[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-970":3,"related-970":59},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":33,"secondary_topics":39,"classification":40,"search_phrases":53,"slug":56,"view_count":57,"doi":8,"paper":8,"created_at":58},970,"数字化与可持续农业：基于PRISMA的系统文献综述 涵盖62项2015-2026年实证研究","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807","原文标题: Digitalisation and Sustainable Agriculture: A PRISMA-Based Systematic Literature Review。作者: Zhanna Smagulova、Urpash Shalbolova、Aigul Mukhanova、Gulshat Duzelbayeva(哈萨克斯坦Korkyt Ata Kyzylorda大学、L.N. Gumilyov欧亚国立大学、纳尔霍兹大学)。本研究基于PRISMA 2020指南对2015-2026年间发表的实证证据进行批判性综合分析，考察数字化对可持续农业发展的影响。在Scopus和Web of Science数据库中识别并分析62项实证研究，采用演绎与归纳相结合的主题分析方法，围绕「三重底线」(经济、环境、社会)框架展开。研究发现2022年后学术关注度显著上升，研究高度集中在亚洲(特别是中国，占42%)、欧洲(22.58%)和非洲(17.7%)；现有研究主要凸显数字化在生产力提升、效率改善、收入增长与资源优化配置、排放减少方面的积极影响，但也记录了劳动力替代、不平等加剧、数字工资不透明等不均衡、情境依赖的社会维度负面结果；整合性分析极其匮乏——仅不到5%的研究同时考察经济、环境和社会三个维度。本综述识别出数字化对可持续农业复杂、不均衡且情境依赖影响的四个未来研究优先方向。",null,"## 1. Introduction\n\nAgriculture occupies a structurally irreplaceable position in the global economy. It contributes approximately 24% of global gross domestic product, employs around 1.3 billion people (roughly 16% of the world’s workforce), and underpins food security across approximately 1.2 to 1.5 billion hectares of cultivated land [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B1-sustainability-18-07807)]. Yet the sector faces mounting pressure on multiple fronts: a growing global population, rising per capita food demand, accelerating climate change, and persistent rural poverty [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B2-sustainability-18-07807)]. These intersecting challenges have renewed the urgency of a question posed by the International Assessment of Agriculture, Science and Technology for Development (IAASTD): how can hunger and poverty be alleviated, rural livelihoods enhanced, and equitable, environmentally, socially, and economically sustainable development advanced through the generation and application of agricultural knowledge and technology [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B3-sustainability-18-07807)]?\n\nOver the past decade, one of the most prominent responses to this challenge has been the rapid digitalisation of the agricultural sector. Digital technologies, including information and communication technologies (ICTs), precision agriculture tools, artificial intelligence, remote sensing, and digital platforms, are increasingly regarded as instruments of agricultural transformation. Existing research identifies a convergence of drivers: economic pressures that reward efficiency gains, environmental imperatives that demand more precise use of resources, and social objectives that require the inclusion of smallholder farmers and rural communities in the benefits of technological change [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B4-sustainability-18-07807)]. Studies from diverse national contexts reflect these dynamics: they document productivity gains in the Chinese agricultural sector [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B5-sustainability-18-07807),[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B6-sustainability-18-07807)], report increased adoption of modern practices among Saudi Arabian farmers following access to digital information [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B7-sustainability-18-07807)], and link digital agriculture to reductions in agricultural carbon emissions [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B8-sustainability-18-07807)]. Finally, the literature highlights that the transformative potential of digital tools depends critically on inclusive, co-created knowledge transfer among farmers, consultants, and other stakeholders [[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B9-sustainability-18-07807)]. Despite this growing body of work, the literature remains fragmented. Most studies focus on a single technology, country, or dimension of sustainability, typically the economic dimension. Integrative analyses that assess the impact of digitalisation across all three dimensions of sustainable development remain scarce, and potential trade-offs between dimensions are insufficiently explored [[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B10-sustainability-18-07807)]. The present study addresses this gap by analysing the impact of digitalisation on the sustainable development of agriculture through a systematic synthesis of empirical evidence and by identifying directions for future research.\n\nTo achieve this aim, three objectives were set: to conduct a PRISMA-compliant systematic review of empirical literature on digitalisation and sustainable agriculture; to systematically identify and compare the positive and negative effects of digitalisation on the economic, environmental, and social dimensions of agricultural sustainability; and to identify research gaps and priority directions for further enquiry. The study is guided by two research questions: (1) Which geographical regions have been the focus of research on digitalisation and agricultural sustainability, and how has the volume of related publications changed from 2015 to 2026? (2) Do all studies report positive sustainability outcomes associated with digitalisation, or have adverse effects also been documented?\n\n### Theoretical Framework\n\nThe analytical structure of this review is grounded in the concept of sustainable development, as defined by the World Commission on Environment and Development (the Brundtland Commission), which characterised sustainability as development that “meets the needs of the present without compromising the ability of future generations to meet their own needs” [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B11-sustainability-18-07807)]. This foundational definition has since been operationalised through the triple-bottom-line framework, which recognises three interdependent dimensions of sustainability: economic, environmental, and social [[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B12-sustainability-18-07807)]. The framework is now embedded in the United Nations’ 2030 Agenda and its 17 Sustainable Development Goals (SDGs) [[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B13-sustainability-18-07807)]. Several of these, including SDG 2 (Zero Hunger), SDG 8 (Decent Work and Economic Growth), SDG 13 (Climate Action), and SDG 15 (Life on Land), are directly relevant to agriculture.