The transition toward inverter-dominated power systems challenges conventional reliability theory, which was developed largely for synchronous-generator-dominated systems and cannot fully capture the coupled effects of fast inverter controls, multi-timescale dynamics, operating uncertainty, and component degradation. This review examines how reliability emerges across control, dynamic, thermal, and aging processes and how these processes can be integrated into a consistent analytical framework. Existing knowledge is synthesized across four dimensions: inverter control behavior, reliability mechanisms, assessment methodologies, and enhancement strategies, with particular emphasis on their physical basis and characteristic timescales. The synthesis shows that grid-following and grid-forming inverters create distinct reliability pathways through interactions among electromagnetic, electromechanical, thermal, protection, and degradation processes, while divergent findings often arise from differences in operating conditions, model fidelity, and timescale representation. Current assessment approaches span probabilistic analysis, dynamic simulation, multi-timescale modeling, multiphysics and physics-of-failure methods, and data-driven artificial intelligence, each involving trade-offs among physical fidelity, computational efficiency, and online applicability. Reliability enhancement is also evolving from isolated converter-level measures toward coordinated control, system-level support, condition-aware operation, and reliability-oriented hardware design, yet these approaches remain weakly integrated with lifecycle assessment and operational decision-making. Key gaps include the absence of a unified reliability theory, incomplete cross-timescale and multiphysics coupling, limited integration of control dynamics with component degradation, and weak links between reliability assessment and real-time operation. Future research should prioritize lifecycle-aware modeling, digital-twin-enabled online assessment, physics-informed data fusion, and adaptive reliability-aware control. By reframing reliability as a cross-timescale process linking mechanisms, assessment, and intervention, this review clarifies the theoretical and methodological basis for reliability-oriented operation and design of inverter-dominated power systems.

抄録全体を表示

Distributed energy management systems are increasingly challenged by the need to achieve low-latency decision-making, efficient coordination of heterogeneous energy resources, and secure distributed intelligence under high renewable energy penetration. This review systematically examines the synergistic integration of edge computing and machine learning as a unified technological paradigm for next-generation distributed energy management, to elucidate its underlying collaborative mechanisms, technological evolution, and future development pathways. A comprehensive analytical framework is established from three complementary dimensions—system architecture, intelligent algorithms, and collaborative operation—and recent advances are synthesized across four key research domains: edge–cloud collaborative architectures, edge-oriented machine learning prediction, edge intelligence-enabled distributed scheduling, and federated learning for privacy-preserving optimization. The analysis demonstrates that edge computing substantially enhances real-time system responsiveness by migrating computation and decision-making from centralized cloud platforms to distributed edge nodes, while machine learning significantly improves renewable generation forecasting, load prediction, and adaptive scheduling capabilities. Their deep integration enables latency-aware optimization, efficient utilization of distributed energy resources, and privacy-preserving collaborative intelligence, thereby establishing a scalable foundation for intelligent energy management in resource-constrained environments. The review further identifies four critical research bottlenecks, including heterogeneous edge resource coordination, cross-scale optimization of integrated multi-energy systems, lightweight and interpretable intelligence, and trustworthy cyber-secure operation. By integrating architectural evolution, algorithmic intelligence, and system-level collaboration into a unified analytical framework, this review clarifies the paradigm shift from cloud-centric management to edge-intelligent distributed coordination and establishes a systematic roadmap for the design, optimization, and deployment of next-generation distributed energy management systems.

抄録全体を表示

The large-scale integration of renewable energy is fundamentally challenging the operational paradigm of modern power systems by intensifying intermittency, reducing system inertia, and increasing spatiotemporal uncertainties across generation, grid, and demand sectors. Developing coordinated regulation and dynamic balancing mechanisms for heterogeneous resources across multiple temporal and spatial scales has therefore become a fundamental challenge for next-generation power systems. This review systematically reconstructs the research landscape of source–grid–load coordinated regulation through a unified framework integrating theoretical foundations, collaborative architectures, enabling technologies, optimization methodologies, dynamic balancing mechanisms, and future directions. From the complementary perspectives of source-side flexibility, grid-side active support, and demand-side interactive response, representative technologies—including renewable power forecasting and grid-forming control, coordinated energy storage, flexible transmission and distribution, wide-area monitoring and digital twins, demand response, aggregated electric vehicle control, and behind-the-meter storage—are classified and comparatively evaluated in terms of regulation capability, response characteristics, economic performance, engineering maturity, and application scenarios. Coordinated optimization strategies encompassing multi-timescale scheduling, multi-agent game-theoretic optimization, artificial intelligence-assisted decision-making, data-driven optimal control, and robust coordinated control are further synthesized to elucidate the mechanisms of resource complementarity, spatiotemporal coordination, information interaction, and value coupling underlying dynamic system balance. The review identifies key bottlenecks, including the lack of a unified theoretical framework, limited heterogeneous data fusion, insufficient interpretability and real-time adaptability of AI models, weak integration of market mechanisms with operational control, and limited resilience under extreme disturbances. Building on these findings, an integrated research roadmap is proposed emphasizing source–grid–load–storage–cloud collaborative intelligence, AI-enabled digital twins, autonomous multi-agent coordination, cross-energy-system optimization, and resilient self-healing power systems. By establishing a unified knowledge architecture and clarifying the mechanisms linking coordinated regulation with dynamic system balance, this review provides a systematic foundation for advancing theoretical innovation, intelligent operation, and engineering implementation in future carbon-neutral power systems.

