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本文来自微信公众号：腾讯研究院 （ID：cyberlawrc），作者：WeCity低碳城市研究组，原文标题：《数字技术如何重构全球农业生态？丨WeCity低碳城市》，题图来自：视觉中国

根据2019年联合国发布的《世界人口展望》报告预计，到2050年，世界人口将增长至97亿，全球需要增加70%的粮食产量。同时，农业用地萎缩、自然资源枯竭、农业劳动力短缺等问题也对未来农业发展提出了挑战，农业正在变得比以往任何时候都更加重要，“粮食危机”也正在为全球媒体所关注。这意味着我们亟需采用更智能、更有效的粮食种植方式，并规范土地、水和能源等有限资源的使用。

According to the World Population Prospects report released by the United Nations in 2019, the world population is projected to grow to 9.7 billion by 2050, and , while issues such as shrinking agricultural land, depletion of natural resources, and shortage of agricultural labour also pose challenges for future agricultural development, agriculture is becoming more important than ever, and the “food crisis” is becoming a concern for the global media. This means that there is an urgent need to adopt smarter and more effective methods of food cultivation and to regulate the use of limited resources such as land, water and energy.

人类的创造力从未离开过农业，当下全球农业正在经历着第四次科技革命，从生产方式到生产力的创新在爆发式增长。已经在其他市场得到验证的一系列关键数字技术，如物联网（IoT）、5G、区块链、人工智能（AI）、增强现实（AR）、数字孪生（Digital Twins）、无人机等正在推动“智能农业革命”，帮助农业实现农业资源的合理利用。这有助于有效降低生产成本，改善生态环境，提高农作物产量和质量，提升农产品附加值和市场品牌影响力。

Human creativity has never left agriculture, and global agriculture is undergoing a fourth technological revolution, with innovation growing in an outbreak from production to productivity. has been validated in other markets with a range of key digital technologies, such as the Internet , 5G, block chains, artificial intelligence (AI) , enhancing reality >, artificial intelligence = "text-remarks" label= note" (Digital& nbsp; Twins) >, and helping to improve the agricultural market and improve the efficiency of agricultural production and the quality of agricultural products.

通过对农业生产、流通、销售、消费等要素与环节的数字化重塑，能够开拓降本增效的智能农业发展模式，对农产品的产量、健康、营养、安全等进行精细化、高效化与规范化的赋能和升级。数字技术能够对农业的种植/养殖对象、环境和全过程进行可视化表达、数字化设计、信息化管理，实现数据、平台、算法与农业各个环节的有效融合。这对改造和转变传统农业生产方式、打造清洁低碳的绿色农业具有重要意义，同时也是实现农业化、数字化与低碳化可持续协调发展的必由之路。

By digitizing factors and links such as agricultural production, circulation, marketing, consumption, etc., smart models of agricultural development can be developed to reduce efficiency gains, fine-tuning, efficiency and upgrading of agricultural production, health, nutrition, safety, etc. Digital technology can provide visualizing, digital design, information management, and effective integration of data, platforms, algorithms and components of agriculture. This is important for transforming and transforming traditional agricultural production patterns, building clean and low-carbon green agriculture, and is essential for achieving sustainable and coordinated development in agriculture, digitalization and low-carbonization.

物联网：通过感知技术实现土壤的绿色化与无害化

数字化正在改变“靠天吃饭”的传统农业生产模式，数字技术对农业生产对象、环境、条件等的调节、控制与管理，也在改变农业与农村的强力依附关系，数据赋能、循环经济驱动的“都市农业”、“垂直农业”方兴未艾。通过对气候监测、虫情监测、土壤分析等实时数据的采集分析，物联网在降低运营成本、提高生产效率和经济效益等方面充分展现了其数字化效能。

