Farming System最新文献

{"title":"Typology-based evaluation of Nutrient Expert® for sustainable maize intensification in smallholder farms of eastern India","authors":"Rupak Goswami ,&nbsp;Sudarshan Dutta ,&nbsp;Hirak Banerjee ,&nbsp;Somsubhra Chakraborty ,&nbsp;Krishnendu Ray ,&nbsp;Kaushik Majumdar ,&nbsp;Jagadish Timsina","doi":"10.1016/j.farsys.2025.100193","DOIUrl":"10.1016/j.farsys.2025.100193","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100193"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Straw return facilitates the availability of soil nitrogen by altering the metabolic distribution and nitrogen cycling processes","authors":"Yu Gao ,&nbsp;Lu Wang ,&nbsp;Mingyue Li ,&nbsp;Yunpeng Qiu ,&nbsp;Qiulai Song ,&nbsp;Tianjiao Ji ,&nbsp;Zhenping Gong ,&nbsp;Chunmei Ma ,&nbsp;Chao Yan","doi":"10.1016/j.farsys.2025.100192","DOIUrl":"10.1016/j.farsys.2025.100192","url":null,"abstract":"<div><div>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 (<em>glsA</em> and <em>ureC</em>), N fixation (<em>Bradyrhizobium</em>, <em>Altererythrobacter</em>), dissimilatory nitrate reduction to ammonium (DNRA, <em>Sorangium</em>, <em>napC</em>, and <em>nirB</em>), and assimilatory nitrate reduction to ammonium (ANRA, <em>nasA</em>). However, despite a reduction in the relative abundance of nitrification microbes and functional genes (e.g., <em>Nitrososphaerag</em>, <em>Nitrospira</em>, <em>Sphingomonas</em>, <em>amoAB</em>, <em>nxrA</em>), 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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100192"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term green manuring reduces net greenhouse gas emissions in upland cropping systems in China","authors":"Penghui Li ,&nbsp;Hao Liang ,&nbsp;Qiu Zhao ,&nbsp;Jiudong Zhang ,&nbsp;Libo Fu ,&nbsp;Dabin Zhang ,&nbsp;Mei Han ,&nbsp;Rui Zhang ,&nbsp;Na Zhao ,&nbsp;Weidong Cao ,&nbsp;Feng Zhou","doi":"10.1016/j.farsys.2025.100191","DOIUrl":"10.1016/j.farsys.2025.100191","url":null,"abstract":"<div><div>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 % (<em>p</em> &lt; 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 (<em>p</em> &lt; 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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100191"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From soil carbon towards system sustainability: Integrating SOC modelling and life cycle assessment to evaluate environmental trade-offs in carbon farming","authors":"Stefano Spotorno ,&nbsp;Anne Gobin ,&nbsp;Diego Armando Arellano Vazquez ,&nbsp;Erica Gagliano ,&nbsp;Adriana Del Borghi ,&nbsp;Michela Gallo","doi":"10.1016/j.farsys.2025.100195","DOIUrl":"10.1016/j.farsys.2025.100195","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100195"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil moisture monitoring technologies in smart agriculture: A comprehensive review","authors":"R. Sreeram ,&nbsp;S. Adithya Krishna ,&nbsp;Aiswarya S. Kumar ,&nbsp;S. Remya ,&nbsp;Yong Yun Cho","doi":"10.1016/j.farsys.2025.100189","DOIUrl":"10.1016/j.farsys.2025.100189","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100189"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating regenerative and climate-smart agriculture for resilient farming systems","authors":"Yuantong Jia ,&nbsp;Ram C. Dalal ,&nbsp;Tong Li ,&nbsp;Yash P. Dang","doi":"10.1016/j.farsys.2026.100216","DOIUrl":"10.1016/j.farsys.2026.100216","url":null,"abstract":"","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100216"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147600266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Roots and the rhizosphere: a perspective on the hidden engine of regenerative, antifragile, and digitally enabled agriculture","authors":"Stefano Cesco ,&nbsp;Monica Yorlady Alzate Zuluaga ,&nbsp;Luciano Cavani ,&nbsp;Luigimaria Borruso ,&nbsp;Vito Armando Laudicina ,&nbsp;Fabrizio Mazzetto ,&nbsp;Tanja Mimmo ,&nbsp;Youry Pii ,&nbsp;Roberto Terzano ,&nbsp;Stefania Astolfi","doi":"10.1016/j.farsys.2026.100199","DOIUrl":"10.1016/j.farsys.2026.100199","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100199"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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","authors":"Shiqi Yang ,&nbsp;Liming Chen ,&nbsp;Xueming Tan ,&nbsp;Xiaohua Pan ,&nbsp;Yanhua Zeng","doi":"10.1016/j.farsys.2025.100194","DOIUrl":"10.1016/j.farsys.2025.100194","url":null,"abstract":"<div><div>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 <em>Actinobacteria</em>. Moreover, the significant enrichment of <em>Cyanobacteria</em> under SR at all stages of the late rice season was associated with an increase in SOC content. These results highlight the importance of <em>Actinobacteria</em> and <em>Cyanobacteria</em> 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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100194"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Metabolite-driven fungal recruitment in rhizosphere explains superiority of organic fertilizer in enhancing the soil fertility of wheat” [Farming System 4 (2026) 100181]","authors":"Shancong Wang ,&nbsp;Xinru Hu ,&nbsp;Reda M.M. Ahmed ,&nbsp;Guihong Yin ,&nbsp;Xiao Jun A. Liu ,&nbsp;Haotian Wang ,&nbsp;Jiameng Guo ,&nbsp;Peng Zhao ,&nbsp;Chang Li ,&nbsp;Qinghua Yang ,&nbsp;Lei Gao ,&nbsp;Ruixin Shao","doi":"10.1016/j.farsys.2026.100221","DOIUrl":"10.1016/j.farsys.2026.100221","url":null,"abstract":"","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100221"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147600267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of inorganic and organic fertilization on soil organic carbon and crop production: a meta-analysis","authors":"Zhiyuan Bai ,&nbsp;Jiajie Xu ,&nbsp;Xiaoyu Shi ,&nbsp;Matthew Tom Harrison ,&nbsp;Jørgen Eivind Olesen ,&nbsp;Robert M. Rees ,&nbsp;Cairistiona F.E. Topp ,&nbsp;Xinya Wen ,&nbsp;Zhenwei Song ,&nbsp;Xiaogang Yin ,&nbsp;Haotian Chen","doi":"10.1016/j.farsys.2026.100211","DOIUrl":"10.1016/j.farsys.2026.100211","url":null,"abstract":"<div><div>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 (&gt;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 &gt; COF &gt; 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.</div></div>","PeriodicalId":100522,"journal":{"name":"Farming System","volume":"4 2","pages":"Article 100211"},"PeriodicalIF":8.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}