抄録全体を表示

The increasing penetration of renewable energy and the deep coupling of heterogeneous energy carriers have introduced fundamental challenges associated with uncertainty characterization, coordinated planning, and low-carbon optimization in multi-energy systems. This review establishes an integrated theoretical framework linking uncertainty modeling, planning decision-making, and low-carbon collaborative optimization to systematically analyze the evolution of multi-energy system planning methodologies under complex uncertainty. First, the review develops a hierarchical classification of uncertainty sources, encompassing renewable generation variability, stochastic load fluctuations, and cross-network coupling effects, and summarizes the transition of uncertainty characterization from probabilistic and scenario-based approaches toward data-driven and structure-aware modeling. Subsequently, stochastic optimization, robust optimization, and distributionally robust optimization are comparatively analyzed from the perspectives of risk representation, decision mechanisms, and engineering applicability, revealing their complementary roles in balancing economic efficiency, system security, and operational flexibility. Furthermore, the review examines low-carbon collaborative optimization mechanisms enabled by source–grid–load–storage coordination, Energy Hub-based multi-energy conversion, carbon market mechanisms, and carbon capture, utilization, and storage (CCUS), highlighting the transition of planning paradigms from cost-oriented optimization toward integrated energy–carbon–flexibility coordination. Based on the reviewed advances, several key scientific challenges are identified, including multi-source uncertainty propagation, dynamic trade-offs between robustness and economy, adaptive planning under extreme events, and collaborative decision-making among heterogeneous stakeholders. This review further proposes future directions toward intelligent, resilient, and adaptive planning frameworks that integrate physics-informed modeling, data-driven learning, multi-timescale optimization, and cross-layer energy–information–carbon coordination. By establishing a unified perspective from uncertainty cognition to collaborative optimization, this review provides a theoretical framework for advancing next-generation multi-energy system planning toward secure, flexible, and low-carbon energy infrastructures.

抄録全体を表示

Multi-energy complementary distributed energy systems (MCDESs) provide a promising framework for coordinating heterogeneous energy carriers and improving renewable energy integration; however, their development is constrained by unresolved challenges in multi-energy coupling representation, cross-scale optimization, and intelligent coordinated operation. This paper systematically reviews recent advances in the modeling, optimization, and operation of MCDESs and proposes a hierarchical analytical framework consisting of four interconnected dimensions: energy coupling mechanisms, system modeling, optimization and decision-making, and coordinated operation. Within this framework, existing approaches are classified from three perspectives, including modeling paradigms, optimization methodologies, and operational strategies. The review summarizes major modeling approaches, including physics-based multi-energy flow network models, energy hub models, and hybrid mechanism–data-driven models, and evaluates optimization techniques ranging from mathematical programming and uncertainty-aware optimization to intelligent algorithms. Furthermore, advances in planning–scheduling–control coordination, multi-timescale optimization, and source–grid–load–storage–hydrogen collaborative operation are critically analyzed. Key scientific challenges are identified, including the absence of unified theories for strongly coupled multi-energy flows, insufficient characterization of uncertainty propagation across heterogeneous energy networks, limited scalability of multi-timescale optimization, incomplete market coordination mechanisms, and inadequate integration of hydrogen-based flexibility resources. To address these gaps, future research directions are proposed toward digital twin-enabled intelligent modeling, physics-informed data-driven integration, renewable–storage–hydrogen coordinated regulation, multi-agent energy market interaction, and life-cycle low-carbon optimization. This review establishes a unified perspective linking physical coupling, computational intelligence, and market mechanisms, providing a theoretical foundation for advancing MCDESs from component-level coordination toward system-wide autonomous operation and scalable low-carbon energy transition.

抄録全体を表示

Solar-driven seawater desalination represents a critical pathway for addressing freshwater scarcity and advancing low-carbon water–energy systems, yet its transition from laboratory-scale innovation to engineering deployment remains constrained by incomplete understanding of multiscale energy conversion mechanisms and insufficient system-level integration strategies. Existing reviews have predominantly focused on specific desalination technologies or localized performance enhancement approaches, lacking a unified framework that connects fundamental energy transformation, technological evolution, and engineering implementation. This review develops a multiscale analytical framework centered on solar energy conversion, heat and mass transport, and integrated energy–water management to systematically elucidate the scientific principles and development pathways of solar-driven seawater desalination. The fundamental mechanisms governing solar absorption, photothermal conversion, interfacial evaporation, phase-change heat transfer, and exergy utilization are first analyzed, followed by a comparative evaluation of representative technologies, including multi-effect distillation, multi-stage flash desalination, membrane distillation, and interfacial solar evaporation, in terms of energy utilization characteristics and operational applicability. Furthermore, key strategies for improving system performance are critically reviewed, encompassing photothermal material engineering, evaporation interface regulation, multistage thermal cascade utilization, thermal management optimization, and salt crystallization control. Beyond component-level enhancement, this review highlights the transition toward multi-energy integrated architectures involving photovoltaic systems, thermal energy storage, industrial waste heat recovery, and regional integrated energy systems. The major scientific and engineering challenges limiting large-scale application are systematically identified, including irreversible energy losses, coupled heat and mass transfer limitations, solar intermittency, degradation induced by fouling and salt crystallization, long-term reliability, and life-cycle economic constraints. Emerging directions, including artificial intelligence-driven optimization, digital twin-enabled lifecycle management, intelligent material design, and Food–Energy–Water Nexus-oriented coordination, are further discussed. By establishing a mechanism-to-system analytical framework, this review bridges the gap between fundamental energy conversion processes and engineering-scale implementation, providing new insights into the design and optimization of efficient, resilient, and low-carbon solar desalination systems.