Digitalization is changing the traditional agricultural production model of “food by heaven” and the regulation, control and management of digital technology for agricultural production objects, environment, conditions, etc., as well as the strong dependence of agriculture on rural areas. Data empowerment, circular economy-driven “urban agriculture” and “vertical agriculture” are on the rise. Through the analysis of real-time data such as climate monitoring, insect monitoring, soil analysis, the network of

农产品种植与培育是应对气候变化与实现绿色发展的重要举措，同时，对农业生产过程中的农药、化肥的过量甚至无节制使用，导致农业本身反而成为环境恶化问题之一。

Farming and nurturing are important initiatives to combat climate change and achieve green development, while excessive and even uncontrolled use of pesticides, fertilizers and fertilizers in agricultural production results in agriculture itself becoming one of the problems of environmental degradation.

为使农民更少地使用化肥，减少对环境造成的伤害，2021年，英国帝国理工学院研究团队开发了一项新型智能传感技术——纸基电化学气体传感器（chemPEGS），可以测量土壤中铵（铵会被土壤中的微生物转化为亚硝酸盐和硝酸盐）的含量。

In order to reduce the use of fertilizers by farmers and to reduce environmental damage, in 2021, the research team at the Imperial College of Technology developed a new intelligent sensor technology - the paper-based electrochemical gas sensor , which can measure the content of ammonium in soil .

利用机器学习人工智能（AI）技术，该传感器可将天气数据、施肥时间、pH值和土壤电导率测量值相结合，根据这些数据来预测土壤当前的总氮含量以及未来12天内的总氮含量，从而推断出最佳施肥时间。通过该传感器技术的使用，不仅可以让农民以最少的肥料实现最大的产量，尤其是针对小麦这样的肥料高需求农作物，既能减少农民的支出，又可以减轻氮肥对环境的危害。

Using machines to learn artificial intelligence , the sensor can combine weather data, fertilization time, pH values and soil conductivity measurements to predict the current total nitrogen content of the soil and the total nitrogen content for the next 12 days, thus inferting the best time for fertilization. By using the sensor technology, will not only allow farmers to produce the maximum yield of

纸基电化学气体传感器（chemPEGS）工作原理（图片来源）

除了对农作物土壤中的微生物与化肥用量的使用监测，物联网技术与AI的结合可以为农作物生长建立全生命周期的土壤肥料管理系统。

In addition to monitoring the use of microbes and fertilizers in crop soils, the integration of matter networking technology with AI can create a life-cycle soil fertilizer management system for crop growth.

SenseGrass公司就开发了一款用于土壤和作物管理的“IoT+AI”系统——SenseGrass Inc。这是一种基于网络的人工智能土壤肥料管理系统，其能够通过专利磁传感器技术测量40多种作物和土壤参数并进行水管理，通过无人机图像进行田间监测，通过机器学习智能分析土壤健康、肥料状况和其他环境因素，为用户提供实时数据，帮助农民和公司做出正确决策，调整运营。

SenseGrass developed an “Iot+AI” system for soil and crop management — SenseGrass Inc. This is a web-based, intelligent soil fertilizer management system capable of measuring over 40 crop and soil parameters and water management through proprietary magnetic sensor technology, field monitoring through drone images, machine-learning intelligence analysis of soil health, fertilizer conditions and other environmental factors, providing real-time data for users, helping farmers and companies to make the right decisions and adapt operations.

因此，数字技术的赋能不只是最大限度地提升农作物的效益，也能够对农业生产过程中的土壤、虫害、天气、化肥等进行量化管理。同时，由于农业大数据的全面性与准确性，基于农作物生长的数据沉淀还可以为农业公司、农产品项目提供金融支持，比如农业贷款、农作物保险。

As a result, digital technology is not only capable of maximizing crop efficiency, but also of quantitative management of soil, pests, weather, fertilizers, etc. in agricultural production. At the same time, because of the comprehensiveness and accuracy of agricultural data, ’s crop-based data deposition can also provide financial support for agricultural companies, agricultural projects, such as agricultural loans, crop insurance, etc.

