Soil nutrient monitoring plays a vital role in advancing sustainable agriculture by maintaining soil health, optimizing crop productivity, and minimizing environmental impacts. This study addresses gaps in unified definitions and standard methodologies by systematically analyzing 93 articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The results highlight five major monitoring approaches: traditional methods, Remote Sensing (RS), Internet of Things (IoT) and smart systems, in situ sensors, and Artificial Intelligence (AI)-based models, each contributing uniquely to nutrient assessment. A noticeable trend toward integrating machine learning and deep learning with sensor technologies underscores the advancement toward real-time, data-driven precision agriculture. The study also explores spatial and temporal publication trends, criteria for site selection, and the validation techniques used to assess monitoring accuracy. A synthesized definition of soil nutrient monitoring is proposed to support future research and standardization. This review highlights the crucial role of soil nutrient monitoring technologies in sustainable agriculture, crop optimization, and environmental management. It provides a comprehensive overview of the techniques employed in monitoring soil nutrients for precision soil management.
Sobhy et al. (2025) studied this question.