Predicting weeds using multi-layer analytics

Groundbreaking innovation tends to happen through multidisciplinary approaches and a range of expertise. That statement has never been truer than in a new national project bringing together precision technologies, remote sensing, and modern machine capabilities with knowledge of weed ecology and population dynamics to predict the emergence of weed patches across paddocks. This project is part of the Grain Automate initiative bringing together weed science expertise from the University of Western Australia and Bayer Crop Science, drone imaging technology from Australian start up InFarm, and geospatial analytics from Canadian start up Geco Agriculture. This episode features Mike Ashworth from the UWA node of the Weed Management Initiative, Tom Giles, GRDC Enabling Technologies Senior Manager, and grower John Young. Contact:       Dr Mike Ashworth  Australian Herbicide resistance initiative, University of Western Australia  [email protected]     Tom Giles  GRDC  [email protected] John Young Grower and GRDC western panel member [email protected]   More Information: Machinery innovations to revolutionise weed controlPartenerships and vision are key to an autonomous future Geco Agriculture InFarm Bayer Crop Science   Project Investment Code:       UWA2307-005RTX Learn more about your ad choices. Visit megaphone.fm/adchoices