SenseGrass Inc土壤肥料管理系统（图片来源）

人工智能：算法支撑的“农民+平台”绿色农业发展模式

人工智能正在被广泛应用于工业领域，由此衍生出“黑灯工厂”“机器换人”“柔性制造”等概念，而人工智能亦能在在农业生产领域大放异彩。

Artificial intelligence is being widely used in the industrial sphere, which leads to concepts such as “black-light plant” “machine-for-man” “soft manufacturing”,

德国的“NaLamKI”是服务于农业生产的数据分析和预测平台，其主要从四个方面优化和提升农业生产的整体效益。

In Germany, the “NalamKI” is a data analysis and forecasting platform for agricultural production, whose main objective is to optimize and enhance the overall benefits of agricultural production in four areas.

首先是数据的全方位采集，通过汇总使用卫星和无人机、土壤传感器、机器人技术、手动数据收集和库存数据收集的传感器和机器数据，创建数据池；

The first is the full-scale collection of

其次是通过数据分析实现对农作物土壤和生长环境的控制，并协助重组营养和作物保护过程，如灌溉、施肥和害虫控制，以确保在质量和数量方面有足够的作物产量，减少排放并保护生物多样性；

Second, to achieve the control of crop soils and growth environments by

再次是农民可通过数据共享实现算法的自主优化，农民将能够共享AI模型并将其传输到NaLamKI平台，以不断改进算法，进而优化农业流程，形成预测和决策辅助；

Once again, farmers can achieve autonomous optimization of algorithms through data sharing, and farmers will be able to share AI models and transmit them to the NaLamKI platform, to continuously improve algorithms and thus optimize agricultural processes to form forecasting and decision support;

最后是“NaLamKI”平台可以构建自主机器人行为模型，使农业更加高效和可持续。人工智能不只是用于对农业生产流程的优化，农民作为农业生产的价值主体，通过AI平台的数据共享，实质上已成为新型农业发展的数据贡献者。

Finally, the “NalamKI” platform can build autonomous robotic behaviour models to make agriculture more efficient and sustainable. Artificial intelligence is not just used to optimize agricultural production processes, and farmers, as value-holders of agricultural production, have become essentially data contributors to new agricultural development through data-sharing on AI platforms.

在苹果园自动收集数据的智能机器人（图片来源）

人工智能除了用于针对土壤、农作物生长状况的数据采集，还能用于评估气象数据以及特定区域的植物病变风险，以实现风险预警。

Artificial intelligence, in addition to data collection for soil, crop growth, can also be used to assess meteorological data and the risk of plant pathologies in a given region in order to achieve risk warning.

GEOPOTATO是一款由地理数据驱动的决策服务智能预警系统，通过将卫星和当地天气数据与流行病学和作物生长模型相结合，以高精度的地理和时间分辨率预测枯萎病的压力，为孟加拉国农民提供有关枯萎病风险的及时警报。GEOPOTATO可自动计算来自自动气象站的天气数据（湿度、温度等），通过感染过程（叶片湿度）的数据表示进行评估。

GEOPOTATO is an intelligent early warning system for geodata-driven decision-making services that provides Bangladesh farmers with timely warning of the risk of abstinence by combining satellite and local weather data with epidemiological and crop growth models with high-precision geographic and temporal resolution to predict the pressure of abstinence. GEOPOTATO automatically calculates weather data from automatic weather stations

此外，GEOPOTATO还可以使用卫星图像处理数据来测量马铃薯作物的生物量增长，通过卫星作物反射率数据用于推算自上次喷洒以来作物的生长情况。在孟加拉国，当GEOPOTATO系统检测到枯萎病风险升高时，会提前3天通过短信和语音消息向订阅的马铃薯农民提供喷洒预防性杀菌剂的早期警报，从而降低农民的种植风险和损失。

In addition, GEOPOTATO can use satellite images to process data to measure the biomass growth of potato crops and use satellite reflectivity data to extrapolate the growth of crops since the last spraying. In Bangladesh, when the GEOPOTATO system detects an increased risk of ailment, early warning of the spraying of preventive microbicides is provided to subscribers of potato farmers three days in advance by text messages and voice messages, thus reducing farmers’ risk and loss of cultivation.

