Site specific crop management (SSCM) or satellite farming is popularly known as precision agriculture (PA). It is an advanced farming technology based on measurement, responsiveness and observation of intra and inter-field volatility in crops.
The advent of satellite navigation or satnav system (GNSS) and Global Positioning System (GPS) has strengthened the propositions of precision agriculture in the recent years. Precision agriculture is aimed at supporting farm management by establishing an artificial decision support system. In addition, such farming technology may optimize returns and increase production capacity while preserving resources. Technology as such, enables farmers to map and locate their positions in a field with the help of advanced GPS technology.
Precision agriculture helps farmers evaluate the viability of agricultural inputs at a given condition by anticipating spatial variability of several variables such as topography/terrain features, crop yield, moisture levels, soil quality and other subordinate readings.
Importance of Imaging Technology in Precision Agriculture
Precision agriculture is a combination of several advanced farming technologies such as crop yield monitoring system, GPS, and variable rate technology. However, much of these technologies are majorly assisted by graphical or imagery inputs. These graphical inputs are generated using a unique field imaging technology. Over the recent past, the application of imaging technology in precision agriculture has significantly increased. The technology offers a vivid and far more precise evaluation of geographical anatomies. Imaging equipment is mounted on farm vehicles such as unmanned tractors and drones capable of feeding both ground and aerial images. Farmers can use these imageries to assess water quality and nitrogen levels. Furthermore, farmers use such images to make well-informed decisions o resource allocation and monitor real-time crop health during cultivation period.
Lack of agricultural workforce is compelling farmers to adopt to such artificial intelligence services which can enable remote operation. Thereby, helping farmers to fully control and operate their farming equipment such as unmanned tractors and drones through handheld computers and laptops from a distant position. Similarly, manufacturers are focusing on developing autonomous equipment capable of sowing and cultivating crop without much of human involvement. Introduction of advanced imagery technologies that can measure plant condition by reading chlorophyll content, canopy vigor and water stress of each individual crop is positively influencing the harvest cycle.
Innovation in Unmanned Vehicle Technology
Advancements and innovation in imaging technology are translating into higher yield with better quality. Scientists and equipment manufacturing companies are jointly working on developing smart imaging technology for irrigation purpose. Experimental projects that involve unmanned farm vehicles with high-end cameras that can identify crops and initiate automated image analysis are expected to revolutionize cultivation methods. Such advanced technologies are expected to aid farmers in estimating yield prior to the harvest, subsequently, suggesting adequate measures during the harvest and post management including marketing, storage, shipping and sales. For instance, CNH Industrial a prominent agriculture equipment manufacturing company has recently showcased an autonomous concept tractor at the Farm Progress Show in Boone, Iowa, United states. The concept vehicle has an onboard radar system LiDAR (light imaging, detection and ranging) and is mounted with several high definition cameras capturing different angles. The vehicle is capable of sensing any moving or stationary object in its path and automatically readjust itself towards the most efficient route. Moreover, the vehicle can run around the clock and can be fully operated via remote operating devices.
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Factors such as introduction of unmanned aerial vehicles (UAV), cost effectiveness, enhanced data accuracy and user-friendly modules are expected to accelerate the use of imaging technology for precision farming. The global market for imaging technology for precision agriculture is estimated to surpass US$ 1,165 Million in revenues by the end of 2024.