[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2860":3,"related-2860":60},{"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":24,"tags":26,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":59},2860,"Optimization of fish feed formulation and pH regulation in on-demand coupled aquaponic systems: A model-based framework for sustainable nutrient and water management","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112358","Optimization of fish feed formulation and pH regulation in on-demand coupled aquaponic systems: A model-based framework for sustainable nutrient and water management。Computers and Electronics in Agriculture","按需耦合鱼菜共生系统中鱼饲料配方与pH调控的优化：面向可持续养分与水管理的模型框架。《农业中的计算机与电子学》",null,"Computers and Electronics in Agriculture","2026-09-17T00:00:00Z","论文",10,false,73,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,20,18,14,9,1,"模型驱动的鱼菜共生饲料与pH协同优化研究，方法新颖但属细分领域学术进展，产业影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"智慧农业","水产养殖","循环水养殖","精准投喂","水质调控",[33,34],"鱼菜共生 饲料配方 pH调控","循环水养殖 智慧农业 水产养殖 水质调控","鱼菜共生饲料配方pH调控-2860",0,"10.1016\u002Fj.compag.2026.112358",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":6,"card":52,"direction":56,"ingested_from":58},"W7213511453",[41,43,46,49],{"name":42,"orcid":9},"Patrick Nestler",{"name":44,"orcid":45},"Christopher Shaw","https:\u002F\u002Forcid.org\u002F0000-0002-3521-0046",{"name":47,"orcid":48},"Werner Kloas","https:\u002F\u002Forcid.org\u002F0000-0001-8905-183X",{"name":50,"orcid":51},"Stefan Streif","https:\u002F\u002Forcid.org\u002F0000-0002-3398-1226",{"tldr":53,"method":54,"finding":55,"direction":56,"opportunity":57},"构建模型框架优化按需耦合鱼菜共生系统的鱼饲料配方与pH调控，实现养分和水可持续管理。","基于模型的优化框架，耦合鱼饲料配方与pH调节，用于按需耦合鱼菜共生系统。","模型框架可优化饲料配方与pH调控，提升养分利用效率并减少水资源消耗。","农业绿色发展与碳","可结合实时传感器数据与机器学习，开发动态自适应调控模型，拓展至多物种共生系统。","openalex","2026-09-18T23:30:01.449988Z",{"total":61,"page":22,"page_size":61,"items":62},6,[63,107,153,201,239,274],{"id":64,"title":65,"url":66,"summary":67,"summary_zh":68,"content":9,"source_name":69,"source_url":66,"published_at":70,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":71,"score_detail":72,"sources":77,"tags":79,"search_phrases":82,"slug":85,"view_count":36,"doi":86,"paper":87,"created_at":106},2020,"Decision support in recirculating aquaculture systems (RAS): A case study of a human–AI interface in prawn hatchery operation","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.atech.2026.102554","The need for sustainable and responsible production in aquaculture calls for innovative implementation of recirculating aquaculture systems (RAS), which are extraordinarily complex, requiring the integration of various fields of science and technology to reach the desired productivity. In this case study, we report a four-month observation using a large language model (LLM) that – collaboratively with human expertise – analyzed and resolved complex challenges in a Macrobrachium rosenbergii RAS hatchery. Unacceptable larval and post-larval