Sensor-Based Real-Time Soil Macronutrient Monitoring and Variable-Rate Fertilizer Application Machinery
- Authors
-
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Muhammad N. IBRAHIM
Author
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Abubakar S. MOHAMMED
Author
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Iyanda M. ANIMASHAUN
Author
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Shehu ABDULKADIR
Author
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- Keywords:
- Soil Macronutient Sensing; NPK sensors; Variable-rate Technology; Precision Agriculture; Autonomous Machinery.
- Abstract
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Sustainable agriculture and increase in the yield of crop production are associated with efficient soil nutrient management. While conventional methods of testing soil in laboratories remain tedious, costly, time-consuming and poorly suited for site-specific decisions, the use of sensors and variable-rate technology (VRT) for site-specific need and effective resource use remains an alternative solution. This systematic review aims to synthesize recent research in real-time soil macronutrient sensing technologies and their integration with VRT systems, evaluate the agronomic, economic, and environmental impact and identify the gaps and future research priorities. Following systematic literature review framework, we analysed studies from Web of Science, Elicit, Consensus, IEEE, ScienceDirect, Scopus, SpringerLink and Peer-reviewed articles from Google Scholar published between 2015 and 2025 on electrochemical, optical and IoT-enabled sensing technologies. Findings reveal that sensor-based VRT achieves nitrogen savings between 19 – 45%, reduction in application errors below 5%, and high yield production maintained. Machine learning models such as Random Forest, XGBoost, and Support vector machines (SVMs) show strong predictive (R2 ≈ 0.812-0.99), though validation remains predominantly on generic datasets. Widespread adoption of sensor technology, particularly among smallholder farmers, remains constrained by high initial and maintenance costs, calibration demands, and cross-sensitivity issues. Crucially, performance varies substantially by sensor type, and field-scale validation remains limited under real-world agricultural conditions. Future research should focus more on the multi-sensor fusion, edge artificial intelligence, digital twin technologies, autonomous agricultural robots, and a closed-loop nutrient management systems to enhance the durability, reliability and scalability of precision fertilization technologies.
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- Published
- 29-09-2026
- Section
- Articles
- License
-
Copyright (c) 2026 Muhammad N. IBRAHIM, Abubakar S. MOHAMMED, Iyanda M. ANIMASHAUN, Shehu ABDULKADIR (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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