\n\nIn the agricultural context, these three dimensions can be defined as follows. Economic sustainability is the capacity of agricultural systems to generate productive output, maintain profitability, and support rural livelihoods over the long term, as reflected in indicators such as total factor productivity, crop yields, income, and market participation. Environmental sustainability is the capacity to preserve natural resources and ecological functions, particularly through reduced carbon emissions, efficient use of land and water, and improvements in biodiversity and soil health. Social sustainability concerns the conditions under which agricultural labour is performed, including the distribution of income gains, equitable access to technology, the quality of working conditions, and the protection of rural communities from displacement or marginalisation.\n\nThis three-dimensional framework directly informs the review’s organisational structure. The synthesis of empirical findings in [Section 3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#sec3-sustainability-18-07807) is organised around these three dimensions, enabling a systematic examination of whether digitalisation contributes to, detracts from, or produces uneven outcomes across economic, environmental, and social sustainability. Critically, the framework also highlights potential trade-offs between dimensions, for example, when gains in economic productivity come at the cost of labour displacement, or when environmental improvements require capital investments that disadvantage smallholders. Recognising these trade-offs is a central objective of this review and a distinctive contribution to the existing literature.\n\n## 2. Materials and Methods\n\n### 2.1. Overview and Design\n\nThis study employs a systematic literature review in line with the PRISMA 2020 guidelines [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B14-sustainability-18-07807)], and the checklist could be found in the [Supplementary Material](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#app1-sustainability-18-07807). The PRISMA framework was selected for its transparent, reproducible protocol for identifying, screening, and synthesising empirical evidence, thereby minimising selection bias and enhancing the reliability of conclusions. The review adopts a combined deductive–inductive analytical approach: deductive methods were used to map the geographical and temporal distribution of research (RQ1), while inductive thematic analysis was applied to synthesise substantive findings across sustainability dimensions (RQ2). Data analysis drew on both quantitative methods, aggregating numerical indicators such as yield changes and productivity growth, and qualitative thematic coding, in which the 62 included studies were systematically categorised according to the economic, environmental, and social dimensions of the theoretical framework described in the “Theoretical Framework” section. A formal meta-analysis was not conducted because preliminary analysis revealed substantial heterogeneity across the included studies in outcome measures, research designs, analytical methods, and reported effect estimates. Consequently, calculating comparable pooled effect sizes and applying statistical methods for quantitative synthesis, including a funnel plot and Egger’s test to assess publication bias, were not methodologically justified.\n\n### 2.2. Data Sources and Search Strategy\n\nA systematic search was conducted in two stages: the first stage was conducted on 29 January 2025 using a single electronic database; Scopus and Web of Science (WoS) was incorporated only in the second stage, the 2026 update (see [Section 2.4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#sec2dot4-sustainability-18-07807)).\n\nScopus was selected as the primary database for its extensive multidisciplinary coverage and strong performance in systematic search retrieval. WoS was included as a complementary source to broaden disciplinary coverage and reduce the risk of database-specific indexing gaps, consistent with best practice in systematic reviewing [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B14-sustainability-18-07807)].\n\nThe search string actually executed in Scopus (Article title, Abstract, Keywords field) was the free-text phrase “digitalisation of agriculture”, which Scopus parsed as digitalisation AND of AND agriculture. The term “precision agriculture” was not used as a separate search term, as the review aimed to examine the broader phenomenon of agricultural digitalisation rather than a single technological approach. Precision agriculture was therefore treated as one form of agricultural digitalisation within the review’s broader conceptual scope. It is important to note that studies focused on precision agriculture and related technologies were identified through the search strategy and are represented among the 62 studies included in the final sample.\n\nThe following filters were then applied sequentially, with the resulting record counts: publication years 2015–2025 (n = 1353); subject areas Computer Science, Environmental Science, Agricultural and Biological Sciences, Social Sciences, Business, Management and Accounting, Economics, Econometrics and Finance, Decision Sciences, and Multidisciplinary (n = 1233); document language limited to English (n = 1186); source\u002Fdocument type limited to Journal and Conference Proceeding (n = 927); the Environmental Science subject category was then excluded to avoid duplication with other categories (n = 717).