抄録全体を表示

The increasing penetration of renewable energy and the transition toward decentralized power systems have highlighted the need to unlock the flexibility potential of distributed energy resources in multi-timescale electricity markets. However, the effective utilization of distributed energy flexibility (DEF) remains constrained by heterogeneous resource characteristics, complex cross-timescale interactions, uncertain user behaviors, and insufficient coordination among market participants. This review systematically examines recent advances in DEF utilization and demand-side coordinated operation, with particular emphasis on the fundamental scientific issues underlying flexibility characterization, market participation, incentive mechanisms, and coordinated optimization. Beyond conventional technology-oriented or market-oriented classifications, a multidimensional analytical framework is proposed that integrates four interconnected perspectives: flexibility resource characterization, coordinated participation mechanisms, value-oriented incentive pricing, and multi-timescale optimization strategies. Within this framework, the mechanisms governing flexibility availability, price signal transmission, aggregator-mediated coordination, and intelligent scheduling are comprehensively analyzed, while recent developments in demand response modeling, market mechanism design, and data-driven optimization are critically synthesized. Furthermore, key theoretical and methodological challenges are identified, including the absence of unified flexibility evaluation standards, incomplete coupling between market mechanisms and operational scheduling, inadequate representation of behavioral uncertainty, unresolved multi-agent benefit coordination, and computational limitations in large-scale cross-timescale optimization. The review further reveals that future DEF development requires a transition from isolated resource dispatch toward an integrated paradigm combining resource–market–operation coordination, in which digital technologies, artificial intelligence, and adaptive decision-making mechanisms enable dynamic flexibility valuation and autonomous system regulation. This review establishes a systematic knowledge framework linking flexibility characterization, market mechanism innovation, and intelligent optimization theory, providing new insights into the value realization of distributed flexibility resources and offering theoretical foundations for the design of resilient, efficient, and adaptive next-generation electricity markets.

抄録全体を表示

The rapid transition toward new-type power systems with high renewable energy penetration has created fundamental challenges for battery energy storage systems (BESS) in terms of multi-timescale flexibility provision, operational adaptability, and system-level value creation. However, existing reviews have primarily focused on battery materials, cell-level performance improvement, or individual technology comparisons, lacking a systematic framework that connects technological evolution with power system requirements. This review establishes a demand-oriented analytical framework integrating grid requirements, performance constraints, technology adaptation boundaries, and system-level coordinated deployment to reassess the evolution pathways and future roles of battery energy storage. Major battery technologies, including lithium-ion batteries, sodium-ion batteries, redox flow batteries, and emerging long-duration storage technologies, are comparatively evaluated from the perspectives of application scenarios, engineering maturity, degradation characteristics, safety challenges, and system integration potential. The review further identifies key scientific and engineering challenges restricting large-scale deployment, including the dynamic boundaries between power-oriented and energy-oriented applications, cross-scale coupling between battery degradation and grid operation, propagation mechanisms of safety risks, limitations of lifetime prediction under stochastic operating conditions, and coordinated operation between BESS and heterogeneous storage resources. The analysis reveals that the development trajectory of battery energy storage is shifting from device-level performance optimization toward system-level functionality enhancement, where flexibility, reliability, lifecycle economics, and grid compatibility are becoming the dominant evaluation criteria. Future research is expected to focus on cross-scale battery–grid modeling, physics-informed artificial intelligence for state awareness and lifetime prediction, intelligent safety management, and coordinated multi-storage optimization. By proposing a system-oriented theoretical framework, this review provides new insights into the transformation of battery energy storage from independent energy conversion devices into intelligent and controllable infrastructure supporting the flexibility, resilience, and sustainable evolution of future power systems.

