Research progress and development trends of agricultural machinery soil-engaging components based on bibliometrics

Soil-engaging components of agricultural machinery can exert a direct influence on the operational efficiency, energy consumption dynamics, and pedological health. In this present study, a bibliometrics analysis was conducted on both English and Chinese literature and invention patent data of the agricultural machinery soil-engaging components in the period from 2000 to 2024. Multidisciplinary databases were also employed for the global coverage, including the Web of Science Core Collection, China National Knowledge Infrastructure (CNKI), Espacenet (European Patent Office), and the China National Intellectual Property Administration (CNIPA). Advanced scientometric visualization tools—CiteSpace and VOSviewer—the research performed was utilized to realize the multidimensional analysis, including the publication volume chronologies, geographical distributions of the contributing nations, structural mappings of the institutional and author collaborative networks, the highly cited seminal works, and keyword co-occurrence/clustering diagnostics. Thereby, the current research landscape evolved on the thematic concentrations and prospective trajectories. Empirical findings demonstrated that the global academic output exhibited an upward trajectory from 2000, and then a plateau phase from post-2017, indicating a fundamental research. Subsequently, the People’s Republic of China emerged as the predominant research in both quantitative output volume and aggregate academic influence in the field. High-impact research entities—institutions and authors—were observed in the themes: the functional optimization on the components with the adaptability to diverse regional soil tillage (e.g., geometric profiling for the draft force mitigation and residue disposal), advanced material strengthening techniques (including wear-resistant surface engineering and composite material integration), tillage regime compatibility (design paradigms tailored for conservation, conventional, or reduced-tillage systems), and intelligent perception integration (sensor-enabled components in real-time load diagnostics and operational monitoring). Collectively, there was an interconnected framework driving the technological progression. Contemporary research hotspots were focused mainly on the conservation tillage (components optimization for the minimal soil disturbance and the maximum residue retention), energy-efficient and anti-adhesive design (innovative component to reduce the energy consumption and soil adhesion), high-fidelity discrete element method (DEM) modeling of the soil-tool interaction mechanics, and smart technology applications (entailing IoT integration, embedded sensing architectures, and adaptive control systems). Some technological challenges were still remained, including the insufficient material performance and inadequate multi-objective optimization (reflecting unresolved tensions between wear resistance, fracture toughness, mass reduction, and cost efficiency), underdeveloped modular system dynamic coupling (evidenced by limited integration and interaction analysis between modular components under operational stresses), and deficient environmental robustness of intelligent sensing (as the vulnerability to extreme field conditions, including moisture ingress, particulate contamination, mechanical vibration, and impact loads). Consequently, the future breakthroughs were concentrated on the novel material innovation (smart materials, nano-composites, and functionally graded structures), systemic intelligent upgrading (AI-driven predictive maintenance and autonomous adjustment algorithms), eco-sustainable development pathways (low-carbon manufacturing, recyclability, and soil health preservation), and multifunctional modular architectures (interchangeable, scalable components for the versatile field operations); These priorities were addressed to promote the soil-engaging components toward the high operational efficiency, quality metrics, and intelligence levels with the low energy intensity. A technological evolution can also provide a strong reference for the sustainable intensification and high-quality production in precision agriculture.