\n\n### 2.3. Eligibility Criteria\n\nInclusion and exclusion criteria were developed collaboratively by all four authors (Zh.S., U.S., A.M., G.D.) before screening and are presented in [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#table_body_display_sustainability-18-07807-t001). The criteria were designed to include only empirical studies that directly examined the impact of digitalisation on agricultural sustainability outcomes, while excluding review articles, theoretical or conceptual papers, and studies focused on non-agricultural sectors.\n\n**Table 1.** Inclusion and exclusion criteria applied in the systematic literature review.\n\n### 2.4. Study Selection\n\nAfter database searches and deduplication, 739 records were retained for title and abstract screening. Screening was conducted independently by three authors (Zh.S., A.M., G.D.) using the eligibility criteria outlined in [Section 2.3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#sec2dot3-sustainability-18-07807). Discrepancies between screeners were recorded: Zh.S. identified 42 eligible articles, A.M. 45, and G.D. 42. All discrepancies were resolved through discussion and consensus arbitration by the fourth author (U.S.). A total of 40 studies were included in the final synthesis. The full selection process is documented in the PRISMA 2020 flow diagram ([Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#fig_body_display_sustainability-18-07807-f001)).\n\n**Figure 1.** PRISMA flowchart illustrating the study selection process for the first search round (Round 1, Scopus, January 2025). See [Table 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#table_body_display_sustainability-18-07807-t002) for the second search round (Round 2, 2026 update). Source: (Page et al., 2021) [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B14-sustainability-18-07807)].\n\n**Table 2.** PRISMA-style flow for the second search round (Round 2, 2026 update), combining Scopus and Web of Science.\n\n**Figure 1.** PRISMA flowchart illustrating the study selection process for the first search round (Round 1, Scopus, January 2025). See [Table 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#table_body_display_sustainability-18-07807-t002) for the second search round (Round 2, 2026 update). Source: (Page et al., 2021) [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B14-sustainability-18-07807)].\n\n[![Image 1: Sustainability 18 07807 g001](https:\u002F\u002Fwww.mdpi.com\u002Fsustainability\u002Fsustainability-18-07807\u002Farticle_deploy\u002Fhtml\u002Fimages\u002Fsustainability-18-07807-g001.png)](https:\u002F\u002Fwww.mdpi.com\u002Fsustainability\u002Fsustainability-18-07807\u002Farticle_deploy\u002Fhtml\u002Fimages\u002Fsustainability-18-07807-g001.png)\n\n#### Search Update (Round 2)\n\nOn 5 February 2026, the Scopus search was re-run, retrieving 278 additional records published in 2026. On 17 February 2026, Web of Science was searched for the first time, covering 2015–2026 and retrieving 259 records. The authors judged that a single-database search was insufficient for a comprehensive review and therefore incorporated WoS at this stage. The combined total of 537 records (278 Scopus + 259 WoS) was screened for duplicates; 25 duplicate records were identified and removed, leaving 512 distinct records (278 Scopus + 234 WoS) for screening against the eligibility criteria in [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#table_body_display_sustainability-18-07807-t001). Applying these criteria to the 512 records identified 22 additional eligible studies, which were added to the 40 studies retained from the first search round, yielding a final total of 62 studies included in the review.\n\n### 2.5. Data Extraction and Quality Assessment\n\nData from the 62 included studies were extracted by three authors (Zh.S., A.M., G.D.) using a standardised extraction template. For each study, the following information was recorded: author(s) and year; country\u002Fregion of study; research design and data collection method; digital technology or intervention examined; sustainability dimension(s) addressed; key quantitative or qualitative findings; and direction of effect (positive, negative, or mixed). The full extraction is presented in the [Appendix A](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#app2-sustainability-18-07807).\n\nNo formal quality appraisal tool (such as the Mixed Methods Appraisal Tool, MMAT [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B15-sustainability-18-07807)], or the Joanna Briggs Institute checklists) [[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B16-sustainability-18-07807)] was used in this review, given the heterogeneity of study designs and methodological approaches across the 62 included studies. This is acknowledged as a limitation of the review (see [Section 4.5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#sec4dot5-sustainability-18-07807)).\n\n### 2.6. Synthesis Approach\n\nGiven the heterogeneity of study designs, geographic contexts, and outcome measures across the included studies, a narrative synthesis was adopted rather than a meta-analysis. Synthesis proceeded in two stages. First, a descriptive analysis mapped the distribution of studies by geographical region, publication year, and sustainability dimension addressed (addressing RQ1). Second, a deductive–inductive thematic analysis synthesised the substantive findings within each sustainability dimension (addressing RQ2). Initial codes were derived deductively from the three-dimensional theoretical framework (economic, environmental, and social sustainability. Sub-themes were then developed inductively from patterns emerging within each dimension. Coding was conducted by three authors (Zh.S., A.M., G.D.) and reviewed for consistency by the fourth (U.S.).\n\n## 3. Results\n\nThis section is organised in accordance with the study’s four guiding research questions. The first question provides contextual information on the digitalisation of agriculture, whereas the subsequent three questions focus on a detailed analysis of how digitalisation affects the sustainable development of the agricultural sector.