Potato Review

AGTECH effective, and better for the environment, said Tom. Instead of spraying an entire field with chemicals that risk running-off into the waterways, precisely-metered doses can now be delivered directly, and only to plants that need them. This approach generates vast amounts of data, much of it stored in the cloud. Once there, it can be used to support a growing wave of new functionality, from mapping crop yields and soil conditions within a field, to performing crop simulations to select the best planting strategies. With most tractors already equipped with the hardware necessary for full self- driving, and a permanent data connection providing access to the computational safety net of big data and experience- based decision-making, it’s a short step from here to the world of full autonomy. “We’re already having these conversations with our clients,” said Tom. “Recent acquisitions by some of the biggest players in the industry point to this happening sooner rather than later. While there’s understandable reticence surrounding self-driving passenger cars, if a tractor gets lost in a field it might end up in a ditch or a hedge, not driving the wrong way up the M1. Many of the challenges for autonomous cars stem from the need to map the precise location of every obstacle, some of which, particularly other cars, are constantly moving. But in agriculture we already know where everything is, even down to the pinpoint location of each individual plant.” More than grower replacement However, agricultural autonomy isn’t about replacing the grower. Intelligent machines that can accompany a lone worker or even deploy themselves, perhaps in response to a weather report, free up the farm owner to attend to other matters. In some areas of the country where a planting window might last only a few days, the ability to get the job done quickly and precisely can have a major impact on an entire year’s productivity. “Hundreds of thousands of connected machines out there, collecting data day in, day out for more than 20 years means there’s a tremendous amount of learning that’s already been done. Now it’s time to capitalise on that investment,” said Tom. Recent developments in machine learning and vision systems have led to technologies such as See & Spray™, the ability to automatically distinguish between weeds and cultivated plants. Photo: John Deere AgVantage UK Ltd Poplar Farm Coates, Peterborough, PE7 2DU 01733 215921 www.agvantage.co.uk info@agvantage.co.uk Proud importer of Dewulf potato and vegetable equipment