Agricultural big data develops a new situation of smart agriculture

[ China Agricultural Machinery Industry News ] With the continuous development and advancement of the agricultural sector, the importance of agricultural data has gradually emerged, and agricultural big data is a typical big data. Therefore, the application of big data technology to agriculture can greatly promote the development and progress of agricultural information service technology, and can also promote the overall development process of China's agricultural sector to a large extent.

First, the importance of agricultural big data to smart agriculture

With the advent of the technological era, with the Internet, multimedia, cloud computing, etc. as the main representatives, the process of China's information development has been promoted, and cloud computing has also greatly promoted the progress of computing power. Imagine if farm managers can keep track of weather change data, market supply and demand data, crop growth data, etc., farm managers and agrotechnical experts can observe the real scene and related data on the farm without leaving the house, and accurately determine whether the crops are The fertilization, watering or spraying can not only avoid the decline of production caused by natural factors, but also avoid economic losses caused by the imbalance between market supply and demand.

In the era of agricultural big data, we can not only regulate agricultural production through the establishment of a comprehensive data platform, but also record and analyze the dynamic changes in the process of agricultural planting and aquaculture, and the process of agricultural product circulation. Through analysis of data and experience, we will formulate a series of regulation and management measures. To make the orderly development of agriculture.

Second, the role of agricultural big data platform

After years of development, we have developed a multi-faceted and multi-disciplinary agricultural information system, and built many different levels of data resources for different fields, forming a huge wealth of information resources. However, due to interests and other reasons, these data lack a unified standard and norm before, the information is not shared, and the information resources are out of line with the business, which inevitably leads to low data utilization and redundant information. The emergence of the intelligent management service platform of Okemei Yitian helper farm will be able to better standardize the data standards and play a huge role in improving the farm management level.

Third, the application of agricultural big data platform

1. Agricultural resource management

Based on GIS and remote sensing technology, establish a digital map of the farm to make scientific decision-making and refined management of the planting land on the farm.

The basic geographic information provided by the Global Positioning System (GPS) is based on a Geographic Information System (GIS) to establish a digital map of the farm. Using remote sensing (RS) technology to perceive the on-the-ground information (earth quality, crops) in the electronic map, comprehensively grasp the range of agricultural planting land, and real-time understanding of comprehensive information such as soil conditions and atmospheric environment in the region and analyze the planting region through the analysis of information differences. Divided into different management areas, targeted planning, real-time query, analysis and decision-making functions of planting agricultural resources.

2. Crop production management

Integrate traditional statistical data and agricultural resource management information to carry out targeted planting management of crops on different farms.

Quantitatively obtain information on environmental factors affecting crop growth (such as soil fertility, water content, seedlings, pests, etc.) in different regions where planting factors are different, and analyze the causes of differences in yields of the blocks, and adopt technically feasible and economical Effective farming practices, differential treatment, and “agriculture” on demand.

3. Crop monitoring and estimation

Remote sensing (RS) technology is used to monitor the growth of crops, take effective measures as needed, and accurately estimate crop yields and harvesting information based on comprehensive analysis of various data.

4. Pest warning

Using GIS, remote sensing, hyperspectral analysis and other techniques to analyze, predict and control plant diseases and insect pests.

5. Agricultural product quality and safety management

Integrate the production environment, production archives, and test data to form traceability data for agricultural product quality and safety.

6. Origin environmental data

The use of remote sensing (RS), sensors and other technical means to comprehensively grasp the environmental data of agricultural production areas, and form a historical record.

7. Production file data

Record the production of agricultural products, and record various agricultural operation information of agricultural products during the growth process.

8. Agricultural product testing data

Record information such as company qualifications, test reports, and certification of product quality.

As a basic industry in China, agriculture faces the severe challenges of increasing demand for agricultural products, shortage of resources, frequent disasters caused by climate change, fragile ecological security, and continued decline in biodiversity. It is also the agriculture centered on agricultural Internet of Things and cloud computing technology. Informatization foundation, upgrade agricultural information service supported by big data, open up a new situation of smart agriculture, and realize the leap-forward development of agricultural modernization and informationization.