基于无人机甜菜叶片氮素积累量的反演  

Inversion of Nitrogen Accumulation in Sugar Beet Leaves Based on UAV Multispectral

作　　者：吴啟贤 汪旭 刘智鑫 邓裕帅 耿贵[1] WU Qixian;WANG Xu;LIU Zhixin;DENG Yushuai;GENG Gui(College of Advanced Agriculture and Ecological Environment,Heilongjiang University,Harbin 150080)

机构地区：[1]黑龙江大学现代农业与生态环境学院,哈尔滨150080

出　　处：《中国糖料》2024年第2期49-56,共8页Sugar Crops of China

基　　金：财政部和农业农村部国家现代农业产业技术体系(糖料)建设项目“甜菜种植制度”(CARS-170209);国家自然科学基金项目(32272148)资助。

摘　　要：【目的】试验研究不同播期甜菜氮素积累量(LNA)与植被指数的相关性,为后期精准施肥和科学管理提供理论依据。【方法】本试验共设置8个播期(3月27日、4月6日、4月16日、4月26日、5月6日、5月16日、5月26日、6月5日),利用大疆精灵4多光谱无人机观测获得甜菜多光谱遥感影像和田间实测冠层氮素积累量(LNA)数据,通过数据计算获得归一化植被指数(NDVI)、绿色归一化植被指数(GNDVI)、归一化差异红边指数(NDRE)、叶片叶绿素指数(LCI)、优化土壤调整植被指数(OSAVI)。采用无人机航拍对甜菜不同播期生长状态进行监测,建立氮素积累量(LNA)的反演模型。【结果】随着生长时期的增加叶片氮素积累量显著提高,随着播期的延后叶片氮素积累量逐渐下降,在4月6日叶片氮素积累量最高。将田间实测LNA分别与5种植被指数相拟合,决定系数(R^(2))均在0.7以上,其中NDRE拟合效果最好,NDRE决定系数(R^(2))为0.885,均方根误差(RMSE)为4.54,标准均方根误差(NRMSE)为8.22%,具有较好的预测效果。【结论】表明无人机遥感技术在甜菜LNA的预测上具有较高的可行性,为探究合理播期、精准施肥、增产增收提供重要的理论依据。【Objective】To investigate the correlation between nitrogen accumulation(LNA)and vegetation index of sugar beet at different sowing dates,and to provide theoretical basis for precise fertilization and scientific management in the later stage,【Methods】In this experiment,eight sowing dates(March 27,April 6,April 16,April 26,May 6,May 16,May 26,June 5)were set up,and multispectral remote sensing images of sugar beet and field measurements of canopy nitrogen accumulation(LNA)data were obtained using DJI Elf 4 multispectral UAV.Green Normalized Vegetation Index(GNDVI),Normalized Difference Red Edge Index(NDRE),Leaf Chlorophyll Index(LCI)and Optimized Soil Adjusted Vegetation Index(OSAVI)were obtained by data calculation.The inverse model of nitrogen accumulation(LNA)was established by monitoring the growth status of sugar beet at different sowing stages using unmanned aerial photography.【Results】The results showed that the leaf nitrogen accumulation increased significantly with the increase of the growth period,and gradually decreased with the delay of the sowing dates,with the highest leaf nitrogen accumulation on April 6.The field measured LNA was fitted with five vegetation indices respectively,and the coefficient of determination(R^(2))was above 0.7,among which NDRE had the best fitting effect,with the coefficient of determination(R^(2))of 0.885,root mean square error(RMSE)of 4.54 and standard root mean square error(NRMSE)of 8.22%,demonstrating a good prediction effect.【Conclusion】It demonstrates that UAV remote sensing technology has high feasibility in the prediction of LNA in sugar beet,which provides an important theoretical basis for exploring reasonable sowing date,precise fertilizer application and increasing yield and income.

关 键 词：甜菜 无人机遥感 多光谱 氮素 植被指数 

分 类 号：S566.3[农业科学—作物学]