Farming System最新文献

Typology-based evaluation of Nutrient Expert® for sustainable maize intensification in smallholder farms of eastern India 基于类型的营养专家®对印度东部小农玉米可持续集约化的评价

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-12-01 DOI: 10.1016/j.farsys.2025.100193

Rupak Goswami , Sudarshan Dutta , Hirak Banerjee , Somsubhra Chakraborty , Krishnendu Ray , Kaushik Majumdar , Jagadish Timsina

Smallholder maize systems in South Asia face challenges of low productivity, inefficient fertilizer use, and rising environmental footprints. Decision-support tools (DST) such as Nutrient Expert® (NE®), built on 4R nutrient stewardship principles, offer promise for achieving sustainable intensification (SI), yet their performance across diverse farm types remains poorly understood. This study assessed NE®-guided fertilization against farmer fertilizer practices (FFP) across 112 farms in four agro-climatic zones of southern West Bengal, India. Farm typologies were delineated using principal component and cluster analysis, resulting in seven distinct farm types (FT) reflecting socio-economic and biophysical heterogeneity. Paired on-farm trials compared NE® and FFP for multiple indicators, including yield, economics, energy use, and greenhouse gas (GHG) emissions. Results show that NE® reduced N, P, and K use by 66 %, 93 %, and 56 %, respectively, while increasing yields across all farm types, with the highest gains in FT-4 (71.1 %), FT-2 (63.0 %), and FT-7 (60.3 %). Gross return above fertilizer cost (GRF) improved in nearly all cases, with FT-2 achieving a 90 % gain. Energy productivity and net energy gain increased in most farm types, while yield-scaled GHG emissions declined in 88.4 % of farms. However, benefits were uneven: FT-3 and FT-5, constrained by setting higher yield targets, coupled with poor resource endowment and weak yield response, showed limited improvements. Thin-plate spline regression further identified farm-type–specific sustainability frontiers, indicating untapped potential for SI beyond current NE® yield targets. Overall, the findings demonstrate the utility of NE® in tailoring realistic yield targets for DST and nutrient management across heterogeneous farm systems, while also highlighting the importance of typology-based scaling strategies.

南亚的小农玉米系统面临着生产力低下、肥料使用效率低下和环境足迹不断增加的挑战。营养专家（NE）等基于4R营养管理原则的决策支持工具（DST）为实现可持续集约化（SI）提供了希望，但对其在不同农场类型中的表现仍知之甚少。本研究对印度西孟加拉邦南部四个农业气气带112个农场的NE®引导施肥与农民施肥实践（FFP）进行了评估。利用主成分和聚类分析对农场类型进行了划分，得出了反映社会经济和生物物理异质性的七种不同的农场类型。配对的农场试验比较了NE®和FFP的多个指标，包括产量、经济、能源使用和温室气体（GHG）排放。结果表明，NE®分别减少了66%、93%和56%的氮、磷和钾的使用，同时提高了所有农场类型的产量，其中FT-4（71.1%）、FT-2（63.0%）和FT-7（60.3%）的产量增幅最大。在几乎所有情况下，高于肥料成本的总回报率（GRF）都有所改善，FT-2的收益达到90%。大多数农场类型的能源生产率和净能源增益都有所提高，而88.4%的农场按产量计算的温室气体排放量有所下降。然而，效益并不均衡：FT-3和FT-5受设定较高产量目标的限制，加上资源禀赋差，产量响应弱，改善有限。薄板样条回归进一步确定了特定农场类型的可持续性前沿，表明SI在当前NE®产量目标之外尚未开发的潜力。总体而言，研究结果证明了NE®在跨异质农场系统为DST和养分管理量身定制现实产量目标方面的效用，同时也强调了基于类型的规模化策略的重要性。

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引用次数: 0

Straw return facilitates the availability of soil nitrogen by altering the metabolic distribution and nitrogen cycling processes 秸秆还田通过改变土壤氮的代谢分布和氮循环过程，促进了土壤氮的有效性

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-11-17 DOI: 10.1016/j.farsys.2025.100192

Yu Gao , Lu Wang , Mingyue Li , Yunpeng Qiu , Qiulai Song , Tianjiao Ji , Zhenping Gong , Chunmei Ma , Chao Yan

