Monitoring of nitrogen accumulation in wheat plants based on hyperspectral data

高光谱成像 均方误差 环境科学 数学 植被(病理学) 作物 天蓬 遥感 回归分析 氮气 农学 统计 植物 生物 化学 地理 医学 有机化学 病理
作者
Xiao Song,Duanyang Xu,Chenchen Huang,Keke Zhang,Shaomin Huang,Doudou Guo,Shuiqing Zhang,Ke Yue,Tengfei Guo,Shasha Wang,Hecang Zang
出处
期刊:Remote Sensing Applications: Society and Environment [Elsevier BV]
卷期号:23: 100598-100598 被引量:12
标识
DOI:10.1016/j.rsase.2021.100598
摘要

Abstract Crop nitrogen nutrition is an important indicator for evaluating crop growth. Rapid and non-destructive estimation of nitrogen accumulation in wheat leaves is of great significance for crop nitrogen fertilizer management. Based on field test data from multiple wheat varieties for different locations, years, nitrogen levels, and growth periods, the relationship between 11 canopy hyperspectral parameters and nitrogen accumulation in wheat plants was studied. According to the results of correlation and regression analysis, the flowering period of wheat was selected as the most suitable growth period for crop growth evaluation (the average R2 was 0.732, and the root mean square error (RMSE) was 0.354). A new vegetation index, NDchI*DDN (referred to as the nitrogen accumulation vegetation index, abbreviated as NAVI), was constructed based on the pairwise combination of traditional vegetation index products. This parameter had a high correlation with plant nitrogen accumulation (R2 = 0.856), and the root mean square error (RMSE) was 0.296. Tested by independent experimental data, the fitting degree of the plant nitrogen accumulation inversion model established with NAVI as the variable was R2 = 0.861, the relative error RE = 9.3%, RMSE = 0.398, and the prediction accuracy was significantly higher than other models. Therefore, construction of a NAVI-based plant nitrogen accumulation monitoring model gave ideal test results, which could reduce the limitations of experimental conditions and is expected to provide new important technical support for precise fertilization.
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