From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management
By Verónica Sáiz-Rubio, Francisco Rovira-Más. Agronomy, 2020
732 citations recorded by the source corpus.
The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. This kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth.
Subfields: Computer Networks and Communications, Plant Science, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/4be9368abc2474d6fd38639e523cf03af1873fd9
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In Computer Networks and Communications
In Plant Science
Citations in the corpus
- From Industry 4.0 to Agriculture 4.0: Current Status, Enabling Technologies, and Research Challenges (2020, background): “work [24] focused on the review of crop data management, in which its decision-making capability enabled by ADSS was presented.”
- Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture (2021, background): “Most of the previously published data either did not deliver enough insights or only focused on various IoT-based architectures, prototypes, improved techniques, and how to use the IoT for monitoring applications and associated environment and crop data management [20,22,23].”