We have just heard about how crop yields can be increased by cultivating or genetically engineering more resistant and nutritious crops. Now we will consider other ways to increase production through the use of technology.
Precision agriculture describes a range of digital technologies designed to make crop and livestock production more accurate and controlled. These tools collect data about the crop or animal environment at a micro scale, allowing for targeted management decisions and inputs.
Precision agriculture is often described as the third agricultural revolution, with the first being the advances in mechanisation from 1900 to 1930 and the second the developments in crop breeding and agro-chemicals in the 1960s (the Green Revolution). Technologies include remote sensing (scanning of the farm landscape using satellites), GPS guidance and auto-steer systems, drones, robotics and telematics (the use of wireless audio and visual data). Some examples are described below.
GPS guidance and auto-steer systems
GPS devices in tractors provide accurate position information, whilst GIS (geographic information systems) provide digital maps of the ground environment e.g. its geology, hydrology and soil. This technology allows farmers to select routes that minimise soil compaction or erosion, or to adjust the application of inputs (e.g. fertiliser, seed) according to ground conditions. This technology has also led to the development of self-steering and self-driving tractors.
Wireless sensors Sensors are devices that collect environmental data e.g. crop leaf area, animal temperature or soil moisture. A wireless sensor is one that relays the data to a mobile device remotely, such as the farmer’s smartphone. Sensors may be installed in fields, mounted on tractors, attached to animals or even placed inside the animal rumen (gut). Livestock sensors allow for the monitoring of individual animals, allowing the farmer to identify infections more rapidly, or to track insemination potential, feeding and digestion.
Drones are unpiloted aircraft with mounted sensors and scanning devices to survey agricultural land. Drones are used to monitor yields and crop health, as well as environmental conditions including soil quality, weeds and moisture levels. Drone surveys are a rapid method of monitoring the field environment that produces immediate data.
Agricultural robots (Agribots) These autonomous robots are used in fleets for manual harvesting and weeding, laser weeding (the laser beam kills weeds), ground monitoring and the application of agrochemicals. Agribots reduce labour costs and allow for inputs to be tailored to crop requirements.
What are the costs and benefits of precision agriculture?
The main benefits of these technologies are their targeted, data-based approach, which may reduce inputs and costs, whilst increasing yields. Their monitoring capabilities and application precision could help agriculture to cope with the environmental effects of climate change. The technologies reduce the costs associated with laboratory analyses and manual field operations and monitoring, although of course these must be offset by investment and maintenance costs of precision equipment.
The disadvantage of precision agriculture is that many of its innovations target large-scale farms in the Global North, as opposed to those parts of the world where food security is a critical issue. Growth is highest in the countries with the necessary technological infrastructure and investment capital, e.g. China, Japan and South Korea.
There is also a risk that farmers must put aside their unique knowledge and skill-set and assume the role of software technicians. Whether it is a daily inspection of each cow in the herd, or an examination of the soil in a field with a spade, a farmer interacts with the farm environment in a multitude of ways. If the farmer must instead be calibrating wireless sensors, or programming a drone, this land-based, experiential knowledge will be eroded.
The future of precision agriculture
It is estimated that the precision agriculture industry will be worth USD 43.5 billion by 2025. Artificial intelligence is expected to be the next development, where it will be used for analysing and interpreting farm data to make management decisions.
Our next article considers the role of organic farming.
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