mortality prompted the integration into hatchery management of an AI decision-support system as a strategic management partner, enabling exploration across chemical, biological, physical, engineering, and behavioral domains. Key interventions suggested by the AI agent included mineral balance recalibration, microbial load diagnostics, behavioral pattern decoding, and lighting and flow engineering. Outcomes were evaluated in terms of a reduction in larval mortality and improved rates of larval metamorphosis to post larvae. Central to the process was the presence of a guiding human entity, steering AI's analytical power through deliberate questioning and contextual framing. This case study suggests that AI has the potential to improve intensive aquaculture systems. However, the tendency of AI agents to oversimplify complex systems requires the direction and guidance of a human expert to lead AI-human conversations. The adoption of LLMs in RAS-based aquaculture, bridging the gaps between raw data and actionable insights, has the potential to drive both the efficiency and the long-term sustainability of the aquaculture industry.","水产养殖可持续和负责任生产的需要，要求创新性地实施循环水养殖系统（RAS），该系统极为复杂，需要整合各种科学和技术领域以实现理想的生产力。在本案例研究中，我们报告了一项为期四个月的观察，使用大型语言模型（LLM）与人类专业知识协作，分析和解决了罗氏沼虾（Macrobrachium rosenbergii）RAS孵化场中的复杂挑战。不可接受的幼体和后期幼体死亡率促使将AI决策支持系统作为战略管理伙伴纳入孵化场管理，从而能够在化学、生物、物理、工程和行为领域进行探索。AI代理建议的关键干预措施包括矿物质平衡重新校准、微生物负荷诊断、行为模式解码以及光照和水流工程。结果通过幼体死亡率的降低和幼体变态为后期幼体的比率提高来评估。该过程的核心是有一个指导性的人类实体，通过有意的提问和情境构建来引导AI的分析能力。本案例研究表明，AI有潜力改善集约化水产养殖系统。然而，AI代理倾向于过度简化复杂系统，需要人类专家的指导和引导来主导AI与人类的对话。在基于RAS的水产养殖中采用LLM，弥合原始数据与可操作见解之间的差距，有潜力推动水产养殖行业的效率和长期可持续性。","Smart Agricultural Technology","2026-09-07T00:00:00Z",78,{"impact":19,"substance":73,"depth":19,"authority":74,"freshness":75,"relevant":22,"comment":76},21,13,8,"核心期刊发表的LLM辅助RAS对虾育苗决策案例，方法新颖、结论有实证支撑，对智慧水产养殖具参考价值，值得进入每日精选。",[78],{"name":69,"url":66},[27,80,81,28,29],"农业人工智能","大语言模型",[83,84],"农业人工智能 大语言模型 循环水养殖 智慧农业","农业人工智能 大语言模型","农业人工智能大语言模型循环水养殖智慧农业-2020","10.1016\u002Fj.atech.2026.102554",{"doi":86,"openalex_id":88,"authors":89,"venue":69,"cited_by_count":36,"oa_url":98,"card":99,"direction":105,"ingested_from":58},"W7167492172",[90,93,95],{"name":91,"orcid":92},"Shai Avraham Shaked","https:\u002F\u002Forcid.org\u002F0000-0003-1995-6419",{"name":94,"orcid":9},"Assaf Shechter",{"name":96,"orcid":97},"Amir Sagi","https:\u002F\u002Forcid.org\u002F0000-0002-4229-1059","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2772375526007793\u002Fpdf",{"tldr":100,"method":101,"finding":102,"direction":103,"opportunity":104},"用大语言模型辅助人类专家，解决罗氏沼虾RAS育苗中幼体高死亡率问题。","四个月案例观察，LLM与人类专家协作分析化学、生物、工程等多域数据。","AI建议的矿物质平衡、微生物诊断等干预降低了幼体死亡率并提高变态率。","农业人工智能与决策模型","可研究LLM在RAS多参数耦合决策中的可解释性与人机协同机制，避免过度简化。","智慧农业 \u002F 农业物联网","2026-09-10T23:30:03.364805Z",{"id":108,"title":109,"url":110,"summary":111,"summary_zh":112,"content":9,"source_name":10,"source_url":110,"published_at":113,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":71,"score_detail":114,"sources":116,"tags":118,"search_phrases":121,"slug":124,"view_count":36,"doi":125,"paper":126,"created_at":152},2281,"Artificial