[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4669":3,"related-4669":107},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":82,"slug":85,"view_count":86,"doi":9,"paper":87,"created_at":106},4669,"REVIEW ON RENEWABLE ENERGY-BASED SMART FERTIGATION CONTROLLER USING NPK SENSOR","https:\u002F\u002Fijmert.com\u002Findex.php\u002Fijmert\u002Farticle\u002Fview\u002F302","Agriculture will require efficient management of water, fertilizers, and energy to improve crop productivity and support sustainable farming practices. Traditional fertilizer application methods will often depend on manual observation and fixed schedules, which will lead to improper nutrient management, nutrient imbalance, and unnecessary fertilizer usage. Smart fertigation systems will provide an effective approach for addressing these limitations by integrating IoT, soil nutrient sensing, and real-time monitoring technologies. In this review, NPK-based soil monitoring and IoT-enabled fertigation approaches will be studied with emphasis on nitrogen, phosphorus, and potassium monitoring for precision agriculture. The proposed system will use an ESP32 microcontroller, NPK sensor, soil moisture sensor, and DHT11 sensor to monitor soil nutrient and environmental conditions in real time. The collected data will be displayed on an LCD and transmitted through Wi-Fi to the Blynk IoT platform for remote monitoring. Based on real-time NPK readings, the fertilizer requirement will be determined, and the appropriate fertilizer-supply motor will be manually operated. Solar energy will be integrated with a solar charge controller and rechargeable battery to reduce dependence on conventional electricity and support sustainable operation. The reviewed approaches will indicate that the integration of NPK sensors, IoT monitoring, fertigation, and renewable energy will provide a promising solution for improving fertilizer utilization, reducing resource wastage, minimizing manual effort, and supporting sustainable precision agriculture.","农业需要高效管理水、肥料和能源，以提高作物生产力并支持可持续农业实践。传统施肥方法往往依赖人工观察和固定日程，这会导致养分管理不当、养分失衡和不必要的肥料使用。智能水肥一体化系统通过整合物联网（IoT）、土壤养分传感和实时监测技术，为解决这些局限提供了一种有效途径。本文综述了基于氮磷钾（NPK）的土壤监测和物联网水肥一体化方法，重点关注精准农业中的氮、磷、钾监测。所提出的系统将使用ESP32微控制器、NPK传感器、土壤湿度传感器和DHT11传感器实时监测土壤养分和环境条件。采集的数据将显示在LCD上，并通过Wi-Fi传输至Blynk物联网平台进行远程监测。根据实时NPK读数确定肥料需求量，并手动操作相应的供肥电机。将太阳能与太阳能充电控制器和可充电电池集成，以减少对传统电力的依赖并支持可持续运行。综述的方法表明，将NPK传感器、物联网监测、水肥一体化和可再生能源相结合，为提高肥料利用率、减少资源浪费、降低人工投入和支持可持续精准农业提供了一种有前景的解决方案。",null,"International Journal of Mechanical Engineering Research and Technology","2026-10-08T00:00:00Z","论文",10,false,46,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":20,"relevant":21,"comment":22},8,14,12,6,1,"综述性论文，提出基于ESP32与NPK传感器的太阳能智能水肥一体化方案，有一定技术参考价值，但属常规技术集成，非重大突破，且期刊权威性一般。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","物联网","精准农业","水肥一体化","可再生能源",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,55,61,68,75],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":54},18,true,[48],"fertigation",[50,51,29,52,53,48],"施肥","肥料","养分管理","fertilizer",[29],{"code":56,"score":17,"supported":46,"title":57,"abstract":58,"tags":60},"I1",[],[28,59],"precision agriculture",[26,28],{"code":62,"score":63,"supported":46,"title":64,"abstract":65,"tags":67},"I5",7,[],[27,66],"IoT",[27],{"code":69,"score":20,"supported":46,"title":70,"abstract":71,"tags":74},"H2",[],[72,73],"土壤","soil",[],{"code":76,"score":77,"supported":46,"title":78,"abstract":79,"tags":81},"H8",3,[],[80],"可持续农业",[],[83,84],"ESP32 NPK传感器 智能灌溉","太阳能 水肥一体化 控制器","ESP32NPK传感器智能灌溉-4669",2,{"doi":9,"openalex_id":88,"authors":89,"venue":10,"cited_by_count":98,"oa_url":6,"card":99,"direction":103,"ingested_from":105},"W7221368129",[90,92,94,96],{"name":91,"orcid":9},"Niharika Bodake",{"name":93,"orcid":9},"Akshata Gaurkar",{"name":95,"orcid":9},"Vaishnavi Chavan",{"name":97,"orcid":9},"S. K. Godase",0,{"tldr":100,"method":101,"finding":102,"direction":103,"opportunity":104},"综述基于NPK传感器与物联网的可再生能源智能水肥一体化控制器方案。","ESP32、NPK\u002F土壤湿度\u002FDHT11传感器、Blynk平台与太阳能供电。","NPK传感+物联网+水肥一体化+可再生能源可提升肥料利用率并减少浪费。","智慧农业 \u002F 农业物联网","肥料供给仍靠手动，可研究基于实时NPK的自动决策与闭环变量施肥控制。","openalex","2026-10-11T23:30:16.034599Z",{"total":20,"page":21,"page_size":20,"items":108},[109,192,271,330,396,452],{"id":110,"title":111,"url":112,"summary":113,"summary_zh":114,"content":9,"source_name":115,"source_url":112,"published_at":116,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":117,"score_detail":118,"sources":122,"tags":124,"primary_topic":128,"secondary_topics":129,"classification":130,"search_phrases":147,"slug":150,"view_count":98,"doi":151,"paper":152,"created_at":191},5327,"Poloxamer‐Enabled Thermoresponsive Biobased Controlled‐Release Fertilizer for On‐Demand Nutrient Delivery","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fadvs.78371","ABSTRACT Synchronizing nutrient release of fertilizers with crop uptake remains a central challenge in precision agriculture. Here, we present a novel temperature‐responsive biobased controlled‐release fertilizer (TRBFs) incorporating Poloxamer 407 (F127) as a thermal switch within a castor oil‐derived polyurethane coating. The optimized TRBF10 (3 wt.% coating rate, 10 wt.% F127 in coating) exhibits a sharp, reversible phase transition at ∼20°C, matching the phenological requirements of overwintering crops. As quantified by digital refractometry, the 30‐day cumulative nitrogen release is suppressed to 9.22% at 10°C (crop dormancy) and increases 8.7‐fold to 80.32% at 30°C (active growth). This scalable technology overcomes intrinsic limitations of conventional diffusion‐controlled coated fertilizers and offers potential for on‐demand nutrient delivery with reduced environmental loss. Our work establishes sustainable strategies for climate‐adaptive precision agriculture and offers new insights and design paradigms for intelligent controlled‐release materials.","摘要 实现肥料养分释放与作物吸收的同步仍是精准农业的核心挑战。本研究提出一种新型温度响应型生物基控释肥料（TRBFs），在蓖麻油衍生聚氨酯包膜中引入泊洛沙姆407（F127）作为热开关。优化后的TRBF10（包膜率3 wt.%，包膜中F127含量10 wt.%）在约20°C时表现出急剧且可逆的相变，与越冬作物的物候需求相匹配。经数字折光法定量测定，30天累积氮释放量在10°C（作物休眠期）被抑制至9.22%，而在30°C（活跃生长期）增加8.7倍至80.32%。该可规模化技术克服了传统扩散控制型包膜肥料的内在局限，为按需养分供给并减少环境损失提供了潜力。本研究为气候适应性精准农业建立了可持续策略，并为智能控释材料提供了新见解与设计范式。","Advanced Science","2026-10-18T00:00:00Z",81,{"impact":45,"substance":119,"depth":45,"authority":18,"freshness":120,"relevant":21,"comment":121},22,9,"该研究提出温敏生物基控释肥，实现按需养分释放，方法新颖、数据扎实，对气候适应性精准农业有参考价值。",[123],{"name":115,"url":112},[26,28,125,126,127],"控释肥","温度响应","蓖麻油基材料",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":131},{"candidates":132,"agricultural_evidence":46},[133,137,141],{"code":32,"score":18,"supported":46,"title":134,"abstract":135,"tags":136},[53],[51,53],[],{"code":56,"score":17,"supported":46,"title":138,"abstract":139,"tags":140},[],[28,59],[26,28],{"code":142,"score":77,"supported":46,"title":143,"abstract":144,"tags":146},"H7",[],[145],"气候适应",[],[148,149],"Poloxamer 温敏控释肥","蓖麻油基材料 智慧农业 温度响应 精准农业","Poloxamer温敏控释肥-5327","10.1002\u002Fadvs.78371",{"doi":151,"openalex_id":153,"authors":154,"venue":115,"cited_by_count":98,"oa_url":112,"card":185,"direction":190,"ingested_from":105},"W7222872607",[155,157,160,162,164,167,169,171,173,176,179,182],{"name":156,"orcid":9},"Jiahui Liu",{"name":158,"orcid":159},"Li J","https:\u002F\u002Forcid.org\u002F0009-0008-8760-1365",{"name":161,"orcid":9},"Ziyao Li",{"name":163,"orcid":9},"Xiangjie Zhao",{"name":165,"orcid":166},"Fengyan Fang","https:\u002F\u002Forcid.org\u002F0009-0009-0081-4796",{"name":168,"orcid":9},"Yan Liu",{"name":170,"orcid":9},"Songyuan Wang",{"name":172,"orcid":9},"Boning Su",{"name":174,"orcid":175},"Yuanyuan Yao","https:\u002F\u002Forcid.org\u002F0000-0002-7439-2970",{"name":177,"orcid":178},"Bin Gao","https:\u002F\u002Forcid.org\u002F0000-0003-3769-0191",{"name":180,"orcid":181},"Shugang Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-1428-9082",{"name":183,"orcid":184},"Yuechao Yang","https:\u002F\u002Forcid.org\u002F0000-0003-4045-0252",{"tldr":186,"method":187,"finding":188,"direction":103,"opportunity":189},"研发含F127温敏开关的生物基包膜控释肥，实现按温度按需释放养分。","蓖麻油基聚氨酯包膜中嵌入Poloxamer 