In recent years, agricultural technological innovation has brought about disruptive and sustainable changes in agricultural practice.

Agricultural technology innovation

For example, intelligent agriculture is an upcoming concept that deploys technologies such as the Internet of Things (IoT), computer vision, and artificial intelligence (AI) into agriculture. Robots and drones accelerate farm automation by replacing manual farm operations such as picking fruits, weeding, or spraying water.

The combination of images from drones and satellites with Global Positioning System (GPS) provides high-resolution and location-specific views in this field. In addition, IoT devices supported by sensor technology collect real-time field data, enabling farmers to make data-driven decisions.

In addition, the widespread adoption of precision agriculture and indoor agriculture in recent years has driven the development of the agricultural Internet of Things. In summary, these technological innovations have brought about disruptive and sustainable changes in agricultural practices. The focus is not only to improve the overall quality and quantity of crops, strengthen livestock management, but also to achieve the ultimate goal of a sustainable future.

Summarize the Ten Major Trends in Global Future Agricultural Technology

1. Agricultural Internet of Things Technology

Agricultural Internet of Things Technology

Monitoring farmland in traditional agriculture requires intensive labor, material resources, time, and effort. The Internet of Things provides alternative solutions for these traditional agricultural methods. IoT devices include one or more sensors that collect data and provide accurate information in real-time through mobile applications or other means. These sensors perform countless activities, such as sensing soil temperature and humidity, tracking plants and livestock, and so on. The Internet of Things also helps with remote monitoring of farms, providing greater convenience for farmers. In addition, the new irrigation system utilizes IoT sensors to automatically supply water to crops. These require the use of evapotranspiration sensors, on-site soil moisture sensors, and rainfall sensors. Utilizing sensor solutions to combine IoT technology with drones, robots, and computer imaging to improve the accuracy and precision of agricultural information.

2. Application of agricultural robots

Agricultural robot applications

The shortage of labor is a key problem faced by farmers, and in large-scale field operations, this problem will be even more severe. Therefore, agricultural robots can assist farmers in fruit picking, harvesting, planting, transplanting, spraying, sowing, and weeding. Farmers are increasingly relying on robots to automatically perform repetitive tasks in the fields. They deploy intelligent agricultural machinery, such as automatic and semi-automatic tractors for harvesting. The tractor is also equipped with autonomous driving technology, making it easier to navigate through farmland. In addition, robots are also used in automated systems for livestock management. This includes automatic weighing scales, incubators, milking machines, and automatic feeders. Robots allow farmers to focus more on improving overall productivity without worrying about slow agricultural production processes.

3. Application of Agricultural Artificial Intelligence

Application of Agricultural Artificial Intelligence

Integrating AI into agriculture can enable farmers to have real-time understanding of field conditions and enable them to be proactive. Artificial intelligence provides predictive insights for predicting weather data, crop yields, and prices, helping farmers make informed decisions. Chatbots provide advice and input to farmers. AI and ML algorithms automatically identify anomalies and diseases in plants and livestock. If necessary, timely detection and corrective response can be achieved. Biotechnology also deploys machine learning algorithms to recommend gene selection. In addition, artificial intelligence provides an easy financing channel for farmers who are denied credit by banks by replacing credit scores. In the future, multiple ways will be provided to utilize AI to propose innovative solutions to improve overall agricultural quality.

4. Agricultural biotechnology

Agricultural biotechnology

Due to pests and plant diseases, a large amount of crop yield is wasted. Although agricultural chemicals have been used in the fields, they are not the best solution in terms of sustainability. On the other hand, the application of biotechnology in agriculture has improved the quality of crops and livestock. Science and technology such as plant breeding, hybridization, genetic engineering, and tissue culture can help identify better traits in plants. A genome editing technology is being utilized abroad to improve target specificity, speed, and accuracy. It produces genetically modified plants with the required qualities, such as disease resistance, drought resistance, insect resistance, and high-yield ability. This has improved the profitability of agricultural production. In addition, agricultural biotechnology methods can also be used to provide solutions for biopesticides, herbicides, fertilizers, and bioplastics used in farmland. These solutions address soil toxicity issues and ensure that negative impacts on the environment are minimized.