\n\n### 3.1. RQ1. Which Geographical Regions Have Been the Focus of Research on the Impact of Digital Technologies on Agricultural Sustainability, and How Has the Volume of Related Publications Evolved in Recent Years?\n\nAll studies included in this review were conducted in countries across three continents, Europe, Asia and Africa. However, the geographic distribution of studies was uneven across these regions (see [Figure 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#fig_body_display_sustainability-18-07807-f002)). Among the 37 studies conducted in Asia (59.7% of the studies), the overwhelming majority, 26 studies or 42% of the total sample, were conducted in China, which is not surprising. China is one of the world’s largest producers of agricultural products and has been striving not only to expand production volumes but also to improve product quality. The Chinese government has strengthened agricultural land protection and implemented various incentives to promote agricultural production [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B17-sustainability-18-07807)]. In addition, the country continues to liberalise trade in agricultural products [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B18-sustainability-18-07807)]. As a result of these combined factors, China has effectively integrated digital technologies into both the production and trade sectors of its agriculture. Following China in the ranking are India (4.84%) and Kazakhstan (3.2%), both of which are major producers of staple crops such as rice and wheat. Other contributing countries include Indonesia (1.6%), Uzbekistan (1.6%), Vietnam (3.2%), Azerbaijan (1.6%) and members of the South Asian Association for Regional Cooperation (SAARC), including Bangladesh, Nepal, Pakistan, Bhutan, the Maldives, and Afghanistan (1.6%).\n\n**Figure 2.** Geographical distribution of studies. Source: Author’s elaboration using Bing Maps.\n\nEurope accounts for 22.58% of the studies (14 articles), making it the second most represented continent. Germany stands out as the most researched country in Europe (6.45%). As one of the leading agricultural producers in the European Union [[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B19-sustainability-18-07807)], German researchers, citing previous studies, argue that nearly 50% of agricultural professional activities in the country could be replaced by digital technologies [[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F15\u002F7807#B20-sustainability-18-07807)]. These trends have contributed to Germany’s heightened interest in the digitalisation of its agricultural sector.\n\nAfrica ranks third in terms of the number of studies, accounting for 17.7% of the total. In Africa, the greatest interest in the impact of digitalisation on agriculture was shown by researchers in Ghana (6.45%) and Sub-Saharan African countries (4.84%). Additional studies were carried out in Tanzania (1.6%), Nigeria (1.6%), Somali (1.6%) and other African nations (1.6%). The focus on digital agriculture in Africa is lar","Sustainability 2026, 18(15), 7807","2026-08-02T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},20,22,12,4,1,"系统综述涵盖62项研究，全面分析数字化对农业可持续性的多维影响，具有较高学术价值和信息增量，但时效性稍差。",[24],{"name":10,"url":6},[26,27,28,29,30,31,32],"数字化","Sustainability","可持续农业","哈萨克斯坦","PRISMA","三重底线","文献综述",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},"H8","sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture","H",[],{"status":41,"locked":14,"version":42,"method":43,"evidence":44},"classified","2026-10-22.2","rules",{"candidates":45,"agricultural_evidence":48},[46],{"code":34,"score":47,"supported":48,"title":49,"abstract":50,"tags":52},15,true,[28],[28,51],"sustainable agriculture",[28],[54,55],"可持续农业 哈萨克斯坦 三重底线 文献综述","可持续农业 哈萨克斯坦","可持续农业哈萨克斯坦三重底线文献综述-970",3,"2026-08-26T00:09:32.321765Z",{"total":60,"page":21,"page_size":60,"items":61},6,[62,127,192,291,368,471],{"id":63,"title":64,"url":65,"summary":66,"summary_zh":67,"content":8,"source_name":68,"source_url":65,"published_at":69,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":70,"score_detail":71,"sources":77,"tags":79,"primary_topic":84,"secondary_topics":85,"classification":86,"search_phrases":98,"slug":101,"view_count":21,"doi":102,"paper":103,"created_at":126},4053,"The parent effect and patriarchal gatekeeping: familial dynamics shaping youth sustainable agriculture entrepreneurship pathways in Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1888230","Inroduction Youth sustainable agricultural entrepreneurship (SAE) in Sub-Saharan Africa is weakened not only by structural constraints but by familial dynamics that have received limited analytical attention. This study examines youth perceptions of how parental attitudes, resource gatekeeping, and patriarchal norms shape youth aspirations and entrepreneurial pathways in Hwedza District, Zimbabwe. Its central argument is that the parent effect - conceptualised as the ways youth perceive parental attitudes, resource control, and gatekeeping as shaping their agricultural entrepreneurship - constitutes a primary household-level constraint on youth SAE. Patriarchal gatekeeping is analysed as the gendered dimension of this parent effect, while the psychology of provisionality and the success tax are presented as supporting constructs specifying the mechanisms through which it operates. Methods The research employed an interpretivist case-study framework, relying on in-depth interviews and focus-group discussions with 32 youth participants and 15 key stakeholders across four wards. Data were analysed using Reflexive Thematic Analysis, guided by Positive Youth Development (PYD) Theory and Hart’s Ladder of Participation, adapted to the household domain as the analytical lens for examining how youth report these dynamics. Results Youth accounts indicate that parents are perceived as gatekeepers in resource allocations, and youth describe anticipatory discouragement from farming. These practices were reported by youth participants as confining them to the lower rungs of household participation, which they associated with erosion of competence, confidence, and connection. Discussion Based on youth accounts, the study suggests that youth agripreneurship interventions cannot treat the household as a passive delivery unit. The research contributes by centring the family as a primary arena of entrepreneurial contestation and by demonstrating the household as a participatory ladder where developmental outcomes are perceived by youth to be conditioned by parental gatekeeping. Implications point to household-centred interventions, formalised family land stewardship agreements, and youth-targeted financial instruments that bypass parental control.","引言 撒哈拉以南非洲的青年可持续农业创业（SAE）不仅受到结构性制约的削弱，还受到家庭动态的影响，而后者所获得的分析关注十分有限。