Evolution and Application of Precision Fertilizer: A Review
Abstract
1. Introduction
2. Materials and Methods
2.1. Research Subject
2.1.1. Structural Innovation and Parameter Optimization of Fertilization Devices
2.1.2. Intelligent Control Algorithms and System Optimization
2.1.3. Numerical Simulation and Simulation Methods
2.1.4. Auxiliary Technologies and Multi-Scenario Adaptation
2.2. Review Methodology
- What are the recent optimizations in fertilization mechanisms?
- What intelligent control algorithms have been integrated into recent fertilizer applicators?
- What are the recent new types of fertilizers and specialized fertilization mechanisms?
- What impact have intelligent fertilizer applicators had on agricultural production?
- What limitations and challenges exist in achieving precision fertilization?
3. Results
3.1. Research Progress of Precision Fertilization Control System at Home and Abroad
3.1.1. Innovative Design of Precision Fertilization Actuators in China
3.1.2. Innovative Design of Precision Fertilization Actuators Abroad
3.2. Domestic and Foreign Intelligent Control System Architecture and Algorithm Optimization Research Progress
3.2.1. Research Progress of Domestic Intelligent Control System Architecture and Algorithm Optimization
3.2.2. Research Progress of Foreign Intelligent Control System Architecture and Algorithm Optimization
3.3. Progress in Research on Key Technologies and System Integration for Variable Fertilization at Home and Abroad
3.3.1. Research Progress on Key Technology and System Integration of Variable Fertilizer Application in Domestic Regions
3.3.2. Research Progress of Key Technology and System Integration of Variable Fertilizer Application in Overseas Countries
3.4. Research Progress on R&D of New Fertilizers and Specialized Fertilizer Application Systems at Home and Abroad
3.4.1. R&D Progress of New Fertilizers and Special Fertilizer Application Systems in China
3.4.2. Research and Development Progress of New Fertilizers and Special Fertilizer Application Systems Abroad
3.5. Key Technology Analysis of Precision Fertilizer Control System
3.5.1. Advances in Sensor and Detection Technology
3.5.2. Control Algorithms and Decision-Modeling Innovations
3.5.3. Actuator and System Integration Technologies
4. Discussion
4.1. Technological Divergence and Convergence in Precision Fertilization
4.2. Practical Implications for Agricultural Systems
- Increased precision and resource efficiency: Systems like the fuzzy PID-based liquid fertilizer control (Zhou et al., [62]) and bat-optimized BP-PID algorithms (Zhu Fenglei et al., [39]) reduce fertilizer application errors to <10% and <5%, respectively, minimizing nutrient runoff and lowering input costs. For example, Pan et al.’s [34] PSO-RBF-PID system achieves a maximum flow error of 2.50%, translating to significant savings for large-scale farms.
- Adaptation to diverse cropping systems: Domestic innovations in organic fertilizer application (Li Zongpeng et al., [53]) and orchard-specific devices (Zongze and Liu Gang, [54]) address the needs of high-value, labor-intensive crops, while foreign drone-based automated fertilization (Bojja et al., [67]) and variable-rate technologies (VRT) cater to large-field monocultures. This diversity highlights the importance of context-specific technology transfer.
- Enabling data-driven agriculture: Prescription map-based systems (Wang Jinfeng et al., [33]) and soil test crop response (STCR) models (Spoorthishankar et al., [81]) facilitate evidence-based decision-making, reducing over-fertilization and improving crop quality. For instance, STCR-derived fertilizer prescriptions achieve balanced nutrient uptake in mung beans, enhancing yields without excess inputs.
4.3. Key Challenges and Research Gaps
- Sensor limitations: While multispectral and hyperspectral sensors effectively detect nitrogen, phosphorus-sensing technology lags (Silva et al., [4]), hindering comprehensive nutrient management. Additionally, non-visual perception systems (e.g., haptic navigation, [23]) are costly and require further miniaturization for widespread adoption.
- Complexity in system integration: Domestic unmanned variable fertilization systems (Gao et al., [40]) and foreign multi-sensor fusion platforms face challenges in synchronizing data from diverse sources (e.g., soil, crop, weather), leading to delays or inaccuracies in real-time decision-making.
- Scalability for smallholder farms: Many advanced technologies (e.g., nanotechnology-enabled fertilizers [3] and drone-based systems [67]) are prohibitively expensive for small-scale farmers, particularly in developing regions. Domestic efforts to prioritize “easy-to-land” technologies offer a model, but broader affordability remains a barrier.
