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In agriculture, data mining is the use of data science techniques to analyze large volumes of agricultural data. Recent advancements in technology, such as sensors, drones, and satellite imagery, have enabled the collection of large amounts of data on soil health, weather patterns, crop growth, and pest activity.
The E-agriculture in Action series of publications, by FAO-ITU, that provides guidance on emerging technologies and how it could be used to address some of the challenges in agriculture through documenting case studies. E-agriculture in Action: Big Data for Agriculture [22] E-agriculture in Action: Blockchain for Agriculture [23]
Precision agriculture (PA) is a management strategy that gathers, processes and analyzes temporal, spatial and individual plant and animal data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of ...
World Census of Agriculture; Contains structural data from agricultural censuses conducted since the 1930s, under the decennial World Programme for the Census of Agriculture. Structural data include the size and number of agricultural holdings, the holder’s gender, the type of land tenure, the legal status of holders, as well as information ...
NASS data helps to ensure an orderly flow of goods and services among agriculture's producing, processing and marketing sectors. Reliable, timely and detailed crop and livestock statistics help to maintain a stable economic climate and minimize the uncertainties and risks associated with the production, marketing and distribution of commodities.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Digital agriculture, sometimes known as smart farming or e-agriculture, [1] are tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture. The Food and Agriculture Organization of the United Nations has described the digitalization process of agriculture as the digital agricultural revolution . [ 2 ]
In 1930 the, then, Imperial Council of Agricultural Research, started a statistical unit to assist the State Departments of Agriculture and Animal Husbandry in planning their experiments, analysis of experimental data, interpretation of results and rendering advice on the formulation of the technical programmes of the Council.