| 小麦植株水分状况遥感监测研究进展与展望 |
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| 引用本文： | 史 博,马祖凯,刘小军,田永超,朱 艳,曹卫星,曹 强.小麦植株水分状况遥感监测研究进展与展望[J].麦类作物学报,2022(4):495-503. |
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| 作者姓名： | 史 博 马祖凯 刘小军 田永超 朱 艳 曹卫星 曹 强 |
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| 作者单位： | (南京农业大学国家信息农业工程技术中心/智慧农业教育部工程研究中心/农业农村部农作物系统分析与决策重点实验室/江苏省信息农业重点实验室/现代作物生产省部共建协同创新中心，江苏南京 210095) |
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| 基金项目： | 国家自然科学基金青年科学基金项目（31601222）；江苏现代农业产业技术体系建设专项（JATS［2020］467，JATS［2020］164） |
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| 摘 要： | 小麦植株水分状况的实时监测和快速诊断对提高农业水分利用效率和作物产量具有关键作用。本文在概述水分监测对小麦重要性的基础上，简要介绍了植株水分遥感监测诊断技术的发展历程和研究现状，明确了不同水分诊断指标的适用条件和优缺点。最后，提出当前研究存在的问题并对发展趋势进行了展望：应加强遥感信息与土壤、气象和表型信息等数据的融合，建立新型水分诊断指标；综合利用星-机-地一体化监测体系，发展数据同化技术；优化遥感数据处理方法，建立自动化处理流程；深入研究小麦需水生理过程和调控机理，结合人工智能等现代技术，实现智能化水分管理。
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| 关 键 词： | 小麦 遥感监测 植株水分状况 诊断指标 |
Progress and Prospects of Wheat Plant Water Status Monitoring by Remote Sensing |
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| SHI Bo,MA Zukai,LIU Xiaojun,TIAN Yongchao,ZHU Yan,CAO Weixing,CAO Qiang.Progress and Prospects of Wheat Plant Water Status Monitoring by Remote Sensing[J].Journal of Triticeae Crops,2022(4):495-503. |
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| Authors: | SHI Bo MA Zukai LIU Xiaojun TIAN Yongchao ZHU Yan CAO Weixing CAO Qiang |
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| Abstract: | Real-time monitoring and rapid diagnosis of wheat plant water status play a key role in improving agricultural water use efficiency and crop yield.Based on an overview of the importance of water monitoring to wheat, this paper briefly introduces the development process and research current status of remote sensing monitoring and diagnosis technology for plant water status, and clarifies the applicable conditions, advantages and disadvantages of different water diagnostic indicators.The existing problems in current research and the prospect in this field are presented.The integration of remote sensing information with soil, meteorological and phenotypic information is suggested to be strengthened, and new water diagnostic indicators need to be established.The satellite-machine-ground integrated work system should be comprehensively utilized by developping data assimilation technology.Remote sensing data processing methods should be optimized by establishing automated processing flow.In-depth studies need to be conducted regarding the physiological process and regulation mechanism of wheat water demand,along with modern technologies such as artificial intelligence, to achieve intelligent water management. |
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| Keywords: | Wheat Remote sensing Plant water status Diagnosis indicators |
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