Co-variant analysis and statistical modelling for improved crop yield

提高作物产量的协变分析和统计模型

• 批准号: LP150100055
• 负责人: Prof Stanley Miklavcic
• 金额: $ 27.5万
• 依托单位: University of South Australia
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-03-22 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP150100055
• 关键词: Co; variant; analysis; statistical; modelling

This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and internal factors correlate with the major growth and development stages at the crop level. This project seeks to develop and implement mathematical and statistical tools to analyse genetic, agronomic and phenomic factors that affect plant performance, to deliver advanced yield prediction.

该项目计划开发数学工具，帮助确定产量最高的谷类植物品种。这是植物育种者的重要责任，许多澳大利亚育种者获得并储存与该问题相关的重要信息。然而，目前还没有数学工具能够共同分析异质和高维数据，以了解外部和内部因素如何与作物层面的主要生长和发育阶段相关。该项目旨在开发和实施数学和统计工具，以分析影响植物性能的遗传，农艺和表型因素，以提供先进的产量预测。