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Chinese Journal of Applied Ecology ›› 2020, Vol. 31 ›› Issue (2): 433-440.doi: 10.13287/j.1001-9332.202002.029

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Model construction and application for nitrogen nutrition monitoring and diagnosis in double-cropping rice of Jiangxi Province, China

LI Yan-da1*, CAO Zhong-sheng1, SUN Bin-feng1, YE Chun1, SHU Shi-fu1, HUANG Jun-bao1, WANG Kang-jun1, TIAN Yong-chao2   

  1. 1Institute of Agricultural Engineering, Jiangxi Academy of Agricultural Sciences/Jiangxi Province Engineering Research Center of Intelligent Agricultural Machinery Equipment/Jiangxi Province Engineering Research Center of Information Technology in Agriculture, Nanchang 330200, China;
    2Nanjing Agricultural University/National Engineering and Technology Center for Information Agriculture, Nanjing 210095, China
  • Received:2019-04-26 Online:2020-02-15 Published:2020-02-15
  • Contact: * E-mail: liyanda2008@126.com
  • Supported by:
    This work was supported by the National Key R&D Program of China (2016YFD0300608), the National Program for Support of Top-notch Young Professionals, the Jiangxi Science and Technology Program (20182BCB22015, 20161BBI90012, 20192BBF60052), the Jiangxi “Double-Thousand Plan”, and the Jiangxi “Voyage Project”.

Abstract: The spectrometer-based nitrogen (N) nutrition monitoring and diagnosis models for double-cropping rice in Jiangxi is important for recommending precise N topdressing rate, achieving high yield, improving grain quality and increasing economic efficiency. Field experiments were conducted in Jiangxi in 2016 and 2017, involving different early rice and late rice cultivars and N application rates. Plant N accumulation (PNA) and canopy spectral vegetation indices (VIs) were measured at tillering and jointing stages with two spectrometers, i.e., GreenSeeker (an active multispectral sensor containing 780 and 660 nm wavelengths) and crop growth monitoring and diagnosis apparatus (CGMD, a passive multispectral sensor containing 810 and 720 nm wavelengths). The VI-based models of PNA were established from a experimental dataset and then validated using an independent dataset. The N topdressing rates for tillering and jointing stages were calculated using the newly developed N spectral diagnosis model and higher yield cultivation experience of double-cropping rice. The results showed that the VIs from two spectrometers were strongly positively correlated with PNA at both growth stages, with the model performance for tillering or jointing stages was better than that for the early growth stages. The exponential equation of normalized difference vegetation index (NDVI(780,660)) from GreenSeeker could be used to estimate PNA with a determination coefficient (R2) in the range of 0.92-0.94, the root mean square error (RMSE), relative root mean square error (RRMSE) and correlation coefficient (r) of model validation in the range of 3.09-5.96 kg·hm-2, 5.8%-18.5% and 0.92-0.98, respectively. The linear equation of difference vegetation index (DVI(810,720)) from CGMD could be used to estimate PNA with a R2 in the range of 0.90-0.93, the RMSE, RRMSE and r of model validation in the range of 3.71-6.33 kg·hm-2, 11.7%-14.3% and 0.93-0.96, respectively. The recommended N topdressing rate with CGMD was higher than that with GreenSeeker. Compared with conventional farmer’s plan, the precision N application plan reduced N fertilizer application rate by 5.5 kg·hm-2, while N agronomic efficiency and net income was improved by 0.8% and 128 yuan·hm-2, respectively. Application of the spectral monitoring and diagnosis method to guiding fertilization could reduce cost and increase grain yield and net income, and thus had great potential for guiding double-cropping rice production.