Agricultural automation. The use of machinery and equipment in agricultural operations to improve their diagnosis, decision-making or performing, reducing the drudgery of agricultural work and/or improving the timeliness, and potentially the precision, of agricultural operations. Agricultural automation includes technologies for precision agriculture. Examples of machinery and equipment used in agricultural automation include:
- tractors that pull, push or put into action a range of implements, equipment and tools that perform farm operations (i.e. automating the performing function);
- sensors, machines, drones and satellites, as well as devices such as smartphones, tablets or software tools (e.g. advisory apps and online farm management) and platforms, to monitor animals, soil, water and plants to support humans making decisions on agricultural tasks1 (i.e. automating the diagnosis function);
- more advanced options, such as weeding robots which spray herbicides with precision only where needed and with exactly what is needed, or drones to monitor conditions remotely and apply fertilizers, pesticides and other treatments from above2, 3 (i.e. automating the three functions: diagnosis, decision-making and performing).
Automated equipment. Systems where some (partly automated) or all (fully automated) functions, a defined activity or behaviour of a machine or a machine system, have been automated to work without human intervention.4
Agricultural mechanization. The use of all levels of technologies, from simple, basic hand tools to more sophisticated, motorized equipment and machinery, to perform agricultural operations.6 Power sources in agricultural mechanization are of three types: hand tool technology (tools and implements that use human muscles as the main power source); draught animal technology (machines, implements and equipment powered by animals); and motorized technology (mechanization powered by engines or motors).7
Agricultural motorized mechanization. The application of all types of mechanical motors or engines, regardless of energy source, to activities associated with agriculture.7
Agricultural producers. Households running agricultural businesses engaged in crop production, livestock production, fisheries, aquaculture, pastoralism or forestry.
Small-scale (agricultural) producers are those running any of the agricultural businesses defined above but operating under greater constraints due to limited access to markets and resources such as land and water, information, technology, capital, assets and institutions.8
Artificial intelligence (AI). Computer systems that use algorithms to analyse their environment and take actions – with some degree of autonomy – to achieve specific goals. AI can be purely software-based, acting in the virtual world (e.g. voice assistants, image analysis software, search engines, speech and face recognition systems), or it can be embedded in hardware devices (e.g. advanced robots, autonomous cars, drones or IoT applications).5
Machine learning. A type of AI and a method of data analysis that uses computer algorithms to automate analytical model building. It is based on identifying patterns in data to improve machine performance by more accurately predicting outcomes without explicit human instructions.
Big data. Large, diverse, complex data sets generated from instruments, sensors, financial transactions, social media, and other digital means, typically beyond the storage capacity and processing power of personal computers and basic analytical software.
Business-to-business model. Relations and sales between companies, rather than between a company and individual clients.9
Business-to-client model. Direct relations and sales of products and services between a company and customers who are the end users of its products or services.9
Conservation agriculture (also referred to as conservation tillage). A farming system that promotes minimum soil disturbance (i.e. little or no tillage), maintenance of permanent soil cover and diversification of plant species. It enhances biodiversity and natural biological processes above and below the ground surface, contributing to increased water- and nutrient-use efficiency and improved and sustained crop production.10
Digital automation in agriculture. The strengthening of automated processes in agricultural machinery and equipment (e.g. tractors and their implements, feeding systems, milking machines) by adding digital tools that increase their efficiency and precision as a result of access to data and digital services through intelligent interoperable networks, platforms and farm management systems.
Disembodied vs embodied digital solutions. Disembodied digital solutions are primarily software-based solutions that do not rely on the use of agricultural machinery but instead require limited hardware resources, generally in the form of a smartphone or a tablet, or software tools such as advisory apps, farm management software, and online platforms. They may include remote sensing and/or UAS but limited to data for decision support and scouting. When digital tools are installed on agricultural machinery and equipment, they are called embodied and they enable the machinery to interact with the environment through direct action (performing), rather than just observations and decision support.9
Electronic identification (EID). The use of a microchip or electronic transponder embedded in a tag, bolus or implant to identify an individual farm animal.5
Farm. Any management-integrated agricultural production unit that produces crops, livestock, agroforestry or aquaculture products.