Straw return (SR) has been extensively utilized to enhance soil organic carbon (SOC) levels and soil fertility in agroecosystems. However, the impact of SR on soil nitrogen (N) dynamics, microbial communities, metabolic processes, and the underlying mechanisms remains largely unexplored. Through a multi-year manipulation of SR under continuous corn cropping (CC) and fallow (FR), we demonstrate that SR promotes N availability by altering soil microbial metabolism. Moreover, SR facilitated N turnover by enhancing metabolic pathways, including arginine biosynthesis, alanine, aspartate, and glutamate metabolism, as well as glycine, serine, and threonine metabolism, and pyrimidine and purine metabolism. Additionally, SR resulted in a significant increase in the abundance of microorganisms and functional genes involved in mineralization (glsA and ureC), N fixation (Bradyrhizobium, Altererythrobacter), dissimilatory nitrate reduction to ammonium (DNRA, Sorangium, napC, and nirB), and assimilatory nitrate reduction to ammonium (ANRA, nasA). However, despite a reduction in the relative abundance of nitrification microbes and functional genes (e.g., Nitrososphaerag, Nitrospira, Sphingomonas, amoAB, nxrA), SR enhanced the content of extractable inorganic N and organic N in the soil. Therefore, SR represents an effective strategy to promote N dynamics and accelerate the restoration of soil fertility. Our results demonstrated that SR alters N cycling processes by modifying microbial community structure and metabolite distribution, thereby increasing soil N availability.

在农业生态系统中，秸秆还田被广泛用于提高土壤有机碳（SOC）水平和土壤肥力。然而，SR对土壤氮动态、微生物群落、代谢过程的影响及其潜在机制在很大程度上仍未被探索。通过玉米连作（CC）和休耕（FR）条件下多年的SR调控，我们发现SR通过改变土壤微生物代谢来促进氮有效性。此外，SR通过增强代谢途径，包括精氨酸生物合成、丙氨酸、天冬氨酸和谷氨酸代谢、甘氨酸、丝氨酸和苏氨酸代谢、嘧啶和嘌呤代谢，促进N的转化。此外，SR还显著增加了参与矿化（glsA和ureC）、固氮（慢生根瘤菌、变红杆菌）、异化硝酸还原为铵（DNRA、Sorangium、napC和nirB）和同化硝酸还原为铵（ANRA、nasA）的微生物和功能基因的丰度。然而，尽管硝化微生物和功能基因（如Nitrososphaerag、Nitrospira、Sphingomonas、amoAB、nxrA）的相对丰度降低，但SR提高了土壤中可提取无机氮和有机氮的含量。因此，SR是促进土壤氮素动态和加速土壤肥力恢复的有效策略。我们的研究结果表明，SR通过改变微生物群落结构和代谢物分布来改变N循环过程，从而增加土壤N有效性。

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引用次数: 0

Long-term green manuring reduces net greenhouse gas emissions in upland cropping systems in China 长期绿色施肥减少了中国旱作系统的温室气体净排放

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.farsys.2025.100191

Penghui Li , Hao Liang , Qiu Zhao , Jiudong Zhang , Libo Fu , Dabin Zhang , Mei Han , Rui Zhang , Na Zhao , Weidong Cao , Feng Zhou

Green manuring enhances multiple agroecosystem services functions, yet its impact on net greenhouse gas mitigation remains controversial, primarily due to a limited number of long-term experiments. To address these challenges, this study investigated the long-term effects of green manure (GM) rotations on 100-cm-depth soil organic carbon (SOC) sequestration, N₂O emissions, and crop yields based on eight long-term experimental sites (7–16 years) in China's upland cropping systems combined with process-based modeling. The results demonstrated that green manuring significantly increased SOC concentration by 8.8 %–14.4 % (p < 0.001) across 0–100 cm soil profiles compared to fallow system, with annual SOC sequestration rates reaching 0.95–1.16 Mg C ha⁻¹ yr⁻¹ (p < 0.001). Notably, topsoil layer (0–40 cm) contributed 67.5 % of total profile SOC accumulation. Green manuring can replace approximately 40 % of synthetic fertilizers of N while maintaining long-term yield stability, though with potential trade-offs in elevated N₂O emissions. The optimal net global warming potential (NGWP) reached −16.47 Mg CO₂-eq ha⁻¹ yr⁻¹ under GM-based system with 30 % reduction in fertilizer N. Meanwhile, under the condition that GM substitution for fertilizer N achieved no yield reduction, the greenhouse gas intensity (GHGI) was optimized within the substitution rate range of 20 %–40 %. The results from process-based modeling demonstrate that substituting 30 % of N fertilizer with GM achieves optimal soil C sequestration while maintaining stable crop yields. These findings provide direct evidence that GM rotation increases C sequestration, addressing previous knowledge gaps in understanding the C sequestration and emission reduction effects of GM-based rotation.