抄録全体を表示

Optimal scheduling of integrated energy systems (IESs) remains challenged by the fragmented treatment of heterogeneous energy modeling, uncertainty-aware decision-making, and coordinated control, which limits a unified understanding of how system representation, optimization, and autonomous operation are intrinsically connected. This review develops a three-dimensional analytical framework encompassing system modeling, uncertainty-aware optimization, and coordinated control to systematically synthesize the evolution, methodological foundations, and emerging paradigms of IES scheduling. It examines multi-energy flow modeling, energy hub representations, source–grid–load–storage coordination, and physics-informed component models, highlighting the fundamental trade-off between physical fidelity and computational tractability. Optimization strategies are then reviewed from stochastic and robust formulations to distributionally robust and data-driven approaches, with emphasis on jointly addressing economic efficiency, decarbonization, reliability, and operational flexibility under uncertainty. The transition from centralized scheduling toward hierarchical and distributed coordination, multi-agent control, virtual power plant aggregation, and autonomous operation is further analyzed from the perspectives of scalability, real-time responsiveness, and adaptability. The review identifies key scientific gaps in cross-scale coupling, interpretable and transferable data-driven modeling, market–physics integration, and the unified treatment of low-carbon objectives, resilience, and cybersecurity. Emerging directions are highlighted in physics–data collaborative modeling, digital twin-enabled optimization, intelligent multi-agent coordination, and cross-regional multi-energy markets. By unifying modeling, uncertainty management, optimization, and control within a coherent analytical framework, this review recasts IES scheduling as a cross-scale, adaptive, and trustworthy system intelligence problem, establishing a conceptual foundation for the transition from isolated optimization algorithms to autonomous and coordinated energy system operation.

抄録全体を表示

Pore–throat architecture governs fluid storage and multiphase transport in tight sandstone reservoirs, yet the mechanisms linking microscopic pore–throat characteristics to gas–water seepage behavior remain poorly constrained. Here, we establish a multi-scale structure–flow characterization framework by integrating mineralogical, petrographic, microscopic, capillary-pressure, and gas–water relative-permeability analyses to elucidate how pore–throat architecture controls reservoir flow behavior in the He 8 Member of the Ordos Basin. The results demonstrate that reservoir quality is governed primarily by the size, connectivity, and heterogeneity of effective throats rather than pore abundance alone. Although relatively limited in occurrence, large effective throats form preferential flow pathways that dominate permeability and gas mobility, whereas micropores primarily contribute to storage while intensifying capillary confinement and fluid retention. Accordingly, Type I reservoirs are characterized by well-developed effective throats, favorable connectivity, low irreducible water saturation, and broad gas–water co-flow intervals, whereas Type III reservoirs are dominated by fine and poorly connected pore–throat systems, strong capillary confinement, elevated irreducible water saturation, and restricted gas mobility. Effective throat radius, mercury withdrawal efficiency, and pore–throat heterogeneity emerge as the principal structural controls on irreducible water saturation, gas relative permeability, and two-phase flow capacity. These findings establish a mechanistic linkage from pore–throat architecture to fluid occurrence and seepage behavior, providing a structure–flow coupled framework that advances tight sandstone reservoir evaluation from static pore-space characterization toward dynamic assessment of flow capacity and development potential.

抄録全体を表示

The dynamic evolution of Paleozoic paleo-uplifts and the migration of erosion centers fundamentally controlled the development and preservation of deep to ultra-deep hydrocarbon systems in the southwestern Tarim Basin, yet their multistage evolutionary processes and tectonic driving mechanisms remain poorly constrained. This study integrates high-resolution 2D–3D seismic interpretation, balanced cross-section restoration, quantitative erosion reconstruction, drilling and logging data, and zircon U–Pb geochronology to reconstruct the formation, modification, and superposed evolution of Paleozoic paleo-uplifts from the Caledonian to Hercynian. The results reveal a systematic migration of erosion centers from the southwestern basin margin northward and subsequently eastward toward the Bachu Uplift, recording a progressive transition of the regional tectonic regime from Proto-Tethyan plate-margin subduction–collision to intraplate far-field stress transmission. The Hetian paleo-uplift experienced a two-stage evolution, evolving from a continental-margin tectonic uplift into an inherited intraplate uplift before undergoing superposed modification by the Maixi and Bachu uplifts, which fundamentally reorganized the pre-existing paleogeomorphology and erosion architecture. These multistage tectonic interactions generated structural transition zones that preferentially controlled reservoir development, hydrocarbon migration pathways, and trap distribution, identifying the Hetian–Maixi–Bachu transition belt as the most prospective domain for deep hydrocarbon accumulation. This study establishes a new dynamic framework linking multistage erosion-center migration, paleo-uplift superposition, and hydrocarbon accumulation, providing a process-based tectono-geomorphic model for understanding deep petroleum systems and guiding exploration of ultra-deep reservoirs in the Tarim Basin.

抄録全体を表示

Understanding why substantial differences in helium enrichment occur under comparable crustal helium-generation conditions remains a critical challenge for evaluating helium resources in continental petroliferous basins. This study investigates the genetic mechanisms of helium enrichment in Paleozoic natural gas from the Daniudi gas field and compares them with those of the adjacent Dongsheng gas field in the Ordos Basin using integrated analyses of natural gas geochemistry, helium isotopes, basement radiogenic helium-generation potential, and tectonic–fault evolution. The results reveal that helium in the Daniudi gas field exhibits generally low concentrations, with a tendency toward higher abundances in shallow reservoirs, and is dominantly derived from crustal radiogenic 4He generated within Archean–Mesoproterozoic metamorphic rocks and granitoids of the crystalline basement, whereas Upper Paleozoic sedimentary rocks contribute only limited helium. Despite broadly comparable basement compositions and radiogenic helium-generation capacities between the Daniudi and Dongsheng gas fields, their helium abundances differ markedly, demonstrating that source potential alone cannot explain differential enrichment. Instead, helium accumulation is primarily governed by the efficiency of post-generation transformation processes. In the Daniudi gas field, underdeveloped deep-seated faults, weak secondary fracture networks, and limited late-stage tectonic reactivation restricted deep helium migration and reservoir-scale redistribution, resulting in a diffusion-dominated, low-efficiency charging system. In contrast, the Dongsheng gas field developed a long-lived fault-controlled transport network that enhanced deep helium release, vertical migration, secondary redistribution, and preservation, producing a high-efficiency enrichment system. Based on these findings, a source–migration–accumulation–preservation coupling framework is established, and two contrasting helium accumulation modes are proposed: a diffusion-dominated, low-efficiency depletion model and a fault-controlled, high-efficiency enrichment model. This study demonstrates that migration efficiency and tectonic reorganization, rather than helium-generation capacity alone, represent the key dynamic controls on crust-derived helium enrichment, providing a new conceptual framework for helium resource assessment and exploration targeting in continental cratonic basins.

