Potential of establishing the universal critical nitrogen dilution curve for drip-irrigated maize

Abstract

Establishing a universal critical nitrogen dilution curve (CNDC) is essential for diagnosing crop nitrogen (N) status at a regional scale. This study aims to develop a universal CNDC based on aboveground biomass (AGB) under high-yield conditions for drip-irrigated spring maize in Xinjiang and to assess parameter uncertainty across different cultivars and regions. Field experiments were conducted at three locations in northern Xinjiang using five widely cultivated maize varieties subjected to various N treatments. Both classical and Bayesian approaches were employed to construct the CNDC, and parameter estimates (Nc=a×AGB^-b) were obtained using both approaches. The Bayesian approach yielded higher parameter estimates (a = 4.17, b = 0.32) compared to the classical approach (a = 3.44, b = 0.27), reflecting a better fit to the data, particularly at higher biomass levels. This suggests that the Bayesian approach more accurately captures the relationship between AGB and N concentration. Although regional and cultivar differences influenced the developmental progression of maize, affecting biomass accumulation and N concentration, the CNDC successfully captured these relationships. Furthermore, the Bayesian approach demonstrated superior performance in validating the relative yield-Nitrogen Nutrition Index (RY-NNI) relationship. This study offers valuable insights for precise N management of drip-irrigated spring maize in arid and semi-arid regions, contributing to the advancement of precision agriculture.