绿色施肥增强了多种农业生态系统服务功能，但其对温室气体净减排的影响仍存在争议，这主要是由于长期试验数量有限。为了应对这些挑战，本研究基于8个长期试验点（7-16年），结合基于过程的模型，研究了绿肥轮作对中国旱作系统100 cm深度土壤有机碳（SOC）固存、N2O排放和作物产量的长期影响。结果表明，与休耕系统相比，绿肥显著提高了0-100 cm土壤有机碳浓度8.8% - 14.4% (p < 0.001)，年有机碳固存率达到0.95-1.16 Mg C ha - 1 yr - 1 （p < 0.001）。表层（0 ~ 40 cm）土壤有机碳累积量占剖面总有机碳积累量的67.5%。绿色施肥可以替代约40%的氮肥合成肥料，同时保持长期产量稳定，尽管可能会增加N2O排放。在氮肥减量30%的转基因体系下，最优净全球变暖潜势（NGWP）达到−16.47 Mg CO2-eq ha−1 yr−1；在转基因替代氮肥不减产量的情况下，温室气体强度（GHGI）在替代率为20% ~ 40%的范围内达到最优。基于过程的模型结果表明，在保持作物稳定产量的同时，用转基因代替30%的氮肥可以实现最佳的土壤碳固存。这些发现提供了转基因旋转增加碳固存的直接证据，解决了以前在理解基于转基因旋转的碳固存和减排效应方面的知识空白。

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引用次数: 0

From soil carbon towards system sustainability: Integrating SOC modelling and life cycle assessment to evaluate environmental trade-offs in carbon farming 从土壤碳到系统可持续性：整合有机碳模型和生命周期评估以评估碳农业的环境权衡

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-12-12 DOI: 10.1016/j.farsys.2025.100195

Stefano Spotorno , Anne Gobin , Diego Armando Arellano Vazquez , Erica Gagliano , Adriana Del Borghi , Michela Gallo

The European Union (EU) is committed to reducing greenhouse gas (GHG) emissions to the atmosphere and promoting sustainable soil and land management practices. Carbon Farming (CF) is a set of practices to mitigate climate change in agriculture through carbon sequestration in soils. While CF practices increase soil organic carbon (SOC) stocks, they are also expected to have environmental impacts and potential trade-offs. However, the environmental impact of CF practices is often overlooked, and a comprehensive evaluation using Life Cycle Assessment (LCA) methodology is required. The RothC model was used to simulate SOC dynamics under different CF practices on arable land in Northern Italy: reduced tillage (RT), farmyard manure (FYM) application, and cover crops (CC). LCA methodology was applied to quantify GHG emissions and other environmental impacts beyond carbon. The results confirmed that different soil management strategies can significantly affect SOC accumulation. FYM application sequesters the most carbon (4.89 t C ha⁻¹ over 20 years) due to exogenous carbon inputs. RT (1.34 t C ha⁻¹) and CC (1.73 t C ha⁻¹) also contribute to sequestration, but at lower rates. However, LCA results revealed significant trade-offs: while FYM maximizes carbon sequestration (0.90 t CO₂ ha⁻¹ yr⁻¹), it substantially increases acidification (+254 %), marine eutrophication (+372 %), terrestrial eutrophication (+243 %), and photochemical ozone formation (+290 %) compared to conventional agriculture. In contrast, CC and RT provide a balanced profile with moderate sequestration benefits (0.32 and 0.25 t CO₂ ha⁻¹ yr⁻¹, respectively) and reduced environmental impacts, with RT showing improvements across all acidification and eutrophication indicators. This research underlines the critical need for comprehensive system assessment of agricultural sustainability, as CF may place too much emphasis on carbon sequestration without fully considering other environmental impacts requiring mitigation.

