Do you understand big data in agriculture

Science and technology is penetrating into the agricultural field in the form of big data, and industry integration has become an important force for the transformation of agricultural production mode. In the development of Chinese agriculture in 4.0 times, the agricultural factor of production has been quietly changed.

The construction of agricultural big data is a systematic project, which is a long-term and arduous task. To this end, we should not only do a good job of top-level design, but also adhere to the problem-oriented, application effectiveness as the test standard, to find the right entry point. According to the analysis of relevant experts, at present, combined with the current situation and demand of the development and application of agricultural big data, we should focus on the following key tasks.

First, strengthen the construction of big data infrastructure

It is necessary to strengthen the construction of "cloud", "network" and "end" infrastructure of agricultural big data, including software infrastructure construction such as national agricultural big data platform and important information system, network infrastructure construction such as Internet and Internet of things, as well as hardware infrastructure construction such as sensor equipment and mobile terminals installed in fields.

Second, accelerate the construction of agricultural digital resources system

China will comprehensively improve its capabilities in data collection, transmission, storage, processing, utilization, and security, strengthen the construction of the agricultural big data standardization system, and accelerate the formation of a cross-level, cross-regional, cross-system, cross-department, and cross-business agricultural digital resource system. Now the most basic, the most critical is to solve the lack of data, the biggest "weak link".

Third, strengthen the scientific and technological innovation and application of agricultural big data

We will encourage relevant departments and research and teaching institutions to strengthen the construction of agricultural big data disciplines, key laboratories and major scientific and technological breakthroughs, and actively strive to incorporate the development and application of agricultural big data into digital agricultural engineering projects and modern agricultural industrial technology systems. It is necessary to cooperate with relevant scientific research and teaching institutions and big data enterprises to launch the development and application of core agricultural big data technologies such as data mining, deep learning, correlation analysis, management and processing, launch a series of agricultural big data products, and innovate and improve the promotion and service methods of agricultural big data.

Fourth, strengthen the integration and implementation of government information resources

We will accelerate the establishment of a system and mechanism for the sharing, opening up, development and utilization of agricultural data resources, further promote business integration and data integration, open up the digital artery of "Internet plus government services", and truly realize the use of data to speak, make decisions, manage and innovate. At the same time, to further promote the integration of the website, promote the construction and innovation of new agricultural media.

5. Enhance cyber security capabilities

In accordance with the requirements of synchronous planning, implementation and implementation of cyber security and construction, we will comprehensively strengthen the construction of cyber security guarantee systems for infrastructure, information systems and data resources. At the same time, big data technology should be applied to improve the ability of major public opinion monitoring.

Vi. Implementation of data

At present, most agricultural big data starts from data sources, such as satellite remote sensing in the sky and underground land equipment, etc., but the lack of actual agricultural application scenarios makes it difficult for data to be directly converted into value and landed. Big data in agriculture can be solved not only in the sky and underground, but also in ground forces and ground propulsion.

The key to the development of agricultural big data is people

Agricultural big data cannot be completed overnight. It needs to be carried out in combination with the actual situation of farmers and agriculture, and may go through 5-6 different stages:

Agricultural stage: the current relatively extensive small-scale peasant economy.

Intelligent agriculture: Local intelligent agriculture is realized by partially automated agricultural machinery, partial satellite meteorological big data and Internet of Things equipment.

Online smart agriculture: Smart agriculture has been able to connect smart devices and data to each other and online, and can communicate with each other and make algorithmic analysis and decisions.

Intelligent agricultural system: The intelligent agricultural operation system in the cloud is realized through the cloud + intelligent equipment + agricultural machinery.

Open intelligent platform: open the cloud and intelligent devices to all agricultural nodes and manufacturers through open interfaces, and realize the distributed intelligent platform of cloud or blockchain.

Big data industry and finance platform: A big data industry and finance platform for agriculture is realized by combining the big data and closed-loop trading, industrial closed-loop and financial service platforms of scene refining. Through these different stages, combined with actual agricultural production and operation, the final agricultural big data can realize the coordination and data exchange within the industry chain of agriculture, rural areas and farmers.

Of course, smart phones and smart agricultural machines have not been fully realized in rural areas, nor have standardized and large-scale farms or bases, and the trading platforms for farms and agricultural products have not been fully realized, which means there is still a long way to go for agricultural big data.

There is a more important factor in this long process: people. At present, most rural farmers are middle-aged and elderly farmers, who have no concept of new technologies and big data, and it is difficult to reform or educate them to make use of them. And young people because of the huge contrast between the cost of human investment and income, leave the city, do not want to return to the countryside; Therefore, the most critical thing is how to establish a new talent system in rural areas, through which agricultural industrialization and agricultural big data can be implemented and practiced.