intelligence-enabled aquacultural engineering systems: A design-oriented review of sensing, modelling, and deployment architectures","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112353","Artificial intelligence-enabled aquacultural engineering systems: A design-oriented review of sensing, modelling, and deployment architectures。Computers and Electronics in Agriculture","人工智能赋能的水产养殖工程系统：面向设计的传感、建模与部署架构综述。农业中的计算机与电子学","2026-09-11T00:00:00Z",{"impact":19,"substance":18,"depth":19,"authority":20,"freshness":75,"relevant":22,"comment":115},"核心期刊发表的水产养殖AI工程系统设计综述，涵盖感知、建模与部署架构，对智慧渔业技术路线有参考价值，但属综述类论文，产业落地影响有限。",[117],{"name":10,"url":110},[27,80,28,119,120],"智能传感","数字渔业",[122,123],"农业人工智能 数字渔业 智慧农业 智能传感","农业人工智能 数字渔业","农业人工智能数字渔业智慧农业智能传感-2281","10.1016\u002Fj.compag.2026.112353",{"doi":125,"openalex_id":127,"authors":128,"venue":10,"cited_by_count":36,"oa_url":110,"card":147,"direction":105,"ingested_from":58},"W7212232512",[129,132,135,138,141,144],{"name":130,"orcid":131},"V. Ravi Sankar","https:\u002F\u002Forcid.org\u002F0000-0002-8580-2920",{"name":133,"orcid":134},"Alzayat Saleh","https:\u002F\u002Forcid.org\u002F0000-0001-6973-019X",{"name":136,"orcid":137},"Armin Ehrampoosh","https:\u002F\u002Forcid.org\u002F0000-0002-5482-3454",{"name":139,"orcid":140},"Phoebe Arbon","https:\u002F\u002Forcid.org\u002F0000-0003-0171-6302",{"name":142,"orcid":143},"Dean R. Jerry","https:\u002F\u002Forcid.org\u002F0000-0003-3735-1798",{"name":145,"orcid":146},"Mostafa Rahimi Azghadi","https:\u002F\u002Forcid.org\u002F0000-0001-7975-3985",{"tldr":148,"method":149,"finding":150,"direction":105,"opportunity":151},"综述AI赋能水产养殖工程系统，从感知、建模到部署架构的设计视角。","设计导向综述，梳理传感器、AI建模与部署架构。","提出面向水产养殖的AI工程系统设计框架与架构分类。","可针对水产养殖场景的轻量化边缘AI与多模态传感融合部署开展实证研究。","2026-09-13T23:30:01.790828Z",{"id":154,"title":155,"url":156,"summary":157,"summary_zh":158,"content":9,"source_name":10,"source_url":156,"published_at":70,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":159,"score_detail":160,"sources":164,"tags":166,"search_phrases":169,"slug":172,"view_count":36,"doi":173,"paper":174,"created_at":200},1881,"A multi-objective bi-level path planning method for a feeding robot in land-based intensive aquaculture facilities","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112346","A multi-objective bi-level path planning method for a feeding robot in land-based intensive aquaculture facilities。Computers and Electronics in Agriculture","陆基集约化水产养殖设施中投喂机器人多目标双层路径规划方法。