Optimizing nitrogen application rate by establishing a unified critical nitrogen dilution curve for maize under different mulching planting patterns

Abstract

Nitrogen (N) nutrition is essential for crop production and a critical N dilution curve (CNDC) could provide a novel strategy for diagnosing plant N status. CNDCs for several crops under different scenarios have been established to optimize N management. However, few studies have been conducted to establish a CNDC for maize (Zea mays L.) under ridge-furrow planting with film mulching over ridges, a planting pattern that has been widely adopted in semi-arid regions due to its improvement in soil water status. In addition, the effects of varied planting patterns on CNDC remain unknown. Therefore, a four-year (2018–2021) field experiment was conducted to establish CNDCs and provide a precise diagnosis of maize N status under different mulching planting patterns. Four N levels (0, 90, 180, and 270 kg N ha1 for the 2018–2020 period; and 100, 150, 200, and 300 kg N ha1 for 2021) were applied under three mulching planting patterns: flat planting without film mulching, ridge-furrow planting with transparent plastic film mulching over ridges, and ridge-furrow planting with biodegradable film mulching over ridges. Taking into consideration of the 95 % credibility intervals, no significant differences in CNDCs and its estimated parameters were observed across years and mulching planting patterns. Therefore, we derived a unified CNDC equation defined as NC = 3.10 W0.40 based on data obtained from the three mulching planting patterns during the four years. Furthermore, no significant differences were observed in critical N nutrition index thresholds. Consequently, the results supported establishing a universal CNDC model to diagnose maize N status in northwest China. The optimal N application rate for maize to obtain great yield and high N use efficiency in the region was 180–200 kg ha1. Further studies are required to evaluate CNDC for maize grown under various N fertilizer types, planting patterns, rainfall years, and regions, which would lead to a more precise diagnosis of maize N status and a more accurate N management regime.