本研究考察了津巴布韦Hwedza地区青年对父母态度、资源守门和父权制规范如何塑造其抱负与创业路径的感知。其核心论点是，父母效应——即青年所感知的父母态度、资源控制和守门行为对其农业创业的塑造方式——构成了家庭层面对青年可持续农业创业的首要制约。父权制守门被分析为这一父母效应的性别维度，而临时性心理与成功税则作为支撑性构念，用以具体说明其运作机制。方法 本研究采用解释主义案例研究框架，对四个选区的32名青年参与者和15名关键利益相关者进行了深度访谈和焦点小组讨论。数据分析采用反思性主题分析法，以积极青年发展（PYD）理论和哈特参与阶梯为指导，并将后者调适至家庭领域，作为分析透镜，用以考察青年如何报告这些动态。结果 青年的叙述表明，父母被视为资源分配中的守门人，青年描述了对务农的预期性劝阻。青年参与者报告称，这些做法将他们限制在家庭参与的低层级，他们将其与能力、信心和联结感的侵蚀联系在一起。讨论 基于青年的叙述，本研究表明，青年农业创业干预不能将家庭视为被动的执行单元。本研究的贡献在于将家庭置于创业争夺的首要场域，并揭示家庭作为一个参与阶梯，青年感知到其发展结果受到父母守门行为的制约。其启示指向以家庭为中心的干预措施、正式化的家庭土地管理协议，以及绕过父母控制的面向青年的金融工具。","Frontiers in Sustainable Food Systems","2026-10-02T00:00:00Z",67,{"impact":72,"substance":17,"depth":73,"authority":74,"freshness":75,"relevant":21,"comment":76},8,17,13,9,"以津巴布韦案例揭示家庭父权与资源把关对青年农业创业的抑制机制，方法扎实、结论有新意，但属区域微观研究，公共影响有限。",[78],{"name":68,"url":65},[28,80,81,82,83],"津巴布韦","农户生计","青年农业创业","性别规范",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[],{"status":41,"locked":14,"version":42,"method":43,"evidence":87},{"candidates":88,"agricultural_evidence":48},[89,93],{"code":34,"score":19,"supported":48,"title":90,"abstract":91,"tags":92},[51],[28],[28],{"code":94,"score":21,"supported":14,"title":95,"abstract":96,"tags":97},"G6",[],[],[81],[99,100],"青年农业创业 可持续农业 农户生计 性别规范","青年农业创业 可持续农业","青年农业创业可持续农业农户生计性别规范-4053","10.3389\u002Ffsufs.2026.1888230",{"doi":102,"openalex_id":104,"authors":105,"venue":68,"cited_by_count":117,"oa_url":118,"card":119,"direction":123,"ingested_from":125},"W7216465950",[106,109,111,114],{"name":107,"orcid":108},"Tonderai James Nyagwaya","https:\u002F\u002Forcid.org\u002F0009-0004-2457-8023",{"name":110,"orcid":8},"Matthew Marembo",{"name":112,"orcid":113},"Peter Mukarumbwa","https:\u002F\u002Forcid.org\u002F0000-0002-2387-9236",{"name":115,"orcid":116},"Precious Kuziva Hove","https:\u002F\u002Forcid.org\u002F0000-0001-5914-7531",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1888230\u002Fpdf",{"tldr":120,"method":121,"finding":122,"direction":123,"opportunity":124},"研究津巴布韦青年视角下父母态度与父权把关如何制约其可持续农业创业路径。","解释主义案例研究，32名青年与15名利益相关者深度访谈及焦点小组，反思性主题分析","父母被视为资源把关者，青年预期性受挫，被限制在家庭参与低层级，削弱能力与信心。","数字乡村与农业信息化","可探索家庭层面干预与青年专属金融工具如何绕过父母控制，促进农业创业参与。","openalex","2026-10-03T23:30:08.285408Z",{"id":128,"title":129,"url":130,"summary":131,"summary_zh":132,"content":8,"source_name":133,"source_url":130,"published_at":134,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":135,"score_detail":136,"sources":139,"tags":141,"primary_topic":146,"secondary_topics":147,"classification":148,"search_phrases":168,"slug":171,"view_count":57,"doi":172,"paper":173,"created_at":191},3283,"INNOVATIVE APPROACHES TO SUSTAINABLE AGRICULTURE: STRATEGY FOR EMPOWERING WOMEN FARMERS IN RESOURCE LIMITED RURAL COMMUNITIES IN SLEMAN, INDONESIA","https:\u002F\u002Fdoi.org\u002F10.20961\u002Fsepa.v23i2.113220","Sustainable agriculture has become a critical framework for addressing food security challenges, particularly in resource-limited rural communities where women farmer groups play a pivotal yet underexplored role in sustaining local food systems. This research aims to examine the role of the Bukle Women Farmer Group (WFG Bukle) in advancing sustainable agriculture through strategic innovations despite resource limitations. Conducted in Klegung Hamlet, Donokerto Village, Sleman Regency, this study adopts a mixed-method case study approach involving eleven purposively selected key informants: one group leader, one deputy leader, seven active members of WFG Bukle, and two non-member community participants. Data were collected through surveys, semi-structured interviews, field observations, and Focus Group Discussions (FGDs) to evaluate farming practices and land use. The findings place WFG Bukle in Quadrant IV of the Internal-External (IE) matrix, indicating strong internal potential (IFE = 3.04) alongside moderate external challenges (EFE = 2.51). Through SWOT-based strategies and a Quantitative Strategic Planning Matrix (QSPM), three priority strategies emerged: empowering women in sustainable farm management (TAS = 5.49), strengthening collaboration with academic and governmental institutions (TAS = 5.09), and improving financial access for farmer groups (TAS = 5.00). The study highlights the importance of eco-friendly farming, technological access, and market linkages in enhancing food security and economic resilience. Strengthening women's roles in decision-making and financial management is crucial for sustainable agriculture, underscoring the need for gender-inclusive policies and cross-sector collaboration to support long-term rural development.","可持续农业已成为应对粮食安全挑战的关键框架，在资源有限的农村社区尤为如此，在这些社区中，女性农民小组在维持地方粮食系统方面发挥着关键但尚未被充分探索的作用。本研究旨在考察布克勒女性农民小组（WFG Bukle）在资源有限的条件下通过战略创新推动可持续农业发展的作用。研究在斯莱曼县多诺克托村克莱贡哈姆雷特开展，采用混合方法案例研究，涉及十一名有目的选取的关键信息提供者：一名小组组长、一名副组长、七名WFG Bukle活跃成员以及两名非成员社区参与者。数据通过问卷调查、半结构化访谈、实地观察和焦点小组讨论（FGD）收集，以评估耕作实践和土地利用情况。研究结果表明，WFG Bukle位于内部-外部（IE）矩阵第四象限，表明其具有较强的内部潜力（IFE = 3.04），同时面临中等程度的外部挑战（EFE = 2.51）。通过基于SWOT的策略和定量战略规划矩阵（QSPM），研究得出三项优先策略：赋权女性参与可持续农场管理（TAS = 5.49）、加强与学术机构和政府机构的合作（TAS = 5.09）、改善农民小组的融资渠道（TAS = 5.00）。本研究强调了生态友好型耕作、技术获取和市场联结在增强粮食安全和经济韧性方面的重要性。