5. Precision agriculture

Precision agriculture 

The sustainability of agriculture refers to the use of eco-friendly methods and inputs with zero or minimal negative impact on the environment. An example of this is crop and livestock management in specific locations, commonly referred to as precision agriculture. Farmers use precise quantities such as water, pesticides, and fertilizers to improve crop yield, quality, and productivity. The different large areas of land in the entire field have different soil properties, receive different sunlight, and have different slopes. Therefore, applying the same treatment to the entire farm is inefficient and can lead to waste of time and resources. To address this issue, many agricultural technology startups are developing precision agriculture solutions to enhance profitability while addressing sustainability challenges.

6. Drones

unmanned aerial vehicle

Improving farm productivity while saving costs is challenging. But drones, also known as unmanned aerial vehicles, can help farmers effectively overcome this problem. Drones collect raw data and convert it into useful information for farm monitoring. Drones equipped with cameras help with aerial imaging and measurement of close and long range areas. These data have optimized the application of fertilizers, water, seeds, and insecticides, promoting precision agriculture. In addition, drones help with livestock tracking, geofencing, and grazing monitoring. They fly over fields to capture images ranging from simple visible light photos to multispectral images that aid in crop, soil, and field analysis. Although drones are not suitable for poultry monitoring as their movements can scare birds, they can be effectively used for livestock monitoring, grazing monitoring, and crop cultivation. Some companies are also researching drones that can measure chlorophyll levels, weed pressure, and soil minerals and chemical composition.

7. Big Data and Analysis

Big Data and Analysis

Big data and analytical techniques transform daily farm data into actionable insights. Statistical data such as crop area, yield, land use, irrigation, agricultural product prices, weather forecasts, and crop diseases lay the foundation for the next agricultural season. Analysis tools utilize data on weather events, farm equipment, water cycle, crop quality, and quantity to extract information related to farm operations. This enables growers to identify potential hidden patterns and relationships. Several startups are providing solutions in the field of farm analysis, enabling farmers to utilize their field data. For example, analyzing data helps to understand soil nutrient levels, acidity and alkalinity, as well as fertilizer requirements, thus enabling data-driven decision-making.

8. Controlled environment agriculture

Controlled environment agriculture

Fluctuations and extreme weather events continue to hinder traditional farming methods. In addition, planting crops in densely populated cities, deserts, or other unfavorable conditions can pose significant challenges. This is overcome through Controlled Environmental Agriculture (CEA). In CEA, plants are affected by a certain proportion of light, temperature, humidity, and nutrients. There are different growth environments, such as indoor agriculture, vertical agriculture, and greenhouses. More and more technologies such as hydroponic and aerial cultivation are being adopted, which involve planting soilless plants in liquid nutrient media or steam. Another such technique is fish vegetable symbiosis, where plants and fish are grown simultaneously. Fish provide nutrients for plants, while plants purify water for fish. The CEA method reduces pests and diseases and increases yield.

9. Regenerative agriculture

Regenerative agriculture

Traditional farming methods lead to long-term soil erosion and crust formation. Usually, cultivation and overgrazing do not give the soil too much time to recover its vitality before the next planting season. On the other hand, regenerative agriculture has the least disturbance to soil, while focusing on improving soil biodiversity and topsoil restoration. It involves different practices, such as no till agriculture, reduced tillage, crop rotation, etc. For example, planting cover crops between planting seasons to cover the soil and restore soil fertility. In addition, renewable agriculture promotes land use as a carbon sink through sequestration. This leads to a reduction in carbon emissions in the atmosphere and a smaller impact on climate change.

Application of 10.5G Internet Technology in Agriculture

Application of 5G Internet Technology in Agriculture

Without connectivity technologies such as 5G, LPWAN, rural broadband, or satellite communication, intelligent agriculture is impossible to achieve. 5G has promoted the adoption of IoT devices, robots, and sensors, enabling them to communicate at high speeds. This enables farmers to monitor data more accurately in real-time and take necessary actions. High speed Internet using fiber optic cables helps to exchange field data in real time, which is critical to improving accuracy. The connection technology supports other technologies such as the Internet of Things, which ultimately work together to form an interconnected farm.

