Core Insights - The report from CICC indicates that AI penetration in agriculture requires long-term evolution, facing challenges such as resource allocation, user habit changes, and technology refinement [1] - AI applications in agriculture are currently in the experimental demonstration phase, with slow penetration rates in certain areas despite rapid advancements in large model applications [1] - The complexity of agricultural environments and the need for precise recommendations pose significant challenges for AI models, which must adapt to various conditions [7][8] Industry Overview - The agricultural sector has seen the emergence of multiple large model products, with competition centered around data accuracy and relevance to customer needs [4] - The investment landscape in smart agriculture has been active from 2015 to 2022, yet only 20-30 companies receive funding each year, indicating a selective investment environment [8] - The Ministry of Agriculture and Rural Affairs has set a goal for agricultural production informationization to reach over 32% by the end of 2028, highlighting the importance of national policies in fostering AI agricultural development [8] Challenges in AI Agriculture - Key challenges hindering AI adoption in agriculture include weak data foundations, high costs, low ROI expectations, and trust barriers among practitioners [1] - The diversity of agricultural data due to varying soil, climate, and crop types complicates the training of reliable AI models [1] - The complexity of agricultural environments limits the generalizability of AI solutions, making it difficult to apply models developed in one context to another [7][8]

Core Viewpoint - The "Smart Electric Photosynthesis" project integrates clean energy management, precision agriculture, and advanced planting technologies to create a new production model for agriculture, addressing high energy consumption issues in traditional farming [2][3][4]. Group 1: Innovation in Agriculture - The "Smart Electric Photosynthesis" solution leverages three main innovations: intelligent clean energy scheduling, lean production process management, and innovative planting techniques, representing a systemic reconstruction of agricultural production methods [3]. - The project aims to create a thinking energy system that goes beyond simple energy replacement, utilizing a self-developed smart energy regulation platform for dynamic monitoring and optimization [3][4]. Group 2: Energy Efficiency and Sustainability - The system achieves a 98% clean energy replacement rate, significantly reducing carbon emissions and energy costs for plant factories [4]. - The integration of AI algorithms and quantum encryption technology allows for real-time optimization of energy allocation based on environmental variables, enhancing energy efficiency [4]. Group 3: Technological Advancements - The smart production platform functions as a digital agronomist, utilizing a billion-parameter AI model to create a digital twin of crop growth, achieving a precision control error of just 0.5% [9]. - The innovative vertical planting system and full-spectrum lighting technology improve light utilization efficiency to 1.2 times the industry standard, while nutrient recycling achieves a 90% utilization rate [11]. Group 4: Economic Impact - The transformation of plant factories has led to a 25% reduction in electricity costs and a 50% decrease in labor costs, significantly enhancing economic benefits for local farmers [14]. - The model demonstrates strong replicability across various agricultural sectors, with potential annual savings of 50 million kilowatt-hours and a reduction of 47,000 tons in carbon emissions [17].

中国作为农业大国，正积极利用科技创新推动乡村全面振兴。广东凭借粤港澳大湾区的优势，在智慧农 机、生物育种等方面取得显著成果，但技术研发与产业落地之间仍存在差距，传统农业企业亟待数字化 转型，科技企业也在寻找应用场景，资本方在寻觅潜力项目。本次活动以"技术赋能+产业升级+资本驱 动"为核心，旨在搭建产学研用对接的桥梁，探索AI与农业融合的路径，为解决农业生产中的关键问题 提供新动能。 据介绍，下一步，广东股权交易中心将进一步发挥广州市资本市场融资对接服务平台作用，持续开 展"领头羊"产融对接活动，优化金融服务体系，多措并举激发民营企业活力，推动资本市场服务民营企 业更加精准、高效，助力广州民营经济高质量发展。 创钰投资智能制造投资部的姜冒翔从资本视角，解读了智慧农业作为未来十年黄金赛道的投资前景，在 人口危机与资源承载力约束下，未来智能巡检机器人、采摘机器人、农用无人机进行智能植保、农田检 测、特种作业，农业AI与大数据进行精准种植管理、作物生长预测、实时决策支持等赛道都将是未来 投资人的关注方向。 随后进入优质项目分享环节，四个极具创新性的项目展示了AI在农业领域的多元应用。 近日，广州资本市场支持民营企业高 ...

