Can PocketNNI, a new smart app for Nitrogen Nutrition Index estimation, reduce the environmental impact of rice?

Abstract

Precision agriculture is increasingly considered as a powerful solution to mitigate the environmental impact of farming systems. This because of its ability to use multi-source information in decision support systems to increase the efficiency of farm management. Among the agronomic practices for which precision agriculture concepts were applied in research and operational contexts, variable rate (VR) nitrogen (N) fertilization plays a key role. A promising approach to make quantitative spatially distributed diagnoses to support VR N fertilization is based on the combined use of remote sensing information and few smart scouting-driven ground estimates to derive maps of nitrogen nutrition index (NNI). In this study, a new smart app for field NNI estimates (PocketNNI) was developed, which can be integrated with remote sensing data and the environmental benefits related to its application were evaluated with Life Cycle Assessment approach. In particular, the environmental performances of rice fertilized according to VR information derived from the integration of Pocket NNI and satellite data was compared with a treatment based on uniform N application. Results showed that VR fertilization allowed reducing the environmental impact by 11.0% to 13.6% as compared to uniform N application. The highest environmental benefits were achieved in terms of energy consumption for fertilizer production and of emission of N compounds. These preliminary results are promising and provide a first quantitative indication of the environmental benefits that can be achieved when digital technologies are used to support N fertilization.