欧洲联盟（欧盟）致力于减少温室气体（GHG）排放到大气中，并促进可持续的土壤和土地管理做法。碳农业（CF）是一套通过土壤固碳来减缓农业气候变化的做法。虽然CF做法增加了土壤有机碳（SOC）储量，但它们也有望产生环境影响和潜在的权衡。然而，CF实践的环境影响经常被忽视，需要使用生命周期评估（LCA）方法进行全面评估。采用RothC模型，模拟了意大利北部不同还田方式（RT、FYM和CC）下土壤有机碳动态变化。LCA方法用于量化温室气体排放和碳以外的其他环境影响。结果表明，不同土壤管理策略对土壤有机碳积累有显著影响。由于外源碳输入，FYM应用固碳最多（4.89 t cha - 1 / 20年）。RT （1.34 t cha - 1）和CC （1.73 t cha - 1）也有助于固存，但速率较低。然而，LCA结果显示了显著的权衡：与传统农业相比，FYM虽然最大限度地提高了碳固储量（0.90 t CO2每−1年−1年），但它大大增加了酸化（+ 254%）、海洋富营养化（+ 372%）、陆地富营养化（+ 243%）和光化学臭氧形成（+ 290%）。相比之下，CC和RT提供了一个平衡的剖面，具有中等的固碳效益（分别为0.32和0.25 t CO2每−1年−1），并减少了环境影响，RT在所有酸化和富营养化指标上都有所改善。这项研究强调了对农业可持续性进行全面系统评估的迫切需要，因为CF可能过于强调碳固存，而没有充分考虑需要缓解的其他环境影响。

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引用次数: 0

Soil moisture monitoring technologies in smart agriculture: A comprehensive review 智能农业中的土壤水分监测技术综述

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.farsys.2025.100189

R. Sreeram , S. Adithya Krishna , Aiswarya S. Kumar , S. Remya , Yong Yun Cho

Soil moisture monitoring is a critical component of modern agriculture, directly impacting crop productivity and resource management. With increasing pressures from climate change, water scarcity, and global food demand, there is a growing need for innovative and data-driven approaches to optimize agricultural practices. This systematic and conceptual review explores the role of advanced technologies in transforming soil moisture monitoring and smart agriculture. It aims to address major global challenges, including food security, water scarcity, and climate variability. By synthesizing advancements in Internet of Things (IoT), machine learning (ML), remote sensing, and related technologies, this review aims to elucidate their contributions to precision farming, resource optimization, and sustainable agricultural practices. The review provides a comprehensive analysis of current trends, methodologies, and technological integrations, identifying key innovations that enhance crop productivity and environmental resilience. It seeks to guide researchers, policymakers, and agritech stakeholders toward scalable, inclusive solutions by highlighting research gaps and proposing future directions for equitable and sustainable agricultural transformation.

土壤水分监测是现代农业的重要组成部分，直接影响作物生产力和资源管理。随着气候变化、水资源短缺和全球粮食需求的压力越来越大，越来越需要创新和数据驱动的方法来优化农业实践。这篇系统的、概念性的综述探讨了先进技术在改造土壤湿度监测和智能农业中的作用。它旨在解决重大的全球挑战，包括粮食安全、水资源短缺和气候变化。通过综合物联网（IoT）、机器学习（ML）、遥感及相关技术的进展，本文旨在阐明它们对精准农业、资源优化和可持续农业实践的贡献。该综述对当前趋势、方法和技术整合进行了全面分析，确定了提高作物生产力和环境抵御力的关键创新。它旨在通过突出研究差距并提出公平和可持续农业转型的未来方向，引导研究人员、政策制定者和农业技术利益相关者寻求可扩展的、包容性的解决方案。

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引用次数: 0

Roots and the rhizosphere: a perspective on the hidden engine of regenerative, antifragile, and digitally enabled agriculture 根与根际：从一个角度看可再生、反脆弱和数字化农业的隐藏引擎

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2026-01-08 DOI: 10.1016/j.farsys.2026.100199