Computers and Electronics in Agriculture",62,{"impact":17,"substance":19,"depth":161,"authority":20,"freshness":162,"relevant":22,"comment":163},16,2,"针对水产养殖投喂机器人的多目标双层路径规划方法，发表于核心期刊，具有专业深度，但影响范围限于细分领域，时效性较低。",[165],{"name":10,"url":156},[27,167,168,28],"路径规划","机器人",[170,171],"智慧农业 水产养殖 路径规划 机器人","智慧农业 水产养殖","智慧农业水产养殖路径规划机器人-1881","10.1016\u002Fj.compag.2026.112346",{"doi":173,"openalex_id":175,"authors":176,"venue":10,"cited_by_count":36,"oa_url":9,"card":195,"direction":105,"ingested_from":58},"W7211896525",[177,180,183,186,189,191,193],{"name":178,"orcid":179},"Yanxin Wang","https:\u002F\u002Forcid.org\u002F0000-0002-4105-7172",{"name":181,"orcid":182},"Xiaochan Wang","https:\u002F\u002Forcid.org\u002F0000-0003-0461-8417",{"name":184,"orcid":185},"Shaoxuan Hu","https:\u002F\u002Forcid.org\u002F0000-0002-4422-1388",{"name":187,"orcid":188},"Yu Shi","https:\u002F\u002Forcid.org\u002F0009-0000-5897-2070",{"name":190,"orcid":9},"Lei Wang",{"name":192,"orcid":9},"Xuekai Huang",{"name":194,"orcid":9},"Bojun Xu",{"tldr":196,"method":197,"finding":198,"direction":105,"opportunity":199},"提出陆基集约化养殖投喂机器人的多目标双层路径规划方法。","多目标双层路径规划，上层全局规划，下层局部避障。","该方法能有效平衡路径长度与能耗，提高投喂效率。","可探索动态环境下多机器人协同投喂的路径规划，或结合实时水质数据优化投喂路径。","2026-09-08T23:30:01.549698Z",{"id":202,"title":203,"url":204,"summary":205,"summary_zh":206,"content":9,"source_name":10,"source_url":204,"published_at":207,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":159,"score_detail":208,"sources":210,"tags":212,"search_phrases":215,"slug":218,"view_count":36,"doi":219,"paper":220,"created_at":238},1820,"Numerical simulation of water dynamics and wastewater treatment effect in spiral substrate for recirculating aquaculture systems of Apostichopus japonicus","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112373","Numerical simulation of water dynamics and wastewater treatment effect in spiral substrate for recirculating aquaculture systems of Apostichopus japonicus。Computers and Electronics in Agriculture","刺参循环水养殖系统中螺旋基质的水动力学与废水处理效果数值模拟。《计算机与电子在农业中的应用》","2026-09-06T00:00:00Z",{"impact":17,"substance":19,"depth":161,"authority":20,"freshness":162,"relevant":22,"comment":209},"针对刺参循环水养殖螺旋基质的数值模拟研究，方法新颖，但影响范围限于细分领域，时效性较低。",[211],{"name":10,"url":204},[27,28,213,214],"数值模拟","循环水系统",[216,217],"循环水系统 数值模拟 智慧农业 水产养殖","循环水系统 数值模拟","循环水系统数值模拟智慧农业水产养殖-1820","10.1016\u002Fj.compag.2026.112373",{"doi":219,"openalex_id":221,"authors":222,"venue":10,"cited_by_count":36,"oa_url":9,"card":233,"direction":105,"ingested_from":58},"W7210275851",[223,225,227,229,231],{"name":224,"orcid":9},"Chenyu Song",{"name":226,"orcid":9},"Yijing Zhou",{"name":228,"orcid":9},"Ruiguang Dong",{"name":230,"orcid":9},"Xiefa Song",{"name":232,"orcid":9},"Meng Li",{"tldr":234,"method":235,"finding":236,"direction":105,"opportunity":237},"模拟循环水养殖系统中螺旋基质的流场与净水效果，优化刺参养殖。","数值模拟（CFD）分析水动力与废水处理效果。","螺旋基质可改善水流分布并增强废水处理能力。","可延伸研究不同基质的流固耦合优化，结合物联网实时监控水质，实现智能调控。","2026-09-07T23:30:01.869886Z",{"id":240,"title":241,"url":242,"summary":243,"summary_zh":9,"content":9,"source_name":244,"source_url":242,"published_at":245,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":246,"score_detail":247,"sources":250,"tags":252,"search_phrases":254,"slug":257,"view_count":36,"doi":258,"paper":259,"created_at":273},1756,"From behavioural monitoring to decision support in aquaculture: an interpretable analytical framework","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.biosystemseng.2026.104587","From behavioural monitoring to decision support in aquaculture: an interpretable analytical framework。