证券研究报告·公司深度研究·IT 服务Ⅱ 托普云农（301556） 智慧农业领军，AI+深度赋能 2025 年 06 月 20 日 买入（首次） | [Table_EPS] 盈利预测与估值 | 2023A | 2024A | 2025E | 2026E | 2027E | | --- | --- | --- | --- | --- | --- | | 营业总收入（百万元） | 459.45 | 488.90 | 658.72 | 874.79 | 1,135.98 | | 同比（%） | 22.47 | 6.41 | 34.74 | 32.80 | 29.86 | | 归母净利润（百万元） | 115.01 | 123.46 | 164.86 | 212.13 | 271.85 | | 同比（%） | 24.09 | 7.35 | 33.53 | 28.67 | 28.15 | | EPS-最新摊薄（元/股） | 1.35 | 1.45 | 1.93 | 2.49 | 3.19 | | P/E（现价&最新摊薄） | 62.17 | 57.91 | 43.37 | 33.71 | 26.30 | [Table_ ...

Group 1 - New productive forces are reshaping the economic landscape and driving high-quality development, with significant advancements in technology and innovation in Qingdao [1][29] - Qingdao has launched a comprehensive plan for optimizing and upgrading traditional manufacturing industries, aiming for over 60% of advanced capacity in key industries by 2027 [1][29] - The city is witnessing the emergence of "invisible unicorn" companies, which are crucial in driving this transformation, with 54 such companies identified, ranking fifth nationally [2][29] Group 2 - The average age of these invisible unicorn companies is under 8 years, holding over 2,000 core patents in strategic fields like semiconductor materials and smart manufacturing [3][29] - Qingdao Huaxin Crystal Technology Co., Ltd. has transitioned from a follower to a leader in the domestic compound semiconductor materials sector, breaking foreign monopolies [5][29] - Qingdao Langfu Technology Co., Ltd. has developed a complete service system for its core products, which are widely used in various industries, transporting over 10 billion liters of liquid annually [10][29] Group 3 - Kaisheng Haofeng Group operates the largest smart glass greenhouse in China, utilizing a digital nervous system to revolutionize agricultural production [12][29] - Qingdao Youwu Intelligent Home Technology Co., Ltd. has developed a smart purification box with high efficiency in purifying formaldehyde, supported by numerous patents [16][29] - Qingdao SIR Intelligent Technology Co., Ltd. has achieved breakthroughs in critical technologies for chip manufacturing, filling domestic gaps and enabling localized mass production [19][29] Group 4 - The invisible unicorn companies in Qingdao are characterized by high technology, high growth, and high valuation, with a significant portion receiving government funding and collaborating with universities [29][32] - The city aims to cultivate 80 invisible unicorns by 2027, with specific initiatives including a 5 billion yuan innovation fund and the establishment of specialized incubation platforms [31][32] - Qingdao's innovation ecosystem is attracting global attention, with nine companies making it to the list of China's top 500 invisible unicorns, collectively valued at 42.1 billion yuan [32][33]

Group 1 - The China International College Students Innovation Competition (2025) was held in Astana, Kazakhstan, focusing on themes of mutual learning and innovation among youth from China and Central Asian countries [1][2] - Over 100 quality projects were presented by students from China, Kazakhstan, Uzbekistan, Kyrgyzstan, and Tajikistan, covering modern agriculture, information technology, green energy, and cultural tourism [1] - The event facilitated deep exchanges among youth and experts in areas such as biological breeding, smart agriculture platform construction, and technology transfer, aiming to enhance China-Central Asia technological collaboration [1] Group 2 - Northwest A&F University has established close cooperation with several Central Asian universities, achieving significant results in joint laboratories, overseas demonstration stations, and talent cooperation [2] - The China International College Students Innovation Competition, initiated in 2015, has become the largest global innovation competition platform, with the first Central Asia regional competition this year to promote youth exchanges and cooperation [2]

即日起至6月29日，智慧农业、空天信息、机器人、金融科技、垂直大模型、医疗大健康、绿色低碳、 网络安全、智能网联、安全应急、低空交通等11项大赛决赛将在雄安未来之城场景汇科创园依次举办， 整个赛程21天。决赛期间还将举办几十场产业、场景、资本对接等活动，来自全国各地的参赛企业团队 既可与不同领域的前沿技术跨界融合，也可与需求单位、投资机构等交流合作，共同开辟新领域、新赛 道。 在雄安打造未来之城场景汇，是河北省委、省政府着眼更好承接北京非首都功能疏解，搭建科技、产 业、金融、场景紧密对接平台，推动先进技术在全省孵化转化产业化所作出的创新性、探索性改革部 署。2024年成功举办的首届场景汇活动成效显著——共推出100项场景项目，其中74项已经开始实施。 377项获奖作品中有不少落地雄安，乃至走向全省、走向全国。 通过一系列举措，雄安未来之城场景汇作为科技、产业、金融、场景紧密对接的综合性平台作用充分显 现。据统计，本届大赛吸引全国30个省（区、市）的2700余家企业团队携3400多项作品参赛。经过预赛 评审，共有981家企业团队的1191项作品晋级决赛，另有500多项先进技术和产品装备、百余项新场景参 展。截至 ...

