The fifth Digital China Construction Summit held recently presented a multi-dimensional digital open model of modern agriculture: in the unmanned farm in the black land of Northeast China, farming and harvest prevention were completed with one click; The carbon budget account book of tea garden in southern mountainous hills is clear at a glance; Can factory hen houses, dead chickens and low-yield chickens be identified at a glance?
Digital Age, Traditional Agriculture? Eat and watch the weather? Facing the loess and facing the sky? Stereotypes have been broken. Smart devices have become? New farm tools? , the data has become? New agricultural materials? Cultivate high yield and excellent production? The field of wisdom? .
A digital journey of an laying hen
Right? Chicken? As far as scientists are concerned, the most time-consuming and frustrating thing is not mixing feed or cleaning the henhouse, but finding a dead chicken among the chickens.
The laying hen farm of Fujian Yangguang Egg Industry Co., Ltd., located in Yuxi Town, Fuqing City, has 12 hen houses, with a single stock of 50,000 feathers. Every day, the breeder of each henhouse spends most of the day checking the henhouse to find dead chickens. ? If not handled in time, it is easy to cause epidemic disease, and eggs will be blocked, so that eggs can not enter the egg conveying line smoothly. ? Li Guobin, director of the farm, said that finding three or two dead chickens among 50,000 chickens is tantamount to finding a needle in a haystack, which is a test for the breeder's body and mind.
Last year? On duty? Mujilang, a robot for laying hens? , liberated? Chicken? . ? Using artificial intelligence technology, Mujiro? It can judge whether the laying hens are dead or not from the morphological characteristics, and give an accurate location. The breeder only needs to remove them in time according to the map. ? Li Guobin said that the state of the chicken head and feet is an important basis for judging the state of laying hens. Generally speaking, the paws of dead chickens are mostly stiff. ? With help? Mujiro? what's up Eyes? The detection rate of dead chickens can reach 99%. ?
Digital agriculture makes raising chickens more effective.
As a leading enterprise in the field of egg poultry, Yangguang Egg Industry set foot in digital agriculture as early as 20 12, and set about building an agricultural Internet of Things system. The system can monitor the environmental data of the henhouse in real time and find it for each egg through the traceability system. Mother's family. But in the view of Yu Jie, the chairman of the company, this system is a bit? Not good-looking? It is not very helpful to improve production efficiency.
? Digital agriculture is not just laying a bunch of sensors, but using massive data to serve production. ? In 20 18, Yang Guang's egg industry was selected as the pilot of digital agriculture in the Ministry of Agriculture and Rural Affairs, and Yu Shu began to make a comeback, reflecting on what digital agriculture should look like.
After several years of exploration, Yangguang egg industry has established a set of digital breeding system. The whole process of laying hens breeding is thus highly digitized: automatic collection of environmental data, automatic environmental control, automatic accurate feeding, automatic dung cleaning, disease monitoring and early warning, automatic collection and packaging of eggs? The world's first commercial chicken-raising robot came out in 2020 and was put into use last year? Mujiro? Is the latest achievement of its digital transformation.
Checking dead chickens is just? Mujiro? One of many skills. Will I? Eighteen martial arts? It comes down to three categories:? Patrol the mountains on behalf of the king? , regularly or as instructed, inspect the henhouse; ? Dynamic liquidation? , timely find and locate dead chickens and low-yield chickens; ? Senior decision-making staff? , automatically generate charts such as environmental cloud picture, abnormal behavior and dead scouring distribution, and provide scientific basis for improving farming methods.
? Mujiro? Did what the breeder wanted to do but couldn't. Taking the investigation of low-yield weak chickens as an example, the laying rate is the most important index in laying hens. Low-yield weak chicken? You can't lay eggs just by eating? The input-output ratio is extremely low. But it is almost impossible to find out which chicken has low yield and weak constitution by manual work. ? Mujiro? But it can accurately identify. Thanks to this, each chicken in Yangguang egg industry can save 0.5 kg of feed in each laying cycle. At present, one kilogram of feed is 3.5 yuan. Cost-saving and efficiency-increasing are remarkable.