GEOPOTATO系统地面传感器（图片来源）

数字孪生：“弹性农业”的数字化解决路径

“数字孪生”不只是被用于城市规划与治理的前沿技术，其具有精准映射、虚实互动、智能干预的特征，这也为新型农业的发展提供更多的可控性与延展性。

“Digital twin” is not just a cutting-edge technology used for urban planning and governance, but it is characterized by precision mapping, virtual interaction, intelligent intervention, which also provides more controllability and extension for the development of new forms of agriculture.

通过“数字孪生”技术创造虚拟农田，从而将物理场景与规划决策进行脱钩，农民将不必依赖现场的直接观察和手动任务，就可以根据实时数字进行远程操作，在数据偏离预期时立即采取行动，并可根据真实数据提前模拟干预后的效果。“数字孪生”使“弹性农业”、“精密农业”成为数字技术介入农业生产的新形态。

Created `Digital twin' makes `elastic agriculture', `precision agriculture', a new form of digital technology intervention in agricultural production.

美国艾奥瓦（Iowa）州立大学弹性农业人工智能研究所（AIIRA）主要通过利用数据科学、机器学习和人工智能技术，为玉米和大豆种植者提供个性化建议，从而提高作物产量，帮助农业科学家开发出产量更高并能够抵抗干旱和其他压力源的种子。

U.S. Aowa (Iowa) State University Institute for Resilient Agricultural Artificial Intelligence (AIIRA) mainly through the use of data science, machine learning and artificial intelligence technology to provide personalized advice to maize and soybean growers in order to increase crop yields, helps agricultural scientists to develop seeds that are more productive and resistant to drought and other stress sources.

AIIRA通过将多元数据与农业领域知识融合在一起，创建一个预测性“数字孪生”框架，对从单个场景到整个农场的一切事物进行虚拟建模，从而快速轻松地测试各种场景，帮助人们更加确定和高效地制定日常决策和未来计划。

AIIRA has been able to test scenes quickly and easily by integrating multiple data with knowledge in agriculture, creating a predictive “digital twin” framework for virtual modelling of everything from a single scene to the entire farm, thus helping people to better define day-to-day decision-making and future plans in a more definitive and efficient manner.

除了快速测试假设或查看各种决策发挥作用的情况外，“数字孪生”框架还可以使数据模型不断吸收天气、土壤成分等数据和植物遗传学知识，从而让农民极大地扩展专业知识。数字技术不仅可以提升农作物的生长质量，而农民为数据模型喂养数据的同时，数据模型的逐渐丰富和扩展也可以反向提升农民的专业知识。

In addition to fast-testing assumptions or looking at how decision-making works, the “digital twin” framework allows data models to absorb data such as weather, soil composition, and plant genetics, thereby allowing farmers to greatly expand their expertise. Digital technology not only improves the growth quality of crops, but the gradual enrichment and expansion of data models can also lead to a reverse upgrading of farmers’ expertise.

智能机器人在田间采集数据（图片来源）

区块链：重塑农产品的产销生态

数字技术在农业流通环节的应用，已不仅限于单一功能与单一价值的孤立式应用，同时也在整合整个农产品的供销链条，重组农产品的价值链。

The application of digital technologies in agricultural flows is no longer limited to isolated applications of a single function and a single value,

区块链、计算机视觉、增强现实等技术的应用，从农产品生态构建、农产品溯源管理、农产品产销链条扩展等环节不断延伸，使农民或农作物种植者在农业生态的价值逐步提升和放大，让末端消费者逐渐由食用者与观摩者进而通过数字技术成为农产品生产的参与者。

The application of block chains, computer visualization, reality enhancement, etc., has been extended from agroeconomy, agricultural traceability management, agricultural product distribution chain expansion, and has enabled farmers or crop growers to gradually increase and magnify the value of agroecology, allowing end-end consumers to move from consumers and viewers to participants in agricultural production through digital technology.

