Characteristics and applications of agricultural big data

The characteristics and applications of agricultural big data are introduced as follows:

The characteristics of agricultural big data meet the five characteristics of big data, one is large data volume (Volume), and the other is processing speed Fast (Velocity), third, many data types (Variety), fourth, large value (Value), and fifth, high accuracy (Veracity). Including the following types:

(1) From a field perspective, the agricultural field is the core (covering sub-sectors such as planting, forestry, animal husbandry, etc.) and gradually expanded to related upstream and downstream industries (feed production, Fertilizer production, agricultural machinery production, slaughtering industry, meat processing industry, etc.), and integrate macroeconomic background data, including statistical data, import and export data, price data, production data, and even meteorological data, etc. (2) From a regional perspective, take domestic regional data as the core and draw on international agricultural data as an effective reference;

Including not only national-level data, but also provincial and municipal data, and even prefecture-level data, for Provide a foundation for precise regional research; (3) From a granularity perspective, it should include not only statistical data, but also basic information about agricultural economic entities, investment information, shareholder information, patent information, import and export information, recruitment information, media information, GIS coordinate information, etc.

(4) From a professional point of view, it should be implemented step by step. First, professional data resources in the agricultural field should be constructed. Secondly, professional sub-field data resources should be gradually and orderly planned, such as pigs for livestock breeds. , broiler chickens, laying hens, beef cattle, dairy cows, mutton sheep and other professional monitoring data.