[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2355":3,"related-2355":97},{"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":32,"secondary_topics":38,"classification":39,"search_phrases":92,"slug":95,"view_count":55,"doi":8,"paper":8,"created_at":96},2355,"黑龙江省农科院佳木斯分院金秋博览会启幕:5000名种地'老把式'田间取经","https:\u002F\u002Fwww.haas.cn\u002Finfo\u002F6401\u002F336021.htm","9月10日黑龙江省农科院佳木斯分院举办金秋博览会田间观摩会，70位专家现场答疑，5000余种地大户观摩智能除草机器人、气吸式智能播种机等装备；省农科院土壤肥料研究所所长王囡命基于TRPF系统的大豆精准施肥技术为农民及农业科研提供施肥处方8000余份，平均增产10%。",null,"9月10日上午，省农科院佳木斯分院的粮油作物单产提升教练田里人山人海，一场别开生面的金秋田间观摩博览会在这里启幕。现场，智能除草机器人，气吸式智能播种机等智能装备，让5000余名种地“老把式”们看直了眼。70位农业专家被围得里三层外三层，玉米、大豆新品种产量咋样，肥料咋使，病虫害咋防，农机咋选，他们一样样讲，一遍遍答，让农民朋友听入了迷。\n\n一场开在田间地头的“农科盛宴”，打通了农业科技成果转化的“最后一公里”，为农民增产增收筑牢了根基，也为粮食安全“压舱石”增添了底气。\n\n**良种配良肥，丰收“底气”田间来**\n\n看到实验田里的“梅亚合玉44”丰收了，王春风走上前，上下打量株高，又小心翼翼地从玉米棒抠下几粒种子，放在手心里翻来覆去地看。“黄粮、棒大、轴细、马牙粒，一看就是好种子。”这位来自佳木斯市郊区四丰镇的农户说，去年村里有人种了这个品种，产量高、抗倒伏能力强，“我打算明年种上上30亩。”\n\n![Image 1](https:\u002F\u002Fwww.haas.cn\u002F__local\u002F7\u002FD9\u002F42\u002FF21A21376B42C395104183EFDEF_3391D2DD_1C2AD.jpeg?e=.jpeg)\n“合玉44”是省农科院佳木斯分院选育的玉米种子之一，种子经营权由梅亚种业独家买断。“去年，有农户来买玉米种子，点名要合玉44。当时，这款省农科院佳木斯分院培育的玉米种子刚审定，知名度还不高。我挺纳闷，一打听才知道，他是在‘金秋博览会’上看见的。”今年公司销售经理王慧带着团队首次参加博览会。她说，富锦来观摩的农民，来了好几台大客车，大伙儿都认这个活动。“省农科院佳木斯分院不仅培育出好品种，还帮经销商和农户搭建了交流、合作的平台。”\n\n一家来自辽宁沈阳的菌肥摊位上，围满了农户和经销商。这是企业负责人马莹第五次参加“金秋博览会”。“每次参展，都收获满满。这次我们带来了十几款微生物肥，得到很多农民朋友的青睐。”她说，一上午的时间，已经有十多家经销商，留下联系方式，表达了想要进一步合作的意愿。\n\n省农科院佳木斯分院土壤肥料研究所所长王囡囡蹲在试验田边，扒开一垄大豆根际的黑土：“我们依托‘基于TRPF系统的大豆精准施肥技术’，为农民及农业科研提供施肥处方8000余份，平均增产10%，被省农业农村厅推介为黑龙江省主推技术。”眼下，她所在的团队正结合无人机、遥感等技术，研发作物营养诊断及智能施肥模型，研究变量施肥处方图——“将来的‘处方’，能精确到每一块地、每一垄。”\n\n**智能农机显身手黑土地种出“科技范儿”**\n\n由兵器工业集团哈一机集团北方防务公司与杭州灿禾农科技有限公司联合研制的智能除草机器人，也亮相了本次博览会。\n\n灿禾农科技工作人员于晓涵介绍，支撑除草机器人顶部的高清摄像头结合AI视觉识别模块，一眼就能分清草和苗；图像信息传给智能控制器，机器再结合深度传感器与算法，在复杂地形里自主规划行进路线。“机器的行距可设定到15厘米到90厘米之间，适合大豆、玉米、马铃薯、甜菜等多种作物种植环境。精准除草，能让农作物增产10%—15%。这台机器已经卖到了黑龙江、内蒙古、新疆等农业主产区。”\n\n![Image 2](https:\u002F\u002Fwww.haas.cn\u002F__local\u002FD\u002F58\u002FE1\u002FA5219F99AFBA5ECE78A7CC78178_C419D505_33F89.jpeg?e=.jpeg)\n黑龙江省众为农机有限公司带来的一款世耕电驱气吸式智能播种机也颇具人气。总经理李杰介绍，这款播种机可实现“一机两用”，能播2行大垄的玉米，也可以播3行大垄的大豆。“去年，农科院教练田，就是用我们机器播种。这次展会，很多农户对我们的机器非常感兴趣，他们问了机器的价格、参数，希望到厂里参观。”李杰说。\n\n“这是我们联合科研单位、涉农企业，给农民打造一站式的服务盛会。”省农科院佳木斯分院院长丁俊杰介绍，在这次活动中，从智能播种机，到大豆、水稻和玉米品种的选育，再到高产栽培技术和病虫害防治，田间地头都能看到。\n\n他认为，让几千个种地大户同时来观摩最新的技术产品实验，农民“短平快”地在这里学到耕、种、管、收的科学知识，意义很大。“农民朋友刚开始来，是照着葫芦画瓢；随着参加届数的增加，他们从照着葫芦画瓢，变成了照着葫芦画葫芦。”\n\n“不怕农民朋友学得慢，就怕我们工作不持续。”丁俊杰感慨道，“金秋博览会”一届一届办下来，变化写在农民的车轮上。“有农户从开捷达来，到开路虎来，这就是举办活动的意义所在。让农民增产增收，农民富了，国家才能更强，粮食安全才能得到保障。”\n\n正午，田埂上的讲解还在继续，专家讲得细，农民问得勤。这场开在田间地头的博览会，正把科技的种子撒进泥土，长成沉甸甸的丰收。","黑龙江省农业科学院 | 2026-09-10","2026-09-10T00:00:00Z","报道",10,false,66,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},16,17,15,12,6,1,"省级农科院田间博览会报道，智能除草机器人、电驱气吸播种机与精准施肥技术等细节充实，多方信源扎实，但属区域活动、时效稍旧，适合主题聚合而非头条精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"智慧农业","精准施肥","农业科技成果转化","智能农机","种业振兴",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,53,60,66,72,77,82,87],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":52},7,true,[],[50,51],"施肥","肥料",[28],{"code":54,"score":55,"supported":47,"title":56,"abstract":57,"tags":59},"A4",3,[],[58],"大豆",[],{"code":61,"score":55,"supported":47,"title":62,"abstract":63,"tags":65},"F4",[],[64],"除草",[],{"code":67,"score":55,"supported":47,"title":68,"abstract":69,"tags":71},"H2",[],[70],"土壤",[],{"code":73,"score":22,"supported":14,"title":74,"abstract":75,"tags":76},"F1",[],[],[31],{"code":78,"score":22,"supported":14,"title":79,"abstract":80,"tags":81},"F5",[],[],[30],{"code":83,"score":22,"supported":14,"title":84,"abstract":85,"tags":86},"G1",[],[],[29],{"code":88,"score":22,"supported":14,"title":89,"abstract":90,"tags":91},"I1",[],[],[27],[93,94],"农业科技成果转化 智慧农业 智能农机 种业振兴","农业科技成果转化 