How Big Data Monitor and Manage Modern Agriculture

How Big Data Monitor and Manage Modern Agriculture

With the outbreak of massive information, agriculture has entered the era of big data. Like big data applications in other industries, obtaining, collecting and analyzing data through technical means can effectively solve problems such as agricultural production and market circulation.

Driven by big data, the thinking mode and working paradigm of agricultural monitoring and early warning have undergone fundamental changes, and the processing and analysis of agricultural products monitoring and early warning information in China will develop in a systematic, integrated and intelligent direction. In this issue, guests will take you to understand how agricultural products monitoring and early warning works and the opportunities that agricultural products monitoring and early warning will face in the future in the era of big data.

Big data enters the agricultural field.

Jim Gray, a database expert and Turing Prize winner, proposed that data-intensive computing has become the fourth scientific research paradigm besides experimental science, theoretical science and computational science. Big data was formally put forward by the academic circles, starting with a series of special articles on "Big Data" published by Nature in September 2008, which introduced the challenges and opportunities brought by the application of big data.

People talk about the massive increase in research data. In 20 1 1 year, Science magazine published a special topic "Dealing with data", pointing out that the ability to analyze data lags far behind the ability to obtain data.

20 12 In March, the US government announced the "Big Data R&D Plan", aiming at promoting scientific research and innovation based on big data. In China, the 424th meeting of Xiangshan Science Conference in May, 20 12 took "Big Data" as the theme, thinking that the era of big data has arrived and big data has become a big problem for all industries. In June165438+1October of the same year, the 445th meeting of Xiangshan Science Conference took the theme of "scientific research informatization in the data-intensive era" to discuss the scientific research informatization in the era of "big data".

These events show that "big data" has entered our lives. So, what is the application of big data in agriculture? Xu Shiwei said, "Agricultural big data is the application and extension of big data in agriculture and an important technical support for monitoring and early warning of agricultural products."

In his view, agricultural big data not only retains the basic characteristics of big data, such as large scale, diverse types, low value density, fast processing speed, high precision and high complexity, but also extends and deepens the information flow within agriculture.

As a strategic resource, data can effectively solve the complex problems faced by agricultural production. From the data acquisition, collection and analysis, agricultural production problems can get twice the result with half the effort.

For example, Xu Shiwei said that if a large number of data such as N, P and K fertility in soil are obtained through sensors and crop ontology detection, and these data are analyzed and sorted out, it can effectively guide the amount and time of fertilization in agricultural production, make reasonable planning, and get the most appropriate input, thus improving production efficiency.

For another example, big data can predict the supply demand of the future market in advance, effectively reduce production input and take appropriate measures for intelligent production, which plays a regulatory role in stabilizing prices.

Big data is the basic support for monitoring and early warning.

Xu Shiwei pointed out that the data acquisition, collection channels and application technical means of agricultural big data cannot be obtained through manual investigation, and it needs to be supported by means of soil sensors, environmental sensors and crop growth life ontology sensors. Due to the update of technology and the reduction of cost, the data acquisition ability in agricultural production and market circulation has been greatly improved.

"Big data has brought agriculture into the era of comprehensive perception, and it is possible to replace samples with the whole; Agricultural production has gained more data support, and has since entered the era of smart agriculture; A large amount of data can optimize production layout and arrange production input; In the era of big data, the market is more conducive to the docking of production and marketing, reducing waste in consumption and reducing postpartum losses. " Xu Shiwei said.

In addition, big data has also brought changes to the management of agriculture. In the past, agricultural management mainly relied on administrative means to guide and arrange production. Big data is conducive to analyzing and extracting features, summarizing trends, guiding the market through the release of market signals, and then guiding production.

Xu Shiwei said that agricultural big data is a high-end management tool for modern agriculture. The so-called monitoring and early warning means monitoring data, which runs through the whole process of agricultural products from production to circulation to consumption and then to the dining table, such as product flow, logistics, capital flow and information flow, so as to achieve matching between production and sales, production and transportation, and production and consumption.

Monitoring and early warning of agricultural products is also the whole process of data collection, information analysis, forecasting and early warning and information release on agricultural products production, market operation, consumer demand, import and export trade and supply and demand balance.

Monitoring and early warning of agricultural products is also the most important foundation for the stable development of modern agriculture, and big data is the basic support for monitoring and early warning. Agricultural development still faces multiple insecurity factors, and it is urgent to use big data technology to break through the predicament.

This is mainly reflected in: the risk of agricultural production has increased, and it is urgent to obtain disaster data in advance, early detection and early warning; The fluctuation of agricultural products market has intensified, and roller coaster ups and downs have occurred from time to time. Timely, comprehensive and effective information is urgently needed to grasp the abnormal market situation and stabilize the market situation. Food safety incidents occur frequently, and the whole process of supervising and punishing violations is in urgent need of transparency.

It can be said that the demand for big data in agricultural product monitoring and early warning is urgent.

The monitoring effect of agricultural products is remarkable.

The monitoring effect of agricultural products is remarkable, and big data is indispensable, which is mainly reflected in the finer monitoring objects and contents, faster data collection, smarter information processing and analysis, and more accurate data services.

With the development of agricultural big data, the data granularity is more detailed, the expression of agricultural product information space is more sufficient, and the content and object of information analysis are more detailed.

Agricultural system is a complex giant system including nature, society, economy and human activities, in which creatures "grow" data in real time, showing the characteristics of digital life. The vigorous development of agricultural Internet of Things, wireless network transmission and other technologies has greatly promoted the massive explosion of monitoring data, and the data has changed from "traditional static" to "intelligent dynamic".

In the context of big data, data storage and analysis capabilities will become the most important core capabilities in the future. In the future, artificial intelligence, data mining, machine learning, mathematical modeling, deep learning and other technologies will be widely used, and the processing and analysis of agricultural products monitoring and early warning information in China will develop in a systematic, integrated and intelligent direction.

For example, China Agricultural Monitoring and Early Warning System (CAMES) has realized simulation and intelligence in the process of mechanism analysis, covering 953 major agricultural products in China, which can realize all-weather real-time monitoring and information analysis of agricultural products, and can be used for multi-type analysis and early warning of different products in different regions.

With the support of big data, the intelligent early warning system automatically obtains the characteristic signals of agricultural objects and transmits them to the judgment system. The judgment system automatically processes, analyzes and discriminates massive data, automatically generates and displays conclusions, finds the flow direction and direction of agricultural product information flow, and extracts the laws of agricultural product market development and operation from complicated information. The final monitoring data and in-depth analysis report of agricultural products market will provide important decision support for government departments to grasp the changes of industrial chain such as production, circulation, consumption, inventory and trade, and to regulate and stabilize the market.