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面向作物干旱胁迫诊断的表型成像技术研究进展OA北大核心CSTPCD

Research progress on the phenotype imaging technology for diagnosis of crop drought stress

中文摘要英文摘要

干旱胁迫是影响作物产量和农业可持续发展的重要因素.作物干旱胁迫的精准诊断是提高农业水资源利用率、推动高水效农业发展的重要基础.表型成像技术能够快速、无损、准确地获取和分析作物的表型特征,为作物干旱胁迫的精准诊断提供了有力支持.该文重点综述了作物干旱胁迫诊断的表型成像技术,首先介绍了RGB成像、三维成像、近红外成像、高光谱成像、叶绿素荧光成像和热成像 6种主流表型成像技术的原理、研究现状、优势及不足,然后总结了结合多种成像方法的融合成像技术的研究现状及应用优势.综述结果表明,单一成像方法存在诸多不足,如成本较高、数据处理复杂、获取表型类型单一等,融合成像技术可在一定程度上有效弥补单一成像技术缺陷.最后根据当前发展现状,从新装置、新设备的研发以及与人工智能新算法的结合两方面,对未来面向作物干旱胁迫诊断的表型成像技术研究进行展望.

Drought stress of crops is an important factor affecting their yield and sustainable agricultural development.Accurate diagnosis of crop drought stress is the basis for improving water resource utilization.Imaging technology can quickly,automatically,non-destructively,accurately acquire and analyze the phenotype characteristics of crops,providing a powerful new tool for crop science research.This paper focuses on the review of phenotype imaging analysis techniques for crop drought stress diagnosis.First,the single imaging technique for crop drought stress diagnosis was introduced,and then we introduced the fusion imaging technique for crop drought stress diagnosis.In the aspect of single imaging technology introduction,firstly,the principles of six phenotype imaging techniques including RGB imaging,3D imaging,near-infrared imaging,hyperspectral imaging,chlorophyll fluorescence imaging and thermal imaging are introduced in this paper,and then we introduced research progress of the single imaging technology in crop drought stress phenotype analysis,beside the research achievements in crop drought stress in recent years were further summarized.Finally,the imaging technology was summarized and prospected at the end of each imaging technology introduction.In the fusion imaging technology of crop drought stress,this paper first summarized the research results of the automatic comprehensive phenotype imaging analysis platform of crop drought stress in recent years,and then summarized and analyzed the research of different fusion imaging methods,analyzed their advantages and disadvantages,and prospected the future research direction of fusion imaging technology in the end.With the horizontal and vertical comparative analysis of the research results of a single imaging technology,we found that RGB imaging technology has the lowest application cost and the most extensive application range,but the lowest accuracy.The 3D imaging solves the problem of crop occlusion in RGB imaging,improves the accuracy,and is widely used in high-throughput phenotype extraction platforms.The information on crop phenotype parameters can be obtained by near-infrared spectroscopy,chlorophyll fluorescence and hyperspectral imaging in a fast and non-destructive way.Among them,the application scope of NIR imaging is limited due to its limited ability to obtain phenotype information and relatively high cost.Chlorophyll fluorescence and hyperspectral imaging are better at obtaining physiological and biochemical parameters of crops,and are widely used in the fusion of imaging methods.Thermal images obtained by infrared thermal imaging are often used to obtain crop physiological parameters,and are also combined with visible light images for phenotype extraction.In the meantime,the method of obtaining crop phenotype by using the fusion of multiple imaging technologies has the advantages of different imaging technologies,which can effectively avoid the defects of a single imaging technology and make up for the deficiencies of obtaining single imaging phenotype parameters,so as to reflect the crop growth status more accurately and efficiently.More accurate feature extraction can be achieved by integrating various image information obtained by various imaging technologies and using artificial intelligence methods for integrated image processing.The use of fusion imaging technology to obtain crop phenotypes will be one of the important directions of crop drought stress phenotypes extraction in the future.Finally,according to the current development situation,future research on phenotypic imaging technology for crop drought stress diagnosis prospects,including the development of new devices and the combination of new artificial intelligence algorithms.

程强;刘雨欣;杨涵青;许新宇;范继泽;颜小飞;杜太生

中国农业大学信息与电气工程学院,北京 100083||农业水资源高效利用全国重点实验室,北京 100083||甘肃武威绿洲农业高效用水国家野外科学观测研究站,武威 733009中国农业大学信息与电气工程学院,北京 100083北京林业大学工学院,北京 100083农业水资源高效利用全国重点实验室,北京 100083||甘肃武威绿洲农业高效用水国家野外科学观测研究站,武威 733009

农业科学

作物干旱胁迫表型分析成像技术精准诊断

cropsdrought stressphenotypingimaging techniquesprecision diagnosis

《农业工程学报》 2024 (020)

1-11 / 11

国家自然科学基金项目(32271990);国家重点研发计划项目(2023YFD2301101-01);拼多多中国农业大学研究基金资助项目(PC2023A02002)

10.11975/j.issn.1002-6819.202307188

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