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Does the Organ-Based N Dilution Curve Improve the Predictions of N Status in Winter Wheat?

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  • Ke Zhang

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China)

  • Xue Wang

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

  • Xiaoling Wang

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

  • Syed Tahir Ata-Ul-Karim

    (Institute for Sustainable Agro-ecosystem Services, The University of Tokyo. Department of Global Agricultural Studies, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8654, Japan)

  • Yongchao Tian

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

  • Yan Zhu

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

  • Weixing Cao

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

  • Xiaojun Liu

    (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
    Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing Agricultural University, Nanjing 210095, China
    Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China
    Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

Accurately summarizing Nitrogen (N) content as a prelude to optimal N fertilizer application is complicated during the vegetative growth period of all the crop species studied. The critical nitrogen (N) concentration (Nc) dilution curve is a stable diagnostic indicator, which performs plant critical N concentration trends as crop grows. This study developed efficient technologies for different organ-based (plant dry matters (PDM), leaf DM (LDM), stem DM (SDM), and leaf area index (LAI)) estimation of Nc curves to enrich the practical applications of precision N management strategies. Four winter wheat cultivars were planted with 10 different N treatments in Jiangsu province of eastern China. Results showed the SDM-based curve had a better performance than the PDM-based curve in N nutrition index (NNI) estimation, accumulated N deficit (AND) calculation, and N requirement (NR) determination. The regression coefficients ‘a’ and ‘b’ varied among the four critical N dilution models: Nc = 3.61 × LDM –0.19 , R 2 = 0.77; Nc = 2.50 × SDM –0.44 , R 2 = 0.89; Nc = 4.16 × PDM –0.41 , R 2 = 0.87; and Nc = 3.82 × LAI –0.36 , R 2 = 0.81. In later growth periods, the SDM-based curve was found to be a feasible indicator for calculating NNI, AND, and NR, relative to curves based on the other indicators. Meanwhile, the lower LAI-based curve coefficient variation values stated that leaf-related indicators were also a good choice for developing the N curve with high efficiency as compared to other biomass-based approaches. The SDM-based curve was the more reliable predictor of relative yield because of its low relative root mean square error in most of the growth stages. The curves developed in this study will provide diverse choices of indicators for establishing an integrated procedure of diagnosing wheat N status, and improving the accuracy and efficiency of wheat N fertilizer management.

Suggested Citation

  • Ke Zhang & Xue Wang & Xiaoling Wang & Syed Tahir Ata-Ul-Karim & Yongchao Tian & Yan Zhu & Weixing Cao & Xiaojun Liu, 2020. "Does the Organ-Based N Dilution Curve Improve the Predictions of N Status in Winter Wheat?," Agriculture, MDPI, vol. 10(11), pages 1-19, October.
    • Handle: RePEc:gam:jagris:v:10:y:2020:i:11:p:500-:d:434640
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    References listed on IDEAS

    as
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