- Long-term environmental impacts: While controlled-release fertilizers and dynamic fertilization methods reduce immediate runoff, their long-term effects on soil microbial communities and groundwater quality are understudied. For example, the ecological risks of nano-fertilizers (Munir et al., [3]) require further assessment.
5. Conclusions
- Investment in next-gen sensors: Developing low-cost, multi-nutrient sensors (especially for phosphorus) and miniaturized non-visual perception tools.
- Simplified system integration: Standardizing communication protocols (e.g., CAN bus) to enable seamless data flow between sensors, controllers, and actuators.
- Inclusive innovation: Designing affordable technologies for smallholders, such as simplified prescription map tools and low-cost adaptive algorithms.
- Long-term ecological studies: Evaluating the impacts of novel fertilizers (e.g., nanomaterials) and precision systems on soil health and biodiversity.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Point | Technical Means | Advantage | Drawbacks | Technological Advances Reflect |
---|---|---|---|---|
Prescription agriculture in the 1990s | Spatial interpolation using GIS to plan field fertilization programs based on historical soil data and crop needs. | The first field-scale differential fertilization, breaking the traditional uniform fertilization mode, reducing fertilizer waste and improving fertilization efficiency. | Relies on historical data and static interpolation, no real-time monitoring capability, unable to respond to field changes, accuracy limited to field scale. | Introducing geographic information technology to promote the initial transformation of agricultural fertilization from “experience-driven” to “data-driven” and to establish a basic framework for spatially differentiated fertilization. |
Post-2010 real-time monitoring system | Soil and crop sensors are used to pick up data, and the Internet of Things is used to do plot fertilization and control. | With real-time monitoring capability, it can adjust the fertilization strategy according to the dynamic data of soil nutrients, crop growth, etc., with the precision of mu level and faster response. | Sensors are costly to deploy, small in coverage, and hardware limits data transmission and processing, making it difficult to seamlessly monitor the entire field. | From static planning to dynamic real-time regulation, real-time data collection and analysis through the sensor network, fertilization accuracy and timeliness are significantly improved. |
Artificial intelligence and robotics in recent years | Fusion of AI algorithms and robotics (agricultural drones) for precise identification of single plants for fertilizer application. | It realizes precise fertilization of single plants, intelligent distribution of fertilizers according to crop status and pest and disease risk and improves resource utilization and automation. | The technology is complex, requires a lot of data and arithmetic, robots, AI chips are costly, and promotion is limited by technology and cost. | Through the deep integration of AI and robotics, we can realize the leap from “group average” to “individual precision” in fertilizer control and promote the transformation of agricultural production paradigm to full data-driven intelligence. |
Fertilizer Application Unit Type | Fertilizer Application Unit Type | Advantage | Drawbacks | Technological Advances Reflect |
---|---|---|---|---|
Multi-stage arc trajectory fertilizer applicator. | Segmented PID control of electro-hydraulic system for millimeter tracking of groove opener trajectory. | Significantly higher fertilizer-root contact coefficients and lower rates of root damage. | Complex electro-hydraulic system and PID control technology, high device cost. | Breaking through traditional fertilizer trajectory limitations to improve fertilizer effectiveness and crop protection. |
Pneumatic variable diameter precision fertilizer discharge system. | “Fertilizer discharge opening + speed control + pneumatic conveying” combination structure. | Fertilizer discharge with high precision, adapted to complex terrain and dynamic operations. | Pneumatic conveying structure requires high maintenance and relies heavily on the stability of the gas source. | Innovative composite structure design, solving the problem of fertilizer discharge accuracy and response speed. |
Rotary centrifugal pellet fertilizer applicator. | Optimization of fertilization chamber structure by discrete element simulation. | Low coefficient of variation of burrow length and low error of fertilizer application to a single burrow under specific working conditions. | Limited adaptability to working conditions, need to be re-optimized for different conditions. | Precise optimization of the structure using simulation technology for high-precision control of granular fertilization. |
Notched-blade spiral fertilizer discharger with three-headed tapering spiral fertilizer discharger. | Improvement of the structure of the fertilizer discharger and optimization of the discharge paths. | Improved uniformity of fertilizer discharge and low average deviation of flow rate. | Spiral structure prone to clogging. | Structural innovation to effectively improve the uniformity and stability of fertilizer discharge. |
