[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4269":3,"related-4269":74},{"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":24,"tags":26,"primary_topic":8,"secondary_topics":32,"classification":33,"search_phrases":69,"slug":72,"view_count":41,"doi":8,"paper":8,"created_at":73},4269,"安徽农科院专家团队深耕砂姜黑土40载智绘粮仓千亿斤","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7691650459328594470","安徽省农科院土肥所与蒙城县院地携手40余年，几代科研人员接力攻关，让曾经旱涝僵瘠的砂姜黑土从亩产不足50公斤跃升至500公斤台阶。安徽砂姜黑土面积2300余万亩约占全国45%。当前推动改土培肥技术与智能水肥装备集成落地，土壤墒情监测仪实时上传云端数据，移动平板电脑生成彩色施肥处方图。",null,"![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F2f2361f18cc94a13886a009d829e2b54~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1791849984&x-signature=l8Il0pGejukmIxi9yISnxYh76jA%3D)\n金秋九月，淮北平原秋收秋种正忙。9月19日，安徽省农科院农业科技成果转化应用项目“砂姜黑土障碍消减与作物周年高产高效技术转化应用”观摩培训会在蒙城县举办，通过技术讲座、展板介绍、实物展示、田间观摩等多元化形式，全面展示砂姜黑土障碍消减、肥沃耕层构建和高效施肥关键技术的研究路径和应用成效。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F59dbb265baf94778a6389fe26ad11a67~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1791849984&x-signature=yDCtyYTDQL%2F5%2FSAcMUaahaHxGA8%3D)\n蒙城县马店试验站的长期定位试验田里，土壤墒情监测仪无声运转，将地下不同深度的土壤水分、温度数据上传云端；田埂上，青年科研人员轻点平板电脑，一张彩色“施肥处方图”跃然屏上，清晰显示哪块地该补氮、哪块地宜加锌。\n\n这里是“十五五”开局之年的江淮粮仓腹地。千亿斤产能从哪里来？安徽用一块土壤的“命运逆袭”作答。安徽省农科院土肥所与蒙城县院地携手四十余年，几代科研人员接力攻关，让曾经“旱、涝、僵、瘠”的砂姜黑土从低产迈向高产；如今，新一代科研人员接过接力棒，将改土培肥技术、高效施肥产品与智能水肥装备集成落地，推动这片土地向“高产且稳产”跃升。一场从“改土增粮”到“稳产增粮”的科技接力，正在为“千亿斤江淮粮仓”夯实最坚实的耕地根基。\n\n**“雨天一包糟，晴天一把刀”：四十年前向“僵土”宣战**\n\n砂姜黑土是我国黄淮海平原特有的中低产田土壤，全国面积约6000万亩，六成以上集中在淮北平原，其中安徽省砂姜黑土面积2300余万亩，约占全国总面积的45%；砂姜黑土土壤黏粒含量高、胀缩性强，干时收缩坚硬、湿时膨胀黏闭，农民形容为“雨天一包糟，晴天一把刀”，旱、涝、僵、瘠四“病”缠身，上世纪六七十年代小麦亩产不足50公斤。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002Fa8b316c6133e4d9bb83e484df14d6717~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1791849984&x-signature=LNOveSyA3Ak7pn2g4d8dpTRgdsU%3D)\n为拔掉穷根，1978年起，省农科院土肥所在马店建立研究基站——蒙城马店试验站，是目前全国研究历史最长、数据最为连续的砂姜黑土长期监测定位点。1982年布设的肥料长期定位试验从未中断，几代科研人员采集的土壤样品编号归档、记录的观测数据积累成册，构建起完整的砂姜黑土肥力演变数据库。以此为支撑，“淮北砂姜黑土区综合治理开发配套技术”获1991年安徽省科学技术进步奖一等奖，为黄淮海平原中低产田改良提供了重要科技支撑。随着配方施肥、秸秆还田、深耕深松、“一喷三防”等技术在蒙城全县和沿淮砂姜黑土地区迅速推开，小麦亩产历经两次跃升，八十年代跃升至200公斤，2003年达到450公斤，之后小麦亩产陆续站上500公斤台阶。\n\n**密植田里的新考题：地力“托不住”高产的“胃口”**\n\n站在亩产500kg的新台阶上，新一代科研人员却看到了新隐忧。\n\n“十五五”时期，粮食增产主攻方向是提单产。高产品种持续更新，种植密度不断加密：玉米亩株数从4000株左右增至5500株以上，小麦以大群体、高生物量夺高产。地上部的“胃口”越来越大，地下部的“饭碗”却没有同步变大。\n\n长期以来，大型机械作业与传统旋耕作业并存，导致耕层浅薄、土壤库容减小。砂姜黑土有效耕层普遍不足20厘米，全省平均仅14.6厘米，犁底层坚硬紧实，土壤蓄水保肥能力差、缓冲性能弱。农业生产中重用轻养的土地利用模式，以及连年高产出从土壤中带走大量养分，导致地力损耗大，土壤养分失衡——密植作物一旦遭遇强风或连阴雨，极易发生倒伏；降水量大时，又因土壤通透性差而导致作物渍害。加之密植条件下施肥作业难度加大，肥料损耗较大，肥料利用率持续走低，良种高产潜力受到明显制约，当前地力已难以托举地上部密植群体的高产能需求。\n\n**技术套餐：良田良种良法良机融合**\n\n随着智能化、信息化的快速发展，传统栽培模式、机械装备与农资产品已难以适配精准化、轻简化、绿色化的生产需求；围绕密植群体构建下的高产稳产、韧性农业发展目标，一支以詹林川、汪霄、蒋发辉、惠晓丽、晋林等青年博士为骨干的攻关团队在马店试验站扎下营盘，在老一辈打下的地基上展开新一轮攻关，组合成砂姜黑土高产稳产的“技术套餐”。