作为一个不可篡改、不可伪造的分布式数据库，区块链在农产品溯源、农业物联网和生产物流方面得到了广泛应用。通过农产品各个环节的上链，区块链技术不只是确保农产品流通和销售环节的真实性与安全性，也整合了供应链和销售链，改变了农产品的生产、流通和销售模式。

As a non-defeating, non-false distributed database, block chains are widely used in agricultural traceability, agronetting, and production logistics. Through the upper chain of agricultural production, block chain technology not only ensures the authenticity and security of the flow and distribution of agricultural products, but also integrates supply and distribution chains and changes the patterns of production, circulation and marketing of agricultural products.

Aqgromalin是印度一个以区块链技术驱动的农场多元化平台，它使农民能够通过其平台实现畜牧业和水产养殖业的生产多元化，并通过组织供应投入和营销产出的方式帮助农民增加农业收入。平台通过打通农场的上下游环节，上游整合亲代育雏场、孵化场、托育所、饲料厂等供应链，下游整合贸易商、零售商和出口商等销售链，简化畜牧业和水产养殖生态系统，形成印度最大的畜牧业和水产养殖网络。

Aqgromalin is a technologically driven farm diversification platform in India that enables farmers to diversify their livestock and aquaculture production through its platforms and to help farmers increase their farm incomes by organizing the supply of inputs and marketing outputs. The platform integrates upstream and downstream supply chains such as pro-breeding farms, incubators, nurseries, feed plants, downstream integration of marketing chains such as traders, retailers and exporters, streamlining livestock and aquaculture ecosystems, and forming India’s largest livestock and aquaculture network.

农民可以通过平台订购投入品运送到农场，农产品成熟后，农民还可以通过平台网络销售农产品。区块链技术在农产品生产、流通、销售等环节的嵌入，不仅打造了从供应链到销售链的闭环，确保了农产品的高质量生产。同时，农民加入到区块链平台生态可以实现前期投入的高效化与末端销售收入的最大化。

Farmers can order inputs from platforms to farms, and when they mature, they can sell their produce through platforms. The embedding of block-chain technologies in the production, circulation, marketing, etc. of agricultural products ensures high-quality production, not only from the supply chain to the marketing chain.

Aqgromalin为农民提供的供应链供销平台（图片来源）

增强现实：从生产端到消费端的“数字农宇宙”

物联网、人工智能、数字孪生等在农业领域的应用，均侧重于对整体环境与状态的数据采集、监测和分析，同时给出的也是针对固定场景、目标面积、制定区域的解决方案。而增强现实（AR）技术则是针对单个动植物的状态监测，并持续性地跟踪管理其生长状态。

Applications in the field of agriculture, such as networking, artificial intelligence, digital twining, all focus on data collection, monitoring and analysis of the overall environment and state, with solutions for fixed scenarios, target areas, and regions. To enhance reality techniques are strong's state monitoring of individual flora and fauna and keeping track of their growth status.

Nedap（荷兰电子软硬件技术公司内达普）的畜牧管理部门于2019年开发了一款针对奶牛的AR监控系统，该产品可以跟踪奶牛发情、位置、进食、反刍、站立和不活跃行为的迹象，从而分析奶牛的生长状态。AR程序可通过手势或语音的方式将相关信息录入系统。

The livestock administration of Nedap

如果奶农佩戴Microsoft Hololens（微软公司MR头戴式显示器），那么奶农的视野中每头奶牛的上方都会显示该奶牛的生长数据。AR除了可以解决大规模养殖奶牛的麻烦，实现针对每一头奶牛精细化喂养和管理的可操作性；同时，还可以通过对每头奶牛进行数据标签化，实现在销售端、用户端的定制化价值开发。