407作热开关，数字折光法测氮释放。","10℃时30天氮累积释放仅9.22%，30℃时增至80.32%，提升8.7倍。","可探索多响应（温湿\u002FpH）智能包膜与田间作物需肥曲线耦合的精准释放调控。","数字乡村与农业信息化","2026-10-19T23:30:28.317764Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":197,"content":9,"source_name":198,"source_url":195,"published_at":199,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":200,"score_detail":201,"sources":206,"tags":208,"primary_topic":212,"secondary_topics":217,"classification":219,"search_phrases":252,"slug":255,"view_count":21,"doi":256,"paper":257,"created_at":270},4694,"Precision Agriculture Approaches for Nutrient Management in Maize: A Comprehensive Review of Productivity, Efficiency and Economic Benefits","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fjeai\u002F2026\u002Fv48i104559","Maize nutrient management is an unusually demanding target for precision agriculture because crop demand, soil nutrient supply, weather, rooting conditions and management history vary simultaneously across space and time. Uniform fertiliser programmes can therefore be efficient in one part of a field and inefficient in another, while a recommendation that is appropriate before planting may become suboptimal after rainfall, mineralisation and crop establishment have altered nutrient availability. This critical narrative review evaluates precision approaches for nutrient management in maize, with emphasis on productivity, nutrient-use efficiency and farm-level economic performance. Literature published from 1 January 1990 to 2 August 2026 was examined using agricultural and multidisciplinary scholarly sources, supplemented by citation searching and bibliographic verification. The evidence was organised around the decision chain linking measurement, diagnosis, prescription and nutrient application. Strongest empirical support exists for site-specific and in-season nitrogen management because nitrogen is mobile, strongly coupled to weather and readily expressed in canopy signals. Chlorophyll meters, active optical sensors, aerial and unmanned aerial vehicle imagery, management zones, crop models and machine-learning approaches can improve the timing or spatial targeting of nitrogen, but diagnostic accuracy does not automatically translate into an economically superior fertiliser prescription. Multi-nutrient decision-support systems broaden precision management beyond nitrogen and can improve the balance of nitrogen, phosphorus and potassium, particularly where farmer practice is poorly aligned with crop demand. Across the evidence base, yield gains are often modest when conventional fertilisation is already adequate; benefits more consistently arise through reduced excess nutrient use, improved nutrient-use efficiency, better risk management or correction of under-fertilisation. Profitability is highly conditional on field heterogeneity, fertiliser and grain prices, baseline management, technology cost, scale and weather. Future progress requires multi-year on-farm validation of complete decision chains, stronger treatment of uncertainty and multi-stress confounding, improved multi-nutrient diagnostics, and economic evaluations that include fixed, transaction and information costs. Precision nutrient management is best understood as an adaptive decision framework rather than a single sensor or variable-rate technology.","玉米养分管理对精准农业而言是一个异常苛刻的目标，因为作物需求、土壤养分供应、天气、根系条件和管理历史在空间和时间上同时变化。因此，均匀施肥方案在田块某一部分可能高效，而在另一部分则可能低效；而播种前适宜的推荐方案，在降雨、矿化和作物建成改变养分有效性之后，也可能变得次优。这篇批判性叙述综述评估了玉米养分管理的精准方法，重点关注生产力、养分利用效率和农场层面经济表现。利用农业与多学科学术来源，检索了1990年1月1日至2026年8月2日发表的文献，并以引文检索和书目核验作为补充。证据围绕连接测量、诊断、处方和养分施用的决策链进行组织。最强的实证支持存在于位点特异性和季内氮管理，因为氮具有移动性、与天气强耦合，并易于在冠层信号中表达。叶绿素仪、主动光学传感器、航空和无人机影像、管理分区、作物模型和机器学习方法可以改善氮的施用时机或空间靶向，但诊断准确性并不会自动转化为经济上更优的施肥处方。多养分决策支持系统将精准管理扩展到氮之外，并能改善氮、磷、钾的平衡，尤其是在农户实践与作物需求严重不匹配的情况下。在整个证据基础中，当常规施肥已经充足时，产量增益往往有限；效益更一致地来自减少过量养分使用、提高养分利用效率、改善风险管理或纠正施肥不足。盈利能力高度取决于田块异质性、肥料和谷物价格、基线管理、技术成本、规模和天气。未来进展需要对完整决策链进行多年农场验证，更有力地处理不确定性和多胁迫混杂，改进多养分诊断，以及纳入固定成本、交易成本和信息成本的经济评价。