强化女性在决策和财务管理中的作用对可持续农业至关重要，凸显了制定性别包容政策和开展跨部门合作以支持农村长期发展的必要性。","SEPA Jurnal Sosial Ekonomi Pertanian dan Agribisnis","2026-09-23T00:00:00Z",63,{"impact":72,"substance":137,"depth":47,"authority":19,"freshness":13,"relevant":21,"comment":138},18,"以印尼Sleman地区女性农户组织为案例，用IE矩阵、SWOT与QSPM提出可持续农业赋权策略，方法规范但属地方性小样本研究，公共影响有限。",[140],{"name":133,"url":130},[142,28,143,144,145],"粮食安全","农村发展","女性农户","SWOT分析",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[],{"status":41,"locked":14,"version":42,"method":43,"evidence":149},{"candidates":150,"agricultural_evidence":48},[151,155,162],{"code":34,"score":47,"supported":48,"title":152,"abstract":153,"tags":154},[51],[28,51],[28],{"code":156,"score":157,"supported":48,"title":158,"abstract":159,"tags":161},"A8",7,[],[142,160],"food security",[142],{"code":163,"score":20,"supported":48,"title":164,"abstract":165,"tags":167},"G",[],[166],"rural development",[143],[169,170],"Sleman 女性农户 可持续农业","印尼 妇女农户组织 粮食安全","Sleman女性农户可持续农业-3283","10.20961\u002Fsepa.v23i2.113220",{"doi":172,"openalex_id":174,"authors":175,"venue":133,"cited_by_count":117,"oa_url":130,"card":185,"direction":190,"ingested_from":125},"W7214033421",[176,179,181,183],{"name":177,"orcid":178},"Fransicus Arifin","https:\u002F\u002Forcid.org\u002F0000-0003-0998-1290",{"name":180,"orcid":8},"Latifa Nuraini",{"name":182,"orcid":8},"Eko Wahyono",{"name":184,"orcid":8},"Akame Cyril Njume",{"tldr":186,"method":187,"finding":188,"direction":123,"opportunity":189},"研究印尼Sleman农村妇女农民小组如何通过战略创新推动可持续农业。","混合方法案例研究，含访谈、观察、FGD及IE矩阵、SWOT、QSPM分析。","小组内部潜力强但外部挑战中等，优先策略为妇女赋权、机构合作与融资改善。","可探索数字工具与市场链接如何赋能资源受限地区妇女农民组织，弥补技术获取与性别包容政策研究空白。","农业人工智能与决策模型","2026-09-23T23:30:38.124265Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":197,"content":8,"source_name":27,"source_url":195,"published_at":198,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":199,"score_detail":200,"sources":202,"tags":204,"primary_topic":209,"secondary_topics":215,"classification":222,"search_phrases":264,"slug":267,"view_count":20,"doi":268,"paper":269,"created_at":290},2659,"Application of Remote Sensing and Machine Learning in Sustainable Agriculture","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18189472","Global agriculture is undergoing a period of profound transformation, driven by the need to increase food production in a context characterized by climate change, the degradation of natural resources and increasing pressure on agricultural ecosystems [...]","全球农业正经历一场深刻变革，其驱动力是在气候变化、自然资源退化以及农业生态系统压力日益增大的背景下提高粮食产量的需求。[...]","2026-09-16T00:00:00Z",77,{"impact":137,"substance":17,"depth":73,"authority":74,"freshness":75,"relevant":21,"comment":201},"发表于核心期刊的遥感与机器学习综述，方法视角新颖、时效性强，对智慧农业技术路线有参考价值，值得进入每日精选。",[203],{"name":27,"url":195},[205,206,207,28,208],"智慧农业","农业人工智能","机器学习","遥感",{"code":210,"slug":211,"name":212,"path":213,"parent_code":214},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[216,217],{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},{"code":218,"slug":219,"name":220,"path":221,"parent_code":214},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":41,"locked":14,"version":42,"method":43,"evidence":223},{"candidates":224,"agricultural_evidence":48},[225,230,234,239,246,253,259],{"code":210,"score":13,"supported":48,"title":226,"abstract":228,"tags":229},[227],"machine learning",[],[206,207],{"code":34,"score":75,"supported":48,"title":231,"abstract":232,"tags":233},[51],[],[28],{"code":218,"score":75,"supported":48,"title":235,"abstract":237,"tags":238},[236],"remote sensing",[],[208],{"code":240,"score":60,"supported":48,"title":241,"abstract":242,"tags":245},"H7",[],[243,244],"气候变化","climate change",[],{"code":247,"score":60,"supported":48,"title":248,"abstract":249,"tags":252},"J3",[],[250,251],"全球农业","global agriculture",[],{"code":254,"score":57,"supported":48,"title":255,"abstract":256,"tags":258},"H6",[],[257],"农业生态",[],{"code":260,"score":21,"supported":14,"title":261,"abstract":262,"tags":263},"I1",[],[],[205],[265,266],"农业人工智能 可持续农业 智慧农业 机器学习","农业人工智能 可持续农业","农业人工智能可持续农业智慧农业机器学习-2659","10.3390\u002Fsu18189472",{"doi":268,"openalex_id":270,"authors":271,"venue":27,"cited_by_count":117,"oa_url":195,"card":284,"direction":288,"ingested_from":125},"W7213301703",[272,275,278,281],{"name":273,"orcid":274},"Mihai Valentin Herbei","https:\u002F\u002Forcid.org\u002F0000-0002-3884-3658",{"name":276,"orcid":277},"Ana-Cornelia Badea","https:\u002F\u002Forcid.org\u002F0000-0003-4521-5403",{"name":279,"orcid":280},"Aleksandar Ristić","https:\u002F\u002Forcid.org\u002F0000-0003-0979-3345",{"name":282,"orcid":283},"Paul Sestraș","https:\u002F\u002Forcid.org\u002F0000-0002-8554-0924",{"tldr":285,"method":286,"finding":287,"direction":288,"opportunity":289},"综述遥感与机器学习在可持续农业中的应用现状与前景。","综述遥感数据与机器学习方法在农业中的应用。","遥感结合机器学习可提升农业监测与可持续管理能力。","农业遥感与作物表型","可探索多源遥感与可解释机器学习融合，用于小农户精准决策与碳核算。","2026-09-16T23:30:28.640661Z",{"id":292,"title":293,"url":294,"summary":295,"summary_zh":296,"content":8,"source_name":297,"source_url":294,"published_at":298,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":299,"score_detail":300,"sources":302,"tags":304,"primary_topic":309,"secondary_topics":310,"classification":311,"search_phrases":350,"slug":353,"view_count":21,"doi":354,"paper":355,"created_at":367},2146,"Carbon-Integrated Climate-Smart Finance for Sustainable Agriculture, Livelihoods & Nature-Based Solutions","https:\u002F\u002Fdoi.org\u002F10.22214\u002Fijraset.2026.84829","Climate-smart agriculture and sustainable rural livelihoods are central to strengthening climate resilience, food security, biodiversity conservation, and sustainable development. Despite substantial investments by governments, development agencies, banks, CSR programmes, and private investors, project appraisal largely relies on conventional indicators such as IRR, NPV, BCR, and ROI, while carbon benefits are typically assessed separately, limiting their integration into investment planning. The Climate Smart Financial Model (CSFM) developed by Srivastava (2026) integrates climate vulnerability, governance, land tenure, water availability, adaptive capacity, and agricultural productivity into financial sustainability assessment. This research proposes a Carbon-Integrated Climate Smart Financial Model (CI-CSFM) that incorporates expected carbon revenue as an endogenous investment variable. It uses methodology-specific ex-ante estimates of eligible\u002Fissuable tCO₂e, expected carbon price, and issuance probability, while treating verified or issued credits as subsequent realized revenue. The CI-CSFM is a financial integration framework, not a carbon quantification methodology. Carbon reductions\u002Fremovals are quantified using applicable approved methodologies and project-specific data, then incorporated into financial appraisal. The framework also integrates additionality, permanence, leakage, monitoring quality, and verification\u002Fissuance risk, and proposes an Integrated Climate Investment Sustainability Index (ICISI) for comparative investment prioritization.","气候智慧型农业与可持续农村生计对于增强气候韧性、粮食安全、生物多样性保护和可持续发展至关重要。