In recent years, the consumer Internet has continued to extend and expand to the industrial Internet. The digital, networked and intelligent transformation of the agricultural industry has accelerated. Smart agriculture has begun to take effect, and the level of intelligence and unmanned has gradually improved.

China is in the process of advancing towards the second centenary goal, and has placed smart agriculture in the overall planning of building a strong network country, a digital China, and a smart society, promoting the construction of smart agriculture to start well and take good steps during the 14th Five Year Plan period.

Smart agriculture is the application of Internet of Things technology to traditional agriculture, using sensors and software to control agricultural production through mobile or computer platforms, providing precise planting, visual management, and intelligent decision-making for agricultural production, making traditional agriculture more intelligent.

01

Four highlights of smart agriculture

1、 New products and technologies are flourishing.

Modern information technology is widely applied in various aspects and fields of agricultural production, with new products, technologies, and models emerging one after another. The digital transformation of agriculture is accelerating, and traditional agriculture is shifting towards intelligence. Intelligent recognition systems for field moisture, crop seedling conditions, disease and pest monitoring, and disaster monitoring are constantly emerging, as well as intelligent robots for cultivation and harvesting.

Especially, products such as automated harvesting equipment, agricultural sensors (environmental monitoring, animal and plant sign monitoring), surveillance cameras, disease and pest monitoring and early warning, and integrated water and fertilizer have been widely applied.

Significant achievements have been made in crop rotation and fallow supervision, remote diagnosis of animal and plant diseases, precision operation of agricultural machinery, drone defense, precision feeding, and fishing bans in the Yangtze River.

2、 Unmanned or few people's farms have emerged from the ground.

With the continuous consolidation of rural network infrastructure, especially the maturity and popularization of big data, 5G, and artificial intelligence technologies, basic conditions have been provided for the development of unmanned or few person farms.

In Changsha, Hunan, Wuhu, Anhui, Jiansanjiang, Heilongjiang, Huzhou, Zhejiang, Chongzhou, Sichuan, Foshan, Guangdong and other places, unmanned or few person farms have emerged. Through remote control of facilities, equipment, machinery, etc., full automatic control or robot autonomous control, all farm production operations are completed.

Among them, the "Internet plus+agricultural irrigation management system", which is built by comprehensive use of big data, the Internet of Things, intelligent control software, and irrigation equipment, is not uncommon to achieve "10000 mu farms, one key management".

3、 The construction of big data has shown initial results.

Data is the foundation of analysis and prediction, and the application of big data in the field of agriculture will further promote the development of smart agriculture.

From a national perspective, the sharing of government data resources and the integration of information systems have achieved phased results. The national integrated government service platform has been basically established, and the pattern of co construction and sharing of government data resources has been basically formed;

From the perspective of industry departments, agricultural and rural departments at all levels have successively launched pilot projects for the full industry chain big data construction of 15 varieties of 8 major categories, including apples and soybeans. Shaanxi has built a national level apple industry big data center, and Chongqing Rongchang has built a national level pig big data center.

From the practice in various regions, Anhui, Zhejiang, Jiangsu, Guangxi and other regions are actively promoting the construction of agricultural and rural big data, and have successively built big data platforms. Zhejiang is vigorously promoting the digital reform of agriculture, rural areas, and farmers throughout the province.

4、 Market entities become the driving force.

The coordinated promotion mechanism of smart agriculture development guided by the government, market entities, and social participation has begun to play a role. A collaborative pattern of active investment from enterprises and extensive participation from farmers and new agricultural management entities is forming, and market entities are becoming an important force in building smart agriculture.

Large enterprises have entered the field of smart agriculture, and three major telecom operators and other Internet enterprises have deployed smart agriculture and entered smart farms.

02

Top 10 Trends in Smart Agriculture

Trend 1: Cost reduction

A set of smart agricultural equipment should be at least hundreds of thousands or millions. A farmer's annual income may only be that small. Therefore, low-cost smart agricultural equipment will become a favorite of more farmers - in other words, low-cost will be one of the trends in smart agriculture.