\n\n**套餐一，“旋松一体”+“苗带旋耕”深松浅旋耕层厚沃技术。**针对砂姜黑土结构不良、耕层浅薄问题，通过“深松浅旋”耕作融合有机物料（秸秆、有机肥）还田增碳扩容，打破犁底层，降低土壤容重，提升耕层蓄水保肥能力。研发的“苗带旋耕播种机”（玉米季）采用行间免耕、苗带局部带状旋耕的少耕模式，集施肥、玉米精量播种于一体，针对性破除砂姜黑土硬土层，解决传统免耕播种质量差、出苗率低的问题，行间保留原有土层结构，为玉米根系穿插提供稳定介质，强化根系锚定、防止雨季倒伏；“旋松一体耕作机”（小麦季）可一次性完成深松、旋耕、碎土清平，较传统深翻一遍加旋耕两遍减少作业次数、降低机械能耗，同时避免重型机械反复碾压导致耕层变浅、亚层土壤紧实等问题。\n\n![Image 4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002Fa3cdb2ae814c423183ab96c57606faf7~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1791849984&x-signature=8FcbMw3U4AoBU1nfXLsP4S7xanY%3D)\n**套餐二，“分层施肥”立体供养一次性轻简施肥技术。**针对密植群体肥料过量“前期烧苗、后期脱肥”的痼疾，将缓控释肥料在耕层土壤中“立体布防”：生物有机肥深施打底，改良土壤、培育地力；高氮缓控失肥料分层施入，苗期少量养分精准提苗，中后期养分按需释放；辅以锌肥、硼肥等功能性肥料结合“一飞三防”无人机叶面喷施，精准补给，缺啥补啥。种肥同播、分层深施、一次完成、不再追肥。示范数据显示：肥料总施用量减少10%～15%，化肥利用率提高10%～20%，玉米增产5%～12%，每亩节本增收约135元；省工、省肥、增产，一举三得。\n\n**套餐三，麦—玉\u002F豆周年水肥一体化技术。**淮北平原水热时空分布不均，旱涝急转频发，传统大水漫灌既浪费水肥，又难以精准匹配作物需求。田间水肥一体化管网整齐排列，让“测土配方施肥”从纸面落到管网；土壤墒情监测仪像“听诊器”，实时感知不同深度土壤的水分与温度；墒情数据叠加气象预报与作物生长模型，由智能算法自动生成灌溉施肥处方——灌多少水、追多少肥、何时执行，种植户在手机上轻轻一点即可远程启停。按需供给、少量多次，水肥一体化把每一滴水、每一粒肥都“算”到作物嘴里，密植群体抗逆稳产能力显著增强。淮北粮田从此有了“旱能精准补、涝能及时控”的主动权。\n\n更深的底气，来自四十余年长期定位试验沉淀的“数据家底”。老一辈采集的土壤样品、记录的肥力数据，如今正被整理成数字化数据库，成为训练智能决策模型、绘制变量施肥处方图的“养料”。老数据“喂”出新算法，长期定位试验在智能农业时代焕发新生。\n\n**套餐四，“锌生物强化”增产提质。**淮北砂姜黑土多为石灰性土壤，锌等微量元素有效性低，作物“隐性饥饿”既拖产量后腿，也拉低品质。科研人员运用生物强化思路，基施与叶面喷施相结合，在小麦生育期精准补锌，既提高籽粒产量，又显著提升籽粒锌含量，让普通麦田产出“富锌小麦”。这项技术一头连着减肥增效、单产提升，一头连着功能农业、优质优价，为种粮农民打开了“提质增收”的第二本账。\n\n**薪火传承、成效斐然，良田沃土交答卷**\n\n四十余年，从“低产”到“高产”，从“改土增粮”到“稳产增粮”，变的是技术、装备与算法，不变的是那句话——良田才能出良粮。经过综合治理，昔日砂姜黑土的“粘僵”属性明显改善：土壤有机质含量提升5%～8%，土壤容重降低7%～9%，田间持水量提高15%以上，膨胀系数下降10%以上，化肥利用率提高10%～20%，粮食周年增产10%以上，实现了砂姜黑土区域耕地质量与周年粮食产能的协同提升，有力服务国家新一轮千亿斤粮食产能提升行动。\n\n“十五五”新征程上，安徽正以科技创新深挖粮食增产潜能，全力建设千亿斤江淮粮仓。而在广袤的淮北平原，那块被三代科研人“驯服”又“武装”起来的砂姜黑土，正以连片翻涌的金黄，给出中国饭碗里的安徽答案。\n\n**来源**：安徽日报\n\n**时间**：2026-9-23\n\n**地点**：安徽亳州\n\n**采编**：姜德惠\n\n**排版**：刘祖尚\n\n![Image 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部署智慧农业与四季接续","https:\u002F\u002Fjx.ifeng.com\u002Fc\u002F8xPB4YCdgGF","《江西省「十五五」农业农村现代化规划》（赣府发〔2026〕16号）围绕32项重点任务展开，明确推进信息技术与农业深度融合，加快农业人工智能技术创新与场景拓展，建设农业农村大数据平台。规划还部署井冈山国家农业科技园区升建国家农高区，推广「村播」「田播」电商直播带货，并开展农产品碳足迹管理与农业碳交易。","（一）提升粮食等重要农产品供给保障水平。坚持产量产能、生产生态、增产增收一起抓，深入实施藏粮于地、藏粮于技战略，落实新一轮粮食产能提升行动，实施粮油作物大面积单产提升行动，建设吨粮片、高产片，促进良田良种良机良法集成增效。优化农产品种植结构，稳定水稻、油菜生产，大力发展油茶产业，提升大豆产能。优化生猪产能综合调控机制，推进牛羊产业扩量提质，促进畜禽养殖节本提质增效。推动农产品品种培优和品质提升，增加营养、健康、风味农产品供给。完善价格、补贴、保险“三位一体”的种粮农民收益保障机制，建立健全与周边省份粮食产销协作机制，强化粮食产购储加销协同保障。\n\n（二）构建多元化食物供给体系。践行大食物观，坚持农林牧渔并举，全方位、多用途开发食物资源。提升“菜篮子”产业质量和效益，推动蔬菜、水果、茶叶、中药材产业优质发展。丰富畜产品供给，发展蜂、兔、肉鸽、鹌鹑等特色养殖。积极发展大水面生态渔业，科学推进稻渔综合种养。发展林下经济，壮大林药和森林食品。发展富硒食品与功能食品，开发新型食品资源。\n\n（三）加强耕地保护与质量提升。严格落实耕地保护党政同责，严守耕地保护红线。统筹农用地布局优化，严格耕地占补平衡管理，规范补充耕地质量验收。科学开展红壤改良利用，推进酸化耕地治理，分阶段实施耕地有机质提升行动。分区分类高质量推进高标准农田建设，对新建和改造提升实行差异化投入，优先在鄱阳湖平原、赣抚平原、吉泰盆地等区域推进整区域建设，逐步把具备条件的永久基本农田建成高标准农田。