智慧农业","农业科技成果转化智慧农业智能农机种业振兴-2355","2026-09-14T00:06:26.437168Z",{"total":21,"page":22,"page_size":21,"items":98},[99,185,284,337,404,551],{"id":100,"title":101,"url":102,"summary":103,"summary_zh":104,"content":8,"source_name":105,"source_url":102,"published_at":106,"category":107,"cover_url":8,"hotness":13,"is_selected":14,"score":108,"score_detail":109,"sources":111,"tags":113,"primary_topic":116,"secondary_topics":117,"classification":129,"search_phrases":161,"slug":164,"view_count":165,"doi":8,"paper":166,"created_at":184},4670,"SMART FERTILIZER DISTRIBUTION SYSTEM: A COMPREHENSIVE REVIEW","https:\u002F\u002Fijmert.com\u002Findex.php\u002Fijmert\u002Farticle\u002Fview\u002F334","Agriculture is an important sector for food production and economic development, and the efficient use of fertilizers is essential for achieving better crop growth and productivity. Conventional fertilizer distribution methods largely depend on manual application, which can lead to uneven distribution, excessive fertilizer usage, increased labor requirements, and wastage of agricultural resources. The development of automation and Internet of Things (IoT) technologies has provided new opportunities for improving fertilizer distribution and management in agricultural fields. This review paper presents a comprehensive study of Smart Fertilizer Distribution Systems, focusing on the technologies, control methods, communication techniques, and approaches reported in existing research. Various systems using microcontrollers, IoT devices, wireless communication, web-based platforms, sensors, motor or pump control, driver circuits, and solenoid valves are reviewed. The working principles of automated fertilizer distribution systems and their role in controlling fertilizer flow and reducing manual intervention are discussed. Different communication technologies, including Wi-Fi and other wireless methods, are compared based on their applicability, cost, operating range, reliability, and control capability. The review also examines the major advantages and limitations of existing systems, such as automation, remote operation, improved fertilizer management, reduced labor, network dependency, power requirements, sensor accuracy, and system complexity. A comparative analysis of selected research works is presented to identify the techniques used, their contributions, and the limitations that remain to be addressed. The review further identifies research gaps and discusses future developments such as automatic fertilizer scheduling, multi-zone fertilizer distribution, real-time monitoring, cloud-based data storage, artificial intelligence, machine learning, and integration with renewable energy sources. The study concludes that smart fertilizer distribution can improve the efficiency, accuracy, and sustainability of fertilizer application and has significant potential for future precision agriculture applications.","农业是粮食生产和经济发展的重要部门，而肥料的高效利用对于实现作物更好生长和生产力提升至关重要。传统的肥料分配方法在很大程度上依赖人工施用，这可能导致分配不均、肥料过量使用、劳动力需求增加以及农业资源浪费。自动化和物联网（IoT）技术的发展为改善农田肥料分配与管理提供了新的机遇。本文综述对智能肥料分配系统进行了全面研究，重点关注现有研究中报道的技术、控制方法、通信技术和方法。本文回顾了使用微控制器、物联网设备、无线通信、基于网络的平台、传感器、电机或泵控制、驱动电路和电磁阀的各种系统。讨论了自动化肥料分配系统的工作原理及其在控制肥料流量和减少人工干预方面的作用。基于适用性、成本、工作范围、可靠性和控制能力，比较了包括Wi-Fi和其他无线方法在内的不同通信技术。本综述还考察了现有系统的主要优势和局限性，如自动化、远程操作、改善肥料管理、减少劳动力、网络依赖、功率需求、传感器精度和系统复杂性。本文对选定的研究工作进行了比较分析，以识别所采用的技术、其贡献以及仍有待解决的局限性。本综述进一步指出了研究空白，并讨论了未来发展方向，如自动肥料调度、多区域肥料分配、实时监测、基于云的数据存储、人工智能、机器学习以及与可再生能源的集成。该研究得出结论，智能肥料分配可以提高肥料施用的效率、准确性和可持续性，并在未来精准农业应用中具有巨大潜力。","International Journal of Mechanical Engineering Research and Technology","2026-10-08T00:00:00Z","论文",61,{"impact":20,"substance":17,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":110},"综述性论文系统梳理智能施肥系统的技术路线与研究空白，对智慧农业领域有参考价值，但属文献综述而非原创突破，时效性一般。",[112],{"name":105,"url":102},[27,114,28,115,30],"农业人工智能","农业物联网",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[118,124],{"code":119,"slug":120,"name":121,"path":122,"parent_code":123},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"code":125,"slug":126,"name":127,"path":128,"parent_code":123},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":40,"locked":14,"version":41,"method":42,"evidence":130},{"candidates":131,"agricultural_evidence":47},[132,137,144,151,157],{"code":33,"score":19,"supported":47,"title":133,"abstract":135,"tags":136},[134],"fertilizer",[51,134],[28],{"code":119,"score":13,"supported":47,"title":138,"abstract":139,"tags":143},[],[140,141,142],"机器学习","machine