Real-time nitrogen management using decision support-tools increases nitrogen use efficiency of rice

Abstract

Several decision support tools have been proposed for precision nitrogen (N) fertilizer application in rice (Oryza sativa L.) to increase nitrogen use efficiency (NUE) and grain yields. However, a comparison of their effectiveness has not been well documented. A field experiment was conducted in western Terai of Nepal during 2017–2018 to identify the appropriate decision support tool for improving NUE and grain yields. Nine N fertilizer management treatments were laid out in a randomized complete block design with three replications. The treatments included a GreenSeeker (GS) optical sensor, soil plant analysis development (SPAD) meter, leaf color chart (LCC), each of these treatments with basal application of N at 25 kg ha−1, urea briquette deep placement (UDP), and the existing government-recommended practice (RP, 100 kg N ha−1). N fertilizer application guided by decision support tools had a significant (p < 0.05) effect on grain yields. UDP produced the highest grain yield (6.80 Mg ha−1) among the treatments. Grain yields were not significantly different among GS, LCC (in combination with basal 25 kg N ha−1), RP, and UDP treatments. However, GS, UDP, and LCC saved N input by 54%, 22%, and 21%, respectively, compared to RP. In addition, GS produced a significantly higher agronomic N use efficiency (ANUE), partial factor productivity of N (PFPN), apparent N recovery (ANR), and utilization efficiency of N (UEN) compared to RP. These results suggest that application of N fertilizer guided by the GS decision support tool can save significant amount of N fertilizer compared to the current RP without compromising grain yield.