Stefano Cesco , Monica Yorlady Alzate Zuluaga , Luciano Cavani , Luigimaria Borruso , Vito Armando Laudicina , Fabrizio Mazzetto , Tanja Mimmo , Youry Pii , Roberto Terzano , Stefania Astolfi

For decades, agricultural optimization has focused primarily on aboveground yield and external inputs while neglecting the complexity and functional integrity of belowground processes. The rhizosphere, the dynamic zone surrounding roots, has long been investigated through isolated components but rarely in a holistic framework, despite its critical role in agroecosystem productivity, soil fertility, and sustainability. Moreover, the translation of this knowledge into routine farm-scale practice remains quite limited. This perspective argues for repositioning the rhizosphere at the center of agricultural innovation. In this review, roots and their microbial partners are not only fundamental for crop performance but also drivers of antifragility, enabling farming systems to withstand and even improve under environmental stresses, while sustaining productivity. Integrating advances in root biology, soil chemistry, microbial ecology, and agronomics, this review shows that rhizosphere processes drive key biogeochemical functions such as carbon sequestration, nutrient cycling, and stress adaptation. Critical gaps include limited integration of root-microbiome traits in crop breeding, lack of field-ready rhizosphere diagnostics, and variable performance of microbial inoculants across soils and climates. Addressing these challenges is essential to operationalize rhizosphere science at field scale and support reduced-input, climate-resilient farming systems. Looking forward, emerging technologies ranging from high-resolution imaging and spectroscopy to artificial intelligence offer unprecedented insight into belowground complexity and a unique opportunity to bridge the gap between experimental insights and real-world farming. Ultimately, the review calls for a paradigm shift embedding rhizosphere processes into crop breeding, farming system design, and management strategies. Recognizing the rhizosphere as a primary entry point for innovation is essential for translating science into practical levers for regenerative, antifragile, and sustainable agriculture.

几十年来，农业优化主要关注地上产量和外部投入，而忽视了地下过程的复杂性和功能完整性。根际是根周围的动态区域，长期以来一直通过孤立的成分进行研究，但很少在整体框架中进行研究，尽管它在农业生态系统生产力、土壤肥力和可持续性中起着关键作用。此外，将这些知识转化为常规农场规模的实践仍然相当有限。这一观点主张将根际重新定位为农业创新的中心。在这篇综述中，根系及其微生物伙伴不仅是作物生产性能的基础，也是抗脆弱性的驱动因素，使农业系统能够承受环境压力，甚至在环境压力下得到改善，同时保持生产力。综合根系生物学、土壤化学、微生物生态学和农学等方面的研究进展，本文综述了根际过程驱动的关键生物地球化学功能，如碳封存、养分循环和胁迫适应。关键的差距包括作物育种中对根微生物性状的整合有限，缺乏现成的田间根际诊断，以及微生物接种剂在不同土壤和气候条件下的不同表现。应对这些挑战对于在田间规模上实施根际科学和支持减少投入、适应气候变化的农业系统至关重要。展望未来，从高分辨率成像和光谱到人工智能等新兴技术为地下复杂性提供了前所未有的见解，并为弥合实验见解与现实农业之间的差距提供了独特的机会。最后，该综述呼吁将根际过程纳入作物育种、耕作系统设计和管理战略的范式转变。认识到根际是创新的主要切入点，对于将科学转化为可再生、反脆弱和可持续农业的实际杠杆至关重要。

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引用次数: 0

Dynamic change of soil organic carbon fractions improved by soil microorganisms at rice critical growth stages under long-term straw return in a double-cropped rice system in southern China 长期秸秆还田条件下双季稻系统土壤微生物对水稻关键生育期土壤有机碳组分的影响

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-12-09 DOI: 10.1016/j.farsys.2025.100194

