新疆农业科学 ›› 2024, Vol. 61 ›› Issue (11): 2705-2712.DOI: 10.6048/j.issn.1001-4330.2024.11.011

• 作物遗传育种·耕作栽培 • 上一篇    下一篇

基于遥感数据构建冬小麦孕穗期变量施氮模型

陈荣1(), 赖宁2, 耿庆龙2, 李永福2, 信会男2, 吕彩霞2, 李娜2, 陈署晃2()   

  1. 1.新疆农业大学资源与环境学院,乌鲁木齐 830052
    2.新疆农业科学院土壤肥料与农业节水研究所,乌鲁木齐 830091
  • 收稿日期:2024-05-20 出版日期:2024-11-20 发布日期:2025-01-08
  • 通信作者: 陈署晃(1973-),女,湖南人,研究员,硕士,研究方向为土壤肥料与农业信息技术,(E-mail)chensh66@163.com
  • 作者简介:陈荣(1997-),男,贵州纳雍人,硕士研究生,研究方向为农业信息化,(E-mail)chenrong2581@163.com
  • 基金资助:
    新疆小麦产业技术体系(XJARS-01-21);新疆维吾尔自治区自然科学基金面上基金(2023D01A95);农业科技创新稳定支持专项(xjnkywdzc-2023002);农业科技创新稳定支持专项(xjnkywdzc-2023007-3);新疆维吾尔自治区重大专项(2022A02011-2);新疆农业科学院自主培育专项(xjnkycxzx-2022004)

Study on variable nitrogen fertilization model of winter wheat during booting period based on remote sensing data

CHEN Rong1(), LAI Ning2, GENG Qinglong2, LI Yongfu2, XIN Huinan2, LYU Caixia2, LI Na2, CHEN Shuhuang2()   

  1. 1. College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    2. Institute of Soil, Fertilizer and Agricultural Water Conservation, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
  • Received:2024-05-20 Published:2024-11-20 Online:2025-01-08
  • Supported by:
    Xinjiang Wheat Industry Agriculture System(XJARS-01-21);General Project of the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2023D01A95);Steadily Stable Support to Agricultural Science and Technology Innovation(xjnkywdzc-2023002);Steadily Stable Support to Agricultural Science and Technology Innovation(xjnkywdzc-2023007-3);Major R & D Project of Xinjiang Uygur Autonomous Region(2022A02011-2);Xinjiang Academy of Agricultural Sciences independent breedingspecial project(xjnkycxzx-2022004)

摘要:

【目的】研究根据冬小麦关键生育期生长需求解析氮丰缺识别和精准定量施氮模型,实现量化施氮,为冬小麦智慧施肥种植的关键技术提供参考。【方法】利用ASD HH2高光谱仪获取不同施氮量的冬小麦冠层反射率,记录叶绿素浓度和产量等信息。通过冬小麦冠层反射率提取14种植被指数,选择最优表征植株氮状况的植被指数,分析施氮量、植被指数和冬小麦的产量之间的关系,构建基于植被指数变量施氮模型。【结果】叶绿素浓度可以准确反映冬小麦的生长状况和施氮效果,不同的施氮量下冬小麦的冠层反射率数据差异显著;归一化植被指数NDVI的相关性好,相关系数达到0.705,较好反映了冬小麦冠层氮素效应的情况;构建了基于NDVI的冬小麦孕穗期变量施氮模型,即Nr=700.59×NDVI2-1693.46×NDVI+955.92。【结论】利用ASD HH2获取高光谱数据构建冬小麦施氮模型与方法。

关键词: 遥感; 植被指数; 施氮模型

Abstract:

【Objective】 The objective of this study is to identify and quantitatively analyze nitrogen abundance and deficiency according to the growth requirements of winter wheat during the key growth periods, so as to realize quantitative nitrogen fertilization, which is the key technology that should be solved in precise fertilization and intelligent planting.【Methods】 ASD HH2 hyperspectrometer was used to obtain the reflectance of winter wheat canopy with different nitrogen application rates, and the chlorophyll concentration and yield were recorded.According to the reflectance of the winter wheat canopy, 14 vegetation indices were extracted, and the vegetation index that best characterized the nitrogen status of plants was selected, and a nitrogen application model based on vegetation index variables was constructed according to the relationship between nitrogen application rate, vegetation index and winter wheat yield.【Results】 (1) Chlorophyll concentration could accurately reflect the growth status and nitrogen application effect of winter wheat, and there were significant differences in the canopy reflectance data of winter wheat under different nitrogen application rates.(2) Correlation analysis showed that the normalized vegetation index NDVI had a good correlation coefficient of 0.705, which better reflected the nitrogen effect of winter wheat canopy.(3) A variable nitrogen fertilization model based on NDVI was constructed at booting stage, i.e., Nr=700.59×NDVI2-1 693.46×NDVI+955.92, which provided a scientific basis for precise nitrogen fertilization of winter wheat.【Conclusion】 The hyperspectral data obtained by ASD HH2 were used to construct a model and method of nitrogen fertilization in winter wheat, which provided an important reference for the in-depth study of precision fertilization of winter wheat.

Key words: remote sensing; vegetation index; nitrogen application model

中图分类号: 


ISSN 1001-4330 CN 65-1097/S
邮发代号:58-18
国外代号:BM3342
主管:新疆农业科学院
主办:新疆农业科学院 新疆农业大学 新疆农学会

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