learning","artificial intelligence",[114],{"code":125,"score":13,"supported":47,"title":145,"abstract":146,"tags":150},[],[147,148,149],"物联网","internet of things","IoT",[115],{"code":88,"score":46,"supported":47,"title":152,"abstract":153,"tags":156},[],[154,155],"精准农业","precision agriculture",[27],{"code":78,"score":22,"supported":14,"title":158,"abstract":159,"tags":160},[],[],[30],[162,163],"智能施肥系统 物联网","精准施肥 自动化","智能施肥系统物联网-4670",0,{"doi":8,"openalex_id":167,"authors":168,"venue":105,"cited_by_count":165,"oa_url":102,"card":177,"direction":181,"ingested_from":183},"W7221394563",[169,171,173,175],{"name":170,"orcid":8},"Anjali Manoj Kumbhar",{"name":172,"orcid":8},"Shruti Prashant Kulkarni",{"name":174,"orcid":8},"Snehal Santosh Khune",{"name":176,"orcid":8},"B. B. Godbole",{"tldr":178,"method":179,"finding":180,"direction":181,"opportunity":182},"综述智能施肥系统的技术、控制与通信方法，并指出研究空白与未来方向。","综述基于微控制器、物联网、无线通信、传感器与电磁阀的自动施肥系统研究。","智能施肥可提升施肥效率、精度与可持续性，但存在网络依赖、功耗与传感器精度等局限。","智慧农业 \u002F 农业物联网","可探索AI驱动的自动施肥调度、多区域分配与云边协同的实时精准施肥系统。","openalex","2026-10-11T23:30:16.128775Z",{"id":186,"title":187,"url":188,"summary":189,"summary_zh":190,"content":8,"source_name":191,"source_url":188,"published_at":192,"category":107,"cover_url":8,"hotness":13,"is_selected":14,"score":193,"score_detail":194,"sources":200,"tags":202,"primary_topic":207,"secondary_topics":208,"classification":209,"search_phrases":265,"slug":268,"view_count":269,"doi":270,"paper":271,"created_at":283},5235,"Role of Smart Fertilization in Modern Agriculture","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijpss\u002F2026\u002Fv38i106378","Global food demand is increasing rapidly owing to population growth, placing considerable pressure on agricultural systems to enhance productivity under constraints on natural resources. Although conventional fertiliser use has contributed significantly to improved yields, its excessive and imbalanced application has resulted in soil degradation, nutrient leaching, groundwater contamination, and increased emissions of nitrous oxide (N₂O), thereby reducing nutrient use efficiency (NUE). In this context, smart fertilisation has emerged as a science-driven nutrient management strategy that emphasises the application of the right nutrient source at the right rate, time and place (4R principle), supported by advanced tools such as soil and plant sensors, remote sensing, geographic information systems, and decision-support platforms. Key components include controlled-release fertilisers, nano-fertilisers, bio-formulations, fertigation systems, variable rate technology (VRT), and unmanned aerial vehicle (UAV)-based crop monitoring. Evidence from multi-location field studies across diverse agro-climatic regions of India and other countries indicates that smart fertilisation can enhance nutrient use efficiency by 50–80%, reduce fertiliser input by 19–30%, and improve crop yields by 22–30% in major crops such as rice, wheat, maize and pulses. With the global fertiliser market exceeding USD 200 billion, the adoption of precision nutrient management technologies is gaining momentum. Overall, smart fertilisation offers a sustainable intensification pathway by improving productivity while simultaneously minimising environmental externalities. However, challenges related to technology accessibility, cost, and farmer adoption remain critical constraints that require policy and institutional support.","由于人口增长，全球粮食需求迅速上升，给农业系统带来了巨大压力，要求在自然资源约束下提高生产力。尽管常规施肥对提高产量作出了显著贡献，但过量和不平衡施肥已导致土壤退化、养分淋失、地下水污染以及氧化亚氮（N₂O）排放增加，从而降低了养分利用效率（NUE）。