Core Insights - The "Smart Agriculture Data Industry Innovation Center" was officially inaugurated at the Shanghai Data Exchange, with four data products from Shanghai Langxia Jintudi Green Agriculture Co., Ltd. successfully listed for trading, indicating Shanghai's efforts to build a comprehensive value chain for smart agriculture data [1] - The center aims to create a credible and value-enhancing agricultural data ecosystem, establishing compliant trading rules and standards to develop a new networked trading system for smart agriculture [1][3] - The data products include a weather and warning database for facilities greenhouses, a multi-source data fusion yield prediction analysis, an indoor environment management query, and an environment management action analysis, which have been successfully traded with Pacific Anxin Agricultural Insurance Co., Ltd. [1][2] Company Insights - Jiqing Technology (Shanghai) Co., Ltd. plays a pivotal role in the value realization of smart agriculture data, focusing on the entire value chain of agricultural data and creating a complete ecological loop covering data collection, governance, circulation, and application [2] - The company has developed a high-precision yield prediction model that integrates multi-source data, with a prediction error controlled within 5%, providing critical data support for agricultural product trading [2] - The company is positioned as a "data element service provider," leveraging its capabilities in data processing and analysis to address the lack of applicable yield measurement equipment and technology in agricultural facilities [2] Future Developments - The "Smart Agriculture Data Industry Innovation Center" plans to leverage the advantages of the Shanghai Data Exchange and the capabilities of Jiqing Technology to gradually build a data trading ecosystem for the smart agriculture industry, focusing on green agriculture, quality improvement, and traceability [3]

推动智慧农业的 创新与发展，光 亚数智农业论坛 9日广州启幕_南 方+_南方plus 6月9至12日，广 州国际照明展览 会（GILE）将 在广州中国进出 口商品交易会展 馆A、B区举 办。 适逢三十 周年，展会 以"360º+1 —— 全方位实践光无 限，跨越一步开 启光照新生 活"为主题，并 首次推出"光亚 行"活动。该活 动旨在打造一个 多元融合、开放 共享的交流平 台，汇聚行业力 量，助力照明业 者突破传统思 维，探索照明技 术与多元领域融 合的无限可能， 推动"光+时 代"行业IP发 展，开拓新增长 点。 自2021年起，展 览会已连续五年 成功举办生物光 学与智慧农业国 际论坛及主题展 区。论坛开办以 来，汇聚了院士 在内近百位各学 科专家，分享技 术成果，推动学 科交叉融合与产 业生态创新。论 坛的持续举办有 效促进我国智慧 农业技术与生物 光学技术的产业 化发展，并加速 了相关产品的市 场化迭代。 今年论坛已全面 升级为"光亚数 智农业论坛" 。 三天的论坛围 绕"智慧农业与 智慧渔业""温室 新技术与能耗管 理""生物光学技 术与光伏农 业""技术创造未 来—企业家论 坛"四大板块。 除了论 ...

Core Viewpoint - The development of smart agriculture in China is gaining momentum, leveraging technologies such as IoT, cloud computing, big data, and artificial intelligence to enhance agricultural productivity and efficiency [1][2]. Group 1: Market Growth and Trends - China's smart agriculture market is projected to grow from 38.774 billion yuan in 2017 to approximately 100 billion yuan by 2024, with a compound annual growth rate of about 15% [1]. - Major global economies are actively advancing smart agriculture, with examples including Germany's smart breeding technologies, the Netherlands' intelligent greenhouse agriculture, and Japan's focus on small smart equipment development [1]. Group 2: Challenges and Policy Recommendations - The agricultural sector in China faces challenges such as fragmented smallholder farming, weak information infrastructure, low data quality, and limited adoption of smart technologies [2]. - Recommendations include enhancing the policy framework for smart agriculture, optimizing strategic goals, and providing financial support for agricultural technology innovation [2]. Group 3: Data Integration and Management - There is a need to deepen the integration of agricultural data resources and establish unified standards for data collection and transmission [3]. - The development of a comprehensive agricultural big data platform is essential to improve data management and enhance production efficiency [3]. Group 4: Regional Development Strategies - Smart agriculture development should be tailored to China's diverse geographical and climatic conditions, focusing on automation in northern plains and precision management in southern hilly areas [4]. - Examples include the establishment of unmanned farms in northern regions and the use of small intelligent machinery in southern areas to improve agricultural practices [4].