturation of multi-omics technologies, an increasing amount of new genetic information has been made available for use in molecular breeding. Traditional manual phenotypic surveys, however, are less efficient, less accurate, and less repeatable, which can have an impact on the application and functional evaluation of target genes.
With the maturation of various new high-throughput imaging technologies, platform equipment such as intelligent greenhouses and drones, as well as remote sensing and hyperspectral imaging, have begun to be used in high-throughput phenotypic surveys of crops, improving the reliability and reproducibility of phenotypic data under specific adversity conditions, which, when combined with the constantly updated effective information of the genome, supports the molecular design breeding. The primary goal of this topic is to discuss the progress of high-throughput gene mining and phenotyping investigations in Triticeae crops, as well as their application to genetic improvement of resistance, tolerance, and yield stability.
The topics include the researches but are not limited to:
• QTL mapping, superior allele mining, functional markers developing and applying for traits related to high yield, stable yield, high resistance, multiple resistance, stress tolerance, and efficient utilization based on high-throughput phenotyping techniques;
• creation, evaluation and application of excellent germplasm resources in Triticeae crops under intelligent greenhouse or climate-environment monitored field conditions;
• multi-omics studies covering metabolome or phenome for specific adversity conditions.
Triticeae crops, such as wheat, barley, and rye, are staple foods for more than 40% of the world's population and account for more than 20% of calorie intake. Given the predicted growth in global population, it is expected that worldwide demand for Triticeae crops would rise sharply in the next years. However, multiple diseases (stripe rust, powdery mildew, Fusarium head blight, etc.), harsh weather (cold and heat, etc.), and limited resources (water, nutrients, etc.) make their production unpredictable. To address the rising demand for these Triticeae crops, high-yielding varieties with good resistance and tolerance should be developed. However, existing staple varieties have been artificially selected for their adaptation performance for the special environment, resulting in poor yield stability and massive losses in response to abnormal climate extremes or novel pathogens. Although, in recent years, with the publication of genomic and pan-genomic sequencing information for Triticeae crops, the successive development of various gene chips, and the maturation of multi-omics technologies, an increasing amount of new genetic information has been made available for use in molecular breeding. Traditional manual phenotypic surveys, however, are less efficient, less accurate, and less repeatable, which can have an impact on the application and functional evaluation of target genes.
With the maturation of various new high-throughput imaging technologies, platform equipment such as intelligent greenhouses and drones, as well as remote sensing and hyperspectral imaging, have begun to be used in high-throughput phenotypic surveys of crops, improving the reliability and reproducibility of phenotypic data under specific adversity conditions, which, when combined with the constantly updated effective information of the genome, supports the molecular design breeding. The primary goal of this topic is to discuss the progress of high-throughput gene mining and phenotyping investigations in Triticeae crops, as well as their application to genetic improvement of resistance, tolerance, and yield stability.
The topics include the researches but are not limited to:
• QTL mapping, superior allele mining, functional markers developing and applying for traits related to high yield, stable yield, high resistance, multiple resistance, stress tolerance, and efficient utilization based on high-throughput phenotyping techniques;
• creation, evaluation and application of excellent germplasm resources in Triticeae crops under intelligent greenhouse or climate-environment monitored field conditions;
• multi-omics studies covering metabolome or phenome for specific adversity conditions.