精准养分管理最好被理解为一个适应性决策框架","Journal of Experimental Agriculture International","2026-10-10T00:00:00Z",71,{"impact":19,"substance":202,"depth":203,"authority":204,"freshness":120,"relevant":21,"comment":205},20,17,13,"系统综述精准养分管理在玉米上的产量、效率与经济性证据，方法学扎实但属学术综述，产业落地价值需长期验证。",[207],{"name":198,"url":195},[26,209,210,28,211,52],"变量施肥","玉米","遥感监测",{"code":213,"slug":214,"name":210,"path":215,"parent_code":216},"A3","maize","\u002Ftopic\u002Ffield-crops\u002Fmaize","A",[218],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":220},{"candidates":221,"agricultural_evidence":46},[222,227,232,237,241,247],{"code":56,"score":223,"supported":46,"title":224,"abstract":225,"tags":226},16,[59],[28,59],[26,28],{"code":213,"score":228,"supported":46,"title":229,"abstract":230,"tags":231},15,[214],[210,214],[210],{"code":32,"score":233,"supported":46,"title":234,"abstract":235,"tags":236},11,[],[50,51,52],[52,209],{"code":69,"score":20,"supported":46,"title":238,"abstract":239,"tags":240},[],[72,73],[],{"code":242,"score":77,"supported":46,"title":243,"abstract":244,"tags":246},"I2",[],[245],"机器学习",[],{"code":248,"score":21,"supported":14,"title":249,"abstract":250,"tags":251},"I3",[],[],[211],[253,254],"玉米 精准施肥 氮肥管理","遥感 变量施肥 养分利用效率","玉米精准施肥氮肥管理-4694","10.9734\u002Fjeai\u002F2026\u002Fv48i104559",{"doi":256,"openalex_id":258,"authors":259,"venue":198,"cited_by_count":98,"oa_url":195,"card":264,"direction":268,"ingested_from":105},"W7221366291",[260,262],{"name":261,"orcid":9},"Piyali Pal",{"name":263,"orcid":9},"Disha Chattopadhyay",{"tldr":265,"method":266,"finding":267,"direction":268,"opportunity":269},"综述玉米精准养分管理在生产力、效率与经济效益上的证据与局限。","系统检索1990-2026年文献，按测量-诊断-处方-施用决策链组织证据。","氮素精准管理证据最强，但诊断精度不必然带来经济更优的施肥处方。","农业人工智能与决策模型","亟需多年多点田间验证完整决策链，并纳入不确定性、多养分诊断与信息成本的经济评价。","2026-10-11T23:30:51.450082Z",{"id":272,"title":273,"url":274,"summary":275,"summary_zh":276,"content":9,"source_name":10,"source_url":274,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":277,"score_detail":278,"sources":281,"tags":283,"primary_topic":287,"secondary_topics":288,"classification":289,"search_phrases":313,"slug":316,"view_count":98,"doi":9,"paper":317,"created_at":329},4673,"RESULT ON RENEWABLE ENERGY-BASED SMART FERTIGATION CONTROLLER USING NPK SENSOR","https:\u002F\u002Fijmert.com\u002Findex.php\u002Fijmert\u002Farticle\u002Fview\u002F301","Agriculture needs good control over water, fertilizers, and energy to make crops grow better and help farming stay sustainable. Old ways of using fertilizers usually relied on looking at the fields by hand and sticking to set times, which often led to wrong use of nutrients, unbalanced soil, and using too much fertilizer. Smart fertigation systems help fix these problems by using IoT, soil nutrient sensors, and real-time tracking. This review looked at NPK-based soil checks and IoT-enabled fertigation, especially focusing on monitoring nitrogen, phosphorus, and potassium to make farming more precise. The system used an ESP32 microcontroller, an NPK sensor, a soil moisture sensor, and a DHT11 sensor to constantly monitor soil nutrients and environmental conditions. The data was shown on an LCD screen and sent via Wi-Fi to the Blynk IoT platform for remote viewing. Based on the real-time NPK levels, the right amount of fertilizer was decided, and the correct fertilizer pump was turned on manually. Solar power was added with a solar charge controller and a battery to cut down on using regular electricity and support eco-friendly farming. The studies showed that combining NPK sensors, IoT, fertigation, and renewable energy offers a great way to use fertilizers better, save resources, cut down on manual work, and help make precision agriculture more sustainable.","农业需要对水、肥料和能源进行良好控制，以使作物生长更好并帮助农业保持可持续性。传统的施肥方式通常依赖人工观察田地并遵循固定时间，这往往导致养分使用不当、土壤失衡以及施肥过量。智能水肥一体化系统通过物联网（IoT）、土壤养分传感器和实时追踪帮助解决这些问题。本综述考察了基于氮磷钾（NPK）的土壤检测和物联网支持的水肥一体化，尤其关注对氮、磷、钾的监测，以使农业更加精准。该系统使用ESP32微控制器、NPK传感器、土壤湿度传感器和DHT11传感器持续监测土壤养分和环境条件。数据在LCD屏幕上显示，并通过Wi-Fi发送到Blynk物联网平台进行远程查看。根据实时NPK水平，确定合适的肥料用量，并手动开启正确的肥料泵。系统还加入了太阳能供电，配有太阳能充电控制器和电池，以减少常规电力使用并支持生态友好型农业。