| 陈龙跃,段丹丹,徐卫兵,等.高通量表型分析在农业的应用与挑战[J].广东农业科学,2024,(8-10):- |
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高通量表型分析在农业的应用与挑战 |
| Applications And Challenges of High-Throughput Phenotyping in Agriculture |
| 投稿时间：2024-06-01 修订日期：2024-07-30 |
| DOI： |
| 中文关键词: 高通量 农作物 表型 大数据 深度学习 挑战 |
| 英文关键词: high-throughput crops phenotypes big data deep learning challenges |
| 基金项目:岭南现代农业科学与技术广东省实验室河源分中心自主科研资助项目(DT20220006)；广东省科技计划资助项目(2023B0208010002) |
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| 摘要点击次数: 10 |
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| 中文摘要: |
| 农作物高通量表型分析作为一种新兴的技术手段,旨在通过分析大量的表型数据,快速、准确地揭示农作物性状与基因和环境之间的关系,进而优化育种效率和准确性、提升作物产量和品质、解决全球人口增加,以及环境恶化趋势下对粮食需求提升的问题。在对农作物高通量表型分析的关键技术架构进行剖析后,从传感器、多尺度观测和大数据挖掘层面阐述了收集、整理和分析农作物表型信息的手段及其不足。在此基础上综述了近年来农作物表型分析的主要应用领域,研究证实农作物高通量表型分析是量化作物性状、监测作物长势、优化田间管理、提升育种效率的有效工具,但其应用性能仍具有提升潜力。最后,探讨农作物高通量表型分析面临的挑战、优化方案、广阔前景及未来发展趋势。表明其在数据处理和解析、跨种、跨组织、跨环境的应用等方面还存在着挑战,但随着对大体量、高复杂度数据处理有着巨大优势的云端大数据处理平台和人工智能等前沿技术的日益发展,同时结合生物技术和基因组学研究方法,农作物高通量表型分析将在对抗全球环境变化和人口增加所带来的粮食短缺隐患中发挥举足轻重的作用。 |
| 英文摘要: |
| As an emerging technical means, high-throughput phenotyping of crops aims to quickly and accurately reveal the relationship between crop traits, genes and environment by analyzing a large amount of phenotypic data, thereby optimizing breeding efficiency and accuracy, and improving crop yield and quality, solving the problem of increased demand for food amid the increasing global population and environmental deterioration. After analyzing the key technical architecture of high-throughput phenotypic analysis of crops, the methods and shortcomings of collecting, sorting and analyzing crop phenotypic information are explained from the aspects of sensors, multi-scale observation and big data mining. On this basis, the main application areas of crop pheno-typing analysis in recent years were reviewed. The study confirmed that high-throughput crop phenotyping analysis is an effective tool for quantifying crop traits, monitoring crop growth, optimizing field management, and improving breeding efficiency. However, its application performance still has potential for improvement. Finally, the challenges, optimization solutions, broad prospects and future development trends of high-throughput phenotyping of crops were discussed. It shows that there are still challenges in data processing and analysis, cross-species, cross-organization, and cross-environment applications. However, with the increasing development of cutting-edge technologies such as cloud big data processing platforms and artificial intelligence, which have great advantages in processing large-volume and high-complexity data, combined with biotechnol-ogy and genomics research methods, high-throughput phenotyping of crops will play a pivotal role in combating food shortages caused by global environmental changes and population increase. |
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