在此背景下，智能施肥作为一种以科学为驱动的养分管理策略应运而生，强调在正确的时间、正确的地点以正确的用量施用正确的养分来源（4R原则），并借助土壤与植物传感器、遥感、地理信息系统和决策支持平台等先进工具加以支撑。其关键组成部分包括控释肥料、纳米肥料、生物制剂、水肥一体化系统、变量施肥技术（VRT）以及基于无人机（UAV）的作物监测。来自印度及其他国家不同农业气候区多点田间研究的数据表明，智能施肥可使养分利用效率提高50%–80%，减少肥料投入19%–30%，并使水稻、小麦、玉米和豆类等主要作物增产22%–30%。随着全球肥料市场规模超过2000亿美元，精准养分管理技术的采用正在加速推进。总体而言，智能施肥通过提高生产力同时最大限度减少环境负外部性，提供了一条可持续集约化路径。然而，技术可及性、成本和农民采用等方面的挑战仍是关键制约因素，需要政策和制度支持。","International Journal of Plant & Soil Science","2026-10-17T00:00:00Z",83,{"impact":195,"substance":195,"depth":196,"authority":197,"freshness":198,"relevant":22,"comment":199},22,18,13,8,"系统综述智能施肥技术体系与多国田间数据，量化增产节肥效果，对智慧农业与绿色投入品方向有参考价值，但属综述性论文且非国内案例，时效与权威度中等。",[201],{"name":191,"url":188},[27,203,28,204,205,206],"无人机","变量施肥","遥感监测","养分利用效率",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":210},{"candidates":211,"agricultural_evidence":47},[212,221,228,235,242,249,254,261],{"code":33,"score":213,"supported":47,"title":214,"abstract":216,"tags":220},20,[215],"fertilization",[50,51,217,218,219],"水肥一体化","养分管理","fertigation",[206,204,28],{"code":222,"score":46,"supported":47,"title":223,"abstract":224,"tags":227},"I3",[],[225,226],"遥感","remote sensing",[205],{"code":229,"score":21,"supported":47,"title":230,"abstract":231,"tags":234},"A1",[],[232,233],"水稻","rice",[],{"code":236,"score":21,"supported":47,"title":237,"abstract":238,"tags":241},"A2",[],[239,240],"小麦","wheat",[],{"code":243,"score":21,"supported":47,"title":244,"abstract":245,"tags":248},"A3",[],[246,247],"玉米","maize",[],{"code":67,"score":21,"supported":47,"title":250,"abstract":251,"tags":253},[],[70,252],"soil",[],{"code":255,"score":21,"supported":47,"title":256,"abstract":257,"tags":260},"I4",[],[258,259],"地理信息","geographic information",[],{"code":88,"score":22,"supported":14,"title":262,"abstract":263,"tags":264},[],[],[27],[266,267],"智能施肥 4R原则","变量施肥技术 无人机","智能施肥4R原则-5235",2,"10.9734\u002Fijpss\u002F2026\u002Fv38i106378",{"doi":270,"openalex_id":272,"authors":273,"venue":191,"cited_by_count":165,"oa_url":188,"card":278,"direction":181,"ingested_from":183},"W7222838957",[274,276],{"name":275,"orcid":8},"S. T. Panusha",{"name":277,"orcid":8},"T. M. Soumya",{"tldr":279,"method":280,"finding":281,"direction":181,"opportunity":282},"综述智能施肥（4R原则+传感器\u002F遥感\u002FVRT）提升养分利用效率与产量的机制与证据。","整合多地点田间试验证据，梳理传感器、遥感、GIS、控释\u002F纳米肥与无人机监测等技术","智能施肥可提高养分利用效率50–80%、减施化肥19–30%、增产22–30%，但受成本与农户采纳制","可研究低成本传感器+无人机变量施肥在小农户场景的适配与采纳机制，及减氮减排的量化评估。","2026-10-18T23:30:07.850055Z",{"id":285,"title":286,"url":287,"summary":288,"summary_zh":8,"content":289,"source_name":290,"source_url":8,"published_at":291,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":292,"score_detail":293,"sources":296,"tags":298,"primary_topic":302,"secondary_topics":303,"classification":304,"search_phrases":332,"slug":335,"view_count":269,"doi":8,"paper":8,"created_at":336},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",63,{"impact":17,"substance":213,"depth":17,"authority":21,"freshness":294,"relevant":22,"comment":295},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。",[297],{"name":290,"url":287},[27,31,217,299,300,301],"寒旱农业","可降解地膜","良种良法",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":305},{"candidates":306,"agricultural_evidence":47},[307,312,316,320,324,328],{"code":33,"score":308,"supported":47,"title":309,"abstract":310,"tags":311},4,[],[217],[217],{"code":88,"score":308,"supported":47,"title":313,"abstract":314,"tags":315},[],[27],[27],{"code":236,"score":55,"supported":47,"title":317,"abstract":318,"tags":319},[],[239],[],{"code":67,"score":55,"supported":47,"title":321,"abstract":322,"tags":323},[],[70],[],{"code":125,"score":55,"supported":47,"title":325,"abstract":326,"tags":327},[],[147],[],{"code":73,"score":269,"supported":14,"title":329,"abstract":330,"tags":331},[],[],[31,301],[333,334],"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":338,"title":339,"url":340,"summary":341,"summary_zh":342,"content":8,"source_name":343,"source_url":340,"published_at":344,"category":107,"cover_url":8,"hotness":13,"is_selected":14,"score":292,"score_detail":345,"sources":347,"tags":349,"primary_topic":351,"secondary_topics":352,"classification":356,"search_phrases":384,"slug":387,"view_count":269,"doi":388,"paper":389,"created_at":403},3920,"Automated