Shiqi Yang , Liming Chen , Xueming Tan , Xiaohua Pan , Yanhua Zeng

The practice of returning straw enhances the accumulation of soil organic carbon (SOC), dissolved organic carbon (DOC), and microbial communities. Nonetheless, the mechanisms in which microbes affect the variations in SOC and DOC during rice critical growth stages remain unclear. This research examines SOC, DOC, and microbial communities at panicle initiation (PI), heading (HS), and maturity (MS) stages in a paddy field, 13 years after long-term straw incorporation under no chemical fertilizers application with straw removal (CK), straw removal with only chemical fertilizer application (F), straw burning return with some chemical fertilizer application (SBR), and straw return in situ with some chemical fertilizer application (SR). Compared to CK, the other treatments significantly enhanced SOC levels throughout all growth stages. Notably, SR exhibited an average increase of 37.9 % during the early rice season and 41.9 % during the late rice season. Compared to F and SBR, SR significantly increased SOC by 7.1 % at the PI stage of early rice, and by 9.2 % and 10.1 % at all late rice growth stages, respectively. SR also significantly enhanced the DOC level at the late growth stages of both rice seasons. Furthermore, SR enhanced microbial diversity at the PI stage in both rice seasons, aiding SOC accumulation. Although DOC had a positive relationship with microbial diversity in the early rice season, this relationship turned negative in the late rice season, likely due to the influence of the phylum Actinobacteria. Moreover, the significant enrichment of Cyanobacteria under SR at all stages of the late rice season was associated with an increase in SOC content. These results highlight the importance of Actinobacteria and Cyanobacteria in promoting the formation of SOC and DOC during key growth periods under long-term straw return. Future research requires the integration of ¹³C labelling with multi-omics to trace microbial-mediated straw carbon sequestration.

秸秆还田提高了土壤有机碳（SOC）、溶解有机碳（DOC）和微生物群落的积累。然而，微生物影响水稻关键生育期有机碳和有机碳含量变化的机制尚不清楚。本研究在长期施用秸秆13年后，在不施用化肥与秸秆去除（CK）、仅施用化肥与秸秆去除(F)、秸秆焚烧还田与部分化肥还田（SBR）和秸秆原地还田与部分化肥还田（SR）的情况下，对稻田穗发期（PI）、抽穗期（HS）和成熟期（MS）的有机碳（DOC）和微生物群落进行了研究。与对照相比，其他处理显著提高了各生育期土壤有机碳水平。值得注意的是，SR在早稻季节平均增加37.9%，在晚稻季节平均增加41.9%。与F和SBR相比，SR在早稻PI期显著提高了7.1%，在所有晚稻生育期分别显著提高了9.2%和10.1%。SR还显著提高了两个水稻季生育后期的DOC水平。此外，SR增加了水稻稻谷期的微生物多样性，促进了有机碳的积累。虽然DOC在水稻早季与微生物多样性呈正相关，但在水稻晚季，这种关系变为负相关，这可能是由于放线菌门的影响。此外，在晚稻季节的各个阶段，SR处理下蓝藻的显著富集与有机碳含量的增加有关。这些结果表明，在长期秸秆还田条件下，放线菌和蓝藻在关键生长时期促进土壤有机碳和有机质形成的重要性。未来的研究需要将13C标记与多组学相结合，以追踪微生物介导的秸秆固碳。

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引用次数: 0

Impacts of inorganic and organic fertilization on soil organic carbon and crop production: a meta-analysis 无机和有机施肥对土壤有机碳和作物生产影响的meta分析

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.farsys.2026.100211

Zhiyuan Bai , Jiajie Xu , Xiaoyu Shi , Matthew Tom Harrison , Jørgen Eivind Olesen , Robert M. Rees , Cairistiona F.E. Topp , Xinya Wen , Zhenwei Song , Xiaogang Yin , Haotian Chen

Enhancing soil organic carbon (SOC) is critical for climate mitigation and stable crop production, yet the effectiveness of different fertilization strategies varies widely across environmental and management contexts. To clarify these inconsistencies, empirical field data from major grain-producing regions of northern China were synthesized using meta-analysis, regression models, random forest algorithms, and partial least squares path modeling to systematically evaluate the impacts of chemical fertilization (CF), organic fertilization (OF), and combined organic–inorganic fertilization (COF) on SOC dynamics. Results showed that CF, OF, and COF increased SOC content by 13 %, 34 %, and 39 %, respectively, with long-term application (>20 years) further amplifying carbon sequestration. Pronounced spatial heterogeneity was observed. In Northeast China (NEC) with higher initial SOC, over 80 % of sites showed absolute SOC gains exceeding 10 g C kg⁻¹, with COF most effective. In Huanghuaihai Farming Region of China (HFR), characterized by lower baseline SOC, relative gains reached 63 %, and OF showed stronger effects. Across soil textures, OF consistently achieved the largest SOC improvements, and under nutrient-limited conditions, SOC enhancement followed the order OF > COF > CF. Test duration emerged as the dominant driver of SOC accumulation, while climate, nitrogen availability, and initial SOC modulated responses under different regimes. Structural equation modeling indicated that SOC mediated yield responses under CF, whereas direct soil and management effects dominated under OF and COF. These findings emphasize that fertilization management strategies should fully consider regional initial SOC levels and integrate carbon-enhancing practices within broader conservation-oriented farming systems to simultaneously enhance soil carbon sequestration, sustain crop productivity, and provide actionable evidence for promoting sustainable agricultural intensification and national carbon neutrality goals.

