Core Insights - The article highlights the successful implementation of smart agriculture in Changsha, specifically in Yun'gai Village, where technology is used to enhance agricultural productivity and protect arable land [1][3]. Group 1: Agricultural Innovation - The smart farm in Yun'gai Village spans 780 acres and utilizes unmanned transplanting machines and intelligent gates to manage water flow based on soil moisture conditions, showcasing the integration of technology in agriculture [1]. - The area has transformed previously abandoned land into productive "ton grain fields," with 53 acres of arable land restored and 6.3 kilometers of water systems improved from 2022 to 2023 [1]. Group 2: Digital Transformation - The farm employs remote sensing satellites, drones, and GIS technology to create a comprehensive digital management system, allowing for precise monitoring of soil fertility, crop growth, and pest alerts [3]. - A digital governance platform has been established to monitor farmland conditions and identify issues such as land degradation and abandonment, enhancing proactive management of agricultural resources [3]. Group 3: Economic and Social Impact - The coordinated efforts in land restoration and ecological construction have led to improved agricultural ecosystems, with local villagers experiencing an average annual income increase of over 10,000 yuan [4]. - The establishment of an agricultural culture experience area allows visitors to engage with both traditional farming methods and modern technology, promoting awareness and appreciation of agricultural practices [4].

Group 1 - The core concept of the news is the establishment of the Tianlifang Smart Science and Technology Park, which aims to integrate smart agriculture technologies and become a national-level agricultural demonstration center by 2027 [1][2] - The Smart Science and Technology Park will cover an area of approximately 40 acres, with a total construction area of about 100,000 square meters, including 80,000 square meters above ground and 20,000 square meters underground [2] - The park will focus on three main directions: smart manufacturing equipment, digital technology research and development, and the integration of primary, secondary, and tertiary industries, promoting breakthroughs in Agriculture 4.0 technologies [2][3] Group 2 - The park aims to attract high-quality resources from leading agricultural enterprises in the Yangtze River Delta, facilitating the transformation of agricultural technology achievements in the region [2] - The project will benefit from supportive policies, including a three-year gradual rent reduction for key enterprises and subsidies for technology research projects, with a maximum of 500,000 yuan available for applications [2] - The integration of traditional agriculture with digital technology will position the Smart Science and Technology Park as a key anchor for the development of smart agriculture in the region [3]

Group 1: Economic and Business Overview - The discussion focused on the current macroeconomic situation [1] - Insights were shared regarding the operational status of various business segments [1] - The company's product capacity layout was addressed [1] Group 2: Strategic Direction and Governance - The company's development strategy was a key topic of conversation [1] - Information about the controlling shareholder and actual controller was provided [1]

6月25日，在新疆阿克苏地区库车市甬库同心村智慧农业植物工厂，工作人员对收获的农作物进行称重打包。 6月25日，在新疆阿克苏地区库车市甬库同心村智慧农业植物工厂，技术人员在培训从当地招聘的农业产业工人。 新疆阿克苏地区库车市甬库同心村智慧农业植物工厂是浙江省宁波市对口援疆项目之一。在宁波市援疆指挥部支持下，该智慧工厂引入宁波企 业先进的无土栽培技术和设备，通过智能调控成功种植多种原本不适宜在当地生存的农作物。从该工厂收获的新鲜蔬菜实现直供当地超市，丰 富了当地居民的饮食结构。此外，该援疆项目还帮助村民在家门口实现就业，为当地培养了农业产业工人，提高了村集体收入，为周边学校开 展农业科技科普提供便利，实现了经济效益与社会效益"双丰收"。 新华社记者 徐宏岩 摄影报道 这是6月25日在新疆阿克苏地区拍摄的库车市甬库同心村智慧农业植物工厂内景。 6月25日，在新疆阿克苏地区库车市甬库同心村智慧农业植物工厂，工作人员为当地小学生讲解无土栽培技术。 6月25日，在新疆阿克苏地区库车市甬库同心村智慧农业植物工厂，当地小学生体验无土栽培。 6月25日，在新疆阿克苏地区库车市甬库同心村智慧农业植物工厂，工作人员在监测记录智能 ...