Biosystems Engineering","Biosystems Engineering","2026-09-05T00:00:00Z",67,{"impact":248,"substance":18,"depth":19,"authority":17,"freshness":162,"relevant":22,"comment":249},15,"论文提出可解释的分析框架，将行为监测转化为决策支持，对水产养殖智能化有实质贡献，但时效性较低。",[251],{"name":244,"url":242},[27,28,253],"决策支持",[255,256],"决策支持 智慧农业 水产养殖","决策支持 智慧农业","决策支持智慧农业水产养殖-1756","10.1016\u002Fj.biosystemseng.2026.104587",{"doi":258,"openalex_id":260,"authors":261,"venue":244,"cited_by_count":36,"oa_url":9,"card":9,"direction":9,"ingested_from":58},"W7208811750",[262,264,266,269,271],{"name":263,"orcid":9},"Haixiang Zhao",{"name":265,"orcid":9},"Zuqiang Liu",{"name":267,"orcid":268},"Zhihong Ma","https:\u002F\u002Forcid.org\u002F0000-0003-4821-6751",{"name":270,"orcid":9},"Weimin Yu",{"name":272,"orcid":9},"Xian Li","2026-09-06T23:30:06.005522Z",{"id":275,"title":276,"url":277,"summary":278,"summary_zh":279,"content":9,"source_name":280,"source_url":277,"published_at":281,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":282,"score_detail":283,"sources":286,"tags":288,"search_phrases":292,"slug":295,"view_count":36,"doi":296,"paper":297,"created_at":321},1603,"Organically enriched water from an integrated agri-aquaculture system enhances antioxidant defense and secondary metabolism in blackberry (Rubus ulmifolius cv. Tupy)","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1927797","Introduction Integrated agri-aquaculture systems can improve water-use efficiency and nutrient recycling in semiarid and arid regions increasingly affected by climate change; however, the physiological responses of fruit crops to aquaculture-derived irrigation water remain poorly understood. This study evaluated the growth, photosynthetic status, and biochemical responses of blackberry ( Rubus ulmifolius cv. Tupy) irrigated with organically enriched water from an integrated tilapia–blackberry system operated under geodesic-dome conditions in semidesert central Mexico. Methods Four irrigation treatments were compared: a conventional nutrient solution, unsupplemented tilapia-culture effluent, tilapia-culture effluent supplemented with mineral nutrients, and well water adjusted to the same pH as the fertilized treatments. Plant growth traits, leaf greenness, normalized difference vegetation index, antioxidant enzyme activities, total phenolic compounds, and flavonoids were monitored for 216 h after irrigation began. Results and discussion Plants irrigated with supplemented tilapia-culture effluent maintained growth and canopy greenness comparable to those receiving the conventional nutrient solution. In contrast, unsupplemented tilapia-culture effluent and well water induced stronger antioxidant and secondary-metabolic responses, particularly in superoxide dismutase and catalase