研究表明，将NPK传感器、物联网、水肥一体化和可再生能源相结合，为更好地利用肥料、节约资源、减少人工劳动以及帮助精准农业实现更可持续发展提供了一种极佳途径。",54,{"impact":17,"substance":223,"depth":18,"authority":19,"freshness":279,"relevant":21,"comment":280},4,"综述性论文，将NPK传感、物联网与光伏供电结合于水肥一体化控制，方法集成有参考价值，但属实验室\u002F综述层面，公共影响有限且时效偏旧。",[282],{"name":10,"url":274},[26,284,29,285,286],"农业物联网","精准灌溉","光伏农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":290},{"candidates":291,"agricultural_evidence":46},[292,296,300,304,308],{"code":32,"score":45,"supported":46,"title":293,"abstract":294,"tags":295},[48],[50,51,29,53,48],[29],{"code":56,"score":63,"supported":46,"title":297,"abstract":298,"tags":299},[],[28,59],[26],{"code":62,"score":63,"supported":46,"title":301,"abstract":302,"tags":303},[],[27,66],[284],{"code":69,"score":20,"supported":46,"title":305,"abstract":306,"tags":307},[],[72,73],[],{"code":309,"score":21,"supported":14,"title":310,"abstract":311,"tags":312},"H3",[],[],[285],[314,315],"ESP32 NPK传感器 水肥一体化","太阳能 智能灌溉 控制器","ESP32NPK传感器水肥一体化-4673",{"doi":9,"openalex_id":318,"authors":319,"venue":10,"cited_by_count":98,"oa_url":274,"card":324,"direction":103,"ingested_from":105},"W7221424039",[320,321,322,323],{"name":91,"orcid":9},{"name":93,"orcid":9},{"name":95,"orcid":9},{"name":97,"orcid":9},{"tldr":325,"method":326,"finding":327,"direction":103,"opportunity":328},"综述基于NPK传感器、物联网与太阳能的智能水肥一体化控制器，实现精准施肥与远程监控。","ESP32、NPK\u002F土壤湿度\u002FDHT11传感器、Blynk物联网平台与太阳能供电","融合NPK传感、物联网、水肥一体化与可再生能源可优化施肥、节约资源并减少人工。","可研究基于实时NPK数据的自动施肥决策算法与闭环控制，替代当前手动开启施肥泵。","2026-10-11T23:30:16.530895Z",{"id":331,"title":332,"url":333,"summary":334,"summary_zh":335,"content":9,"source_name":336,"source_url":333,"published_at":337,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":338,"score_detail":339,"sources":341,"tags":343,"primary_topic":346,"secondary_topics":347,"classification":348,"search_phrases":375,"slug":378,"view_count":21,"doi":379,"paper":380,"created_at":395},4559,"Comparative analysis of gradient boosting and random forest regressors for nutrient prediction in smart agriculture","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-74825-5","Accurate estimation of nutrient concentrations can support monitoring in hydroponic systems. This study compares Random Forest Regressor (RFR) and Gradient Boosting Regressor (GBR) for predicting nitrogen, phosphorus, and potassium from pH, electrical conductivity, temperature, and relative humidity in a precompiled agricultural sensor dataset. The framework uses mean imputation, correlation-based feature selection, and ensemble regression. Observations were randomly divided into 80% training and 20% test partitions; preprocessing, feature selection, and grid-search optimization with five-fold cross-validation were confined to the training partition. On the held-out test partition, GBR achieved lower MAE and RMSE and higher R² than RFR for all three nutrients. Unweighted arithmetic means of the reported nutrient-specific test metrics were MAE 3.60 versus 4.06, mean nutrient RMSE 4.22 versus 4.90, and mean nutrient R² 0.89 versus 0.84 for GBR and RFR, respectively. These summaries were calculated from the rounded nutrient-specific entries and are not pooled metrics. The comparison rests on one train–test split without quantified variability because fold-level scores were not retained and repeated-seed evaluations were unavailable. Missing acquisition metadata and unverified nutrient units further limit interpretation. The findings support GBR as a candidate for nutrient estimation within this dataset; external validation and operational evaluation are required before use in automated fertigation.","在水培系统中，准确估算养分浓度有助于实现有效监测。本研究基于一个预编译的农业传感器数据集，比较了随机森林回归器（Random Forest Regressor, RFR）与梯度提升回归器（Gradient Boosting Regressor, GBR）在利用pH、电导率、温度和相对湿度预测氮、磷、钾方面的性能。该框架采用均值插补、基于相关性的特征选择和集成回归。观测数据被随机划分为80%的训练集和20%的测试集；预处理、特征选择以及基于五折交叉验证的网格搜索优化均仅限于训练集内进行。在留出的测试集上，GBR对三种养分的预测均取得了比RFR更低的MAE和RMSE以及更高的R²。对报告中各养分测试指标取未加权算术平均值，GBR和RFR的结果分别为：MAE 3.60对4.06，平均养分RMSE 4.22对4.90，平均养分R² 0.89对0.84。这些汇总值系根据四舍五入后的各养分指标计算得出，并非合并指标。