完善高标准农田立项、建设、验收和管护机制，编制高标准农田建设全流程工作规范，统一建设标准、施工工艺、管理流程，压实管护责任。开展高标准农田整治提升行动，按照“集中修复一批、改造提升一批、疏通灌溉一批、置换退出一批”分类施策，逐步补齐设施短板、消除存量问题。健全完善问题发现响应处置机制。实施大中型灌区现代化建设与改造，推动井冈灌区、赣抚平原灌区等项目建设，强化高标准农田渠系与灌区骨干工程衔接。\n\n（四）提升农业防灾减灾救灾能力。发展韧性农业，完善农业气象、水文、地质灾害等监测预警机制。推进防洪排涝抗旱设施建设，持续开展农田沟渠修复整治、中小河流和平原涝区治理。完善农机应急救灾设施装备条件,健全和落实救灾机具配置、救灾备荒种子储备和应急调用机制，加快补齐烘干、仓储等设施装备短板。强化病虫疫情和重大动物疫病监测预警、联防联控和应急处置，建强县乡动植物疫病防控专业队伍。","凤凰网江西 2026-10-21","2026-10-21T00:00:00Z","政策",80,{"impact":17,"substance":137,"depth":19,"authority":138,"freshness":20,"relevant":22,"comment":139},23,8,"省级「十五五」农业农村现代化规划全文，条款与数字细节充实，涉及智慧农业、高标准农田、粮食产能等实质部署，值得进入每日精选。",[141],{"name":132,"url":129},[27,143,144,145,30],"高标准农田","十五五规划","大食物观",{"code":147,"slug":148,"name":149,"path":150,"parent_code":151},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",[],{"status":154,"locked":14,"version":35,"method":36,"evidence":155},"classified",{"candidates":156,"agricultural_evidence":42},[157,164,168,174,180,184,189,193],{"code":158,"score":159,"supported":42,"title":160,"abstract":162,"tags":163},"J2",11,[161],"农业农村现代化",[161],[],{"code":64,"score":20,"supported":42,"title":165,"abstract":166,"tags":167},[27],[],[27],{"code":147,"score":75,"supported":42,"title":169,"abstract":170,"tags":173},[],[171,172],"农业碳","碳足迹",[],{"code":175,"score":99,"supported":42,"title":176,"abstract":177,"tags":179},"I2",[],[178],"农业人工智能",[],{"code":54,"score":22,"supported":14,"title":181,"abstract":182,"tags":183},[],[],[30],{"code":185,"score":22,"supported":14,"title":186,"abstract":187,"tags":188},"E2",[],[],[145],{"code":59,"score":22,"supported":14,"title":190,"abstract":191,"tags":192},[],[],[143],{"code":194,"score":22,"supported":14,"title":195,"abstract":196,"tags":197},"J1",[],[],[144],[199,200],"江西 十五五 农业农村现代化规划","江西 高标准农田 鄱阳湖平原","江西十五五农业农村现代化规划-5498",0,"2026-10-22T00:06:58.106992Z",{"id":205,"title":206,"url":207,"summary":208,"summary_zh":209,"content":8,"source_name":210,"source_url":207,"published_at":211,"category":212,"cover_url":8,"hotness":13,"is_selected":14,"score":213,"score_detail":214,"sources":218,"tags":220,"primary_topic":224,"secondary_topics":229,"classification":230,"search_phrases":264,"slug":267,"view_count":202,"doi":8,"paper":268,"created_at":286},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。","International Journal of Mechanical Engineering Research and