Fee-for-service. In the context of farm machines, a business arrangement whereby the farmer pays a provider for machine services on a per unit basis (e.g. per ha, hour, animal or tonne harvested), rather than owning the machine.5
Global navigation satellite system (GNSS). Any system that uses satellite signals to provide location information. Examples include the global positioning system (GPS) of the United States of America, the European Galileo system, GLONASS of the Russian Federation, and the Chinese BeiDou system.5
Autosteer. A GNSS-enabled technology that provides automated steering and positioning in the landscape for self-propelled agricultural machines (e.g. tractors, combine harvesters, forage harvesters, sprayers). With the most advanced autosteer, the computer does almost all the steering in the field, including turning at the end of a row. Autosteer technology typically requires a human operator present on the seat of the machine to take over in case there is a malfunction or other problem. It is a good example of a precision farming technology.5
Global positioning system (GPS). The United States of America’s GNSS. Because it was the first GNSS available for civilian use, GPS is sometimes used as a generic term for GNSS.5
Internet of things (IoT). A system in which devices – including mobile phones, sensors, drones, machines and satellites – are connected to the internet.9
Interoperability. The ability of machines and equipment to create, exchange and consume data due to clear and shared expectations regarding the contents, contexts and meaning of those data.9
On the go. In the context of farm machines, a situation in which machine operation is adjusted while moving through a field based on an algorithm using sensor data without direct human intervention.5
Operator assistance system. A system that helps human operators of farm machines. Typically, it uses sensor data from several sources on the machine to assist the operator in making decisions; it can automatically adjust machine settings to optimize the operator’s priorities (e.g. fuel efficiency, speed of work accomplished, product quality) and was first introduced on combine harvesters.5
Precision agriculture. A management strategy that gathers, processes and analyses temporal, spatial and individual data and combines them with other information, to manage variations in the field accurately and to support management decisions and precise machine action for improved resource-use efficiency, productivity, quality, profitability and sustainability of agricultural production.11
Precision livestock farming. A data-based livestock management strategy that monitors and controls individual animal or group productivity, environment, health and welfare in a continuous, real-time and automated manner. It focuses on improving resource-use efficiency, productivity, quality, profitability and sustainability of livestock production.5
Protected agriculture. The production of high-value vegetables and other horticultural crops in greenhouses and vertical farms. It allows farmers to grow cash crops on small plots in marginal, water-deficient areas where traditional cropping may not be viable. It is also called protected cultivation or protected crop production.9
Remote sensing. The process of gathering information about objects on earth from a distance, using aircraft, satellites or other platforms carrying sensors.9
Robot. A machine capable of autonomous operation without direct human intervention.12 It can be stationary (e.g. a milking robot) or mobile (e.g. autodriving). The word tends to be used mainly in the media and by the general public, and robots are often anthropomorphized. More technical discussions prefer to use terms like autonomous machine or autonomous equipment.13
Leg robot. A mobile autonomous machine with articulated limbs instead of wheels for movement.5
Milking robot. Any milking machine that automates the milking of dairy animals, especially dairy cattle, without human labour. They are also called automatic milking systems (AMS).
Swarm robots. Multiple, relatively small mobile autonomous machines that accomplish work done by one large machine in conventional mechanization.
Robotics. An interdisciplinary branch of computer science and engineering, which involves design, construction, operation and use of robots. It integrates many fields, including mechanical engineering, electrical engineering, information engineering, mechatronics, electronics, bioengineering, computer engineering, control engineering, software engineering, and mathematics.
Uncrewed aerial system (UAS). A large system including aircraft (drones) with mounted sensor(s), a ground control station operated by the pilot and the software used to analyse the data gathered by the sensor(s).9
Uncrewed aerial vehicle (UAV) or Drone. A flying autonomous machine. It can be guided by remote control or using a device that is software-controlled. In agriculture, it is often used to collect aerial images or to apply fertilizer, seed, pesticides or other crop inputs.5, 9
Unstructured supplementary service data (USSD). A message service that is more interactive than SMS. Characterized by the use of codes that start with * and end with # (e.g. *845#). A USSD message has a maximum of 182 characters and is used to access information on agriculture, health, news, weather etc.14
Variable rate technology (VRT). A technology based on a combination of equipment and software to vary the application of fertilizer, pesticides, seed and other crop inputs within fields to optimize yield based on the needs of crops so that the highest possible yields are obtained with the least possible inputs.5
Map-based VRT. A VRT based on a map that documents spatial information on site-specific conditions within the field. A human analyst prepares this spatial information map beforehand in a separate activity to be used in guiding the VRT.
Planter row shut-offs. A GNSS-enabled VRT approach that controls individual row seeder units, based on a prescription map or sensor data. Often used to avoid seeding in non-crop areas or double seeding in end rows.
Sensor-based VRT. A VRT that is based on sensor reading collected on the go in the field, so the information guiding the VRT is automatically collected (different from a map-based VRT). Typically, the sensor is in the front of the applicator, a computer using an algorithm to vary rates is on the machine, and the application equipment is in the back of the machine.
Sprayer boom section controllers. A GNSS- enabled VRT approach that controls parts of a farm sprayer boom based on a prescription map or sensor data. Section width may vary from several metres to a single nozzle. Current technology allows nozzles to be turned on, off and pulsated at various rates.
Vertical farming. Indoor farming with a completely controlled environment, used for growing crops vertically year-round.9
Virtual fencing. A technology based on equipping animals with GNSS transponders to determine their location that uses audio alerts, electric shocks or other prompts to keep animals within geolocated boundaries. It potentially eliminates the need for physical fencing, and the GNSS helps growers locate animals grazing in large open pastures.5
