The Future of Agriculture.

A technological revolution in farming led by advances in robotics and sensing technologies looks set to disrupt modern practice.

Over the centuries, as farmers have adopted more technology in their pursuit of greater yields, the belief that ‘bigger is better’ has come to dominate farming, rendering small-scale operations impractical. But advances in robotics and sensing technologies are threatening to disrupt today’s agribusiness model. “There is the potential for intelligent robots to change the economic model of farming so that it becomes feasible to be a small producer again,” says robotics engineer George Kantor at Carnegie Mellon University in Pittsburgh, Pennsylvania.

Twenty-first century robotics and sensing technologies have the potential to solve problems as old as farming itself. “I believe, by moving to a robotic agricultural system, we can make crop production significantly more efficient and more sustainable,” says Simon Blackmore, an engineer at Harper Adams University in Newport, UK. In greenhouses devoted to fruit and vegetable production, engineers are exploring automation as a way to reduce costs and boost quality (see ‘Ripe for the picking’). Devices to monitor vegetable growth, as well as robotic pickers, are currently being tested. For livestock farmers, sensing technologies can help to manage the health and welfare of their animals (‘Animal trackers’). And work is underway to improve monitoring and maintenance of soil quality (‘Silicon soil saviours’), and to eliminate pests and disease without resorting to indiscriminate use of agrichemicals (‘Eliminating enemies’).

Although some of these technologies are already available, most are at the research stage in labs and spin-off companies. “Big-machinery manufacturers are not putting their money into manufacturing agricultural robots because it goes against their current business models,” says Blackmore. Researchers such as Blackmore and Kantor are part of a growing body of scientists with plans to revolutionize agricultural practice. If they succeed, they’ll change how we produce food forever. “We can use technology to double food production,” says Richard Green, agricultural engineer at Harper Adams.

Ripe for the picking

The Netherlands is famed for the efficiency of its fruit- and vegetable-growing greenhouses, but these operations rely on people to pick the produce. “Humans are still better than robots, but there is a lot of effort going into automatic harvesting,” says Eldert van Henten, an agricultural engineer at Wageningen University in the Netherlands, who is working on a sweet-pepper harvester. The challenge is to quickly and precisely identify the pepper and avoid cutting the main stem of the plant. The key lies in fast, precise software. “We are performing deep learning with the machine so it can interpret all the data from a colour camera fast,” says van Henten. “We even feed data from regular street scenes into the neural network to better train it.”

In the United Kingdom, Green has developed a strawberry harvester that he says can pick the fruit faster than humans. It relies on stereoscopic vision with RGB cameras to capture depth, but it is its powerful algorithms that allow it to pick a strawberry every two seconds. People can pick 15 to 20 a minute, Green estimates. “Our partners at the National Physical Laboratory worked on the problem for two years, but had a brainstorm one day and finally cracked it,” says Green, adding that the solution is too commercially sensitive to share. He thinks that supervised groups of robots can step into the shoes of strawberry pickers in around five years. Harper Adams University is considering setting up a spin-off company to commercialize the technology. The big hurdle to commercialization, however, is that food producers demand robots that can pick all kinds of vegetables, says van Henten. The variety of shapes, sizes and colours of tomatoes, for instance, makes picking them a tough challenge, although there is already a robot available to remove unwanted leaves from the plants.

Another key place to look for efficiencies is timing. Picking too early is wasteful because you miss out on growth, but picking too late slashes weeks off the storage time. Precision-farming engineer Manuela Zude-Sasse at the Leibniz Institute for Agricultural Engineering and Bioeconomy in Potsdam, Germany, is attaching sensors to apples to detect their size, and levels of the pigments chlorophyll and anthocyanin. The data are fed into an algorithm to calculate developmental stage, and, when the time is ripe for picking, growers are alerted by smartphone.

So far, Zude-Sasse has put sensors on pears, citrus fruits, peaches, bananas and apples (pictured). She is set to start field trials later this year in a commercial tomato greenhouse and an apple orchard. She is also developing a smartphone app for cherry growers. The app will use photographs of cherries taken by growers to calculate growth rate and a quality score.

Growing fresh fruit and vegetables is all about keeping the quality high while minimizing costs. “If you can schedule harvest to optimum fruit development, then you can reap an economic benefit and a quality one,” says Zude-Sasse.

Eliminating enemies

The Food and Agriculture Organization of the United Nations estimates that 20–40% of global crop yields are lost each year to pests and diseases, despite the application of around two-million tonnes of pesticide. Intelligent devices, such as robots and drones, could allow farmers to slash agrichemical use by spotting crop enemies earlier to allow precise chemical application or pest removal, for example. “The market is demanding foods with less herbicide and pesticide, and with greater quality,” says Red Whittaker, a robotics engineer at Carnegie Mellon who designed and patented an automated guidance system for tractors in 1997. “That challenge can be met by robots.”

“We predict drones, mounted with RGB or multispectral cameras, will take off every morning before the farmer gets up, and identify where within the field there is a pest or a problem,” says Green. As well as visible light, these cameras would be able to collect data from the invisible parts of the electromagnetic spectrum that could allow farmers to pinpoint a fungal disease, for example, before it becomes established. Scientists from Carnegie Mellon have begun to test the theory in sorghum (Sorghum bicolor), a staple in many parts of Africa and a potential biofuel crop in the United States.

Agribotix, an agriculture data-analysis company in Boulder, Colorado, supplies drones and software that use near-infrared images to map patches of unhealthy vegetation in large fields. Images can also reveal potential causes, such as pests or problems with irrigation. The company processes drone data from crop fields in more than 50 countries. It is now using machine learning to train its systems to differentiate between crops and weeds, and hopes to have this capability ready for the 2017 growing season. “We will be able to ping growers with an alert saying you have weeds growing in your field, here and here,” says crop scientist Jason Barton, an executive at Agribotix.

Modern technology that can autonomously eliminate pests and target agrichemicals better will reduce collateral damage to wildlife, lower resistance and cut costs. “We are working with a pesticide company keen to apply from the air using a drone,” says Green. Rather than spraying a whole field, the pesticide could be delivered to the right spot in the quantity needed, he says. The potential reductions in pesticide use are impressive. According to researchers at the University of Sydney’s Australian Centre for Field Robotics, targeted spraying of vegetables used 0.1% of the volume of herbicide used in conventional blanket spraying. Their prototype robot is called RIPPA (Robot for Intelligent Perception and Precision Application) and shoots weeds with a directed micro-dose of liquid. Scientists at Harper Adams are going even further, testing a robot that does away with chemicals altogether by blasting weeds close to crops with a laser. “Cameras identify the growing point of the weed and our laser, which is no more than a concentrated heat source, heats it up to 95 °C, so the weed either dies or goes dormant,” says Blackmore.

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