抄録全体を表示

Ultra-low-permeability sandstone reservoirs are characterized by complex pore–throat architectures that constrain the mobilization of remaining oil, yet the controls on its microscopic occurrence and the mechanisms by which chemical flooding improves its recovery remain poorly resolved. Focusing on the Shigang Oilfield in the Subei Basin, this study develops an integrated framework linking mineralogical composition, pore–throat structure, seepage behavior, and displacement dynamics through petrographic characterization, online nuclear magnetic resonance displacement, petrophysical and sensitivity measurements, core flooding, and numerical simulation. The results show that micropore–fine-throat systems dominate the reservoir, with limited seepage capacity and pronounced water and velocity sensitivities that promote clay swelling and particle migration during injection. Waterflooding preferentially advances through dominant flow channels, leaving trapped and adsorbed oil concentrated in medium- and small-sized pore throats. Its distribution is governed by the coupled effects of pore–throat heterogeneity, capillary forces, and wettability. Surfactant-assisted secondary waterflooding improves oil mobilization and displacement efficiency by reducing oil–water interfacial tension and modifying the mobility and flow distribution of the displacing phase. By integrating pore-scale oil occurrence with macroscopic displacement response, this study establishes a mechanistic framework for interpreting and optimizing synergistic chemical flooding in ultra-low-permeability sandstone reservoirs.

抄録全体を表示

The differentiation between adsorbed and free oil and its control on shale oil mobility remain critical uncertainties in evaluating lacustrine shale oil sweet spots, particularly under nanoscale confinement where fluid occurrence deviates from conventional reservoir behavior. This study investigates the pore-scale mechanisms governing shale oil occurrence and mobility in the Shahejie Formation shale oil reservoirs of the Dongying Sag by integrating saturation, centrifugal displacement, and low-field nuclear magnetic resonance experiments. A quantitative framework was developed to distinguish adsorbed, free, and movable oil fractions and to establish the coupling relationships among oil occurrence state, pore structure, and mobility. The results demonstrate that organic matter abundance exerts a dual control on shale oil enrichment and producibility by promoting both pore development and oil–rock interfacial adsorption. Organic-rich shales exhibit higher oil-bearing capacity, stronger adsorption-layer development, and enhanced nanoscale confinement effects, resulting in a greater proportion of adsorbed oil while maintaining substantial free-oil reserves due to their multiscale pore systems. Free oil occurrence is strongly governed by pore size, with a critical pore-size threshold controlling the transition from adsorbed to free oil, whereas medium-to-large pores and microfractures represent the dominant domains for free-oil accumulation and migration. Further analysis reveals that shale oil mobility is not determined by resource abundance alone but by the dynamic balance among organic matter enrichment, effective flow space, and oil–rock interaction intensity. Based on these findings, an integrated evaluation framework coupling adsorption–free oil differentiation, pore-scale occurrence, and fluid mobility was proposed, providing new insights into the mechanisms of shale oil enrichment and recoverability and offering a theoretical basis for more accurate sweet-spot identification and efficient development of lacustrine shale oil reservoirs.

抄録全体を表示

Crop reproductive development represents the most heat-sensitive phase determining grain set and yield stability, yet the mechanisms by which reproductive tissues perceive, integrate, and respond to heat stress across multiple regulatory levels remain insufficiently understood. This review synthesizes recent advances in the molecular basis of reproductive-stage heat tolerance, focusing on the coordinated regulation of protein quality control mediated by heat shock proteins and heat shock transcription factors, phytohormone signaling networks, reactive oxygen species homeostasis, transcriptional regulation, and epigenetic reprogramming that collectively safeguard reproductive development under high-temperature stress. It further summarizes progress in translating these mechanistic insights into genetic improvement through the integration of quantitative trait locus mapping, candidate gene discovery, molecular markers, genomic selection, and genome editing. Despite these advances, major challenges remain, including the limited understanding of tissue-specific heat-response mechanisms in reproductive organs, insufficient resolution of cross-regulatory interactions among signaling pathways, and the lack of integrative frameworks linking multi-omics information with field-scale phenotypic performance. By integrating evidence across molecular, cellular, physiological, and genetic levels, this review proposes a systems-level framework for dissecting reproductive-stage heat tolerance and establishes a conceptual foundation for mechanism-guided breeding strategies to enhance crop resilience and yield stability under future climate warming.

