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.
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