Leaf Color Chart (LCC)-BasedNitrogen Fertilizer Recommendation UsingPaddy Leaf Image Color Classification","https:\u002F\u002Fdoi.org\u002F10.70818\u002Fijbass.2026.v07i02.0075","The demand for accurate and timely assessment of crop health is high in precision agriculture to support proper nutrient management. In this work, we present an intelligent deep learning-based solution that evaluates the colour of paddy rice leaves to provide real-time, context-sensitive recommendations regarding the addition of nitrogen fertilizers to grow rice sustainably. For optimum nitrogen management and sustainability in the production of rice crops, an accurate assessment of the color of paddy leaves is required. Herein, we present a deep learning-based framework for paddy leaf color classification with the capability of recommending an appropriate amount of nitrogen fertilizer as needed in real-time. In this research, the Paddy Net dataset containing 12,000 augmented rice leaf images will be used for training the neural network used for classifying the rice leaf's color based on the Leaf Color Chart (LCC) system, which consists of LCC levels from 2 to 5. Additionally, several deep learning architectures were trainedand tested, specifically Custom CNNs, VGG16, ResNet50 and EfficientNetB7, to identify which architecture provided the best classification performance of rice leaf color. In terms of the experimental results, it can be concluded that the Custom CNN with a classification accuracy of 97.55% significantly outperforms the transfer learning models, VGG16 (78.89%) and EfficientNetB7 (78.67%). To also improve practicality, multimodal vision-language model LLa MA 3.2-11B Vision is integrated into the system, allowing it to provide real-time, context-based nitrogen fertilizer recommendations based on visual input images. Additionally, the proposed framework takes into account other agronomic factors such as the growth stage of the crop, type of soil, and fertilizer application history. This allows for more accurate and relevant recommendations. The proposed framework allows for precise and objective nitrogen management without the subjective use of visual assessment methods typically used by farmers. Overall, the proposed system for fertilizer application is significant for the development of precision agriculture because it increases the efficiency of the decision-making process, optimizes the use of fertilizer, and increases the practice of sustainable rice cultivation.","在精准农业中，对作物健康状况进行准确且及时评估的需求很高，以支持合理的养分管理。在这项工作中，我们提出了一种基于深度学习的智能解决方案，通过评估水稻叶片的颜色，实时提供与情境相关的氮肥添加建议，以实现水稻的可持续种植。为了实现水稻作物生产中的优化氮管理和可持续性，需要对水稻叶片颜色进行准确评估。在此，我们提出了一个基于深度学习的稻田叶片颜色分类框架，能够根据实时需求推荐适量的氮肥。在本研究中，包含12,000张增强水稻叶片图像的Paddy Net数据集将用于训练神经网络，该网络基于叶色卡（Leaf Color Chart, LCC）系统对水稻叶片颜色进行分类，LCC等级从2到5。此外，我们训练并测试了多种深度学习架构，特别是自定义CNN、VGG16、ResNet50和EfficientNetB7，以确定哪种架构在水稻叶片颜色分类中表现最佳。从实验结果可以得出结论，自定义CNN以97.55%的分类准确率显著优于迁移学习模型VGG16（78.89%）和EfficientNetB7（78.67%）。为提高实用性，系统还集成了多模态视觉语言模型LLaMA 3.2-11B Vision，使其能够基于视觉输入图像提供实时、基于情境的氮肥推荐。此外，所提出的框架还考虑了其他农艺因素，如作物生长阶段、土壤类型和施肥历史，从而提供更准确和相关的建议。该框架实现了精确、客观的氮管理，避免了农民通常采用的主观视觉评估方法。