Emphasis | Precision Fertilization Implementing Agency | Advantage | Technological Progressiveness |
---|---|---|---|
Through structural optimization and algorithmic innovation, it solves the problem of uniformity and reliability of fertilizer application devices, which is applicable to scenarios such as corn, tea plantations, and orchards, and the technology is easy to land. | Bi-variable fertilizer application system with independent control of the fertilizer discharge unit. | Independent adjustment of each row of fertilizer rows, adapting to complex boundary conditions. | Achieving precise control of variable application of corn-based fertilizers. |
Two-stage spiral fertilizer discharger. | Achieving smooth application of organic fertilizers. | Addressing uneven application of organic fertilizers. | |
Sliced fertilizer discharger structure. | Fertilizer rationing on a plant-by-plant basis. | Improvement of positioning accuracy of seedling corn fertilization. |
Emphasis | Precision Fertilization Implementing Agency | Advantage | Technological Progressiveness |
---|---|---|---|
The integration of intelligent perception (discrete element simulation, haptic navigation) and interdisciplinary technologies (machine vision, autonomous navigation) to improve the accuracy of fertilizer application is innovative, but navigation and other scenarios are limited in their application in real environments. | Rotary centrifugal granular fertilizer hole discharge device | Good adaptability and good fertilizer agglomeration characteristics | Optimization of key parameters of the hole application device |
Spiral fertilizer discharger with notched blades | Reduced coefficient of fluctuation of fertilizer discharge uniformity and improved uniformity | Optimization of the structure of the spiral fertilizer discharger | |
Tactile sensing system | Toward autonomous navigation in cornfields without visual dependence | A new navigation solution for precision fertilization of dense crops |
Emphasis | Intelligent Control System Architecture and Algorithm Optimization | Advantage | Technological Progressiveness |
---|---|---|---|
Domestic research has shown a remarkable shift from traditional control to intelligent optimization, and a variety of advanced algorithms have been introduced into the field of fertilization control. | Particle swarm optimization (PSO)-based RBF-PID algorithm. | Minimized tracking error in regulation time, superior to traditional PID and RBF-PID control algorithms. | Improved dynamic control accuracy. |
Bat Algorithm for optimizing initial weights of BP neural networks/BP-PID algorithm. | Effectively reduces the effects of system time lag and nonlinearity. | Enhanced nonlinear adaptation. | |
An elastic collision model constructed based on Hertz theory and analyzed by DEM-CFD gas–solid coupling. | Dome dispensers outperform other configurations. | Provides a theoretical basis for structural improvement of the dispensing device. | |
Intermittent fertilization control system based on fruit tree canopy detection and construction of intermittent ultrasonic sensors to fertilization control system. | The coefficient of variation of fertilizer uniformity is less than 7% for intermittent application units. | Addressing the lack of banded intermittent fertilization devices in standardized orchards. | |
Hybrid optimization of fractional order proportional-integral-derivative (PID) algorithms. | Narrowest range of steady-state conductivity with lowest regulation time and overshoot. | A feasible method is provided for the control of nonlinear time-lag systems. | |
Liquid fertilizer targeted variable fertilizer application control system based on fuzzy PID algorithm. | Reduced system response time and error control within 10 percent. | Provides a viable solution for combining precision variable fertilization with targeted fertilization. |
Emphasis | Intelligent Control System Architecture and Algorithm Optimization | Advantage | Technological Progressiveness |
---|---|---|---|
In terms of intelligent control system architecture and algorithm optimization, foreign research focuses more on multi-sensor fusion and complex system modeling, resulting in a variety of innovative control strategies. | EDEM-CFD coupling method | Quickly optimize the structure of the fertilizer applicator. | Simulating operating conditions with EDEM-CFD coupling for fertilizer applicator design. |
Flower Fertilization Optimization Algorithm (FFO) | Outperforms 14 state-of-the-art meta-heuristics on 32 benchmark optimization problems. | Parameter-optimized PID controller successfully applied to Maglev train positioning. | |
Venturi fertilizer applicator structure optimization | Determine the optimal parameter range to maximize suction flow. | Provide a quantitative basis for fertilization agencies |
Emphasize | Key Technology and System Integration of Variable Fertilization | Vantage | Technological Progressiveness |