2025.06. 24 丰农控股集团总农艺师王兴林表示，近五年时间，团队在AI方面的实践包括了图像识别、病虫害管 理、生产力评估、农场综合管理、精准施肥用药等方面。我国农业文明虽然悠久，但工业化冲击对农 业发展带来的提升空间，目前来看仍然很大。也因此，丰农的定位仍以农业服务为核心，通过AI工 具属性来服务农业发展。 AI农业智能化提升慢的原因可以归结为三大方面：数据基础薄弱、高成本与低ROI预期、场景复杂性 与信任壁垒。由于土壤、气候、作物品种多样等原因，农业数据分散，农业相关数据集不足以训练可 靠AI模型，且缺乏实时数据收集能；智能农机、无人机等农业AI设备成本高昂，农业行业投资回报 周期长；从业者更信任经验，将AI视为辅助工具。 本文字数：1342，阅读时长大约3分钟 作者 | 第一财经 吕倩 6月24日，中金公司研究部发布的研报显示，AI渗透需长期演进，尤其从技术萌芽到企业大规模部署 阶段，会经历资源分配、用户习惯转变、技术与场景打磨、产品迭代等节点，可能存在短期阵痛。今 日收盘，AI应用(8841683)指数收涨2.55%。一方面，大模型落地行业应用进展迅速，但同时，部分 领域AI渗透率仍增长缓慢。A ...

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].

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_ ...

（原标题：从田间到全球，中国智慧农业加速出海） 6月18日，欧美同学会2005委员会在京城举办首届"领悟·创新产业论坛"，以"从田间到全球——科技赋 能乡村振兴"为主题，深入探讨农业数字化转型、全球产业链布局及可持续发展路径等诸多关键议题。 当前，中国农业正面临着劳动力老龄化问题日益严重、自然灾害与气候变化以及增产不增收等多重严峻 挑战。 与此同时，据Grand View Research报告显示，全球智慧农业市场规模预计到2030年将达到547.1亿美 元，中国凭借强大的政策支持与快速迭代的技术，正逐步成为该领域的重要参与者。 多项AI技术落地农业全场景 针对农村老龄化问题，欧美同学会2005委员会创始理事、友成企业家乡村发展基金会常务副理事长、前 国务院参事汤敏在发言中介绍，"乡村振兴领头雁"计划已成功培训20万返乡青年掌握AI技术应用。此 外，"数字游民"模式方兴未艾，城市青年将远程办公与乡村生活有机结合，为农村发展注入了新的活力 与生机。 目前，越来越多的AI应用场景在农业领域落地生根。会上，汤敏分享了利用AI技术推动土地流转和农 业生产智能化的生动案例。例如，借助"土流网"能够对土地农田的各类数据（ ...

转自：推广 文 | 徐雅琳 新质生产力正以前所未有的深度和广度重塑经济格局，成为高质量发展的核心驱动力。Deepseek国产大模 型崛起、人形机器人亮相春晚、"独角兽""瞪羚"企业首次写入政府工作报告、地方规划密集出台……无不 彰显其全方位、深层次的影响力。 青岛华芯晶电科技有限公司这家成立仅12年的企业，已在国内化合物半导体材料领域实现从跟跑到领跑的 跨越。尤其是在半导体衬底材料领域打破国外垄断，其磷化铟衬底、氧化镓衬底等产品广泛应用于集成电 路、光通信、人工智能等领域。 以制造业立市、矢志向"智造"跃升的青岛，正在通过深度融合科技与产业创新，全力拥抱新质生产力，赋 能城市高质量发展。 4月，青岛重磅出台《传统优势制造业优化升级培育发展新质生产力实施方案（2025-2027年）》，瞄准高 端供给、数智赋能、绿色转型三大方向，推出21项具体举措。方案设定了清晰目标：到2027年，重点行业 先进产能占比超60%，规上工业企业关键工序数控化率超76%，工业重点领域能效标杆产能比例突破 38%。这不仅为青岛传统制造业转型升级绘制了精准路线图，更为新质生产力的蓬勃生长开辟了广阔天 地。 青岛对新质生产力的探索已初见成 ...