抄録全体を表示

The increasing frequency of concurrent heat waves and drought events under climate change poses a major challenge to crop productivity and climate resilience. However, the molecular basis of crop adaptation to combined heat–drought stress (CHDS) remains insufficiently understood because responses to combined stresses cannot be adequately explained by the linear superposition of individual heat or drought responses. This review addresses the central question of how plants integrate multiple environmental signals to achieve adaptive regulation under CHDS. By synthesizing recent advances in stress perception, signal transduction, transcriptional reprogramming, hormonal crosstalk, metabolic adjustment, and post-transcriptional/post-translational regulation, we highlight that CHDS induces a dynamic reorganization of regulatory networks characterized by non-additive responses, context-dependent signaling priorities, and trade-offs between growth maintenance and stress defense. We further propose a systems-level framework in which Ca²⁺ and reactive oxygen species signaling act as early information-processing modules, transcription factor networks and hormone interactions function as regulatory integration layers, and multi-omics-driven network modeling facilitates the identification of potential regulatory hubs. Current limitations, including insufficient field validation, genotype- and developmental stage–dependent variability, and incomplete integration of root–rhizosphere interactions, are critically evaluated. Finally, emerging strategies involving dynamic modeling, multi-omics-guided target discovery, gene editing, synthetic biology, and microbiome-based regulation are discussed to advance the rational improvement of combined stress tolerance. This review establishes a network-based conceptual framework for understanding crop adaptation to concurrent heat and drought stresses and provides theoretical foundations for developing predictive and design-oriented approaches toward climate-resilient agriculture.

抄録全体を表示

Crop rotation optimization has evolved from experience-based management toward a complex decision science problem involving multi-scale processes, competing objectives, and dynamic constraints under global climate change and increasing resource pressures. The rapid advancement of Big Data, remote sensing, Internet of Things, and artificial intelligence technologies has reshaped the theoretical and methodological framework of crop rotation research by enabling integrated information perception, process simulation, predictive analysis, and intelligent decision-making. This review systematically synthesizes recent advances in crop rotation optimization from the perspective of the “data–model–decision” framework. At the data level, multi-source heterogeneous observations, including remote sensing, sensor networks, and field monitoring, provide critical support for characterizing spatial–temporal variability and system states. At the modeling level, process-based models, data-driven approaches, and hybrid modeling paradigms offer complementary capabilities for mechanism interpretation, predictive accuracy, and system representation. At the decision level, multi-objective optimization, reinforcement learning, and scenario-based analysis facilitate the coordination of production efficiency, economic benefits, soil health, resource conservation, and environmental sustainability. However, key challenges remain in integrating heterogeneous data streams, balancing model interpretability and generalization, quantifying uncertainty, and translating computational solutions into operational management strategies across spatial scales. By critically comparing existing methodologies and identifying their applicability boundaries and synergistic pathways, this review proposes an integrated conceptual framework for intelligent crop rotation optimization that links observation, mechanism understanding, and adaptive decision-making. The findings provide theoretical foundations and methodological guidance for developing trustworthy, scalable, and sustainable crop rotation decision-support systems in future agricultural landscapes.

抄録全体を表示

Intercropping can enhance agroecosystem functioning through complementary resource use and niche differentiation, yet how plant interactions across aboveground and belowground domains translate into multifunctional benefits, and how these effects vary with environmental and management contexts, remains insufficiently resolved. This review develops an integrated framework of “ecological mechanisms–functional consequences–system optimization” to connect interaction processes with system-level performance and identify pathways toward predictable intercropping design. We synthesize how canopy and root complementarity, rhizosphere microbial interactions, and biogeochemical regulation jointly shape resource-use efficiency, productivity, stability, and ecological regulation, while assessing their context dependence across crop traits, spatial configurations, management regimes, and environmental conditions. We further identify critical barriers to scalable implementation, including weak coordination between agronomic design and mechanization, the lack of intercropping-oriented crop ideotypes, incomplete resolution of microbiome-mediated interactions, and limited digital tools for system-level optimization. Building on these gaps, we propose a transition from empirical evaluation toward mechanism-based design, multi-objective optimization, and intelligent management that explicitly accounts for ecological trade-offs and environmental constraints. By linking interaction mechanisms to functional outcomes and optimization strategies, this framework provides a basis for transforming intercropping from a site-specific cultivation practice into a predictable, scalable, and sustainability-oriented agroecosystem design strategy.

抄録全体を表示

Soil organic carbon (SOC) stabilization in intercropping systems is increasingly recognized as a microbially mediated process, yet the mechanisms by which plant–plant interactions regulate rhizosphere microbial carbon transformation and microbial necromass formation remain unresolved. Using a long-term peanut–maize intercropping experiment, this study investigated peanut rhizosphere soils collected from zones adjacent to and distant from maize plants to elucidate how neighboring maize regulates microbial processes associated with SOC stabilization. Integrated analyses of microbial carbon metabolism, oxidative enzyme activity, microbial necromass carbon, soil respiration, and SOC demonstrated that maize proximity suppressed polyphenol oxidase activity while enhancing microbial carbon metabolic capacity, substrate utilization diversity, microbial necromass carbon accumulation, and SOC storage, without altering soil respiration. Mechanistically, SOC stabilization was driven primarily by improved microbial carbon-use efficiency and enhanced conversion of plant-derived carbon into persistent microbial necromass, rather than by increased carbon inputs or reduced carbon mineralization. These findings establish a mechanistic framework linking plant–plant interactions, microbial carbon metabolic reprogramming, microbial necromass formation, and SOC stabilization, providing new insights into the microbial carbon pump in agroecosystems and a theoretical foundation for designing intercropping systems that maximize long-term soil carbon sequestration.