Recently? Mujiro? A chart of abnormal behavior of laying hens was fed back in the background: chickens in a certain area frequently open their mouths. ? Combined with environmental data, it was found that the temperature in this area was uneven and the smell was strong, which was improved and optimized in time to provide a comfortable growth environment for each chicken. ? Yu Yi said that this easily overlooked detail is actually the emotional expression of laying hens.
Through technical iteration and deep learning, Mujiro? Will also become smarter. In my imagination, the future? Mujiro? Is it expected to pass? Looking forward to it? Multi-dimensional accurate identification of the health status of laying hens, but also through big data analysis, to provide a more accurate nutritional model for laying hens, how much carbohydrate, protein, vitamins and fiber to supplement, rather than relying on experience, all data should be used to achieve the purpose of accurate feeding and grain saving? .
Digital solutions to industry pain points
Behind the digital journey of a laying hen is the digital transformation of Fujian agriculture.
? Promote the deep integration of digital technologies such as agricultural Internet of Things, satellite remote sensing, 5G, artificial intelligence, blockchain, cloud computing and big data with agricultural production and operation. ? Chen Hong, director of the Market and Information Division of the Provincial Department of Agriculture and Rural Affairs, said that starting from 20 17, Fujian took the lead in organizing the construction of a modern agricultural wisdom park in the country, and digitally empowered Fujian's advantageous industries such as tea, edible fungi, fruits, vegetables and livestock and poultry.
According to the data, Fujian has built five national digital agriculture demonstration bases, more than 60 provincial-level modern agricultural intelligent parks and 700 agricultural Internet of Things application bases, with a cumulative financial investment of 65.438+0.5 billion yuan, inciting social capital of more than 65.438+0.000 billion yuan and radiating more than 65.438+0.000 new agricultural business entities in the province.
Digital technology directly points to the pain point of traditional agriculture and realizes the process reengineering of agricultural production and management.
How does agriculture play a role in the context of peak carbon dioxide emissions and carbon neutrality? Digitalization makes agricultural carbon budget clear. Fujian Bama Tea Co., Ltd. introduced meteorological observation system to record the temperature, precipitation, radiation and other related meteorological data of tea garden in real time.
? We use meteorological data, combined with the field measured leaf area index, vegetation aggregation index and other indicators, and deduce the carbon flux of tea trees through the ecological process model. Through sampling and laboratory physical and chemical analysis, the soil organic carbon storage in tea garden was estimated. ? Wang Miaomiao, a researcher at the Institute of Digital Agriculture of the Provincial Academy of Agricultural Sciences, said? After understanding the background of agricultural carbon sink, it laid the foundation for future agricultural carbon sink trading. ?
At the 5th Digital Summit held recently, Fujian Bama Tea Co., Ltd. displayed a tea garden through a visual platform. Carbon ledger? Located in 400 mu Chashan, Xiping Town, Anxi County, the annual net carbon sequestration of tea trees can reach 1.0 1.66 tons; The carbon storage of 0-20 cm soil layer is about 1 108.46 tons.
Tea processing also has emission reduction potential. In Anxi, an intelligent system that can simulate the tea-making process of a master will soon be put into commercial use. ? We deeply integrate the technologies of Internet of Things, intelligent control, digital twinning and artificial intelligence into the production of oolong tea, such as drying, cooling, shaking, deactivating enzymes, kneading, Bao Qing and drying. ? Li Zhipeng, a researcher at the Digital Institute of the Provincial Academy of Agricultural Sciences, said that in 20 19, the Institute joined forces with many tea-making masters in Anxi to form a collaborative innovation team to jointly tackle the key technologies of Tieguanyin intelligent primary processing. This technology accurately collects data such as strength, time and times of artificial tea making, and records indicators such as water loss rate of tea, and finally achieves the effects of artificial simulation, precise production, energy saving and emission reduction? .
The epidemic situation of African swine fever has brought great impact to pig breeding. Digital agriculture escorts agricultural biological safety. ? In the past, pig dishes and weighing were manually operated, which invisibly increased the risk of infection. ? Wu Sci-tech Service Team, a scientific and technical staff member of the Institute of Agricultural Engineering Technology of the Provincial Academy of Agricultural Sciences, launched a digital agriculture pilot project in Fujian Xingyuan Agriculture and Animal Husbandry Technology Co., Ltd. to explore an intelligent agriculture scheme for animal disease prevention and control.
