Agricultural big data is the practice of big data concepts, technologies, and methods in agriculture. Agricultural big data involves various links such as agricultural production, sales logistics, industry supervision, and auxiliary decision-making. It is a cross industry, cross professional, and cross business data analysis and mining, as well as data visualization.

The system mainly covers the following contents:

1. List of institutions

Display the affiliated planting and aquaculture institutions through rich forms of representation such as maps and charts.

The map information includes administrative divisions and institutional locations, and displays the aggregation effect of institutional locations. Use menu shortcuts to switch between displaying the distribution and details of institutions on the map; Display different institutions (divided into three types: regulatory, testing, and law enforcement) with different annotation icons; Select the township administrative division and display the institutional situation of the area in the information window (the upper part displays the statistics of the number of supervision, testing, law enforcement, and township institutions; the lower part displays a list of institutions, which displays the name and type information of the institutions); Select an institution and display the personnel information of the institution in the information window (showing the total number and personnel list of the institution, with personnel names displayed in the personnel list).

The chart information includes statistical information of regulatory agencies, types and corresponding agency information of regulatory agencies, personnel list information of three types of agencies in Yucheng supervision, testing, and law enforcement, and list information of village level regulatory information officers.

2. Heat map of agricultural production

Distribution of planting bases

The map information includes the location of the planting base and the location information of the planting base area. The location of the planting base is represented in the form of points; The area of the planting base is represented in the form of layers. When the location of the planting base is displayed and the mouse is moved over the base, an automatic base information window will pop up (base name, region, person in charge, contact phone number, and total area).

The chart information includes statistical information on the number and area of all planting bases, as well as a list of all planting bases. The list information includes the base name, region, person in charge, contact phone number, and total area.

Distribution of breeding sites

The map information includes the locations of livestock breeding sites and aquaculture sites. Use menu shortcuts to switch between displaying livestock breeding sites and aquaculture sites on the map; Select a specific breeding site and display its information in the information window, including the name of the breeding site, its jurisdiction, responsible person, and contact information.

The chart information includes statistical information on the number of all livestock breeding points, the number of aquaculture breeding points, a list of all livestock breeding points (including breeding point names, regions, responsible persons, contact phone numbers, and total area), and a list of all aquaculture points (including breeding point names, regions, responsible persons, contact phone numbers, and total area).

3. Agricultural situation analysis

Disaster weather warning

Analyze and compare the meteorological data of the region over the years. Estimate the probability of disaster weather occurrence. Provide guidance on production scheduling.

Interface with the Meteorological Bureau, real-time access to weather conditions and display them. We will provide timely reminders for extreme weather and weather related to agricultural production and daily life. There are three functions: real-time weather, meteorological warning, and agricultural weather.

Regional production safety

By switching menus, the safety of the base can be demonstrated through time selection, height, and display of different types of inputs. The chart information includes the number of inputs used in different months/quarters of the selected year.

Resource and Environmental Analysis

The actual impact of natural environment and environmental pollution on agricultural production in the region. The natural environment refers to the universal impact of long-term cultivation of a single agricultural product on soil fertility. Environmental pollution monitoring is integrated with relevant environmental pollution data to predict and analyze agricultural production.

4. Basic data for traceability of agricultural products

Provide support for traceability through the credibility of government departments. Real time monitoring of key elements in the production process is achieved through quality inspection enforcement, sample analysis, and input supervision.

5. Production warning and analysis

Production and estimation

By analyzing the distribution of production and planting, as well as the situation of enterprises, the crops produced in the region are sorted and analyzed. Combined with data from multiple dimensions such as previous production yields, disaster weather, and human impact, the products are estimated and analyzed.

Emergency Response Plan

Based on multi-dimensional data from big data platforms, predict risk points in agricultural production and prepare emergency plans in advance for these risk points.

6. Leadership cockpit

The comprehensive system integrates all data, including collection, processing, key indicator (KPI) calculation, data mining, and diversified data display functions. It focuses on managers as its main service targets, and designs and implements a key indicator system through the construction of a comprehensive indicator framework. Through clear and concise graphical displays of indicators, it reflects the display of key indicators, risk warning reminders, trend analysis and prediction in production, operation and management processes, providing strong support for business decision-making and implementation monitoring.