抄録全体を表示

Long-term resource inputs can improve soil condition and crop productivity, yet how soil texture shapes the translation of these inputs into soil quality and yield remains insufficiently resolved. We investigated whether contrasting fluvo-aquic soil textures differ not only in the magnitude of their responses to long-term management, but also in the soil attributes and pathway structures associated with productivity. A 7-year field experiment compared five straw–mineral fertilizer–chicken manure regimes in sandy, loamy, and clayey fluvo-aquic soils, integrating soil quality assessment with random forest analysis and partial least squares path modeling. Long-term resource inputs increased both wheat yield and integrated soil quality across soil textures, but response magnitudes varied among textures, and the additional response to partial replacement of mineral N with chicken manure was also texture dependent. The soil attributes most strongly associated with yield likewise differed among textures: sandy soil showed associations spanning nutrient availability, carbon status, and pH; loamy soil showed stronger joint associations of nutrient supply with organic matter and microbial properties; and clayey soil was more closely associated with nutrient availability and pH-related conditions. Pathway analysis further indicated a shared but nonidentical linkage structure in which management regimes were associated with key soil properties, integrated soil quality, and wheat productivity, with pathway organization varying among textures. These findings indicate that soil texture is associated not only with differences in response magnitude, but also with the configuration of soil attributes and their linkage with integrated soil quality and crop productivity. The study thus advances long-term soil-management assessment from evaluating input effects alone toward a texture-aware framework centered on management inputs–key soil properties–soil quality–crop productivity, providing a basis for context-specific diagnosis of soil functional constraints.

抄録全体を表示

Long-term straw returning is known to improve soil quality and winter wheat productivity, yet its effects on the spatial regulation of grain formation within the spike and the underlying mechanisms remain poorly understood, particularly in structurally constrained sandy ginger black soils. Based on a long-term field experiment in the Huaibei Plain of China, this study compared four straw management practices to elucidate how long-term straw returning regulates yield formation across two hierarchical spatial scales: main-stem versus tiller spikes and spikelet versus grain positions. Long-term straw returning significantly reshaped the spatial pattern of spike fertility, although the magnitude and pathway of regulation differed among straw management strategies. Wheat straw mulching after shredding most effectively enhanced the fertility of main-stem spikes, increased grain set in upper spikelets, and promoted grain filling at key grain positions, whereas maize straw incorporation preferentially improved grain filling in tiller spikes and inferior grain positions. In contrast, continuous wheat–maize straw returning produced comparatively smaller improvements in yield formation. Rather than simply increasing grain number, long-term straw returning enhanced yield primarily by optimising within-spike assimilate allocation through improved soil hydrothermal conditions, more synchronised nutrient supply, and stronger source–sink coordination, thereby simultaneously increasing grain number per spike and grain weight. These findings establish a multiscale spatial regulatory framework linking soil management to within-spike grain formation, providing new mechanistic insight into how long-term straw returning enhances wheat productivity and offering a theoretical basis for precision residue management in structurally constrained soils.

抄録全体を表示

Nitrogen use efficiency (NUE) in wheat arises from coordinated phenotypic plasticity and nitrogen-responsive regulation, yet the links between multidimensional plant traits and their molecular basis remain insufficiently resolved. Here, twenty genetically diverse wheat (Triticum aestivum L.) genotypes were evaluated across contrasting nitrogen supplies using a hydroponic system, and an integrated NUE assessment framework was developed by combining seedling morphological and physiological traits with multivariate statistical analyses. Root system architecture and biomass allocation emerged as key phenotypic determinants of NUE, revealing distinct genotype-specific strategies for nitrogen acquisition and utilization. The integrated framework reduced trait redundancy, differentiated NUE performance across genotypes, and identified four contrasting NUE response types, providing a multidimensional basis for germplasm classification. Molecular validation further showed that the candidate gene TaSPX1 displayed distinct nitrogen-responsive expression patterns associated with NUE variation, particularly through coordinated responses to nitrogen limitation and excess, suggesting a potential role in linking nitrogen signaling with root adaptation and resource allocation. Collectively, this study establishes a phenotype–classification–molecular validation framework that connects plant-level NUE variation with candidate regulatory responses, providing a mechanistic basis for identifying nitrogen-efficient germplasm and guiding precision breeding for sustainable wheat production.

