Plowing operations can improve the quality of the shallow soil layer, but plowing tractors still cause compaction effects on the deeper soil layers. The temporal and spatial accumulation of compaction effects can hinder crop growth, thereby reducing the overall efficiency of plowing operations and creating obstacles to soil ecological health. It is urgent to address the bottlenecks in mechanized ecological operations. This paper addresses the unclear mechanical effects of heavy-duty tractor tillage equipment on soil compaction in the tillage layer. By integrating and constructing a ‘‘heavy-duty tractor-tillage layer soil’’ system dynamics coupling model, it identifies the primary influencing factors of joint tillage operations on soil compaction in the tillage layer and explores the response patterns of tillage equipment parameters to the soil compaction process. The research results indicate that as the number of compaction operations increases, soil compaction increases, and soil stress transmission shows a gradually decreasing trend; when the tillage unit’s operating speed is 3 km/h, the soil stress at a depth of 10 cm can reach a maximum of 499.2 kPa; when the operating speed is 6 km/h, the soil stress at a depth of 10 cm reaches a maximum of 469.1 kPa; when the operating speed is 9 km/h, the soil stress at a depth of 10 cm reaches a maximum of 438.8 kPa; when the acceleration and longitudinal acceleration increase, soil stress correspondingly increases; when the direction of lateral acceleration changes, the center of gravity of the tractor shifts, and the trends in soil stress on the inner and outer sides of the tires are opposite. The research findings can provide theoretical references for improving the operational efficiency of the unit and the development of black soil protection and utilization technologies.

Bacterial diversity in the plough layer, widely regarded as the "second life" of agroecosystems, can sustain the maize yield for long-term soil fertility. Alternatively, the large-scale mechanized flat-planting has been widely adopted for maize cultivation in northern China. Moderate to severe soil compaction has occurred, particularly in the tractor chassis coverage zones. This compaction can alter the soil’s physical structure and chemical properties, potentially triggering cascading negative effects on the microbial communities. Notably, it is still lacking in the response mechanisms of the plough layer bacterial diversity to mechanical compaction. In this study, a two-year field experiment was conducted for sustainable soil management in the plot head areas. An emphasis was also placed on the tractor-induced compaction gradients (0, 3, and 7 passes) and soil depths. Metagenomic sequencing was employed to systematically evaluate the bacterial diversity, abundance, and activity under these conditions. The ecological consequences of the compaction were used to identify the critical thresholds for microbial resilience. The experimental design integrated the soil sampling over multiple depths within the plough layer (0–10 cm), particularly for both compacted zones and adjacent undisturbed controls. Soil physicochemical parameters, including the moisture content, bulk density, were measured to quantify the compaction-induced variations. Bacterial community profiles were analyzed using 16S rRNA gene sequencing. The dominant phyla were selected, such as Acidobacteria, Proteobacteria, and Actinobacteria, which were known for their functional roles in nutrient cycling and soil health. Magnitude variance analysis and time series modeling were applied to assess the fluctuations in the bacterial abundance and community dynamics. While the stress response indices were calculated to evaluate the microbial recovery potential post-compaction. Results demonstrated that the mechanical compaction significantly modified the soil physicochemical properties. For instance, seven-pass compaction increased the bulk density by 12%–16%. There were the outstanding shifts in community composition, due to the less hospitable environment of the aerobic bacteria. Specifically, Acidobacteria—a phylum associated with oligotrophic conditions—exhibited a 7% reduction in the relative abundance under high compaction. Actinobacteria shared the moderate sensitivity suitable for the physicochemical stressors, which was recognized for their resilience in the nutrient-poor environments to degrade complex organic compounds. Time series data further highlighted that there was a delayed recovery of bacterial diversity in heavily compacted soils. The resilience was altered in the soil structure, such as the reduced macropore connectivity and oxygen diffusion, which disrupted microbial habitat heterogeneity. Stress response models indicated that the compaction-induced physicochemical properties were exerted on the selective pressures, thus favoring stress-tolerant taxa while suppressing functionally sensitive groups. The stress-adapted taxa after compaction temporarily stabilized the ecosystem functions, but the long-term soil health was compromised to reduce the functional redundancy. The precision soil practices mitigated these risks, such as the intermittent deep tillage or controlled traffic farming. As such, the compaction was alleviated to preserve the microbial diversity. These findings can provide significant implications for sustainable agriculture. In conclusion, there was a significant interaction among mechanical compaction, soil microbiology, and agroecosystem resilience. Soil physics and microbial ecology can also be bridged to optimize mechanized farming. The indispensable microbial communities can also be sustained for food security.

Developments in agricultural mechanization have witnessed a gradual transition from manned equipment to unmanned equipment. Meanwhile, the psychological load of the tractor drivers’ original field operations has been transferred to unmanned tractor monitors. This study constructed a psychological load paradigm model and identified the physical meaning of parameters based on the leaky bucket principle and the basic hypothesis of ergonomics. The mapping architecture of the psychological load measurement principle was analyzed, and the feasibility of the questionnaire measurement method was demonstrated. Further, an evaluation questionnaire index system was designed. A continuous method was selected to conduct a man-machine semi-physical test to obtain an evolution paradigm model of six types of psychological loads using a multivariate nonlinear regression method. The structural parameters of the paradigm were analyzed, and the degree of coupling of psychological load generation and mitigation was deconstructed item by item. The driving mechanism and evolution law of psychological load were analyzed. Consequently, a real vehicle was designed and constructed and a topology test was conducted to verify the scientific applicability and universality of the paradigm model, respectively. The results confirmed that a continuous psychological questionnaire could effectively measure a driver’s psychological load. The interaction of various psychological loads constituted the distributed state- space of psychological load, and the dynamic paradigm model drove the psychological load of the human-computer interaction interface. The paradigm model evolution was a negative exponential growth model that included comfort and fatigue accumulation rates. With the accumulation of working time, the specific rules and parameters of the psychological load changed for different drivers, but the evolution paradigm was the same. According to the state-space analysis of the mental load model, the mental model exhibited controllability, observability, stability, and so on, which accurately revealed the evolution law of mental load. The research results provide a positive design for human-computer interaction.