A new method uses advanced machine learning technology to reduce error in yield prediction and make greenhouses more efficient.
With a global food crisis becoming ever more worrying, we have seen innovation help make farming more efficient. For example, the American sloth-like robot which helps farmers to monitor their crops. It does so by taking pictures of the crops and sending them onto the farmers. Farmers can thus gain information about their crop progress with minimal effort. Similarly, the invention of a solar-powered robot which is able to weed gardens makes life easier for avid gardeners. Technology is proving to be key to a sustainable future for agriculture worldwide. This is where Motorleaf comes in. With their Agronomist.ai platform they are able to predict crop yield with great accuracy.
The Canadian-based company has taken advantage of cutting-edge technology to provide advances in prediction services for commercial greenhouses. With artificial intelligence and machine learning they have been able to help improve the greenhouses’ predictions and reduce financial loss. In addition to providing custom yield production algorithms, Motorleaf helps consumers in a number of ways. Greenhouse operators benefit from never before seen insights thanks to a combination of previous and live sensor data. There are two options available, one designed for indoor commercial farms measuring up to an acre, and one for crop testing facilities. Farmers pick from various sensor devices which can be easily installed and used to monitor the environment. With an improved yield prediction service, commercial growers are much better informed. This influences the number of laborers they hire, their prices, and buyer relations. Through providing greenhouse operators with precise, personalized data, Motorleaf acts as a global agronomist.
With agricultural efficiency becoming increasingly necessary, this technology is likely to expand to other farming methods. How else could technology help farmers to reduce waste and improve yield? Will technology take over from human intuition when it comes to farming in the future?