尽管政府、发展机构、银行、企业社会责任项目以及私人投资者已投入大量资金，但项目评估在很大程度上仍依赖内部收益率（IRR）、净现值（NPV）、效益成本比（BCR）和投资回报率（ROI）等传统指标，而碳效益通常被单独评估，限制了其纳入投资规划。Srivastava（2026）开发的气候智慧型财务模型（CSFM）将气候脆弱性、治理、土地权属、水资源可得性、适应能力和农业生产力纳入财务可持续性评估。本研究提出碳整合气候智慧型财务模型（CI-CSFM），将预期碳收益作为内生投资变量纳入其中。该模型采用特定方法学下合格\u002F可签发tCO₂e的事前估算、预期碳价格和签发概率，同时将已核证或已签发的碳信用视为后续实现的收益。CI-CSFM是一个财务整合框架，而非碳量化方法学。碳减排\u002F清除量采用适用的获批方法学和项目特定数据进行量化，随后纳入财务评估。该框架还整合了额外性、永久性、泄漏、监测质量以及核证\u002F签发风险，并提出综合气候投资可持续性指数（ICISI），用于比较性投资优先排序。","International Journal for Research in Applied Science and Engineering Technology","2026-09-10T00:00:00Z",69,{"impact":19,"substance":17,"depth":73,"authority":19,"freshness":72,"relevant":21,"comment":301},"提出碳收益内生化的气候智慧型农业金融评估框架，方法有创新但属学术论文，对国内农业信息化实践影响有限。",[303],{"name":297,"url":294},[28,305,306,307,308],"气候智慧农业","农业金融","农业碳汇","碳交易",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},[],{"status":41,"locked":14,"version":42,"method":43,"evidence":312},{"candidates":313,"agricultural_evidence":48},[314,318,322,328,333,339,344],{"code":34,"score":75,"supported":48,"title":315,"abstract":316,"tags":317},[51],[],[28],{"code":156,"score":60,"supported":48,"title":319,"abstract":320,"tags":321},[],[142,160],[],{"code":254,"score":60,"supported":48,"title":323,"abstract":324,"tags":327},[],[325,326],"生物多样性","biodiversity",[],{"code":240,"score":20,"supported":48,"title":329,"abstract":330,"tags":332},[],[331],"climate resilience",[305],{"code":334,"score":57,"supported":48,"title":335,"abstract":336,"tags":338},"H3",[],[337],"水资源",[],{"code":260,"score":57,"supported":48,"title":340,"abstract":341,"tags":343},[],[342],"smart agriculture",[],{"code":345,"score":346,"supported":14,"title":347,"abstract":348,"tags":349},"H4",2,[],[],[307,308],[351,352],"气候智慧农业 可持续农业 农业碳汇 农业金融","气候智慧农业 可持续农业","气候智慧农业可持续农业农业碳汇农业金融-2146","10.22214\u002Fijraset.2026.84829",{"doi":354,"openalex_id":356,"authors":357,"venue":297,"cited_by_count":117,"oa_url":294,"card":360,"direction":366,"ingested_from":125},"W7212148295",[358],{"name":359,"orcid":8},"Deepak Srivastava",{"tldr":361,"method":362,"finding":363,"direction":364,"opportunity":365},"提出碳整合气候智慧金融模型，将碳收益作为内生投资变量纳入农业项目财务评估。","构建CI-CSFM框架，用事前碳减排量、碳价与签发概率估算碳收入，并设ICISI","碳收益可内生融入财务评估，提升气候智慧农业投资决策的整合性与可比性。","农业绿色发展与碳","可探索碳收益不确定性、签发风险与农业项目财务指标耦合的实证与工具化研究。","智慧农业 \u002F 农业物联网","2026-09-11T23:30:10.587397Z",{"id":369,"title":370,"url":371,"summary":372,"summary_zh":373,"content":8,"source_name":374,"source_url":371,"published_at":375,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":376,"score_detail":377,"sources":380,"tags":382,"primary_topic":386,"secondary_topics":391,"classification":398,"search_phrases":453,"slug":456,"view_count":57,"doi":457,"paper":458,"created_at":470},1305,"IoT-Based Soil Condition Monitoring System for Supporting Precision and Sustainable Agriculture in West Java","https:\u002F\u002Fdoi.org\u002F10.55981\u002Fjet.807","West Java Province is one of the largest horticultural producers in Indonesia. The horticulture subsector in West Java covers tens of thousands of hectares of farmland and contributes approximately 1.8% to the province’s total Gross Regional Domestic Product (GRDP). However, this sector faces serious challenges. Climate change has increased the frequency of droughts and floods, disrupting horticultural production. In addition, soil fertility has declined due to unsustainable farming practices; many agricultural lands in West Java contain less than 2% organic matter as a result of long-term chemical fertilizer use. These challenges have led to decreased productivity and threaten the sustainability of horticultural farming. Precision agriculture emerges as a solution to these issues. This concept leverages IoT technologies such as the ESP32 microcontroller with SPIFFS, soil sensors, and a web-based dashboard to monitor land conditions in real time and manage inputs more efficiently. The IoT-based soil monitoring system developed in this study was tested in a farmer’s yard in Pameungpeuk Subdistrict, Garut. The results demonstrated practical benefits, including improved irrigation efficiency (up to ~30% water savings) and reduced risk of crop losses through early detection of drought conditions. Moreover, the application of IoT in potato cultivation in West Java has been shown to double seed tuber yields from 15,000 to 30,000 tubers. These findings are consistent with regional policy directions, as reflected in the West Java Regional Medium-Term Development Plan (RPJMD) and the “Petani Milenial” (Millennial Farmers) program, which promote sustainable agricultural modernization through IoT-based technologies to enhance the productivity of young farmers.","西爪哇省是印度尼西亚最大的园艺生产地之一。该省的园艺分部门覆盖数万公顷农田，约占全省地区生产总值（GRDP）总额的1.8%。然而，该部门面临严峻挑战。气候变化增加了干旱和洪水的发生频率，扰乱了园艺生产。此外，由于不可持续的耕作方式，土壤肥力下降；长期使用化肥导致西爪哇许多农业用地的有机质含量低于2%。这些挑战导致生产力下降，并威胁到园艺农业的可持续性。精准农业应运而生，成为解决这些问题的方案。这一概念利用物联网（IoT）技术，如搭载SPIFFS的ESP32微控制器、土壤传感器和基于网页的仪表盘，实时监测土地状况并更高效地管理投入。本研究中开发的基于物联网的土壤监测系统在加鲁特县帕梅翁佩乌克分区的一位农民庭院中进行了测试。结果表明其具有实际效益，包括提高灌溉效率（节水约30%）以及通过早期检测干旱状况降低作物损失风险。此外，物联网在西爪哇马铃薯种植中的应用已被证明可使种薯产量翻倍，从每公顷15,000个增加到30,000个。