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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 ...
FarmBot is an open source precision agriculture CNC farming project consisting of a Cartesian coordinate robot farming machine, software and documentation including a farming data repository. [1] [2] The project aims to "Create an open and accessible technology aiding everyone to grow food and to grow food for everyone." [2]
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.
Digital agriculture includes (but is not limited to) precision agriculture. Unlike precision agriculture, digital agriculture impacts the entire agri-food value chain — before, during, and after on-farm production. [6] Therefore, on-farm technologies, like yield mapping, GPS guidance systems, and variable-rate application, fall under the ...
Some useful resources for learning about e-agriculture in practice are the World Bank's e-sourcebook ICT in agriculture – connecting smallholder farmers to knowledge, networks and institutions (2011), [2] ICT uses for inclusive value chains (2013), [3] ICT uses for inclusive value chains (2013) [4] and Success stories on information and ...
Precision livestock farming (PLF) is a set of electronic tools and methods used for the management of livestock.PLF involves automated monitoring of animals to improve their production, reproduction, health, welfare, and impact on the environment.
An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, [1] [2] [3] cloud seeding, [4] planting seeds, harvesting, environmental monitoring and soil analysis.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]