---|---|---|---|
Domestic scholars have carried out a large number of systematic studies mainly in the field of realizing the dynamic matching between the amount of fertilizer applied and the needs of crops and soil conditions, which is the key to precise fertilization | Prescription map generation and intelligent decision modeling | High reliability of electronic prescription maps to guide fertilizer application | Enabling dynamic and intelligent decision-making on fertilizer application rates |
Genetic algorithm optimized fuzzy PID control | Significant improvement in response time over traditional PID and fuzzy PID control | Enhanced system immunity and dynamic response | |
Fertilizer shaft speed self-calibration and adaptive control | Significant performance improvement over the original linear model | Improvement of fertilizer application stability under different working conditions | |
Variable formulation fertilizer control system based on prescription maps | Meets the requirements for rapid automated formulation and precise variable fertilizer application | Preloaded soil prescription maps based on good utility and economy |
Emphasize | Key Technology and System Integration of Variable Fertilization | Vantage | Technological Progressiveness |
---|---|---|---|
In terms of key technology and system integration of variable fertilization, foreign research pays more attention to the in-depth integration with the precision agriculture platform to realize the whole process intelligence from data collection to decision-making execution. | Using distributed autoregressive lag methods | Data support for regional variable fertilization strategy development | Prospective guidance for fertilization strategies |
Automated drone fertilization using a drone guidance system | Effectively regulate drone movement for precise and efficient fertilizer application | Automation and Intelligence of Fertilizer Application | |
Nanoparticle controlled release mechanisms | Reduced nutrient losses and greenhouse gas emissions, increased yields and economic benefits | Providing new controlled-release materials and technology paths for precise fertilization |
Emphasis | Research and Development of New Fertilizers and Special Fertilizer Application Systems | Advantage | Technological Progressiveness |
---|---|---|---|
Domestic research for organic fertilizers, liquid fertilizers, and other special application equipment; special fertilizer system research and development has become another hotspot for domestic research | Based on fuzzy PID algorithm + conductivity detection feedback method | Fertilizer concentration fluctuation range is stable, improving the uniformity of fertilizer application | Promote intelligent upgrading of water-fertilizer integration system |
Biogas slurry mixed farming machines and their systems | Mixed fertilizer components concentration error is small, proportioning accuracy and stability is high | Filling the technology gap for intelligent application of biogas fertilizer | |
External grooved wheel structure + LIDAR method | Enabling on-target fertilization on demand | Innovative orchard precision fertilization model |
Emphasis | Research and Development of New Fertilizers and Special Fertilizer Application Systems | Advantage | Technological Progressiveness |
---|---|---|---|
The research and development of new fertilizers and special fertilization systems is the frontier of precision fertilization research in foreign countries, mainly in the combination of functional fertilizers and intelligent release systems. | Innovative orchard precision fertilization model | Foliar fertilizers containing humic acid and boron significantly optimize wine quality. | Providing a theoretical basis for foliar fertilization technology |
Monitoring and fertilization decision rules to optimize nitrogen recycling | Reduction in nitrogen fertilizer application | Innovative farm-scale fertilization model | |
Multi-criteria decision-making (MCDM) approach. | Providing scientific selection basis for mechanized fertilization of orchards | Providing new ways to make decisions about fertilizer mechanization | |
Fertilizer prescription equation based on soil test crop response (SCTR) | Balanced nutrient application is achieved for optimal yield and nutrient uptake | New reference for other crop fertilization methods |
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Wang, L.; Gao, J.; Qureshi, W.A. Evolution and Application of Precision Fertilizer: A Review. Agronomy 2025, 15, 1939. https://doi.org/10.3390/agronomy15081939
Wang L, Gao J, Qureshi WA. Evolution and Application of Precision Fertilizer: A Review. Agronomy. 2025; 15(8):1939. https://doi.org/10.3390/agronomy15081939
Chicago/Turabian StyleWang, Luxi, Jianmin Gao, and Waqar Ahmed Qureshi. 2025. "Evolution and Application of Precision Fertilizer: A Review" Agronomy 15, no. 8: 1939. https://doi.org/10.3390/agronomy15081939
APA StyleWang, L., Gao, J., & Qureshi, W. A. (2025). Evolution and Application of Precision Fertilizer: A Review. Agronomy, 15(8), 1939. https://doi.org/10.3390/agronomy15081939