抄録全体を表示

Nitrate acts as both a nitrogen source and a signal regulating root system architecture (RSA), but whether extracellular Ca²⁺ participates in nitrate-mediated root developmental plasticity remains unclear. Here, a factorial hydroponic system combining nitrate availability with extracellular Ca²⁺ manipulation was used to dissect their interactive effects on wheat seedling RSA. Nitrate availability strongly reshaped root development, with optimal supply promoting primary root elongation, lateral root formation, and overall root system expansion, whereas nitrate deficiency and excess nitrate disrupted these traits. Strikingly, the effects of extracellular Ca²⁺ availability depended on nitrate status: reducing extracellular Ca²⁺ had limited effects under nitrate deficiency but strongly suppressed primary root elongation, lateral root formation, and root system expansion under nitrate supply, shifting RSA toward a shorter and less branched architecture. Similar responses to Ca deficiency and EGTA treatment further supported a specific role of extracellular Ca²⁺ availability in nitrate-dependent RSA regulation. Collectively, these findings support a nitrate–extracellular Ca²⁺–RSA regulatory framework in which extracellular Ca²⁺ functions as a nitrate-dependent component of root developmental plasticity, providing a mechanistic basis for understanding coordinated nutrient signaling and improving root-mediated nitrogen acquisition in crops.

抄録全体を表示

Differences in soil moisture conditions and rhizosphere environments between cropping systems may alter wheat nitrogen(N) demand and yield formation, but how these environmental constraints reshape N-use strategies remains unclear. Field experiments in the Chengdu Plain, China, compared rice–wheat and upland wheat systems under contrasting N rates and basal-to-topdressing ratios to determine how cropping systems regulate canopy development, dry matter accumulation, and yield responses to N supply. The results showed that cropping systems markedly altered wheat growth strategies and N responsiveness. Rice–wheat exhibited weaker early canopy establishment, biomass accumulation, and grain yield, but greater yield responsiveness to optimized N supply. Increasing early-season N availability enhanced vegetative growth and pre-anthesis dry matter accumulation, thereby increasing assimilate remobilization to grains during filling. In contrast, upland wheat showed greater growth potential under more favorable soil conditions, with yield formation relying more strongly on sustained post-anthesis photosynthetic activity and assimilate accumulation promoted by appropriately delayed N supply. These contrasting responses revealed a rotation-dependent regulatory framework linking cropping system, soil ecological conditions, N supply dynamics, dry matter formation, and yield formation. The findings demonstrate that N management should be tailored to system-specific ecological constraints and biomass formation pathways, providing a mechanistic basis for precision N management across contrasting wheat rotation systems.

抄録全体を表示

Phosphorus (P) supply strongly influences yield formation in high-yield drip-irrigated wheat, yet how P availability coordinates biomass production with nitrogen (N)–P allocation and utilization during yield formation remains insufficiently resolved. A two-year field experiment with contrasting P application rates was conducted in drip-irrigated spring wheat (Triticum aestivum L.) in northern Xinjiang, China, to determine how P supply regulates dry matter production, assimilate remobilization, and N–P utilization efficiency. Grain yield showed a nonlinear response to P supply, with an intermediate P level maximizing yield by sustaining dry matter accumulation, promoting pre-anthesis assimilate remobilization, and enhancing the coordinated accumulation and redistribution of N and P to grains. Excessive P application, however, produced diminishing yield returns because additional biomass and nutrient accumulation were not proportionally translated into grain formation, resulting in lower P utilization efficiency. The integrated physiological responses indicated that yield advantage under optimal P supply depended not on maximizing biomass or nutrient accumulation per se, but on synchronizing continuous biomass production with coordinated N–P acquisition and efficient assimilate and nutrient remobilization during grain filling. These findings establish a P-regulated resource-allocation framework in which yield formation emerges from the coordination of biomass production, N–P coupling, and post-anthesis redistribution, providing a mechanistic basis for shifting high-yield drip-irrigated wheat from input-driven P management toward efficiency-oriented nutrient regulation.

抄録全体を表示

Water and nitrogen constraints jointly limit the productivity and resource-use efficiency of irrigated dryland spring wheat, yet how arbuscular mycorrhizal fungi (AMF) coordinate plant carbon–nitrogen metabolism to stabilize yield under simultaneous resource limitation remains unresolved. Using a split–split plot field experiment with Funneliformis mosseae inoculation under contrasting irrigation and nitrogen regimes, this study disentangled the AMF-mediated regulatory pathway from symbiosis establishment to yield formation. AMF maintained functional symbiosis with wheat roots under moderate resource reduction, whereas severe water and nitrogen limitation suppressed colonization. Under moderate water-saving and nitrogen-reduction conditions, AMF alleviated resource constraints by enhancing rhizosphere resource acquisition, sustaining photosynthetic capacity, promoting nitrogen assimilation, and improving water- and nitrogen-use efficiency, thereby maintaining biomass accumulation and grain yield. These benefits diminished under excessive nitrogen reduction, revealing a resource-availability threshold for effective mycorrhizal regulation. Integrative analysis further showed that yield stabilization arose from a coordinated cascade linking stable symbiosis with resource acquisition, physiological compensation, photosynthetic maintenance, nitrogen assimilation, and carbon–nitrogen metabolic coordination, rather than from any single trait. This study establishes an AMF-mediated water–nitrogen synergistic regulation framework that explains how mycorrhizal symbiosis reorganizes plant resource allocation under coupled resource constraints and provides a mechanistic basis for optimizing low-input, resource-efficient wheat production.

抄録全体を表示