总体而言，所提出的施肥系统对精准农业的发展具有重要意义，因为它提高了决策过程的效率，优化了肥料使用，并促进了可持续水稻种植实践。","International Journal of Business Arts and Scientific Study","2026-09-30T00:00:00Z",{"impact":20,"substance":213,"depth":18,"authority":21,"freshness":198,"relevant":22,"comment":346},"用深度学习与视觉语言模型实现水稻叶色分级与氮肥实时推荐，方法新颖、数据规模可观，但期刊影响力有限，属细分领域技术进展。",[348],{"name":343,"url":340},[27,114,28,232,350],"氮肥管理",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[353],{"code":229,"slug":233,"name":232,"path":354,"parent_code":355},"\u002Ftopic\u002Ffield-crops\u002Frice","A",{"status":40,"locked":14,"version":41,"method":42,"evidence":357},{"candidates":358,"agricultural_evidence":47},[359,364,370,374,380],{"code":33,"score":360,"supported":47,"title":361,"abstract":362,"tags":363},19,[134],[50,51,218,134],[350,28],{"code":229,"score":13,"supported":47,"title":365,"abstract":366,"tags":369},[],[232,367,233,368],"稻田","paddy",[232],{"code":88,"score":46,"supported":47,"title":371,"abstract":372,"tags":373},[],[154,155],[27],{"code":119,"score":46,"supported":47,"title":375,"abstract":376,"tags":379},[],[377,378],"深度学习","deep learning",[114],{"code":67,"score":21,"supported":47,"title":381,"abstract":382,"tags":383},[],[70,252],[],[385,386],"水稻 叶片颜色 氮肥推荐","Paddy Net 深度学习 叶色卡","水稻叶片颜色氮肥推荐-3920","10.70818\u002Fijbass.2026.v07i02.0075",{"doi":388,"openalex_id":390,"authors":391,"venue":343,"cited_by_count":165,"oa_url":340,"card":397,"direction":401,"ingested_from":183},"W7214974109",[392,394],{"name":393,"orcid":8},"Rusanara Akhter",{"name":395,"orcid":396},"Md Zahidul Islam","https:\u002F\u002Forcid.org\u002F0000-0002-4868-4945",{"tldr":398,"method":399,"finding":400,"direction":401,"opportunity":402},"用深度学习对水稻叶片颜色分级，并结合多模态大模型实时推荐氮肥用量。","Paddy Net 1.2万张增强叶片图像，训练Custom CNN、VGG16","Custom CNN分类准确率达97.55%，显著优于VGG16（78.89%）和Efficient","农业人工智能与决策模型","可探索轻量化模型部署到手机端，并结合多源农情数据提升跨品种、跨区域推荐泛化能力。","2026-10-01T23:30:59.367113Z",{"id":405,"title":406,"url":407,"summary":408,"summary_zh":409,"content":8,"source_name":410,"source_url":407,"published_at":411,"category":107,"cover_url":8,"hotness":13,"is_selected":14,"score":412,"score_detail":413,"sources":416,"tags":418,"primary_topic":420,"secondary_topics":422,"classification":430,"search_phrases":490,"slug":493,"view_count":55,"doi":494,"paper":495,"created_at":550},3759,"Synergistic interaction effects of precision phosphorus fertigation and residue management on productivity, profitability, and resource-use efficiency of wheat under conservation agriculture","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1944629","Phosphorus (P) management under conventional surface-broadcast application in calcareous soils of the Indo-Gangetic Plains (IGP) suffers from severe fixation losses, limiting phosphorus-use efficiency (PUE) to 10–25% and contributing to yield gaps in wheat, a globally important food security crops. A two-year (2023–24 and 2024–25) split-plot field experiment was conducted within a mid-term conservation agriculture (CA)-based maize-wheat-greengram system to evaluate nine phosphorus fertigation levels and split application schedules through subsurface drip fertigation (SSDF), combined with two residue management practices (retention: R+, no-retention: R-), on growth, yield, water productivity, economics, and resource-use efficiency and post-harvest available phosphorus of wheat (cv. HD 2967). Treatments included no-P (control), SSDF of P as DAP at 50, 75, and 100% of the recommended dose (RDP; 60 kg P 2 O 5 ha −1 ) applied either fully as basal (10 DAS) or split (10 and 25 DAS), along with a nano-DAP foliar spray, compared against conventional CA with flood irrigation and basal broadcast P (CA-FI-100% RDP-B). SSDF treatments consumed only 178–275 mm of total water input against 437–452 mm under flood irrigation. Among SSDF treatments, 100% RDP applied in two splits (100% RDP-2S) consistently recorded the highest growth attributes, grain yield (6.23 and 6.31 t ha −1 ), and economic returns (BCR: 1.8–2) across both years, improving grain yield by 10.6–11.5% and net returns by 13.7% over CA-FI-100% RDP-B. Notably, 75% RDP-2S was statistically comparable to 100% RDP-2S for yield and profitability, demonstrating that a 25% reduction in P dose under precision SSDF does not compromise productivity. Total and irrigation water productivity improved by 127.7 and 156.7%, respectively, under 100% RDP-2S over CA-FI-100% RDP-B. Residue retention further enhanced productivity, increasing grain yield by 