Trend 2: Easy operation

Farmers who are engaged in traditional agriculture feel dizzy when they hear about the Internet and computers, and even think: I haven't graduated from junior high school. Let me operate computers and computers. Aren't you a troublemaker?

The fundamental purpose of smart agriculture is to serve agriculture and farmers, rather than making them feel like they are causing trouble. Therefore, intelligent devices that are easy to operate and learn will become popular in rural areas - this is an inevitable trend in the development of smart agriculture.

Trend Three: Expert Participation in Production

Experts will participate in production, which is a major change brought by smart agriculture to traditional agriculture.

Farmers can send their questions and difficulties encountered during the planting and breeding process to experts online for analysis. But the outcome still depends on oneself and cannot rely solely on experts.

Trend 4: Strengthening Collaboration

Smart agriculture will make division of labor more clear. Farmers do their own things well and entrust other tasks to professionals - of course, collaboration and feedback here will be more frequent.

Trend 5: Visualization dominates

Nowadays, consumers want to buy reliable agricultural products, which includes understanding when these vegetables are sown, harvested, which pesticides are used, and even understanding the growth process of these agricultural products through video. So, in the future, agriculture or smart agriculture will inevitably have the trend of visualization.

Trend 6: Vertical smart agriculture becomes the development direction

Everything emphasizes segmentation, and smart agriculture is no exception. With development, more vertical sub sectors of smart agriculture will emerge in the future. Smart agriculture will serve agriculture, rural areas, and farmers more accurately.

Trend 7: Integrated Smart Agriculture

In this era, integration and cross-border are all emphasized. It seems that without integration, one cannot survive - this may sound like "nonsense," but in fact, there is a truth to it.

It is undeniable that the depth and width of smart agriculture will have the shadow of other industries, such as the Internet, cloud computing, urban agriculture, and the integration of agriculture and tourism. Therefore, the development of smart agriculture cannot be without the word "integration".

Trend 8: Smart Agriculture in Marketing

The sales of agricultural products have always been a major constraint on agricultural development, and all means to help sell products are welcomed by farmers. Smart agriculture aims to liberate productivity, improve efficiency, sell products faster, and enable farmers to become prosperous faster. This is also one of the important development paths for smart agriculture.

Trend 9: More and more "laymen" are emerging

Smart agriculture is already a high-tech, high-precision and cutting-edge industry. Without a certain knowledge reserve, it is difficult to efficiently do a good job in smart agriculture.

At present, technology companies and IT elites are all engaged in smart agriculture in China. These "elite new farmers" are often close to technology, but too far from agriculture. To design intelligent devices that meet the needs of farmers, it is necessary to have a broad and in-depth understanding of agricultural needs and study agriculture seriously.

Trend 10: Smart agriculture will eventually be surpassed

Transcendence is the future of smart agriculture.

What will be the next agriculture for traditional agriculture, mechanized agriculture, and smart agriculture? As land resources and other resources become increasingly scarce, planting and breeding are no longer just limited to Earth. People are constantly turning their attention to space and dreaming of agricultural production on other planets.

Science and technology have been constantly developing and advancing, and assumptions that we cannot imagine now may become commonplace in the near future.

From traditional to modern, agriculture will gradually develop into a smart agriculture stage that utilizes the Internet of Things, cloud computing, and precision technology, achieving optimal resource utilization and minimal cost investment, and achieving intelligent management levels in crop production, transportation, and sales - which will take a long time.

At present, what we need to do is to fully promote and utilize smart agriculture to do the things in front of us, protect the environment, reduce pollution, liberate labor force, let smart agriculture light up cities and life, let our descendants thrive on this beautiful planet, and jointly build a beautiful home.

In the past two years, new technologies such as 5G, artificial intelligence (AI) and edge computing have gradually popularized and are affecting a traditional industry - agriculture that has lasted for thousands of years. Alibaba Dharma Institute has released the "Top 10 Technology Trends for 2021", one of which is that agriculture is entering the era of data intelligence.

New technologies have made agricultural crop monitoring, precision breeding, and on-demand allocation of environmental resources a reality. Agriculture is no longer reliant on the heavens. China's agriculture is undergoing digital and intelligent transformation, and is about to enter the era of smart agriculture.