提高土壤有机碳（SOC）对减缓气候变化和稳定作物生产至关重要，但不同施肥策略的有效性在不同的环境和管理背景下差异很大。为了阐明这些不一致性，利用meta分析、回归模型、随机森林算法和偏最小二乘路径模型综合了中国北方主要产粮区的经验田间数据，系统评价了化学施肥（CF）、有机施肥（of）和有机无机复合施肥（COF）对土壤有机碳动态的影响。结果表明，CF、OF和COF分别增加了13%、34%和39%的有机碳含量，长期施用（20年）进一步增强了碳固存。观察到明显的空间异质性。在初始有机碳含量较高的东北地区，超过80%的土壤有机碳绝对增益超过10 g C kg−1，以COF最有效。黄淮海农区（HFR）土壤基础有机碳较低，相对增收达63%，其中of的增收效果较强。在不同土壤质地下，有机肥对土壤有机碳的改善效果最大，在养分限制条件下，土壤有机碳的增强顺序依次为>； COF >； CF。试验持续时间是土壤有机碳积累的主要驱动因素，而气候、氮有效性和初始有机碳在不同条件下的调节作用。结构方程模型表明，土壤有机碳介导了CF条件下的产量响应，而土壤和管理的直接效应在OF和COF条件下起主导作用。这些研究结果强调，施肥管理策略应充分考虑区域初始有机碳水平，并在更广泛的保护性耕作系统中整合碳增强实践，以同时增强土壤固碳，维持作物生产力，并为促进可持续农业集约化和国家碳中和目标提供可操作的证据。

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引用次数: 0

Machine learning reveals that duration dominates rate in driving soil nitrogen cycling responses to long-term fertilization 机器学习表明，持续时间在驱动土壤氮循环对长期施肥的响应中占主导地位

IF 8.4

Farming System

Pub Date : 2026-04-01 Epub Date: 2025-12-22 DOI: 10.1016/j.farsys.2025.100196

Beilei Wei , Jinrong Wang , Shunting He , Yongfeng Sun , Xiaoqi Zhang , Shijie He , Huarong Ling , Qingfang Yao , Zhigang Huang , Ziting Wang

Intensive nitrogen fertilization in agricultural ecosystems has profound impacts on soil nitrogen cycling, yet the mechanistic understanding of how long-term nitrogen inputs alter microbial-mediated nitrogen transformations remains limited. While previous research has focused primarily on application rates, the temporal dimension of nitrogen management has been largely overlooked. Here, we present a global meta-analysis of 2824 observations from 88 field studies specifically examining how nitrogen application duration, rather than just amount, shapes soil nitrogen cycling processes. Machine learning analysis revealed application duration as the dominant driver of nitrogen cycling changes, explaining greater variance than that explained by application rates across all functional genes examined. Long-term nitrogen application (>20 years) dramatically increased ammonia-oxidizing bacteria (AOB) abundance by 904 % while modestly affecting ammonia-oxidizing archaea (AOA) by 142 %, fundamentally altering the balance of ammonia oxidation processes. In acidic soils with long-term nitrogen application, AOB responses (1107 %) substantially exceeded AOA responses (179 %), demonstrating that substrate availability becomes the primary driver of microbial community structure structure under long-term nitrogen enrichment. Our findings demonstrate that nitrogen application duration, more than amount, determines soil nitrogen cycling responses, creating progressive changes with substantial shifts occurring after 20 years of continuous fertilization. These results reveal duration-dependent mechanisms that provide a new framework for nitrogen management, enabling simultaneous maintenance of agricultural productivity and reduction of environmental impacts through duration-optimized application strategies.