14.0–15.0% and net returns by 26.4–27.5%. Post-harvest soil available P was 18.0 and 43.3% higher under SSDF than under CA-FI-100% RDP-B at 0–15 and 15–30 cm, respectively. The interaction of split P fertigation and residue retention was consistently superior for grain yield and water productivity. These findings establish 75–100% RDP delivered through split SSDF, combined with residue retention, as an agronomically superior, water-efficient, economically viable strategy for sustainable wheat intensification in the semi-arid IGPs.","在印度河-恒河平原（IGP）石灰性土壤上，常规地表撒施条件下的磷（P）管理面临严重的固定损失，导致磷利用效率（PUE）仅为10–25%，并造成小麦——一种全球重要的粮食安全作物——的产量差距。在中期保护性农业（CA）为基础的玉米-小麦-绿豆轮作体系中，开展了一项为期两年（2023–24和2024–25）的裂区田间试验，评估九种磷肥滴灌水平和分次施用方案通过地下滴灌施肥（SSDF）对小麦（品种HD 2967）生长、产量、水分生产力、经济效益、资源利用效率及收获后土壤有效磷的影响，并结合两种秸秆管理方式（还田：R+，不还田：R-）。处理包括：无磷（对照）、以DAP形式通过SSDF施用推荐施磷量（RDP；60 kg P₂O₅ ha⁻¹）的50%、75%和100%，分别以全部基施（播种后10天）或分次施用（播种后10天和25天），同时配合纳米DAP叶面喷施，并与常规保护性农业配合漫灌和基施撒施磷（CA-FI-100% RDP-B）进行比较。SSDF处理的总水分投入仅为178–275 mm，而漫灌条件下为437–452 mm。在SSDF处理中，100% RDP分两次施用（100% RDP-2S）在两年中均持续表现出最高的生长指标、籽粒产量（6.23和6.31 t ha⁻¹）和经济效益（BCR：1.8–2），较CA-FI-100% RDP-B分别提高籽粒产量10.6–11.5%和净收益13.7%。值得注意的是，75% RDP-2S在产量和盈利能力上与100% RDP-2S无统计学差异，表明在精准SSDF下减少25%的磷用量不会影响生产力。与CA-FI-100% RDP-B相比，100% RDP-2S处理下总水分生产力和灌溉水分生产力分别提高了127.7%和156.7%。秸秆还田进一步提高了生产力，使籽粒产量增加14.0–15.0%，净收益增加26.4–27.5%。收获后土壤有效磷在0–15 cm和15–30 cm土层中，SSDF较CA-FI-100% RDP-B分别高出18.0%和43.3%。分次磷肥滴灌与秸秆还田的交互作用在籽粒产量和水分生产力方面始终表现最优。这些研究结果表明，通过分次SSDF施用75–100% RDP并结合秸秆还田，是一种农艺上优越、水分高效、经济可行的策略，可用于半干旱印度河-恒河平原小麦的可持续集约化生产。","Frontiers in Sustainable Food Systems","2026-09-28T00:00:00Z",80,{"impact":196,"substance":195,"depth":196,"authority":197,"freshness":414,"relevant":22,"comment":415},9,"两年田间试验证实分次地下滴灌施磷配合秸秆还田可减磷25%并显著提升小麦产量与水肥利用效率，数据扎实、结论可靠，对半干旱地区精准水肥管理有直接参考价值。",[417],{"name":410,"url":407},[27,28,239,419,217],"保护性耕作",{"code":236,"slug":240,"name":239,"path":421,"parent_code":355},"\u002Ftopic\u002Ffield-crops\u002Fwheat",[423,424],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"code":425,"slug":426,"name":427,"path":428,"parent_code":429},"H8","sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture","H",{"status":40,"locked":14,"version":41,"method":42,"evidence":431},{"candidates":432,"agricultural_evidence":47},[433,437,441,446,450,457,461,468,474,480,486],{"code":33,"score":17,"supported":47,"title":434,"abstract":435,"tags":436},[219],[50,219],[217,28],{"code":236,"score":19,"supported":47,"title":438,"abstract":439,"tags":440},[240],[239,240],[239],{"code":425,"score":20,"supported":47,"title":442,"abstract":444,"tags":445},[443],"conservation agriculture",[443],[419],{"code":243,"score":21,"supported":47,"title":447,"abstract":448,"tags":449},[],[246,247],[],{"code":451,"score":21,"supported":47,"title":452,"abstract":453,"tags":456},"A8",[],[454,455],"粮食安全","food security",[],{"code":67,"score":21,"supported":47,"title":458,"abstract":459,"tags":460},[],[70,252],[],{"code":462,"score":21,"supported":47,"title":463,"abstract":464,"tags":467},"H3",[],[465,466],"灌溉","irrigation",[],{"code":469,"score":55,"supported":47,"title":470,"abstract":471,"tags":473},"A7",[],[472],"轮作",[],{"code":475,"score":55,"supported":47,"title":476,"abstract":477,"tags":479},"H5",[],[478],"秸秆还田",[],{"code":481,"score":55,"supported":47,"title":482,"abstract":483,"tags":485},"H7",[],[484],"干旱",[],{"code":88,"score":22,"supported":14,"title":487,"abstract":488,"tags":489},[],[],[27],[491,492],"地下滴灌 磷肥 小麦","保护性耕作 秸秆还田 小麦","地下滴灌磷肥小麦-3759","10.3389\u002Ffsufs.2026.1944629",{"doi":494,"openalex_id":496,"authors":497,"venue":410,"cited_by_count":165,"oa_url":407,"card":545,"direction":181,"ingested_from":183},"W7214579192",[498,500,503,505,507,509,511,514,516,518,520,522,524,527,529,531,534,537,540,543],{"name":499,"orcid":8},"Kadagonda Nithinkumar",{"name":501,"orcid":502},"Anchal Dass","https:\u002F\u002Forcid.org\u002F0000-0003-3909-1803",{"name":504,"orcid":8},"Devika A. R.",{"name":506,"orcid":8},"Arjun