From precision agriculture to smart agriculture

Precision agriculture is a modern agricultural production system that originated in the United States in the 1990s. With the help of intelligent agricultural machinery and equipment, it automatically sows, sprays, fertilizes, and harvests, with work efficiency far exceeding that of traditional farmers, and can further reduce costs.

But for areas that are not suitable for mechanized scale planting, as well as some high value-added fruits and vegetables, a more detailed approach is needed. With the cross field application of new technologies such as artificial intelligence and edge computing, the types of precision agriculture are gradually enriched and move towards smart agriculture.

5G+AI+edge computing Helps Smart Agriculture

In 2019, China officially entered the 5G era. 5G technology will first directly promote the technological upgrading of agricultural sensor connection types and data, and IoT devices in fields such as agriculture, animal husbandry, fruit and vegetable industry, and aquaculture will be maturely applied.

Network connection enables precise control and real-time data transmission of agricultural machinery. At the same time, as a supplement to cloud computing, edge computing, together with artificial intelligence (AI), provides real-time and efficient local decision-making on the edge of the network and the device side closer to the data source.

For example, in the edge AI computer in a greenhouse, it is not necessary for the cloud to decide when and how much water to water. The edge AI computer can independently determine and execute related tasks, and synchronize with the cloud platform if necessary.

Compared with cloud computing, edge computing is closer to users and more efficient in data processing and analysis at edge nodes. Due to the distribution of data at the edges, the network can receive more effective protection and the security of data can be strengthened.

In addition, using edge computing to complete partial data processing can shorten the response time of commands, reduce the data flow from devices to the cloud, and form collaborative services with cloud computing.

Edge AI technology is used for the growth process of crops, which can achieve real-time monitoring and early warning, integrated automatic irrigation of water and fertilizer, pest control and disaster assessment, and improve agricultural productivity.

So far, 5G ensures the real-time and efficient transmission of agricultural big data, edge computing provides computing power for data analysis and processing, and artificial intelligence provides intelligent analysis, management and decision-making of data models, which together constitute the technical foundation of smart agriculture and provide technical support for the development of efficient smart agriculture.

Application of Smart Agriculture Scenarios

Introduce two representative agricultural scenarios: greenhouse and live pig farming

It is important to accurately control and manage the growth environment and stages of plants in greenhouse scenes. This is reflected in the use of technologies such as data collection, water and fertilizer control, intelligent management, and digital farm platforms to manage planting processes such as seedling cultivation, planting, growth management, harvesting, and fallow.

Deploy edge AI computers inside the greenhouse, obtain key indicator data through sensing and collection devices, intelligently judge and control the water and fertilizer system for irrigation and fertilization, control lighting through the canopy system, and visually monitor the growth status of crops. And regularly synchronize relevant data to the cloud based agricultural management system to provide a basis for scientific decision-making.

Another field, intelligent animal husbandry, is most commonly used in dairy farms, pig farms, and chicken farms. The precision feeding system of a pig farm needs to achieve functions such as pig quantity statistics, weight estimation, motion trajectory tracking, slaughter monitoring, and abnormal situation warning.

With the help of edge computer application monitoring technology, including intelligent recognition, each pig's identity, movement track, oestrus and health status are monitored, and the squeezed piglets are intelligently detected, so as to effectively improve the survival rate and slaughter rate of live pigs. Edge AI has achieved humanization of the entire pig farming process and intelligent and scientific management of the operation process.

Based on machine vision analysis technology, managers can always grasp the situation of each region and analyze historical records to make more suitable and comprehensive decisions.

Nowadays, traditional agricultural production scenarios are developing towards intensification and intelligence. Intensification will greatly reduce production costs and increase production revenue; Intelligence will promote data perception, intelligent management, and intelligent decision-making throughout the entire production process, achieving interconnectivity in agricultural scenarios.

At the same time, through new technological means, the production and circulation of meat and vegetables can be traced from the source, from the fields to the dining table, ensuring the quality and safety of the "vegetable basket" and helping to modernize and upgrade China's agriculture.