Technology","2026-10-08T00:00:00Z","论文",54,{"impact":138,"substance":215,"depth":216,"authority":87,"freshness":41,"relevant":22,"comment":217},16,14,"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。",[219],{"name":210,"url":207},[27,221,28,222,223],"农业物联网","精准灌溉","光伏农业",{"code":40,"slug":225,"name":226,"path":227,"parent_code":228},"fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",[],{"status":154,"locked":14,"version":35,"method":36,"evidence":231},{"candidates":232,"agricultural_evidence":42},[233,240,247,254,259],{"code":40,"score":19,"supported":42,"title":234,"abstract":236,"tags":239},[235],"fertigation",[45,237,28,238,235],"肥料","fertilizer",[28],{"code":64,"score":241,"supported":42,"title":242,"abstract":243,"tags":246},7,[],[244,245],"精准农业","precision agriculture",[27],{"code":248,"score":241,"supported":42,"title":249,"abstract":250,"tags":253},"I5",[],[251,252],"物联网","IoT",[221],{"code":48,"score":75,"supported":42,"title":255,"abstract":256,"tags":258},[],[51,257],"soil",[],{"code":260,"score":22,"supported":14,"title":261,"abstract":262,"tags":263},"H3",[],[],[222],[265,266],"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":8,"openalex_id":269,"authors":270,"venue":210,"cited_by_count":202,"oa_url":207,"card":279,"direction":283,"ingested_from":285},"W7221424039",[271,273,275,277],{"name":272,"orcid":8},"Niharika Bodake",{"name":274,"orcid":8},"Akshata Gaurkar",{"name":276,"orcid":8},"Vaishnavi Chavan",{"name":278,"orcid":8},"S. K. Godase",{"tldr":280,"method":281,"finding":282,"direction":283,"opportunity":284},"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。","智慧农业 \u002F 农业物联网","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。","openalex","2026-10-11T23:30:16.530895Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":292,"content":8,"source_name":210,"source_url":290,"published_at":211,"category":212,"cover_url":8,"hotness":13,"is_selected":14,"score":293,"score_detail":294,"sources":296,"tags":298,"primary_topic":300,"secondary_topics":301,"classification":302,"search_phrases":328,"slug":331,"view_count":332,"doi":8,"paper":333,"created_at":345},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。",46,{"impact":138,"substance":216,"depth":87,"authority":75,"freshness":75,"relevant":22,"comment":295},"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。",[297],{"name":210,"url":290},[27,251,244,28,299],"可再生能源",{"code":40,"slug":225,"name":226,"path":227,"parent_code":228},[],{"status":154,"locked":14,"version":35,"method":36,"evidence":303},{"candidates":304,"agricultural_evidence":42},[305,310,314,318,322],{"code":40,"score":19,"supported":42,"title":306,"abstract":307,"tags":309},[235],[45,237,28,308,238,235],"养分管理",[28],{"code":64,"score":138,"supported":42,"title":311,"abstract":312,"tags":313},[],[244,245],[27,244],{"code":248,"score":241,"supported":42,"title":315,"abstract":316,"tags":317},[],[251,252],[251],{"code":48,"score":75,"supported":42,"title":319,"abstract":320,"tags":321},[],[51,257],[],{"code":323,"score":99,"supported":42,"title":324,"abstract":325,"tags":327