该比较仅基于一次训练-测试划分，且未量化变异性，因为未保留折级评分，也无法进行重复随机种子评估。缺失的采集元数据和未经核实的养分单位进一步限制了结果解读。研究结果表明，在该数据集内GBR可作为养分估算的候选方法；在用于自动化施肥之前，仍需进行外部验证和运行评估。","Scientific Reports","2026-10-09T00:00:00Z",63,{"impact":17,"substance":45,"depth":228,"authority":18,"freshness":17,"relevant":21,"comment":340},"方法对比扎实但仅单次划分、缺乏外部验证，属细分领域技术进展，未达每日精选门槛。",[342],{"name":336,"url":333},[26,245,29,344,345],"养分预测","无土栽培",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":349},{"candidates":350,"agricultural_evidence":46},[351,356,360,366,371],{"code":56,"score":120,"supported":46,"title":352,"abstract":354,"tags":355},[353],"smart agriculture",[],[26],{"code":32,"score":63,"supported":46,"title":357,"abstract":358,"tags":359},[],[50,48],[29],{"code":361,"score":279,"supported":46,"title":362,"abstract":363,"tags":365},"B7",[],[364],"hydroponic",[345],{"code":62,"score":77,"supported":46,"title":367,"abstract":368,"tags":370},[],[369],"农业传感",[],{"code":242,"score":21,"supported":14,"title":372,"abstract":373,"tags":374},[],[],[245],[376,377],"随机森林 梯度提升 养分预测","水培 氮磷钾 传感器","随机森林梯度提升养分预测-4559","10.1038\u002Fs41598-026-74825-5",{"doi":379,"openalex_id":381,"authors":382,"venue":336,"cited_by_count":98,"oa_url":333,"card":390,"direction":103,"ingested_from":105},"W7221072509",[383,386,388],{"name":384,"orcid":385},"Shaista Farhat","https:\u002F\u002Forcid.org\u002F0009-0008-9348-8370",{"name":387,"orcid":9},"Dr. Chokka Anuradha",{"name":389,"orcid":9},"Dawit Tafesse Gebreyohannes",{"tldr":391,"method":392,"finding":393,"direction":103,"opportunity":394},"比较梯度提升与随机森林回归器，用水培传感器数据预测氮磷钾浓度。","预处理、相关性特征选择、网格搜索五折交叉验证，对比GBR与RFR。","GBR在三种养分预测上MAE、RMSE更低、R²更高，但仅单次划分且缺变异量化。","可开展多源传感器融合、重复种子评估与外部验证，提升养分预测稳健性并接入自动施肥。","2026-10-10T23:30:07.557842Z",{"id":397,"title":398,"url":399,"summary":400,"summary_zh":9,"content":401,"source_name":402,"source_url":9,"published_at":403,"category":404,"cover_url":9,"hotness":13,"is_selected":14,"score":338,"score_detail":405,"sources":408,"tags":410,"primary_topic":415,"secondary_topics":416,"classification":417,"search_phrases":447,"slug":450,"view_count":86,"doi":9,"paper":9,"created_at":451},4401,"永昌县以科技破局寒旱农业 — 智慧节水+良种良法打造西北高原现代农业新路","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7692759630434337321\u002F","甘肃永昌县新城子镇刘克庄村构建泵房自控、水肥一体化、土壤监测、田间气象监测、物联网传输五大智慧农业体系,实现「手机管农田」;东寨镇双桥村浅埋滴灌搭配可降解地膜穴播技术将每亩用水量从 280-300 立方米压减至 200-220 立方米;引进小麦新品种 12 个,春小麦陇春 44 号「揭榜挂帅」试点力争示范田亩产突破 700 公斤。","![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F12d93550385645579927b82829e5b7e8~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=MtVHDXueQJNwxmIMI4ep4noPpeg%3D)\n河西走廊秋风起，永昌县新城子镇刘克庄村的马铃薯田绿浪翻涌。种植大户王泽俊站在地头，掏出手机轻点屏幕，远处出水阀门应声开启。“所有的截止阀、出水阀都是智慧农业，不管在什么地方都可以在手机上操作，省了人力，还省了钱。”王泽俊的话语里，透着新农人的从容与底气。\n\n这幅“手机管农田”的场景，正是永昌县以科技赋能现代农业的生动缩影。近年来，永昌县聚焦“省级乡村振兴样板县”目标，以科技破局、以产业提质、以融合增效，推动农业从“传统种植”向“现代高效”转型，在西北寒旱大地上蹚出一条可复制、可推广的高原现代农业新路。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F68d73df7424bc320a29aa38fe598247f~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=%2BGfPKtrMcnwex6FY%2B7lnY2l%2Fatc%3D)\n**智慧节水**\n\n**让每一滴水都精准抵达根系**\n\n永昌地处河西走廊，蒸发量大、水资源紧缺，节水是农业绕不开的命题。\n\n在新城子镇刘克庄村，由泵房自控、水肥一体化、土壤监测、田间气象监测、物联网传输五大体系构成的智慧农业管理系统，全天候采集“四情”数据，水肥供给按需精准调控，彻底改变了昔日大水漫灌、施肥过量的粗放模式。而在东寨镇双桥村精准化农技创新试点，浅埋滴灌搭配可降解地膜穴播技术，将每亩用水量从常规的280至300立方米压减至200至220立方米，全生育期减少2至3次灌溉，每亩节水80立方米以上。铺设的生物可降解地膜120天后自然分解，收割后无需人工回收，杜绝了农田白色污染。\n\n245亩核心试点配齐北斗导航播种、水肥一体化管网、墒情监测仪和全域监控，单套系统可覆盖千亩耕地，仅需一人即可远程调控。节水与增绿，在这片戈壁灌区实现了统一。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F9d756288bb0088de5cc517f6397175b9~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=zl4NtRNrjaX8PQ0B5%2BiRCLXUGqs%3D)\n**良种良法**\n\n**把试验田里的答案写进大田**\n\n科技增产，种子是芯片，方法是钥匙。永昌县在小麦种植技术上的探索，正是一条不断迭代、步步升级的路子。\n\n在东寨镇双桥村丰泽园农民种植专业合作社的小麦试验田里，地膜精量穴播、宽幅匀播试验田同步作业，播种机来回穿梭、精准播种。合作社长期钻研小麦种植新技术，从尝试浅埋滴灌小麦技术起步，如今已更新迭代为膜上穴播、膜下滴灌水肥一体化技术。今年采用的生物可降解地膜精量穴播膜下滴灌水肥一体化栽培模式，相比过去技术更加节省种子，一亩地用种量约40斤，用水量节省30%，产量增加20%，增产增收效果显著。在双桥村220亩小麦试验场所，引进小麦新品种12个，播量试验划分每亩60斤、70斤、80斤等梯度，农技人员用数据破除“播种越多产量越高”的旧观念，春小麦陇春44号高产创建“揭榜挂帅”试点同步推进，力争示范田亩产突破700公斤。\n\n在新城子镇邵家庄村千亩冬小麦试验示范基地，针对寒旱灌区水资源匮乏、低温干旱胁迫突出等痛点，核心示范种植济麦44号等品种，设置播期、播量、新品种筛选等多组梯度试验，将精量穴播、干播湿出、动态施肥、黑色地膜与品种筛选深度耦合，形成“种-播-水-肥-膜”一体化技术体系。