activities and in the temporal dynamics of phenolic compounds and flavonoids, whereas phenylalanine ammonia-lyase showed a weaker and later response. These patterns suggest that mineral-supplemented effluent primarily supported vegetative performance, whereas unsupplemented effluent was associated with a nutritional elicitation response potentially related to relative nutrient limitation and biologically active components in the effluent. During the 216-h evaluation period, unsupplemented effluent maintained plant performance comparable to that under the fertilized treatments, suggesting that aquaculture-derived water may reduce mineral-fertilizer inputs during specific crop stages. Because the experiment was short-term, no conclusions can be drawn regarding long-term productivity, fruit quality, or sustained plant responses. Overall, the findings support the potential of integrated agri-aquaculture systems as a water-smart approach for blackberry cultivation in water-limited semidesert environments.","引言 综合农业-水产养殖系统可提高半干旱和干旱地区（日益受气候变化影响）的水分利用效率和养分循环利用；然而，果树作物对水产养殖源灌溉水的生理响应仍知之甚少。本研究评估了在墨西哥中部半沙漠地区测地穹顶条件下，以罗非鱼-黑莓综合系统产生的有机富集水灌溉黑莓（Rubus ulmifolius cv. Tupy）时的生长、光合状态及生化响应。方法 比较了四种灌溉处理：常规营养液、未补充矿质营养的罗非鱼养殖废水、补充矿质营养的罗非鱼养殖废水，以及与施肥处理调节至相同pH值的水井水。在灌溉开始后的216小时内，监测了植株生长性状、叶片绿色度、归一化差异植被指数、抗氧化酶活性、总酚类化合物及黄酮类化合物。结果与讨论 以补充矿质营养的罗非鱼养殖废水灌溉的植株，其生长和冠层绿色度与接受常规营养液的植株相当。相比之下，未补充矿质营养的罗非鱼养殖废水和井水诱导了更强的抗氧化和次生代谢响应，尤其是超氧化物歧化酶和过氧化氢酶活性以及酚类化合物和黄酮类化合物的时间动态变化，而苯丙氨酸解氨酶则表现出较弱且较迟的响应。这些模式表明，补充矿质营养的废水主要支持营养生长性能，而未补充矿质营养的废水则与营养激发响应相关，该响应可能涉及相对养分限制及废水中生物活性成分的作用。在216小时的评估期内，未补充矿质营养的废水维持的植株性能与施肥处理相当，表明水产养殖源水可在特定作物阶段减少矿质肥料投入。由于本实验为短期研究，无法就长期生产力、果实品质或植株持续响应得出结论。总体而言，研究结果支持综合农业-水产养殖系统作为水资源有限半沙漠环境中黑莓种植的水智能型方法的潜力。","Frontiers in Sustainable Food Systems","2026-09-03T00:00:00Z",66,{"impact":17,"substance":19,"depth":161,"authority":74,"freshness":284,"relevant":22,"comment":285},7,"研究探索鱼菜共生系统灌溉黑莓的生理响应，为半干旱地区节水农业提供新思路，但属短期试验，影响有限。",[287],{"name":280,"url":277},[27,28,289,290,291],"节水灌溉","循环农业","黑莓",[293,294],"循环农业 智慧农业 水产养殖 节水灌溉","循环农业 智慧农业","循环农业智慧农业水产养殖节水灌溉-1603","10.3389\u002Ffsufs.2026.1927797",{"doi":296,"openalex_id":298,"authors":299,"venue":280,"cited_by_count":36,"oa_url":277,"card":316,"direction":105,"ingested_from":58},"W7207518495",[300,303,305,307,309,312,314],{"name":301,"orcid":302},"Priscila Sarai Flores-Aguilar","https:\u002F\u002Forcid.org\u002F0000-0001-5708-4960",{"name":304,"orcid":9},"Ireri A. Carbajal-Valenzuela",{"name":306,"orcid":9},"Carlos Olvera-Olvera",{"name":308,"orcid":9},"Genaro Martin Soto-Zarazúa",{"name":310,"orcid":311},"Gobinath Chandrakasan","https:\u002F\u002Forcid.org\u002F0000-0002-3919-3677",{"name":313,"orcid":9},"Edgar Rivas-Araiza",{"name":315,"orcid":9},"Jose L. Gonzalez-Cordoba",{"tldr":317,"method":318,"finding":319,"direction":105,"opportunity":320},"研究罗非鱼-黑莓综合养殖系统中有机富集水对黑莓生长和生理的影响。","比较四种灌溉处理，监测生长、光合、抗氧化酶和次生代谢物。","补充矿物质的养殖废水维持生长，未补充的诱导抗氧化和次生代谢响应，可减少化肥。","长期效应和果实品质未知，可研究养殖废水灌溉对黑莓产量和品质的长期影响及机制。","2026-09-04T23:30:07.706501Z"]