If the dairy farmer wears Microsoft Hollens

AR视野下奶牛上方的数据（图片来源）

在数字技术的助力下，食品溯源已经不仅是通过防伪二维码以识别食品的产地、生产日期、真伪等信息，如何为用户提供更周全的烹饪指导知识，并为用户深度了解和参与食品的生长或培植过程，也正在成为数字技术介入现代农业发展的一部分。

With the help of digital technology, food traceability has become a part of digital technology's involvement in modern agricultural development, not only by identifying the food's origin, date of production, authenticity and so on, but also by providing users with a better knowledge of cooking instructions and by providing users with a deeper understanding of and participation in the growth or cultivation of food.

ABP Food Group（欧洲食品加工供应商ABP）和ASDA（原英国连锁零售超市艾思达，现属沃尔玛旗下子公司）开发了一种身临其境的交互式WebAR体验，旨在通过包装上的二维码激活，提供有关肉类产地和烹饪指导等信息，体验如何烹制完美和牛牛排的3D动画场景。这种AR体验和互动步骤可以让顾客对自己的烹饪充满信心，并有效地增加客户的参与感和满足感。

APP Food Group and ASDA

Patrón Tequila（百加得旗下烈酒品牌培恩龙舌兰）也推出了一款移动应用程序，该应用程序使用AR技术向消费者展示龙舌兰酒的制作方法，并为用户在家品尝美酒提供指导。此外，用户还可以在数字生成的田地中种植龙舌兰，参与虚拟龙舌兰酒的制作，该田地可以通过iPhone摄像头投射到任何平面场景中。在虚拟龙舌兰种植体验的每个阶段，均有调酒师通过视频对烈酒的口味特征和桶陈年进行指导说明。

Patrón Tequila

WebAR互动场景展示图（图片来源）

计算机视觉技术正在重新定义食物种植、加工、运输和消费方式。丰富的视觉数据可以通过机器学习加以利用和处理，然后反馈给农产品种植者或灌溉枢纽。

computer visual technology is redefining the way food is grown, processed, transported and consumed. rich visual data can be used and processed through machine learning and then fed back to farmers or irrigation hubs.

Intello Labs是一家利用人工智能、机器学习和计算机视觉技术来优化食品质量评估和农业供应链的科技公司，致力于从种植者到包装商，从出口商到食品服务商，通过将食品质量数字化，实现公平定价并减少食品浪费。该公司研发的Intello Track平台在食品质量的数字化溯源方面具有三大特征：

Intello Labs, a technology company that uses artificial intelligence, machine learning and computer visual technology to optimize food quality assessment and agricultural supply chains, works to achieve fair pricing and reduce food waste by digitizing food quality, from growers to packagers, exporters to food service providers. The Intello Track platform developed by the company has three main features in the digital traceability of food quality:

一是通过数字化流程确保商品的合规性和可追溯性，保证整个供应链的标准化；

One is to ensure the compliance and traceability of commodities through digital processes and the standardization of the entire supply chain;

二是通过数据分析确保商品的可审计性和公平定价，并根据仪表盘数据定期调整供应链；

Second, it ensures the auditability and fair pricing of commodities through data analysis and regularly adjusts the supply chain on the basis of dashboard data;

三是通过人工智能手段消除质量检测中的人为偏见，标准化食品质量并防止食物损失。

Thirdly, artificial intelligence is used to eliminate artificial bias in quality testing, standardize food quality and prevent food loss.

由此使Intello Track实现了商品全链条的可追溯和高透明度。此外，Intello Labs的Fruit Sort方案借助人工智能、计算机视觉、双重量传感器等技术实现智能高效的水果分拣；Intello Grade方案则通过新一代传感器和数据分析相结合完成食品的最佳品种分级工作，实现更高质量和更高利润的输出。

thus enabled IntroTrack to achieve traceability and high transparency in the entire chain of commodities. Intello Labs' Fruit Sort programme, in addition, achieves efficient and intelligent fruit separation through technologies such as artificial intelligence, computer visualization, dual-volume sensors, and intello Grade, in combination with new generation sensors and data analysis, achieves better quality and higher profit-making output of foods.