其中“干播湿出”技术可减少水资源浪费40%，冬小麦越冬存活率提升至95%以上。\n\n在红山窑镇河沿子村，1830亩马铃薯现代农业科技试验示范基地里，30亩试验区引进甘农薯7号、克新等8个品种，开展29项次田间试验：密度试验区里5000株、6000株、7000株三个梯度次第排开，有机肥施用量在1000至3000公斤区间设置5个梯度，4项灌溉量梯度试验为节水精准灌溉积累数据。永昌县农技中心主任丁文庆说：“待9月中旬收获测产后，我们将形成一套适配本地的技术参数，为全县马铃薯生产技术升级提供科学依据。”\n\n从浅埋滴灌到膜上穴播、膜下滴灌水肥一体化，从单一品种到多梯度对比筛选，永昌的良种良法配套体系正日趋成熟。\n\n![Image 4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F8dfcb7ea98f68df17b1b13778e93c153~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=SbZKMt%2FmRzhfTwum6tzSnthAfBs%3D)\n**服务下沉**\n\n**让技术从纸面走进田间**\n\n科技落地，关键在人。永昌县推行“县管乡用、下沉到村”服务机制，每名农技人员固定包联行政村、对接十余户种植大户。灌浆期的小麦田里，永昌县农业技术推广服务中心主任丁文庆带领技术小组穿行垄间，卷尺、测墒仪、记录本一刻不离，蹲身拨开麦株记录穗长、穗粒数和土壤湿度，现场为农户讲解“一喷三防”要点。全县累计组织150余人次农技人员下沉一线，指导检修各类农机具1.3万台（套），计划推广小麦浅埋滴灌20万亩以上、玉米宽窄行20万亩以上、马铃薯垄膜滴灌6万亩以上，目前已落实小麦浅埋滴灌9.2万亩。\n\n在红山窑镇高古城村，县科协把科普下乡活动办到田间地头，农技专家面对面讲解高原夏菜水肥管理与病虫害防控，本土种植户现场演示无人机植保作业，理论宣讲与实操实训深度融合，打通了农技科普服务“最后一公里”。丰泽园农民种植专业合作社负责人张琰忠感慨：“从前种地凭经验，如今农技人员常态化驻田，每一项管理措施都有数据支撑。”\n\n![Image 5](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F74d5c638e987466d7506e20d5127fb24~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=mdDszQ0hXPFOFFBFJoIiBpl%2BLd0%3D)\n**产业融合**\n\n**从一粒种到一条链**\n\n科技的力量，不止于田间。在水源镇方沟村，翻新升级后的日光温室大棚里，西葫芦、小乳瓜挂满藤蔓，种植户利用部分温室开展育苗，多元种植搭配设施提质，还吸纳周边群众就近务工。永昌县重点发展宜机化钢架大棚与高标准日光温室，着力打造西河片区特色食用菌、城郊片区集约化育苗、东河片区反季节瓜菜、清河片区“春提早秋延后”高原夏菜四个设施种植业集群发展带。2026年计划新建日光温室353座、钢架大棚1064座，更新改造日光温室175座。\n\n在畜牧领域，甘肃元生农牧科技有限公司聚焦肉羊良种繁育，集成精液采集、稀释、保鲜、精准输精等关键技术，依托胚胎工程打通优质种源快速繁育通道。永昌县深挖“永昌肉羊”国家地理标志产品优势，整合养殖、繁育、加工、流通全产业链数据，搭建从“牧场到餐桌”的全程追溯体系，让优质肉羊凭借“甘味”品牌走向更广阔的市场。立足国家级现代农业产业园建设，永昌紧扣“世界奶绵羊之窗”定位，力争年底奶绵羊养殖规模达7万只，推动羊产业向全链条融合迈进。\n\n全县统筹推进生物育种产业化布局，在水源、六坝两镇规模化开展转基因玉米示范种植，形成小麦、马铃薯、玉米多元的粮食科技提升格局，丰富“牛羊菜果薯药粮种”八大产业科技支撑体系。\n\n从新城子镇的智慧薯田到双桥村的节水麦浪，从邵家庄村的冬小麦试验到河沿子村的马铃薯攻关，从方沟村的大棚四季到元生公司的良种繁育，永昌县以智慧农田建设为核心抓手，持续加大农业数字化基础设施投入，推广智能物联网管控模式，扩大智慧农业覆盖范围。站在“十五五”开局的新起点，这片曾经“靠天吃饭”的寒旱之地，正用科技重新定义耕耘——数据在云端奔跑，阀门在指尖开合，良种在试验田里比拼，农技人员的脚步丈量着每一块地头。农业强、农村美、农民富的振兴图景，正在永昌沃野上徐徐铺展。\n\n![Image 6: 图片](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fd0ce336604fc90ef9437d20b22b06d42~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1792022866&x-signature=0YjY2roixNeBRjKaS%2BUMSiIxed8%3D)\n来源：爱永昌客户端\n\n编辑：常远\n\n责编：刘欢欢\n\n审核：谢晓玲","今日头条 金昌发布 2026-10-04","2026-10-04T00:00:00Z","报道",{"impact":223,"substance":202,"depth":223,"authority":20,"freshness":406,"relevant":21,"comment":407},5,"县域寒旱农业科技转型的扎实报道，节水、良种、农技下沉数据具体，但属地方动态，全国性影响有限。",[409],{"name":402,"url":399},[26,411,29,412,413,414],"种业振兴","寒旱农业","可降解地膜","良种良法",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":418},{"candidates":419,"agricultural_evidence":46},[420,424,428,434,438,442],{"code":32,"score":279,"supported":46,"title":421,"abstract":422,"tags":423},[],[29],[29],{"code":56,"score":279,"supported":46,"title":425,"abstract":426,"tags":427},[],[26],[26],{"code":429,"score":77,"supported":46,"title":430,"abstract":431,"tags":433},"A2",[],[432],"小麦",[],{"code":69,"score":77,"supported":46,"title":435,"abstract":436,"tags":437},[],[72],[],{"code":62,"score":77,"supported":46,"title":439,"abstract":440,"tags":441},[],[27],[],{"code":443,"score":86,"supported":14,"title":444,"abstract":445,"tags":446},"F1",[],[],[411,414],[448,449],"永昌县 智慧节水 马铃薯","陇春44号 小麦 揭榜挂帅","永昌县智慧节水马铃薯-4401","2026-10-08T00:06:56.970004Z",{"id":453,"title":454,"url":455,"summary":456,"summary_zh":457,"content":9,"source_name":458,"source_url":455,"published_at":459,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":460,"score_detail":461,"sources":463,"tags":465,"primary_topic":469,"secondary_topics":470,"classification":471,"search_phrases":517,"slug":520,"view_count":86,"doi":521,"paper":522,"created_at":533},4350,"Role of Science and Technology in Poverty Alleviation Through Smart Agriculture Process in Nigeria","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijcsmt.vol.11.no3.2025.pg.158.165","A smart Agriculture, is also known as precision agriculture which is rapidly growing field that involves the integration of technology and data analysis to optimize agriculture