Wenbin Zhang

Agricultural drip fertigation is a highly coupled dynamic process in which precision resource management depends on the coordinated performance of the entire equipment chain. Against the backdrop of global water scarcity and excessive fertilizer application, improving the full-process precision of mixing, injection, sensing, control, distribution, and terminal delivery has become a prerequisite for the wider adoption of fertigation. This review evaluates advanced process-monitoring technologies and closed-loop control architectures within modern cyber-physical fertigation systems, covering fertilizer solution preparation and mixing, injection devices, liquid- and solid-phase state sensing, intelligent control algorithms, and pipeline distribution with terminal emitters. Online mixing has evolved from gravity-based batch pre-mixing toward continuous metered injection with vortex-guided static mixing, electrical conductivity (EC) sensing with drift compensation and granular mass flow detection form the perceptual basis of closed-loop regulation, control has advanced from proportional–integral–derivative (PID) controllers through variable-universe fuzzy logic to artificial neural network (ANN) hybrids with metaheuristic optimization, and pipeline pressure regulation together with emitter anti-clogging strategies determine long-term distribution uniformity. A quantitative analysis shows that the attainable precision of the sensing–decision–execution chain is bounded by the coupling among sensor accuracy, process delays, control performance, and actuator response rather than by any single device. The review identifies five unresolved gaps—sensor reliability, multi-season field validation, interoperability, low-cost automation, and fertilizer-type adaptability—and recommends that future research prioritize low-cost Internet of Things (IoT) sensor arrays on low-power wide-area networks, edge–cloud collaborative control, and foundation-model-driven autonomous decision-making, co-designed as one coupled specification.

Agrivoltaic systems configure photovoltaic power generation and agricultural production within the same land space, providing a new pathway for alleviating the conflict between energy development and farmland conservation; however, array shading and structural constraints also alter crop growth and agricultural equipment operating environments. Following the PRISMA process, this review searched studies published from 2010 to 2026 in the Web of Science Core Collection, Scopus, and China National Knowledge Infrastructure, and ultimately included 206 publications. The review focuses on array-induced environmental reconfiguration, equipment adaptation, light–thermal sensing and prediction, and coordinated agrivoltaic operation. Existing evidence indicates that the environmental effects of agrivoltaic systems are clearly influenced by climate and array configuration; in representative vertical or tracking systems, annual-scale photosynthetically active radiation decreased by approximately 11% to 34%. Mismatch among module height, row spacing, and implement width reduces field-operation efficiency, which fell to approximately 45% under severe mismatch in some experiments; elevated arrays also cause GNSS signal attenuation and increase the difficulty of continuous positioning beneath the panels. Because existing studies differ considerably in site conditions, evaluation indicators, and validation periods, the above results mainly reflect representative performance ranges. Matching criteria between photovoltaic arrays and agricultural machinery have not yet been established, long-term field-measured data in complex field environments are insufficient, model adaptability across regions is limited, and coordinated scheduling of agricultural production and photovoltaic operation and maintenance remains inadequate. Overall, coordinated design of arrays and agricultural machinery, multi-sensor fusion navigation, environmental prediction corrected for array structure, and hierarchical scheduling under safety constraints are the main development directions for intelligent coordinated operation of agrivoltaic systems.

Long-term intensive agriculture has contributed to soil compaction, carbon depletion, nutrient imbalances, and disruption of microbial ecological processes, collectively constraining multiple soil functions relevant to agricultural sustainability. Crop straw return is widely considered a potential strategy for alleviating these constraints. However, existing studies and reviews have often evaluated direct straw return, straw-derived biochar, and straw-based compost separately or through individual soil indicators, limiting understanding of how biomass transformation, amendment properties, and site conditions jointly shape soil responses. To address this gap, this review comparatively synthesizes the reported mechanisms, outcomes, limitations, and potential application contexts of these three strategies within a soil multifunctionality framework. The reviewed literature is characterized by substantial heterogeneity in soil type, climate, feedstock, amendment preparation, application rate, experimental duration, and management conditions; therefore, the direction, magnitude, and persistence of reported effects require context-specific interpretation. Direct straw return was often associated with changes in soil structure, labile-carbon availability, water retention, and microbial activity, although these responses varied with straw type, incorporation depth, moisture conditions, decomposition rate, and nitrogen availability. Biochar was frequently linked to carbon stabilization, sorption, nutrient retention, and pH buffering, but the magnitude of these effects varied with feedstock properties, pyrolysis conditions, application rate, soil characteristics, and climatic context. Compost was commonly associated with increases in nutrient availability and microbial activity, whereas its performance varied with maturity, raw-material composition, salinity and pathogen risks, and field management. These comparisons suggest that the three strategies should not be assumed to be functionally equivalent, although their effects may overlap and potential combinations may be beneficial under some conditions. Based on patterns identified across the reviewed literature, we synthesize an interpretive framework linking dominant soil constraints with amendment properties and targeted soil functions. This literature-derived framework is intended to organize context-dependent evidence and support adaptive straw-return management rather than provide a universal prescription. Future research should prioritize standardized soil multifunctionality indicators, long-term multi-site comparisons, and integrated assessments of agronomic benefits, carbon persistence, nutrient losses, greenhouse gas emissions, and economic feasibility.

Crop rotation is a key practice for improving soil health, reducing chemical inputs, and ensuring sustainable agricultural productivity. This review synthesizes research from major agricultural regions worldwide, including North America, Europe, South America, South Asia, and Africa, with additional case studies from China to illustrate regional applications. This study presents a streamlined framework that integrates climate adaptability, crop combinations, yield-enhancing mechanisms, technological support, and regional optimization. By analyzing plant–soil–microbe interactions—including improvements in soil physical structure, nutrient cycling, microbial processes, and suppression of pests and diseases—we elucidate how rotation systems enhance the yield of subsequent crops. Precision agriculture technologies, such as variable-rate fertilization and remote sensing, have been shown to improve resource use efficiency and reduce labor input in certain cropping systems. Diversified crop rotations can substantially offset direct greenhouse gas emissions through enhanced soil carbon sequestration. The design of region-specific recommended rotation patterns should follow the principles of resource matching, stable yield and efficiency enhancement, and sustainability. This framework provides a practical reference for designing region-specific rotation systems and advancing sustainable agricultural development.

Due to topographic and climatic constraints, a large proportion of grain is cultivated in relatively flat areas, where it is highly susceptible to lodging caused by natural disasters or improper field management. However, research on the full-process intelligent harvesting of lodged grain remains limited. This paper aims to examine the current state of the grain industry and its level of mechanization, with a focus on the challenges in mechanized harvesting of lodged grain, including the lack of suitable equipment, high harvest losses, and low operational efficiency. The article provides a comprehensive review of the key technologies critical to achieving fully automated intelligent harvesting, including the acquisition of lodging information, combine harvester operations, and the development of intelligent modular systems. It also summarizes recent advancements in cutting-edge mechanized grain harvesting equipment. Additionally, the article presents recommendations for the future development and research of mechanized grain harvesting technologies, focusing on grain lodging feature recognition, equipment modularization, and the integration of intelligent technologies. The aim is to offer valuable insights for advancing progress in this field.