因此，大到规模化农产品的质量溯源，小到一颗苹果的质量分级与品控，通过人工智能与相关技术的综合性运用，可以大大降低农产品在流通环节的损耗，并最大限度规避市场的不确定性因素。

Thus, can significantly reduce the loss of agricultural products in the flow chain and minimize market uncertainties through the combination of artificial intelligence and associated technology.

Intello Track操作平台示意图（图片来源）

小结

从数字技术在农业领域的应用案例可知，通过物联网、人工智能、区块链、数字孪生、增强现实等多种数字技术的综合运用，能够在成本、劳动力和资源等方面实现生产力和效率的优化。物联网可对土壤、天气、化肥用量等实时感知、数据收集和分析；人工智能的算法模型可实现对农作物的精密管理与监测，并为最终用户提供决策帮助；区块链在产品质量溯源、供销链条整合等方面提供保障；增强现实可从生产端到销售端实现对农产品的动态数据监测与种植培育场景的体验式参与。

It is clear from the case of applications of digital technology in agriculture that productivity and efficiency can be optimized in terms of cost, labour, and resources through a combination of digital technologies, such as networking, artificial intelligence, block chains, digital combing, and enhancing reality. Material networking can provide real-time perception, data collection and analysis of soil, weather, fertilizer use, etc.; algorithm models of artificial intelligence can achieve precision management and monitoring of crops and provide decision-making support to end-users; block chains provide guarantees in terms of product quality traceability, supply chain integration; and the reality can be enhanced through empirical participation in dynamic data monitoring and cultivation of agricultural products from the end of production to the end of marketing.

数字技术在农业领域的应用本质是从刀耕火种到“网耕数养”的工具革命，同时也是通过数据、平台、算法重建农民、土地、农产品与消费者四者之间在生产、流通、销售、消费等链条的生态关系的过程。

The essence of the application of digital technology in agriculture is a revolution of tools from slash and fire to “net tillage”, and the process of re-establishing ecological relations between farmers, land, agricultural products and consumers through data, platforms, algorithms, production, circulation, marketing, consumption, etc.

数字技术正在引领农业的未来。数字技术能够帮助农业生产、监测和规划，帮助农民在节约资源的同时提高产量。将数字技术应用于农业生产主要有三个目标：

Digital technology is leading the future of agriculture. Digital technology can help agricultural production, monitoring and planning, and help farmers to increase production while saving resources.

零饥饿，建立可持续和高产的农业实践并提高全球总产量；

Zero Hunger, Building sustainable and high-yielding agricultural practices and increasing total global production;

气候行动，减少氮泄漏对土壤和地下水的负面影响；

Climate Action to reduce the negative effects of nitrogen spills on soil and groundwater;

保护、恢复和促进陆地生态系统的可持续利用，减少人类对因养分利用效率低而导致的土壤退化的影响。

protects, restores and promotes the sustainable use of terrestrial ecosystems and reduces human impacts on soil degradation resulting from inefficient nutrient use.

在新兴市场日益普及的数字农业解决方案将使全球可持续和高效的粮食生产成为可能，而其将确保在全球范围内减轻农业外部环境的负面因素，最大限度提升农业在生产、流通、消费等环节对碳中和的贡献。

Digital agricultural solutions, increasingly prevalent in emerging markets, will make it possible to produce food globally in a sustainable and efficient manner, which will ensure that the negative factors of the agricultural external environment are mitigated globally and that the contribution of agriculture to carbon neutrality is maximized along production, circulation and consumption.

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本文来自微信公众号：腾讯研究院 （ID：cyberlawrc），作者：WeCity低碳城市研究组

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