? Workers can remotely control the intelligent hardware in the pig farm through the mobile phone terminal, and realize intelligent pig dishes, intelligent weighing, fat monitoring, intelligent feeding and traceability management, which greatly reduces personnel intervention and effectively reduces the infection risk of pigs. ? In Wu Shuo, due to more scientific and refined production management, the delivery of antibiotics, additives and veterinary drugs can be effectively controlled, thus ensuring food safety and greatly reducing the management cost of piggery.
How to make better use of digital agriculture
Rising labor costs, favorable policies, technological progress, coupled with user education in recent years, digitalization has increasingly become a new direction of agricultural modernization transformation, and ushered in a new round of investment and entrepreneurship. However, in the eyes of the industry, the breadth and depth of digital agriculture development need to be expanded.
Li Zhipeng found in the investigation that many digital agriculture projects exist? Re-construction and light operation? Phenomenon. ? Some projects show more ingredients than the actual application effect. ? He said that many digital agricultural projects only realized simple information transmission and display, and failed to combine with agricultural production and management, making it difficult to solve practical problems in agricultural production.
In Li Zhipeng's view, although many agricultural information service enterprises have made great efforts to build platforms, they lack professional management and operation services, which makes the utilization rate of digital agricultural system low and allows some farmers and agricultural enterprises to produce? Useless theory of information technology? Prejudice.
Lin Qiong, an associate researcher at the Institute of Soil and Fertilizer of the Provincial Academy of Agricultural Sciences, believes that the key to the deep integration of digital technology and agriculture lies in tapping the potential of data, so that data can truly guide agricultural production and management? New agricultural materials? .
? Insufficient data, poor data and useless data are the key problems that restrict agricultural digitalization. ? Lin Qiong takes data collection in vegetable greenhouses as an example. At present, the data collected by digital agricultural projects are mostly concentrated on environmental data such as illumination, temperature and humidity, and the research and development of plant sensors is limited, which lacks real-time grasp of crop growth data. ? For example, if the temperature in greenhouse is high, what effect will it have on the growth, flowering, fruit expansion, sugar accumulation and growth stress of tomato? ? Lin Qiong said that only by linking environmental factors with crop growth can we really speak with data and accurately adjust management measures, otherwise we will still rely heavily on artificial experience.
Li Zhipeng advocates breaking data isolated islands and improving data quality. ? At present, the formulation of digital agricultural standards and norms is relatively lacking, resulting in poor data quality, and agricultural information can not be enjoyed, analyzed and applied effectively in real time. ? He suggested strengthening the construction of industry standards related to digital agriculture, and formulating a number of industry standards related to agricultural sensors, agricultural data collection and data transmission to promote the enjoyment and application of agricultural data interconnection.
In this regard, Fujian has made a breakthrough. In recent years, Fujian Province has implemented Fujian? Agricultural cloud 13 1? Information engineering aims to build an agricultural big data resource center, improve the three application systems of agricultural production, management and agricultural product quality and safety services, and build the whole province? Integrated information service platform for agriculture, countryside and farmers.
? We are speeding up the improvement of Fujian? Agricultural cloud 13 1? Project to build a provincial agricultural and rural big data center with collaborative computing capabilities, algorithms, data and application resources. ? Chen Hong said that the next step will be to further improve the data collection and gathering at the provincial, city, county, township (town) and village levels, build a real-time dynamic data collection system and database, and conduct in-depth mining and analysis of the data of the entire agricultural industry chain and rural areas to accelerate the full release of the value of digital resources.
Cultivating applied talents is another key to the development of digital agriculture. Fujian New World Science and Technology Group Co., Ltd. is a technical supporter of several provincial modern agricultural wisdom parks. Wu Zhonggang, the project leader, found that many projects achieved good results in the initial stage of construction, but the follow-up operation was weak. ? Most farmers and agricultural enterprises lack the experience and knowledge of information technology and the ability of equipment operation and data analysis. ? He suggested improving the training mechanism of agricultural digital talents, so that digital agricultural technology can be really used and used well.