},"H8",[],[326],"可持续农业",[],[329,330],"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":8,"openalex_id":334,"authors":335,"venue":210,"cited_by_count":202,"oa_url":290,"card":340,"direction":283,"ingested_from":285},"W7221368129",[336,337,338,339],{"name":272,"orcid":8},{"name":274,"orcid":8},{"name":276,"orcid":8},{"name":278,"orcid":8},{"tldr":341,"method":342,"finding":343,"direction":283,"opportunity":344},"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。","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。","2026-10-11T23:30:16.034599Z",{"id":347,"title":348,"url":349,"summary":350,"summary_zh":351,"content":8,"source_name":352,"source_url":349,"published_at":353,"category":212,"cover_url":8,"hotness":13,"is_selected":14,"score":354,"score_detail":355,"sources":357,"tags":359,"primary_topic":363,"secondary_topics":364,"classification":365,"search_phrases":392,"slug":395,"view_count":22,"doi":396,"paper":397,"created_at":412},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":138,"substance":19,"depth":86,"authority":216,"freshness":138,"relevant":22,"comment":356},"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。",[358],{"name":352,"url":349},[27,360,28,361,362],"机器学习","养分预测","无土栽培",{"code":40,"slug":225,"name":226,"path":227,"parent_code":228},[],{"status":154,"locked":14,"version":35,"method":36,"evidence":366},{"candidates":367,"agricultural_evidence":42},[368,373,377,383,388],{"code":64,"score":20,"supported":42,"title":369,"abstract":371,"tags":372},[370],"smart agriculture",[],[27],{"code":40,"score":241,"supported":42,"title":374,"abstract":375,"tags":376},[],[45,235],[28],{"code":378,"score":41,"supported":42,"title":379,"abstract":380,"tags":382},"B7",[],[381],"hydroponic",[362],{"code":248,"score":99,"supported":42,"title":384,"abstract":385,"tags":387},[],[386],"农业传感",[],{"code":175,"score":22,"supported":14,"title":389,"abstract":390,"tags":391},[],[],[360],[393,394],"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":396,"openalex_id":398,"authors":399,"venue":352,"cited_by_count":202,"oa_url":349,"card":407,"direction":283,"ingested_from":285},"W7221072509",[400,403,405],{"name":401,"orcid":402},"Shaista Farhat","https:\u002F\u002Forcid.org\u002F0009-0008-9348-8370",{"name":404,"orcid":8},"Dr. Chokka Anuradha",{"name":406,"orcid":8},"Dawit Tafesse Gebreyohannes",{"tldr":408,"method":409,"finding":410,"direction":283,"opportunity":411},"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":414,"title":415,"url":416,"summary":417,"summary_zh":8,"content":418,"source_name":419,"source_url":8,"published_at":420,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":421,"score_detail":422,"sources":424,"tags":426,"primary_topic":429,"secondary_topics":435,"classification":440,"search_phrases":488,"slug":491,"view_count":202,"doi":8,"paper":8,"created_at":492},4460,"中国农科院资划所牵头智慧农作体系观摩会在山东桓台举行 