农业生态系统中密集施氮对土壤氮循环有着深远的影响，但长期氮输入如何改变微生物介导的氮转化的机制理解仍然有限。虽然以前的研究主要集中在施用量上，但氮管理的时间维度在很大程度上被忽视了。在此，我们对来自88个实地研究的2824个观测结果进行了全球荟萃分析，专门研究了施氮时间（而不仅仅是施氮量）如何影响土壤氮循环过程。机器学习分析显示，施用时间是氮循环变化的主要驱动因素，比所有功能基因的施用量所解释的差异更大。长期施氮（20年）使氨氧化细菌（AOB）丰度显著增加了904%，而对氨氧化古细菌（AOA）的影响则为142%，从根本上改变了氨氧化过程的平衡。在长期施氮的酸性土壤中，AOB响应（1107%）大大超过AOA响应（179%），表明长期富氮条件下，底物有效性成为微生物群落结构结构的主要驱动因素。研究结果表明，施氮时间比施氮量更能决定土壤氮循环响应，并在连续施肥20年后发生实质性变化。这些结果揭示了依赖于持续时间的机制，为氮素管理提供了一个新的框架，通过持续时间优化的施用策略，可以同时维持农业生产力和减少环境影响。

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引用次数: 0

Geospatial and geostatistical analysis of land fragmentation and parcel shape indicators for sustainable farm structure in land consolidation 土地整理中土地破碎化的地理空间和地理统计分析以及可持续农业结构的地块形状指标

IF 8.4

Farming System

Pub Date : 2026-01-01 Epub Date: 2025-09-09 DOI: 10.1016/j.farsys.2025.100173

Fırat Arslan , Hasan Değirmenci

Land consolidation (LC) is one of the key implementations to improve farm structure by enhancing parcel shape and reducing land fragmentation. Many researchers have developed indicators to measure parcel shape deformation and land fragmentation levels; however, these indicators often lack consistency for assessing land consolidation projects. In this study, we demonstrate that our newly developed New Parcel Shape Index (NSI) and New Land Fragmentation Index (NLFI) are more effective for assessing land consolidation projects. Geospatial and geostatistical analyses were applied to calculate the new indicators using ArcGIS-ArcMAP, with Excel utilised for calculating and comparing other indicators. To test these analyses, the cadastral data and reports of the Türkiye Malatya Province Arguvan District Tatkınlık Village Land Consolidation project were used as material.

As a result, it was observed that parcels with NSI values approaching 1 were close to a rectangular shape, while those deviating from an NSI value of 1 exhibited deformation. Other shape indices were found to perform poorly in parcel shape analysis. In measuring the level of land fragmentation, farms with small NLFI values were observed to be less fragmented than those with large NLFI values. Other land fragmentation indexes showed poor performance compared to NLFI. As a result, NSI is recommended for shape analysis, and NLFI is recommended for assessing land fragmentation. These indices can be utilised in before and after LC evaluations or in determining priority LC areas.

土地整理是改善农业结构、增强土地形态、减少土地细碎化的重要手段之一。许多研究人员开发了测量地块形状变形和土地破碎化程度的指标；然而，这些指标在评估土地整理项目时往往缺乏一致性。研究结果表明，新开发的“新地块形状指数”（NSI）和“新土地破碎化指数”（NLFI）对土地整理项目的评价更为有效。利用ArcGIS-ArcMAP进行地理空间和地理统计分析，计算新指标，利用Excel计算和比较其他指标。为了验证这些分析，使用了拉马提亚省rkiye Malatya省Arguvan区Tatkınlık村庄土地整理项目的地籍数据和报告作为材料。结果表明，NSI值接近1的地块接近矩形形状，而偏离NSI值为1的地块则呈现变形。其他形状指标在包裹形状分析中表现不佳。在测量土地破碎化程度时，观察到具有小NLFI值的农场比具有大NLFI值的农场碎片化程度更低。与NLFI相比，其他土地破碎化指数表现不佳。因此，NSI被推荐用于形状分析，而NLFI被推荐用于评估土地破碎化。这些指标可用于LC评估前后或确定优先LC领域。

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引用次数: 0