Singh",{"name":508,"orcid":8},"Susama Sudhishri",{"name":510,"orcid":8},"Vinod Kumar Singh",{"name":512,"orcid":513},"Sanjay Singh Rathore","https:\u002F\u002Forcid.org\u002F0000-0001-6725-1478",{"name":515,"orcid":8},"Sarvendra Kumar",{"name":517,"orcid":8},"Teekam Singh",{"name":519,"orcid":8},"Jitendra Rajput",{"name":521,"orcid":8},"Pravin Kumar Upadhyaya",{"name":523,"orcid":8},"R. N. Sahoo",{"name":525,"orcid":526},"ARPULA SAIRAM","https:\u002F\u002Forcid.org\u002F0009-0009-9034-6032",{"name":528,"orcid":8},"Aye Aye San",{"name":530,"orcid":8},"K. S. Sachin",{"name":532,"orcid":533},"Mummasani Asritha","https:\u002F\u002Forcid.org\u002F0009-0002-4619-9943",{"name":535,"orcid":536},"Ramanjit Kaur","https:\u002F\u002Forcid.org\u002F0000-0001-5117-050X",{"name":538,"orcid":539},"Mona Nagargade","https:\u002F\u002Forcid.org\u002F0000-0003-1062-512X",{"name":541,"orcid":542},"Vishal Tyagi","https:\u002F\u002Forcid.org\u002F0000-0001-5593-3076",{"name":544,"orcid":8},"Subhash Babu",{"tldr":546,"method":547,"finding":548,"direction":181,"opportunity":549},"研究保护性农业下精准磷肥滴灌与秸秆还田对小麦产量、收益和资源效率的协同效应。","两年裂区田间试验，地下滴灌分次施磷与秸秆还田处理，测产量、水生产力与经济指标。","75–100%推荐磷量分次滴灌配秸秆还田可增产10%以上、节水超一倍且不减产。","可探索基于土壤磷素实时监测的变量施磷决策模型，并与秸秆还田互作机制结合优化。","2026-09-29T23:30:06.859116Z",{"id":552,"title":553,"url":554,"summary":555,"summary_zh":8,"content":556,"source_name":557,"source_url":8,"published_at":558,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":559,"score_detail":560,"sources":563,"tags":565,"primary_topic":568,"secondary_topics":569,"classification":570,"search_phrases":594,"slug":597,"view_count":22,"doi":8,"paper":8,"created_at":598},3699,"让智慧农业技术扎根更多田块——天津静海政协专题协商纪实","https:\u002F\u002Fwww.rmzxw.com.cn\u002Fc\u002F2026-09-23\u002F3979822.shtml","天津市静海区政协围绕智能农业水肥一体化开展专题视察，发现水分利用率达90%以上，但简易设备每亩约500元、大田利润薄、农户主动应用意愿不强。委员建议每年举办培训班、建设示范基地、对接高校科研院所研发简便便宜设备、完善农业节水政策。","本报讯（通讯员 赵泽宇 刘弋涵 记者 李宁馨）麦收渐远，玉米拔节。田垄间，一条条滴灌带像毛细血管，把水肥精准送到作物根部；大棚里，喷药机器人、多功能水肥一体机次第铺开；直播间里，紫苏产品、香油、冬菜正被一单单拍下。这幅智慧农业图景背后，有着天津市静海区政协农业界别委员们一次次调研、一场场协商的身影。\n\n“一亩地到底能省多少水、增多少产？”合作社的玉米田边，静海区政协主席会议成员带着委员们蹲下身，拨开土层查看滴灌带的铺设情况，向合作社负责人细细追问。这是区政协农业和农村委围绕“智能农业水肥一体化”开展专题视察的一幕。委员们走进有机肥生产车间、水肥一体化灌溉现场和智能农机应用场景，一边看一边记，把问题清单带回了座谈会。\n\n近几年，静海区在多个农业合作社开展了初级智能水肥一体化应用示范。委员们看重的不仅是降本增效，更是生态效益——水分利用率达到90%以上，滴灌不破坏土壤结构，化肥流失大幅减少。“这不是简单的省水省肥，而是农业生产方式的一次转型。”委员们同时发现：一套简易设备每亩约500元，大田利润薄，农户主动应用意愿不强；部分农田水利设施与微灌、喷灌不配套；技术培训覆盖不够，农村青年劳动力又不足。\n\n随着调研协商的不断深入，委员们提出，每年举办初级智能水肥一体化培训班；建设不同模式的示范基地，配备墒情自动监测站；对接高校、科研院所和智慧农业企业，研发更简便、更便宜的设备和肥料；完善农业节水政策，鼓励新型经营主体先用起来。\n\n水肥一体化技术应用只是静海智慧农业发展的一角。“打造智慧农业应用场景，科技赋能农业产业提质增效”专题视察中，委员们走进天津智能农业研究院，喷药机器人、多功能水肥一体机、装配式柔性多源蓄热智能日光温室等应用场景让委员们深受启发。\n\n“智能农机实现自动化、精准化作业，专业系统做数据分析和决策支持，效率和资源利用率还能再提。”在委员们看来，智能农机与智慧农业的结合是现代农业发展的重要方向，要让技术从实验室走向田垄，要整合特色农产品资源，让好产品卖出好价钱。\n\n委员们深入崇泰庄园和春光农场开展走访服务，邀请规划资源、文旅、乡镇等多部门参与，围绕智慧农业、特色文化资源禀赋和农文旅康养融合发展开展协商。委员们提出坚持规划引领、注重整体推进、补强体验链条、强化宣传推介等建议，为乡村产业振兴寻找新的增长点。\n\n一块田连着一条链，良种、良法与良机，在委员们的视野里拼成一幅完整的美丽乡村图景。“调研问需—协商问策—跟踪问效”的履职方式，正让智慧农业建议一步步落到田间。静海区政协农业和农村委相关负责人表示，将持续聚焦智慧农业发展、乡村振兴等重点领域，深入开展调研、积极建言献策，让智慧农业技术在更多田块扎根。","人民政协网","2026-09-23T00:28:00Z",49,{"impact":198,"substance":561,"depth":197,"authority":414,"freshness":294,"relevant":22,"comment":562},14,"地方政协专题协商纪实，呈现水肥一体化推广中的成本、设施与培训短板及建议，有实质内容但属区域动态，公共价值有限。",[564],{"name":557,"url":554},[27,566,30,217,567],"乡村振兴","农业节水",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":571},{"candidates":572,"agricultural_evidence":47},[573,577,581,585,589],{"code":88,"score":414,"supported":47,"title":574,"abstract":575,"tags":576},[27],[],[27],{"code":33,"score":308,"supported":47,"title":578,"abstract":579,"tags":580},[],[217],[217],{"code":462,"score":55,"supported":47,"title":582,"abstract":583,"tags":584},[],[567],[],{"code":78,"score":22,"supported":14,"title":586,"abstract":587,"tags":588},[],[],[30],{"code":590,"score":22,"supported":14,"title":591,"abstract":592,"tags":593},"G",[],[],[566],[595,596],"天津静海 水肥一体化","静海区政协 智慧农业","天津静海水肥一体化-3699","2026-09-29T00:08:19.232767Z"]