Molecular Soil Biology 2025, Vol.16, No.4, 162-174 http://bioscipublisher.com/index.php/msb 169 Figure 5 Schematic overview of measured parameters by different methods and devices (Adopted from Liang et al., 2021) Image caption: NDRE, Normalized Difference Red Edge Index; NDREUAV, NDRE calculated with the canopy reflectance obtained by UAV; NDREASD, NDRE calculated with the close-range canopy reflectance obtained by ASD; SPAD, SPAD value measured by SPAD-502 chlorophyll meter; N%N-Pen, nitrogen content measured by N-pen meter; N%EQA, nitrogen content measured by elementary quantitative analysis (EQA) (Adopted from Liang et al., 2021) Soil sensors also play a critical role in precision agriculture by providing real-time data on soil nitrogen levels. This information allows for site-specific nitrogen management, which can optimize nitrogen application rates and timings to match crop needs more precisely. Studies have demonstrated that integrating UAV data with soil nitrogen content can improve the spatial and temporal variability understanding of nitrogen status in crops, leading to more efficient nitrogen use and reduced environmental impact (Argento et al., 2020). 6.2 Nutrient mapping and decision support systems Nutrient mapping and decision support systems are essential components of precision nitrogen management. Variable rate technology (VRT) and GIS-based models enable the precise application of nitrogen fertilizers based on the spatial variability of soil and crop nitrogen status. These technologies help in creating detailed nutrient maps that guide the application of nitrogen at variable rates, ensuring that each part of the field receives the optimal amount of fertilizer (Argento et al., 2020; Blaise, 2021). Decision support systems (DSS) integrate various data sources, including remote sensing, soil sensors, and weather data, to provide real-time recommendations for nitrogen management. These systems can predict the nitrogen requirements of crops at different growth stages and under varying environmental conditions, thereby improving NUE. For instance, studies have shown that using DSS in conjunction with UAV-based remote sensing can lead to significant reductions in nitrogen fertilizer use while maintaining or even increasing crop yields (Argento et al., 2020; Zha et al., 2020). 6.3 Smart fertilization technologies Smart fertilization technologies, such as slow-release and controlled-release nitrogen products, are designed to improve NUE by synchronizing nitrogen release with crop demand. These fertilizers release nitrogen gradually over time, reducing losses due to volatilization, leaching, and denitrification. The use of nitrification inhibitors and urease inhibitors further enhances the efficiency of nitrogen fertilizers by slowing down the conversion processes that lead to nitrogen losses (Alam et al., 2023; Vijayakumar et al., 2023). The development of nanofertilizers represents another innovative approach to smart fertilization. Nanofertilizers have a higher surface area and can be engineered to release nutrients in a controlled manner, improving the uptake efficiency by plants. Integrating these advanced fertilization technologies with precision agriculture tools and
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