千亩玉米单产提升8%—12%","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F03\u002Fcontent_591573.html","中国农业科学院农业资源与农业区划研究所牵头粮食作物精准智慧化生产管理关键技术与集成示范项目黄淮海麦玉轮作主产区智慧农作体系应用示范观摩会在山东桓台中化MAP桓台农场举行；项目构建以多源感知为基础、智能诊断为核心、农机精准执行为保障、数据平台为中枢的智慧农作技术体系，千亩示范方玉米单产较周边常规种植对照提升8%—12%，优质品率稳定在88%以上，化肥、农药、灌溉用水量较常规种植分别减少10%—15%、8%—10%、12%—18%。","![Image 4](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Findex\u002Fimages\u002Fshare_logo.jpg)\n\n[![Image 5](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Findex\u002Fimages\u002Flogo.png)](http:\u002F\u002Fwww.stdaily.com\u002F)\n\n*   [时政](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fszxw\u002Fnode_357.html)\n*   [热点](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Frdxw\u002Fnode_327.html)\n*   [政务](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fzwxw\u002Fnode_362.html)\n*   [深瞳](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fstbd\u002Fnode_434.html)\n*   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马爱平\n\n近日，由中国农业科学院农业资源与农业区划研究所牵头的“粮食作物精准智慧化生产管理关键技术与集成示范”项目黄淮海麦玉轮作主产区智慧农作体系应用示范观摩会，在山东桓台中化MAP桓台农场举行。\n\n与会人员实地观摩项目针对黄淮海小麦—玉米轮作精准智慧生产现实需求，围绕麦玉种、肥、水、药管理关键环节研发的作物表型监测、精量播种、养分诊断与变量追肥、精准灌溉、病虫害监测与变量喷施等系列新技术、新装备，现场考察了集实时监测、智能诊断、定量调控、变量作业于一体，农艺农机信息深度融合的区域智慧农作技术体系及示范成效。\n\n![Image 8](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F03\u002F591573_4296d9a8-883a-4a2a-98e1-7290f3adff4fcopy.jpg)\n\n据中化MAP桓台农场负责人介绍，这套数字技术解决方案通过精准播种、变量施肥和智能灌溉等核心环节的优化，实现千亩示范方玉米单产较周边常规种植对照提升8%—12%，优质品率稳定在88%以上；同时，实现农业资源的节约，化肥、农药和灌溉用水量较常规种植分别减少10%—15%、8%—10%、12%—18%，资源利用效率得到显著提升，目前已形成面向周边普通农户和新型经营主体的技术培训、推广和辐射服务能力。\n\n![Image 9](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F03\u002F591573_e7499078-dee9-4a40-bf66-504e09cef576copy.jpg)\n\n项目首席科学家吴文斌研究员表示，玉米是我国种植面积最大、产量最高的粮食作物。但长期以来，我国玉米种植生产管理整体偏粗放。播种质量参差不齐，关键农情信息获取滞后，水肥药施用多依赖传统经验，不仅造成玉米单产与先进国家相比有较大差距，也带来农业资源浪费、农田生态压力加大等问题。为此，项目组联合中化MAP团队，选择灌溉条件完善、机械化基础扎实的MAP桓台农场作为核心基地，打造玉米生产方式数字化转型升级示范区。该项目构建一套以多源感知为基础、智能诊断为核心、农机精准执行为保障、数据平台为中枢的智慧农作技术体系，实现玉米种植全过程的数据驱动和精准管控。\n\n（中国农业科学院农业资源与农业区划研究所供图）\n\n责任编辑：陈可轩\n\n相关稿件：\n\n![Image 10](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Fimages\u002Fpinglun.png)网友评论\n\n评论\n\n最热评论\n\n没有更多评论了\n\n[热点](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Frdxw\u002Fnode_327.html)\n\n[![Image 11](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-10\u002F08\u002F592769_1df74a15-67d5-4910-aece-debcc638606a_1009x6734106423copy.JPG)](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-10\u002F08\u002Fcontent_592769.html)\n\n[国庆假期服务消费旺盛 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