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

• Main Authors: Ke Zhang, Xue Wang, Xiaoling Wang, Syed Tahir Ata-Ul-Karim, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaojun Liu
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Agriculture
• Subjects: critical nitrogen dilution curve; leaf area index; N diagnosis; dry matters; grain yield
• Online Access: https://www.mdpi.com/2077-0472/10/11/500

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, R² = 0.77; Nc = 2.50 × SDM^–0.44, R² = 0.89; Nc = 4.16 × PDM^–0.41, R² = 0.87; and Nc = 3.82 × LAI^–0.36, R² = 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.