Journal Publication

Improving the prediction of plant N status for field crops require robust estimation of their critical N dilution curves and their parameters. For maize (Zea mays L.), several studies have contributed to develop separate critical N curves for different genotype, environment, and management (GxExM) combinations, but so far no rigorous analysis has been formally conducted to assess if the use of different curves is fully supported by experimental data and to understand if a more universal curve could be used for defining the plant N status of this crop.

This study presents a global synthesis of maize data related to plant biomass and plant N concentration (%N) with the main objective of implementing a Bayesian framework for fitting critical N curves (Nc = A1 W ^−A2) and testing the existence of differences in the main parameters of the curve (A1 and A2) across varying GxExM combinations. Five publications including trials with at least four sampling times for plant biomass were selected based on a systematic review of the literature. Biomass and %N pairs (n = 369) measured during vegetative growth were extracted from the selected papers and included in a dataset covering four countries (China, US, Canada, and France) and twenty different GxExM combinations.

Results of the Bayesian analysis revealed that the critical plant %N and biomass fitted for each GxExM combination presented negligible statistical differences for A1 but minor variation for A2 reflecting changes in N dilution pattern with biomass mostly when W was above 5 Mg ha^-1 (%Nc<2%). A hypothesis of changes in plant canopy architecture, related to variations in GxM (e.g., plant density, row spacing, hybrids) related to variations in the N dilution curve was postulated and needs further evaluation. Refining the estimation of %Nc will improve the assessment of plant N status.