Robots bringing huge benefits to farming

Farming is embracing a technological revolution that involves the likes of computers, global positioning systems (GPS), unmanned drones, driverless tractors, and robots and much more. The industry is on the brink of enjoying major developments in robots that could take the hard work and drudgery out of harvesting fruit and vegetables by hand.

There are two critical factors that separate a robot from a machine - the capacity to be autonomous or to act with some degree of decision, and presence of actuators, which allow a machine to alter its environments. This precludes computers and fridges from being called robots.

Researchers are using their knowledge of soft robotics to create deformable manipulators, or "hands", that can manipulate "fragile" produce, such as broccoli, strawberries and mushrooms. Currently, UK researchers are working on a harvesting robot that can handle and cut iceberg lettuces with the same handling care as human harvesters.

The technology has the potential to be deployed at any time of day and impact positively on the productivity and life quality of agricultural workers.

Researchers now envisage robots that could perform multiple tasks. For example, inter-changeable tools would allow switching between tasks such as seeding, tillage, spraying and harvesting.

You could also have robots for agriculture and food production that would perform other useful tasks at the same time such as surveillance, keeping a watchful eye on crops, livestock and expensive farm machinery, while carrying out their primary duties on the farm or in the factory.

Satellite imaging is used a lot in agriculture nowadays. A drawback with that technology is that the images aren't as good when there is cloud cover, but low-flying drones can consistently produce high resolution pictures of crops and their condition.

Different sensors - visible light, infra-red and thermal - are being used to identify different features of crops. Researchers have created a database that, for example, recognise weed types, the presence of disease, plant stress levels, crop damage, and crop yield potential.

Identifying weeds, their density and precise location within a field could, with a GPS-programmed sprayer, result in localised spraying and a big saving in chemical costs. Similarly, by identifying chlorophyll content in the crop plants the technique could be used for variable rate nitrogen fertiliser application.