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Acta Agron Sin ›› 2017, Vol. 43 ›› Issue (12): 1835-1844.doi: 10.3724/SP.J.1006.2017.01835

• TILLAGE & CULTIVATION · PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Remote Detection of Canopy Leaf Nitrogen Status in Soybean by Hyperspectral Data under Monoculture and Intercropping Systems

CHEN Jun-Xu, HUANG Shan, FAN Yuan-Fang, WANG Rui, LIU Qin-Lin, YANG Wen-Yu*,YANG Feng*   

  1. Key Laboratory of Crop Eco-physiology and Farming System in Southwest, the Ministry of Agriculture / College of Agronomy, Sichuan Agricultural University / Sichuan Engineering Research Center for Crop Strip Intercropping System, Sichuan 611130, China
  • Received:2017-03-09 Revised:2017-05-10 Online:2017-12-12 Published:2017-06-08
  • Contact: 杨峰, E-mail: f.yang@sicau.edu.cn; 杨文钰, E-mail: mssiyangwy@sicau.edu.cn E-mail:m17740901718@163.com
  • Supported by:

    The work was supported by the National Key Research and Development Program of China (2016YFD0300602).

Abstract:

Non-destructive monitoring of soybean nitrogen status is important for precise N management in soybean production. In this study, the quantitative correlation between soybean leaf nitrogen status and canopy hyperspectral reflectance was investigated. Field experiments were conducted. With four nitrogen application rates for two years under monoculture and intercropping systems. The nitrogen accumulation of canopy leaves showed a single-peak changing trend in the process of soybean growth. The maximum value in monoculture and intercropping was 8.7 g m–2, 8.38 g m–2, respectively, at pod stage under N3 treatment. The raw hyperspectral reflectance and the leaf nitrogen accumulation had the same changing trend at different growth stages with different planting patterns. The peak value of the raw hyperspectral reflectance in the 700–1000 nm occurred at pod stage. In the first-order derivative spectrum, the red edge amplitude values increased first and then decreased. The position of the red edge changed as “Red shift” and “Blue shift” with the increase or decrease of leaf nitrogen accumulation. The results of the correlation analysis showed that the linear model and the power model by using the Difference Spectral Index (DSI: 771, 755) based on the best spectral band combination (BSBC) had the greatest accuracy to estimate the leaf nitrogen status of soybean.

Key words: Soybean, Nitrogen accumulation, Hyperspectral reflectance, Model

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