这些发现与区域政策方向一致，正如西爪哇省中期发展规划（RPJMD）和“千禧农民”计划所反映的那样，这些政策通过基于物联网的技术促进可持续农业现代化，以提高年轻农民的生产力。","Jurnal Elektronika dan Telekomunikasi","2026-08-31T00:00:00Z",61,{"impact":47,"substance":137,"depth":378,"authority":13,"freshness":346,"relevant":21,"comment":379},16,"论文展示IoT土壤监测系统在西爪哇的应用，节水30%并提升马铃薯产量，对区域精准农业有参考价值，但时效性较低。",[381],{"name":374,"url":371},[205,383,384,28,385],"物联网","精准农业","土壤监测",{"code":387,"slug":388,"name":389,"path":390,"parent_code":214},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",[392,397],{"code":393,"slug":394,"name":395,"path":396,"parent_code":38},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},{"status":41,"locked":14,"version":42,"method":43,"evidence":399},{"candidates":400,"agricultural_evidence":48},[401,406,412,416,422,427,434,440,447],{"code":387,"score":47,"supported":48,"title":402,"abstract":404,"tags":405},[403],"IoT",[383,403],[383],{"code":393,"score":407,"supported":48,"title":408,"abstract":409,"tags":411},14,[394],[410,394],"土壤",[],{"code":34,"score":19,"supported":48,"title":413,"abstract":414,"tags":415},[51],[28],[28],{"code":240,"score":75,"supported":48,"title":417,"abstract":418,"tags":421},[],[243,419,244,420],"干旱","drought",[],{"code":260,"score":72,"supported":48,"title":423,"abstract":424,"tags":426},[],[384,425],"precision agriculture",[205,384],{"code":428,"score":60,"supported":48,"title":429,"abstract":430,"tags":433},"A5",[],[431,432],"马铃薯","potato",[],{"code":334,"score":60,"supported":48,"title":435,"abstract":436,"tags":439},[],[437,438],"灌溉","irrigation",[],{"code":441,"score":60,"supported":48,"title":442,"abstract":443,"tags":446},"J2",[],[444,445],"农业现代化","agricultural modernization",[],{"code":448,"score":57,"supported":48,"title":449,"abstract":450,"tags":452},"F3",[],[451],"fertilizer",[],[454,455],"可持续农业 土壤监测 智慧农业 精准农业","可持续农业 土壤监测","可持续农业土壤监测智慧农业精准农业-1305","10.55981\u002Fjet.807",{"doi":457,"openalex_id":459,"authors":460,"venue":374,"cited_by_count":117,"oa_url":371,"card":465,"direction":366,"ingested_from":125},"W7204810936",[461,463],{"name":462,"orcid":8},"Ayu Latifah",{"name":464,"orcid":8},"Dendi Ardimansah",{"tldr":466,"method":467,"finding":468,"direction":366,"opportunity":469},"开发基于IoT的土壤监测系统，支持西爪哇精准可持续农业，提高灌溉效率并增产。","使用ESP32微控制器、SPIFFS、土壤传感器和Web仪表盘构建实时监测系统。","系统节省约30%灌溉用水，马铃薯种薯产量翻倍至3万块，符合区域政策。","可扩展至更多作物和地区，结合机器学习预测土壤养分，优化施肥策略，提升系统普适性。","2026-09-01T23:30:12.797772Z",{"id":472,"title":473,"url":474,"summary":475,"summary_zh":8,"content":8,"source_name":476,"source_url":474,"published_at":477,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":478,"score_detail":479,"sources":481,"tags":483,"primary_topic":485,"secondary_topics":488,"classification":490,"search_phrases":501,"slug":504,"view_count":57,"doi":505,"paper":506,"created_at":520},1272,"Biodiversity isn’t measured in tons: Making sense of nature in the context of sustainable agriculture","https:\u002F\u002Fdoi.org\u002F10.32942\u002Fx28t1r","In this review, we articulate several important, but often overlooked concepts, trends, and perspectives in the biodiversity monitoring space, specifically in the context of transforming agriculture and the wider food system. We describe the common approaches to biodiversity monitoring — those focused on species, communities, functions, habitats, etc — and the methods and tools commonly used to track change. We then describe a set of fundamental ecological principles that are often overlooked by practitioners entering the agrobiodiversity space for the first time, particularly those with technical, industrial, and policy expertise in agriculture-adjacent fields who seek to incorporate biodiversity into their research and operations. For these practitioners, we discuss the importance of abundance, the timelines along which population trends can be quantitatively established, the geographical scales at which ecological interactions play out, and the implications therein for anyone looking to monitor the effect of farm management practices. We attempt to describe the complexities that arise when navigating the intersection of ecological, agricultural, and social systems, highlighting the multiple sets of voices, values, and priorities that come into play in this space. From intergovernmental panels to individual farmers, the agrobiodiversity space holds a multitude of arenas of where decisions are made. We raise the question of “why, how, and for whom are we monitoring biodiversity?” to encourage practitioners new to this space to consider the implications of their approach. Finally, we discuss the conflicts and trade-offs that emerge in the intersection of productivity, profits, carbon and biodiversity, and explore the challenges in finding a balance between them in the transition toward a more sustainable form of agriculture.","OpenAlex","2026-08-28T00:00:00Z",73,{"impact":137,"substance":18,"depth":137,"authority":19,"freshness":57,"relevant":21,"comment":480},"综述性论文，系统梳理农业生物多样性监测的概念、方法与挑战，对农业可持续发展有参考价值。",[482],{"name":476,"url":474},[28,257,325,484],"监测方法",{"code":254,"slug":326,"name":486,"path":487,"parent_code":38},"生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",[489],{"code":34,"slug":35,"name":36,"path":37,"parent_code":38},{"status":41,"locked":14,"version":42,"method":43,"evidence":491},{"candidates":492,"agricultural_evidence":48},[493,497],{"code":254,"score":74,"supported":48,"title":494,"abstract":495,"tags":496},[326],[326],[257,325],{"code":34,"score":75,"supported":48,"title":498,"abstract":499,"tags":500},[51],[],[28],[502,503],"可持续农业 生物多样性 农业生态 监测方法","可持续农业 生物多样性","可持续农业生物多样性农业生态监测方法-1272","10.32942\u002Fx28t1r",{"doi":505,"openalex_id":507,"authors":508,"venue":8,"cited_by_count":117,"oa_url":514,"card":515,"direction":366,"ingested_from":125},"W7204518041",[509,512],{"name":510,"orcid":511},"Iqbal Singh Bhalla","https:\u002F\u002Forcid.org\u002F0000-0002-5611-8361",{"name":513,"orcid":8},"Philip Loring","https:\u002F\u002Fecoevorxiv.org\u002Frepository\u002Fobject\u002F14661\u002Fdownload\u002F25513\u002F",{"tldr":516,"method":517,"finding":518,"direction":364,"opportunity":519},"综述农业生物多样性监测的概念、方法、原则及权衡，强调监测目的与尺度。","综述常见监测方法（物种、群落等）及工具，讨论生态原则与多系统交叉。","监测需关注丰度、时间尺度、地理尺度，并权衡生产力、碳与生物多样性。","可研究农业管理措施对生物多样性的多尺度影响，及权衡碳与生物多样性的决策模型。","2026-09-01T04:03:13.203738Z"]