practice and increase efficiency in crop production in Nigeria to control the food shortage and scarcity. The smart agricultural it involves the use of sensor, drone satellite imagery and other technologies to monitor crops growth, soil condition, and weather partner. this information can be used to optimized irrigation, fertilization and pest control practice, ultimately leading to higher crop yield and reduce the waste of resource, more also smart agriculture involves the use of data analytic to analyze the collected data and identify pattern and correlations. This information can be used to informed decision about the planting, harvesting and storage. Automation is another key feature of smart agriculture, as it allows for more efficient and cost-effective farming practice, such as automated irrigation system and robotic harvesting equipment. Looking Nigeria in food shortage there are so many benefit of smart agricultural practice in a numerous way which include, increase efficiency, reduce waste and improve sustainability, it can also help to reduce the environmental impact of agriculture by reducing the use of pesticide and fertilizer, as well as reducing greenhouse gas emission through more efficiency farming practice. So in a nutshell smart agriculture present a high significant opportunity to improve the sustainability and productivity of agriculture. It can help farmers to make more inform decisions, reduce waste, and increase efficiency ultimately leading to a more sustainability and profitable agriculture sector and boost the economy growth of Nigeria.","智慧农业，又称精准农业，是一个快速发展的领域，涉及技术与数据分析的整合，以优化尼日利亚的农业实践并提高作物生产效率，从而控制粮食短缺和匮乏。智慧农业涉及利用传感器、无人机、卫星影像及其他技术来监测作物生长、土壤状况和天气模式。这些信息可用于优化灌溉、施肥和病虫害防治实践，最终实现更高的作物产量并减少资源浪费。此外，智慧农业还涉及利用数据分析来分析所收集的数据并识别模式和相关性。这些信息可用于为种植、收获和储存方面的决策提供依据。自动化是智慧农业的另一个关键特征，因为它能够实现更高效且更具成本效益的农业实践，例如自动化灌溉系统和机器人收割设备。鉴于尼日利亚面临粮食短缺，智慧农业实践在许多方面具有诸多益处，包括提高效率、减少浪费和改善可持续性，它还可以通过减少农药和化肥的使用来帮助降低农业对环境的影响，并通过更高效的农业实践减少温室气体排放。总而言之，智慧农业为改善农业的可持续性和生产力提供了重大机遇。它可以帮助农民做出更明智的决策、减少浪费并提高效率，最终形成更具可持续性和盈利性的农业部门，并促进尼日利亚的经济增长。","INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY E-ISSN","2026-10-05T00:00:00Z",31,{"impact":17,"substance":20,"depth":406,"authority":279,"freshness":17,"relevant":21,"comment":462},"主题相关但为泛泛综述，缺乏新数据与方法创新，信源权威性低，不宜进入每日精选。",[464],{"name":458,"url":455},[26,466,467,28,468],"农业遥感","农业无人机","尼日利亚农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":472},{"candidates":473,"agricultural_evidence":46},[474,479,484,490,497,501,507,513],{"code":56,"score":475,"supported":46,"title":476,"abstract":477,"tags":478},19,[353],[26,28,353,59],[26,28],{"code":32,"score":120,"supported":46,"title":480,"abstract":481,"tags":483},[],[50,53,482],"fertilization",[],{"code":361,"score":20,"supported":46,"title":485,"abstract":486,"tags":489},[],[487,488],"温室","greenhouse",[],{"code":491,"score":20,"supported":46,"title":492,"abstract":493,"tags":496},"F4",[],[494,495],"农药","pesticide",[],{"code":69,"score":20,"supported":46,"title":498,"abstract":499,"tags":500},[],[72,73],[],{"code":309,"score":20,"supported":46,"title":502,"abstract":503,"tags":506},[],[504,505],"灌溉","irrigation",[],{"code":508,"score":77,"supported":46,"title":509,"abstract":510,"tags":512},"F6",[],[511],"robotic harvesting",[],{"code":248,"score":21,"supported":14,"title":514,"abstract":515,"tags":516},[],[],[466],[518,519],"尼日利亚 智慧农业 减贫","尼日利亚农业 农业无人机 农业遥感 智慧农业","尼日利亚智慧农业减贫-4350","10.56201\u002Fijcsmt.vol.11.no3.2025.pg.158.165",{"doi":521,"openalex_id":523,"authors":524,"venue":458,"cited_by_count":98,"oa_url":527,"card":528,"direction":103,"ingested_from":105},"W7220743666",[525],{"name":526,"orcid":9},"Aminu Ahmed","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJCSMT\u002FVOL. 11 NO. 3 2025\u002FRole of Science and Technology 158-165.pdf",{"tldr":529,"method":530,"finding":531,"direction":103,"opportunity":532},"综述智慧农业技术如何通过精准农业助力尼日利亚减贫与粮食安全。","文献综述，整合传感器、无人机、卫星影像、数据分析与自动化技术。","智慧农业可提高效率、减少浪费、增强可持续性并促进经济增长。","可针对尼日利亚小农户开展低成本传感器与无人机应用的本土化实证研究。","2026-10-07T23:30:12.855407Z"]